+++ /dev/null
-# ----------------------------------------------------------------------------
-# CMake file for cvtest. See root CMakeLists.txt
-#
-# ----------------------------------------------------------------------------
-project(opencv_test)
-
-file(GLOB test_srcs "src/*.cpp")
-source_group("Src" FILES ${test_srcs})
-file(GLOB test_hdrs "src/*.h*")
-source_group("Include" FILES ${test_hdrs})
-
-include_directories("${CMAKE_SOURCE_DIR}/include/opencv"
- "${CMAKE_SOURCE_DIR}/modules/core/include"
- "${CMAKE_SOURCE_DIR}/modules/imgproc/include"
- "${CMAKE_SOURCE_DIR}/modules/features2d/include"
- "${CMAKE_SOURCE_DIR}/modules/flann/include"
- "${CMAKE_SOURCE_DIR}/modules/calib3d/include"
- "${CMAKE_SOURCE_DIR}/modules/highgui/include"
- "${CMAKE_SOURCE_DIR}/modules/objdetect/include"
- "${CMAKE_SOURCE_DIR}/modules/video/include"
- "${CMAKE_SOURCE_DIR}/modules/legacy/include"
- "${CMAKE_SOURCE_DIR}/modules/contrib/include"
- "${CMAKE_CURRENT_SOURCE_DIR}/src"
- "${CMAKE_CURRENT_BINARY_DIR}")
-
-include_directories(../cxts)
-
-set(the_target "opencv_test")
-
-add_executable(${the_target} ${test_srcs} ${test_hdrs})
-
-if(PCHSupport_FOUND)
- set(pch_header ${CMAKE_SOURCE_DIR}/tests/cv/src/cvtest.h)
- if(${CMAKE_GENERATOR} MATCHES "Visual*" OR ${CMAKE_GENERATOR} MATCHES "Xcode*")
- if(${CMAKE_GENERATOR} MATCHES "Visual*")
- set(${the_target}_pch "src/cvtest.cpp")
- endif()
- add_native_precompiled_header(${the_target} ${pch_header})
- elseif(CMAKE_COMPILER_IS_GNUCXX AND ${CMAKE_GENERATOR} MATCHES ".*Makefiles")
- add_precompiled_header(${the_target} ${pch_header})
- endif()
-endif()
-
-# Additional target properties
-set_target_properties(${the_target} PROPERTIES
- DEBUG_POSTFIX "${OPENCV_DEBUG_POSTFIX}"
- RUNTIME_OUTPUT_DIRECTORY "${CMAKE_BINARY_DIR}/bin/"
- )
-
-
-add_dependencies(${the_target} opencv_ts opencv_core opencv_imgproc opencv_calib3d opencv_features2d opencv_objdetect opencv_video opencv_highgui opencv_legacy opencv_contrib)
-
-# Add the required libraries for linking:
-target_link_libraries(${the_target} ${OPENCV_LINKER_LIBS} opencv_ts opencv_core opencv_imgproc opencv_calib3d opencv_features2d opencv_objdetect opencv_video opencv_highgui opencv_legacy opencv_contrib)
-
-enable_testing()
-get_target_property(LOC ${the_target} LOCATION)
-add_test(cvtest "${LOC}")
-
-if(WIN32)
-install(TARGETS ${the_target} RUNTIME DESTINATION bin COMPONENT main)
-endif()
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-static const char* accum_param_names[] = { "size", "channels", "depth", "use_mask", 0 };
-static const CvSize accum_sizes[] = {{30,30}, {320, 240}, {720,480}, {-1,-1}};
-static const CvSize accum_whole_sizes[] = {{320,240}, {320, 240}, {720,480}, {-1,-1}};
-static const int accum_depths[] = { CV_8U, CV_32F, CV_64F, -1 };
-static const int accum_channels[] = { 1, 3, -1 };
-
-class CV_AccumBaseTestImpl : public CvArrTest
-{
-public:
- CV_AccumBaseTestImpl( const char* test_name, const char* test_funcs );
-
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- double get_success_error_level( int test_case_idx, int i, int j );
- void get_timing_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types,
- CvSize** whole_sizes, bool *are_images );
- double alpha;
-};
-
-
-CV_AccumBaseTestImpl::CV_AccumBaseTestImpl( const char* test_name, const char* test_funcs )
- : CvArrTest( test_name, test_funcs, "" )
-{
- test_array[INPUT].push(NULL);
- test_array[INPUT_OUTPUT].push(NULL);
- test_array[REF_INPUT_OUTPUT].push(NULL);
- test_array[TEMP].push(NULL);
- test_array[MASK].push(NULL);
- optional_mask = true;
- element_wise_relative_error = false;
-
- default_timing_param_names = 0;
- depth_list = accum_depths;
- size_list = accum_sizes;
- whole_size_list = accum_whole_sizes;
- cn_list = accum_channels;
-
- return;
-} // ctor
-
-
-void CV_AccumBaseTestImpl::get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- int depth = cvTsRandInt(rng) % 3, cn = cvTsRandInt(rng) & 1 ? 3 : 1;
- int accdepth = std::max((int)(cvTsRandInt(rng) % 2 + 1), depth);
- int i, input_count = test_array[INPUT].size();
- CvArrTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- depth = depth == 0 ? CV_8U : depth == 1 ? CV_32F : CV_64F;
- accdepth = accdepth == 1 ? CV_32F : CV_64F;
- accdepth = MAX(accdepth, depth);
-
- for( i = 0; i < input_count; i++ )
- types[INPUT][i] = CV_MAKETYPE(depth,cn);
-
- types[INPUT_OUTPUT][0] = types[REF_INPUT_OUTPUT][0] = types[TEMP][0] = CV_MAKETYPE(accdepth,cn);
-
- alpha = cvTsRandReal(rng);
-
- return;
-}
-
-
-double CV_AccumBaseTestImpl::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- return CV_MAT_DEPTH(test_mat[INPUT_OUTPUT][0].type) < CV_64F ||
- CV_MAT_DEPTH(test_mat[INPUT][0].type) == CV_32F ? FLT_EPSILON*100 : DBL_EPSILON*1000;
-}
-
-
-void CV_AccumBaseTestImpl::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool* are_images )
-{
- CvArrTest::get_timing_test_array_types_and_sizes( test_case_idx, sizes, types,
- whole_sizes, are_images );
- types[INPUT_OUTPUT][0] = CV_MAKETYPE(MAX(CV_32F, CV_MAT_DEPTH(types[INPUT][0])),
- CV_MAT_CN(types[INPUT][0]));
-
- alpha = 0.333333333333333;
-}
-
-
-CV_AccumBaseTestImpl accum_base( "accum", "" );
-
-
-class CV_AccumBaseTest : public CV_AccumBaseTestImpl
-{
-public:
- CV_AccumBaseTest( const char* test_name, const char* test_funcs );
-};
-
-
-CV_AccumBaseTest::CV_AccumBaseTest( const char* test_name, const char* test_funcs )
- : CV_AccumBaseTestImpl( test_name, test_funcs )
-{
- depth_list = 0;
- size_list = 0;
- whole_size_list = 0;
- cn_list = 0;
-
- default_timing_param_names = accum_param_names;
-}
-
-
-/// acc
-class CV_AccTest : public CV_AccumBaseTest
-{
-public:
- CV_AccTest();
-protected:
- void run_func();
- void prepare_to_validation( int );
-};
-
-
-CV_AccTest::CV_AccTest(void)
- : CV_AccumBaseTest( "accum-acc", "cvAcc" )
-{
-}
-
-
-void CV_AccTest::run_func(void)
-{
- cvAcc( test_array[INPUT][0], test_array[INPUT_OUTPUT][0], test_array[MASK][0] );
-}
-
-
-void CV_AccTest::prepare_to_validation( int )
-{
- const CvMat* src = &test_mat[INPUT][0];
- CvMat* dst = &test_mat[REF_INPUT_OUTPUT][0];
- CvMat* temp = &test_mat[TEMP][0];
- const CvMat* mask = test_array[MASK][0] ? &test_mat[MASK][0] : 0;
-
- cvTsAdd( src, cvScalarAll(1.), dst, cvScalarAll(1.), cvScalarAll(0.), temp, 0 );
- cvTsCopy( temp, dst, mask );
- return;
-}
-
-CV_AccTest acc_test;
-
-
-/// square acc
-class CV_SquareAccTest : public CV_AccumBaseTest
-{
-public:
- CV_SquareAccTest();
-protected:
- void run_func();
- void prepare_to_validation( int );
-};
-
-
-CV_SquareAccTest::CV_SquareAccTest()
- : CV_AccumBaseTest( "accum-squareacc", "cvSquareAcc" )
-{
-}
-
-
-void CV_SquareAccTest::run_func()
-{
- cvSquareAcc( test_array[INPUT][0], test_array[INPUT_OUTPUT][0], test_array[MASK][0] );
-}
-
-
-void CV_SquareAccTest::prepare_to_validation( int )
-{
- const CvMat* src = &test_mat[INPUT][0];
- CvMat* dst = &test_mat[REF_INPUT_OUTPUT][0];
- CvMat* temp = &test_mat[TEMP][0];
- const CvMat* mask = test_array[MASK][0] ? &test_mat[MASK][0] : 0;
-
- cvTsMul( src, src, cvScalarAll(1.), temp );
- cvTsAdd( temp, cvScalarAll(1.), dst, cvScalarAll(1.), cvScalarAll(0.), temp, 0 );
- cvTsCopy( temp, dst, mask );
-}
-
-CV_SquareAccTest squareacc_test;
-
-
-/// multiply acc
-class CV_MultiplyAccTest : public CV_AccumBaseTest
-{
-public:
- CV_MultiplyAccTest();
-protected:
- void run_func();
- void prepare_to_validation( int );
-};
-
-
-CV_MultiplyAccTest::CV_MultiplyAccTest()
- : CV_AccumBaseTest( "accum-mulacc", "cvMultiplyAcc" )
-{
- test_array[INPUT].push(NULL);
-}
-
-
-void CV_MultiplyAccTest::run_func()
-{
- cvMultiplyAcc( test_array[INPUT][0], test_array[INPUT][1],
- test_array[INPUT_OUTPUT][0], test_array[MASK][0] );
-}
-
-
-void CV_MultiplyAccTest::prepare_to_validation( int )
-{
- const CvMat* src1 = &test_mat[INPUT][0];
- const CvMat* src2 = &test_mat[INPUT][1];
- CvMat* dst = &test_mat[REF_INPUT_OUTPUT][0];
- CvMat* temp = &test_mat[TEMP][0];
- const CvMat* mask = test_array[MASK][0] ? &test_mat[MASK][0] : 0;
-
- cvTsMul( src1, src2, cvScalarAll(1.), temp );
- cvTsAdd( temp, cvScalarAll(1.), dst, cvScalarAll(1.), cvScalarAll(0.), temp, 0 );
- cvTsCopy( temp, dst, mask );
-}
-
-CV_MultiplyAccTest mulacc_test;
-
-
-/// running average
-class CV_RunningAvgTest : public CV_AccumBaseTest
-{
-public:
- CV_RunningAvgTest();
-protected:
- void run_func();
- void prepare_to_validation( int );
-};
-
-
-CV_RunningAvgTest::CV_RunningAvgTest()
- : CV_AccumBaseTest( "accum-runavg", "cvRunningAvg" )
-{
-}
-
-
-void CV_RunningAvgTest::run_func()
-{
- cvRunningAvg( test_array[INPUT][0], test_array[INPUT_OUTPUT][0],
- alpha, test_array[MASK][0] );
-}
-
-
-void CV_RunningAvgTest::prepare_to_validation( int )
-{
- const CvMat* src = &test_mat[INPUT][0];
- CvMat* dst = &test_mat[REF_INPUT_OUTPUT][0];
- CvMat* temp = &test_mat[TEMP][0];
- const CvMat* mask = test_array[MASK][0] ? &test_mat[MASK][0] : 0;
- double a[1], b[1];
- int accdepth = CV_MAT_DEPTH(test_mat[INPUT_OUTPUT][0].type);
- CvMat A = cvMat(1,1,accdepth,a), B = cvMat(1,1,accdepth,b);
- cvSetReal1D( &A, 0, alpha);
- cvSetReal1D( &B, 0, 1 - cvGetReal1D(&A, 0));
-
- cvTsAdd( src, cvScalarAll(cvGetReal1D(&A, 0)), dst, cvScalarAll(cvGetReal1D(&B, 0)), cvScalarAll(0.), temp, 0 );
- cvTsCopy( temp, dst, mask );
-}
-
-CV_RunningAvgTest runavg_test;
-
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-#if 0
-
-//extern "C"{
-// #include "HighGUI.h"
-//}
-
-
-static char cTestName[] = "Image Adaptive Thresholding";
-static char cTestClass[] = "Algorithm";
-static char cFuncName[] = "cvAdaptThreshold";
-static int aAdaptThreshold()
-{
-
- CvPoint *cp;
- int parameter1 = 3;
- double parameter2 = 10;
- int width = 128;
- int height = 128;
- int kp = 5;
- int nPoints2 = 20;
-
- int fi = 0;
- int a2 = 20;
- int b2 = 25,xc,yc;
-
- double pi = 3.1415926;
-
- double lower, upper;
- unsigned seed;
- char rand;
- AtsRandState state;
-
- long diff_binary, diff_binary_inv;
-
- int l,i,j;
-
- IplImage *imBinary, *imBinary_inv, *imTo_zero, *imTo_zero_inv, *imInput, *imOutput;
- CvSize size;
-
- int code = TRS_OK;
-
-// read tests params
- if(!trsiRead( &width, "128", "image width" ))
- return TRS_UNDEF;
- if(!trsiRead( &height, "128", "image height" ))
- return TRS_UNDEF;
-
-// initialized image
- l = width*height*sizeof(uchar);
-
- cp = (CvPoint*) trsmAlloc(nPoints2*sizeof(CvPoint));
-
- xc = (int)( width/2.);
- yc = (int)( height/2.);
-
- kp = nPoints2;
-
- size.width = width;
- size.height = height;
-
- int xmin = width;
- int ymin = height;
- int xmax = 0;
- int ymax = 0;
-
-
- for(i=0;i<nPoints2;i++)
- {
- cp[i].x = (int)(a2*cos(2*pi*i/nPoints2)*cos(2*pi*fi/360.))-
- (int)(b2*sin(2*pi*i/nPoints2)*sin(2*pi*fi/360.))+xc;
- if(xmin> cp[i].x) xmin = cp[i].x;
- if(xmax< cp[i].x) xmax = cp[i].x;
- cp[i].y = (int)(a2*cos(2*pi*i/nPoints2)*sin(2*pi*fi/360.))+
- (int)(b2*sin(2*pi*i/nPoints2)*cos(2*pi*fi/360.))+yc;
- if(ymin> cp[i].y) ymin = cp[i].y;
- if(ymax< cp[i].y) ymax = cp[i].y;
- }
-
- if(xmax>width||xmin<0||ymax>height||ymin<0) return TRS_FAIL;
-
-// IPL image moment calculation
-// create image
- imBinary = cvCreateImage( size, 8, 1 );
- imBinary_inv = cvCreateImage( size, 8, 1 );
- imTo_zero = cvCreateImage( size, 8, 1 );
- imTo_zero_inv = cvCreateImage( size, 8, 1 );
- imOutput = cvCreateImage( size, 8, 1 );
- imInput = cvCreateImage( size, 8, 1 );
-
- int bgrn = 50;
- int signal = 150;
-
- memset(imInput->imageData,bgrn,l);
-
- cvFillPoly(imInput, &cp, &kp, 1, cvScalarAll(signal));
-
-// do noise
- upper = 22;
- lower = -upper;
- seed = 345753;
- atsRandInit( &state, lower, upper, seed );
-
- uchar *input = (uchar*)imInput->imageData;
- uchar *binary = (uchar*)imBinary->imageData;
- uchar *binary_inv = (uchar*)imBinary_inv->imageData;
- uchar *to_zero = (uchar*)imTo_zero->imageData;
- uchar *to_zero_inv = (uchar*)imTo_zero_inv->imageData;
- double *parameter = (double*)trsmAlloc(2*sizeof(double));
-
- int step = imInput->widthStep;
-
- for(i = 0; i<size.height; i++, input+=step, binary+=step, binary_inv+=step, to_zero+=step,to_zero_inv+=step)
- {
- for(j = 0; j<size.width; j++)
- {
- atsbRand8s( &state, &rand, 1);
- if(input[j] == bgrn)
- {
- binary[j] = to_zero[j] = (uchar)0;
- binary_inv[j] = (uchar)255;
- to_zero_inv[j] = input [j] = (uchar)(bgrn + rand);
- }
- else
- {
- binary[j] = (uchar)255;
- binary_inv[j] = to_zero_inv[j] = (uchar)0;
- to_zero[j] = input[j] = (uchar)(signal + rand);
- }
-
- }
- }
-
-
-
- cvAdaptiveThreshold( imInput, imOutput, (double)255, CV_ADAPTIVE_THRESH_MEAN_C, CV_THRESH_BINARY, parameter1, parameter2 );
- diff_binary = atsCompare1Db( (uchar*)imOutput->imageData, (uchar*)imBinary->imageData, l, 5);
-
- cvAdaptiveThreshold( imInput, imOutput, (double)255, CV_ADAPTIVE_THRESH_MEAN_C, CV_THRESH_BINARY_INV, parameter1, parameter2 );
- diff_binary_inv = atsCompare1Db( (uchar*)imOutput->imageData, (uchar*)imBinary_inv->imageData, l, 5);
-
- if( diff_binary > 5 || diff_binary_inv > 5 )
- code = TRS_FAIL;
-
- cvReleaseImage(&imInput);
- cvReleaseImage(&imOutput);
- cvReleaseImage(&imBinary);
- cvReleaseImage(&imBinary_inv);
- cvReleaseImage(&imTo_zero);
- cvReleaseImage(&imTo_zero_inv);
-
- trsWrite( ATS_CON | ATS_LST | ATS_SUM, "diff_binary =%ld \n", diff_binary);
- trsWrite( ATS_CON | ATS_LST | ATS_SUM, "diff_binary_inv =%ld \n", diff_binary_inv);
-
- trsFree(parameter);
- trsFree(cp);
- return code;
-}
-
-
-void InitAAdaptThreshold( void )
-{
-/* Test Registartion */
- trsReg(cFuncName,cTestName,cTestClass,aAdaptThreshold);
-} /* InitAAdaptThreshold */
-
-#endif
-
-/* End of file. */
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-#include <limits.h>
-
-//
-// TODO!!!:
-// check_slice (and/or check) seem(s) to be broken, or this is a bug in function
-// (or its inability to handle possible self-intersections in the generated contours).
-//
-// At least, if // return TotalErrors;
-// is uncommented in check_slice, the test fails easily.
-// So, now (and it looks like since 0.9.6)
-// we only check that the set of vertices of the approximated polygon is
-// a subset of vertices of the original contour.
-//
-
-class CV_ApproxPolyTest : public CvTest
-{
-public:
- CV_ApproxPolyTest();
- ~CV_ApproxPolyTest();
- void clear();
- //int write_default_params(CvFileStorage* fs);
-
-protected:
- //int read_params( CvFileStorage* fs );
-
- int check_slice( CvPoint StartPt, CvPoint EndPt,
- CvSeqReader* SrcReader, float Eps,
- int* j, int Count );
- int check( CvSeq* SrcSeq, CvSeq* DstSeq, float Eps );
-
- bool get_contour( int /*type*/, CvSeq** Seq, int* d,
- CvMemStorage* storage );
-
- void run(int);
-};
-
-
-CV_ApproxPolyTest::CV_ApproxPolyTest():
- CvTest( "contour-approx", "cvApproxPoly" )
-{
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;
-}
-
-
-CV_ApproxPolyTest::~CV_ApproxPolyTest()
-{
- clear();
-}
-
-
-void CV_ApproxPolyTest::clear()
-{
- CvTest::clear();
-}
-
-
-/*int CV_ApproxPolyTest::write_default_params( CvFileStorage* fs )
-{
- CvTest::write_default_params( fs );
- if( ts->get_testing_mode() != CvTS::TIMING_MODE )
- {
- write_param( fs, "test_case_count", test_case_count );
- }
- return 0;
-}
-
-
-int CV_ApproxPolyTest::read_params( CvFileStorage* fs )
-{
- int code = CvTest::read_params( fs );
- if( code < 0 )
- return code;
-
- test_case_count = cvReadInt( find_param( fs, "test_case_count" ), test_case_count );
- min_log_size = cvTsClipInt( min_log_size, 1, 10 );
- return 0;
-}*/
-
-
-bool CV_ApproxPolyTest::get_contour( int /*type*/, CvSeq** Seq, int* d,
- CvMemStorage* storage )
-{
- CvRNG* rng = ts->get_rng();
- int max_x = INT_MIN, max_y = INT_MIN, min_x = INT_MAX, min_y = INT_MAX;
- int i;
- CvSeq* seq;
- int total = cvTsRandInt(rng) % 1000 + 1;
- CvPoint center;
- int radius, angle;
- double deg_to_rad = CV_PI/180.;
- CvPoint pt;
-
- center.x = cvTsRandInt( rng ) % 1000;
- center.y = cvTsRandInt( rng ) % 1000;
- radius = cvTsRandInt( rng ) % 1000;
- angle = cvTsRandInt( rng ) % 360;
-
- seq = cvCreateSeq( CV_SEQ_POLYGON, sizeof(CvContour), sizeof(CvPoint), storage );
-
- for( i = 0; i < total; i++ )
- {
- int d_radius = cvTsRandInt( rng ) % 10 - 5;
- int d_angle = 360/total;//cvTsRandInt( rng ) % 10 - 5;
- pt.x = cvRound( center.x + radius*cos(angle*deg_to_rad));
- pt.y = cvRound( center.x - radius*sin(angle*deg_to_rad));
- radius += d_radius;
- angle += d_angle;
- cvSeqPush( seq, &pt );
-
- max_x = MAX( max_x, pt.x );
- max_y = MAX( max_y, pt.y );
-
- min_x = MIN( min_x, pt.x );
- min_y = MIN( min_y, pt.y );
- }
-
- *d = (max_x - min_x)*(max_x - min_x) + (max_y - min_y)*(max_y - min_y);
- *Seq = seq;
- return true;
-}
-
-
-int CV_ApproxPolyTest::check_slice( CvPoint StartPt, CvPoint EndPt,
- CvSeqReader* SrcReader, float Eps,
- int* _j, int Count )
-{
- ///////////
- CvPoint Pt;
- ///////////
- bool flag;
- double dy,dx;
- double A,B,C;
- double Sq;
- double sin_a = 0;
- double cos_a = 0;
- double d = 0;
- double dist;
- ///////////
- int j, TotalErrors = 0;
-
- ////////////////////////////////
- if( SrcReader == NULL )
- {
- assert( false );
- return 0;
- }
-
- ///////// init line ////////////
- flag = true;
-
- dx = (double)StartPt.x - (double)EndPt.x;
- dy = (double)StartPt.y - (double)EndPt.y;
-
- if( ( dx == 0 ) && ( dy == 0 ) ) flag = false;
- else
- {
- A = -dy;
- B = dx;
- C = dy * (double)StartPt.x - dx * (double)StartPt.y;
- Sq = sqrt( A*A + B*B );
-
- sin_a = B/Sq;
- cos_a = A/Sq;
- d = C/Sq;
- }
-
- /////// find start point and check distance ////////
- for( j = *_j; j < Count; j++ )
- {
- CV_READ_SEQ_ELEM( Pt, *SrcReader );
- if( StartPt.x == Pt.x && StartPt.y == Pt.y ) break;
- else
- {
- if( flag ) dist = sin_a * Pt.y + cos_a * Pt.x - d;
- else dist = sqrt( (double)(EndPt.y - Pt.y)*(EndPt.y - Pt.y) + (EndPt.x - Pt.x)*(EndPt.x - Pt.x) );
- if( dist > Eps ) TotalErrors++;
- }
- }
-
- *_j = j;
-
- //return TotalErrors;
- return 0;
-}
-
-
-int CV_ApproxPolyTest::check( CvSeq* SrcSeq, CvSeq* DstSeq, float Eps )
-{
- //////////
- CvSeqReader DstReader;
- CvSeqReader SrcReader;
- CvPoint StartPt, EndPt;
- ///////////
- int TotalErrors = 0;
- ///////////
- int Count;
- int i,j;
-
- assert( SrcSeq && DstSeq );
-
- ////////// init ////////////////////
- Count = SrcSeq->total;
-
- cvStartReadSeq( DstSeq, &DstReader, 0 );
- cvStartReadSeq( SrcSeq, &SrcReader, 0 );
-
- CV_READ_SEQ_ELEM( StartPt, DstReader );
- for( i = 0 ; i < Count ; )
- {
- CV_READ_SEQ_ELEM( EndPt, SrcReader );
- i++;
- if( StartPt.x == EndPt.x && StartPt.y == EndPt.y ) break;
- }
-
- ///////// start ////////////////
- for( i = 1, j = 0 ; i <= DstSeq->total ; )
- {
- ///////// read slice ////////////
- EndPt.x = StartPt.x;
- EndPt.y = StartPt.y;
- CV_READ_SEQ_ELEM( StartPt, DstReader );
- i++;
-
- TotalErrors += check_slice( StartPt, EndPt, &SrcReader, Eps, &j, Count );
-
- if( j > Count )
- {
- TotalErrors++;
- return TotalErrors;
- } //if( !flag )
-
- } // for( int i = 0 ; i < DstSeq->total ; i++ )
-
- return TotalErrors;
-}
-
-
-//extern CvTestContourGenerator cvTsTestContours[];
-
-void CV_ApproxPolyTest::run( int /*start_from*/ )
-{
- int code = CvTS::OK;
- CvMemStorage* storage = 0;
- ////////////// Variables ////////////////
- int IntervalsCount = 10;
- ///////////
- //CvTestContourGenerator Cont;
- CvSeq* SrcSeq = NULL;
- CvSeq* DstSeq;
- int iDiam;
- float dDiam, Eps, EpsStep;
-
- for( int i = 0; i < 30; i++ )
- {
- CvMemStoragePos pos;
-
- ts->update_context( this, i, false );
-
- ///////////////////// init contour /////////
- dDiam = 0;
- while( sqrt(dDiam) / IntervalsCount == 0 )
- {
- if( storage != 0 )
- cvReleaseMemStorage(&storage);
-
- storage = cvCreateMemStorage( 0 );
- if( get_contour( 0, &SrcSeq, &iDiam, storage ) )
- dDiam = (float)iDiam;
- }
- dDiam = (float)sqrt( dDiam );
-
- storage = SrcSeq->storage;
-
- ////////////////// test /////////////
- EpsStep = dDiam / IntervalsCount ;
- for( Eps = EpsStep ; Eps < dDiam ; Eps += EpsStep )
- {
- cvSaveMemStoragePos( storage, &pos );
-
- ////////// call function ////////////
- DstSeq = cvApproxPoly( SrcSeq, SrcSeq->header_size, storage,
- CV_POLY_APPROX_DP, Eps );
-
- if( DstSeq == NULL )
- {
- ts->printf( CvTS::LOG,
- "cvApproxPoly returned NULL for contour #%d, espilon = %g\n", i, Eps );
- code = CvTS::FAIL_INVALID_OUTPUT;
- goto _exit_;
- } // if( DstSeq == NULL )
-
- code = check( SrcSeq, DstSeq, Eps );
- if( code != 0 )
- {
- ts->printf( CvTS::LOG,
- "Incorrect result for the contour #%d approximated with epsilon=%g\n", i, Eps );
- code = CvTS::FAIL_BAD_ACCURACY;
- goto _exit_;
- }
-
- cvRestoreMemStoragePos( storage, &pos );
- } // for( Eps = EpsStep ; Eps <= Diam ; Eps += EpsStep )
-
- ///////////// free memory ///////////////////
- cvReleaseMemStorage(&storage);
- } // for( int i = 0; NULL != ( Cont = Contours[i] ) ; i++ )
-
-_exit_:
- cvReleaseMemStorage(&storage);
-
- if( code < 0 )
- ts->set_failed_test_info( code );
-}
-
-
-CV_ApproxPolyTest contour_approx;
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2009, PhaseSpace Inc., all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The names of the copyright holders may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-#if 0
-
-#if defined WIN32 || defined _WIN32
-#include "direct.h"
-#else
-#include <sys/stat.h>
-#endif
-
-using namespace cv;
-
-//global variable
-#ifndef MAX_PATH
-#define MAX_PATH 1024
-#endif
-
-char g_filepath[MAX_PATH];
-
-//objects for virtual environmnt
-
-/*****************************Camera class ************************************************/
-class Camera
-{
-public:
- Camera(void);
- virtual ~Camera(void);
-
- inline void SetPosition(double x, double y, double z)
- {
- position[0] = x;
- position[1] = y;
- position[2] = z;
- }
-
- inline double* GetPosition() { return position; }
-
- inline void SetDistortion(double r1, double r2, double t1, double t2)
- {
- distortion[0] = r1;
- distortion[1] = r2;
- distortion[2] = t1;
- distortion[3] = t2;
- }
- inline void SetIntrinsics( double fx, double fy, double cx, double cy ) //fx,fy,cx,cy
- {
- intrinsic[0] = fx;
- intrinsic[1] = 0;
- intrinsic[2] = cx;
- intrinsic[3] = 0;
- intrinsic[4] = fy;
- intrinsic[5] = cy;
- intrinsic[6] = 0;
- intrinsic[7] = 0;
- intrinsic[8] = 1.0;
- }
-
- CvPoint3D64f ConvertPoint2WCS( CvPoint3D64f pt )
- {
- double tmp[3];
- CvMat tmp_point = cvMat( 3, 1, CV_64FC1, tmp );
-
- CvMat rot = cvMat( 3, 3, CV_64FC1, rotation );
- CvMat trans = cvMat( 3, 1, CV_64FC1, translation );
- CvMat in_point = cvMat( 3, 1, CV_64FC1, &pt );
-
- // out = inv(R) * (in - t)
-
- cvSub(&in_point, &trans, &tmp_point);
- cvGEMM( &rot, &tmp_point, 1, NULL, 0, &tmp_point, CV_GEMM_A_T /* use transposed rotmat*/ );
-
- CvPoint3D64f out;
- out.x = tmp[0];
- out.y = tmp[1];
- out.z = tmp[2];
-
- return out;
- }
-
- inline void SetRotation( double* rotmat ) //fx,fy,cx,cy
- {
- memcpy( rotation, rotmat, 9 * sizeof(double) );
- }
-
- double* GetRotation()
- {
- return rotation;
- }
-
- void ComputeTranslation()
- {
- //convert camera position in WCS into translation vector of the camera
- //t = -R*pos
- translation[0] = -(rotation[0]*position[0]+rotation[1]*position[1]+rotation[2]*position[2]);
- translation[1] = -(rotation[3]*position[0]+rotation[4]*position[1]+rotation[5]*position[2]);
- translation[2] = -(rotation[6]*position[0]+rotation[7]*position[1]+rotation[8]*position[2]);
- }
-
- double* GetTranslation()
- {
- return translation;
- }
- double* GetIntrinsics()
- {
- return intrinsic;
- }
-
- double* GetDistortion()
- {
- return distortion;
- }
-
- void SetResolution(CvSize res)
- {
- resolution = res;
- }
- CvSize GetResolution()
- {
- return resolution;
- }
- void saveCamParams(FILE* stream);
- void readCamParams(FILE* stream);
-
-
-protected:
- double distortion[4]; //distortion coeffs according to OpenCV (2 radial and 2 tangential)
- double intrinsic[9]; //matrix of intrinsic parameters
- double translation[3]; //camera's translation vector
- double rotation[9]; //camera rotation matrix (probably need to convert to camera axis vector
- double position[3]; //camera's position in WCS
-
- CvSize resolution;
-};
-
-Camera::Camera(void)
-{
- //default parameters
- translation[0] = translation[1] = translation[2] = 0.0;
- rotation[0] = rotation[1] = rotation[2] =
- rotation[3] = rotation[4] = rotation[5] =
- rotation[6] = rotation[7] = rotation[8] = 0.0;
- rotation[0] = rotation[4] = rotation[8] = 1.0;
-
- distortion[0] = distortion[1] = distortion[2] = distortion[3] = 0.0;
-}
-
-Camera::~Camera(void)
-{
-}
-
-void Camera::saveCamParams(FILE * stream)
-{
- float tmp0 = 0.0f, tmp1 = 1.0f;
-
- // printing camera distortion. 4 parameters
- fprintf(stream, "%.12f %.12f %.12f %.12f\n", distortion[0], distortion[1],
- distortion[2], distortion[3]);
-
- //printing camera intrinsics matrix
- fprintf(stream, "%.12f %.12f %.12f %.12f %.12f %.12f %.12f %.12f %.12f\n",
- intrinsic[0], intrinsic[1], intrinsic[2],
- intrinsic[3], intrinsic[4], intrinsic[5],
- intrinsic[6], intrinsic[7], intrinsic[8]);
-
- //printing camera extrinsic transform
- fprintf(stream, "%.12f %.12f %.12f %.12f %.12f %.12f %.12f %.12f %.12f %.12f %.12f %.12f %.12f %.12f %.12f %.12f\n",
- rotation[0], rotation[1], rotation[2], translation[0],
- rotation[3], rotation[4], rotation[5], translation[1],
- rotation[6], rotation[7], rotation[8], translation[2],
- tmp0, tmp0, tmp0, tmp1);
-}
-
-void Camera::readCamParams(FILE* stream)
-{
- double dummy;
-
- // read camera distortion. 4 parameters
- fscanf(stream, "%lf %lf %lf %lf\n", &(distortion[0]), &(distortion[1]), &(distortion[2]), &(distortion[3]) );
-
- //read camera intrinsics matrix
- fscanf(stream, "%lf %lf %lf %lf %lf %lf %lf %lf %lf\n",
- &(intrinsic[0]), &(intrinsic[1]), &(intrinsic[2]),
- &(intrinsic[3]), &(intrinsic[4]), &(intrinsic[5]),
- &(intrinsic[6]), &(intrinsic[7]), &(intrinsic[8]));
-
- //read camera extrinsic transform
- fscanf(stream, "%lf %lf %lf %lf %lf %lf %lf %lf %lf %lf %lf %lf %lf %lf %lf %lf\n",
- &(rotation[0]), &(rotation[1]), &(rotation[2]), &(translation[0]),
- &(rotation[3]), &(rotation[4]), &(rotation[5]), &(translation[1]),
- &(rotation[6]), &(rotation[7]), &(rotation[8]), &(translation[2]),
- &dummy, &dummy, &dummy, &dummy);
-}
-
-/******************************** body**************************************************/
-
-class RigidBody
-{
- //global position of body's center
- double pos[3];
- double rotation[9]; //body's rotation matrix
-
- int* m_ids; //points ids, these are integer numbers not necessarily zero-based indices
- CvPoint3D64f* m_points3D; //these are points in object coordinate system
- CvPoint3D64f* m_points3D_WCS; //these are points in WCS
- int m_numPoints;
-
-public:
-
- RigidBody()
- {
- m_ids = 0;
- m_points3D = 0;
- m_points3D_WCS = 0;
- m_numPoints = 0;
-
- SetPosition(0,0,0);
- double t[9] = {1,0,0,0,1,0,0,0,1};
- SetRotation( t );
- }
- virtual ~RigidBody() {}
-
- virtual void SetPosition(double x, double y, double z )
- {
- pos[0] = x;
- pos[1] = y;
- pos[2] = z;
- }
-
- virtual void SetRotation( double* rotmat )
- {
- memcpy( rotation, rotmat, 9 * sizeof(double) );
- }
-
- void Save(char* fname, bool wcs /* 1 - save coordinates in wcs, 0 - save coordinates in object coordinate system*/ )
- {
- FILE* fp = fopen(fname, "w");
- fprintf(fp, "%d\n", m_numPoints );
- if( wcs )
- {
- for( int i = 0; i < m_numPoints; i++ )
- {
- fprintf(fp, "%d %.12f %.12f %.12f\n", m_ids[i], m_points3D_WCS[i].x, m_points3D_WCS[i].y, m_points3D_WCS[i].z );
- }
- }
- else
- {
- for( int i = 0; i < m_numPoints; i++ )
- {
- fprintf(fp, "%d, %.12f, %.12f, %.12f\n", m_ids[i], m_points3D[i].x, m_points3D[i].y, m_points3D[i].z );
- }
- }
- fclose(fp);
- }
-
- void Load(char* fname)
- {
- clear_points();
- FILE* fp = fopen(fname, "r");
- fscanf(fp, "%d\n", &m_numPoints );
- //allocate arrays
- m_points3D = new CvPoint3D64f[m_numPoints];
- m_points3D_WCS = new CvPoint3D64f[m_numPoints];
- m_ids = new int[m_numPoints];
-
- for(int i = 0; i < m_numPoints; i++ )
- {
- fscanf(fp, "%d %lf %lf %lf\n", &(m_ids[i]), &(m_points3D[i].x), &(m_points3D[i].y), &(m_points3D[i].z));
- }
- }
-
- void clear_points()
- {
- if(m_points3D)
- delete m_points3D;
- m_points3D = NULL;
- if(m_points3D_WCS)
- delete m_points3D_WCS;
- m_points3D_WCS = NULL;
- if( m_ids )
- delete m_ids;
- m_ids = NULL;
- m_numPoints = 0;
- }
-
- void generate_random( int n, double x_min, double x_max,
- double y_min, double y_max,
- double z_min, double z_max )
- {
- clear_points();
- m_numPoints = n;
- m_points3D = new CvPoint3D64f[m_numPoints];
- m_points3D_WCS = new CvPoint3D64f[m_numPoints];
- m_ids = new int[m_numPoints];
-
- //fill ids
- for( int i = 0 ; i < n; i++ )
- {
- m_ids[i] = i;
- }
-
- CvRNG rng;
-
- CvMat values = cvMat( m_numPoints, 1, CV_64FC3, m_points3D );
-
- cvRandArr( &rng, &values, CV_RAND_UNI,
- cvScalar(x_min, y_min, z_min), // min
- cvScalar(x_max, y_max, z_max) // deviation
- );
- }
- CvPoint3D64f* GetPoints3D(bool wcs)
- {
- if( wcs )
- {
- //fill points in WCS accordingly to rotation matrix and board position
- for(int i = 0; i < NumPoints(); i++ )
- {
- m_points3D_WCS[i].x = rotation[0]*m_points3D[i].x +
- rotation[1]*m_points3D[i].y +
- rotation[2]*m_points3D[i].z + pos[0];
-
- m_points3D_WCS[i].y = rotation[3]*m_points3D[i].x +
- rotation[4]*m_points3D[i].y +
- rotation[5]*m_points3D[i].z + pos[1];
-
- m_points3D_WCS[i].z = rotation[6]*m_points3D[i].x +
- rotation[7]*m_points3D[i].y +
- rotation[8]*m_points3D[i].z + pos[2];
- }
- //return points in global cooordinates
- return m_points3D_WCS;
-
- }
- else
- return m_points3D;
- }
-
- double* GetRotation() { return rotation; }
-
- int NumPoints()
- {
- return m_numPoints;
- }
-
- int* GetPointsIds()
- {
- return this->m_ids;
- }
-
-};
-
-
-/********************************* environment *****************************************/
-#define PT_INVISIBLE 0
-#define PT_VISIBLE 1
-#define PT_OUTBORDER 2
-
-class Environment
-{
-public:
- Environment(void);
- virtual ~Environment(void);
-
- inline int NumCameras()
- {
- return (int)m_cameras.size();
- }
-
- inline int AddCamera(Camera* cam)
- {
- m_cameras.push_back(cam);
- return (int)m_cameras.size();
- }
-
- RigidBody* GetBody()
- {
- return m_body;
- }
-
- void SetNoise(float n)
- {
- noise = n;
- }
-
- int Capture();
- int Save(char* filename);
-
-protected:
-
- std::vector<Camera*> m_cameras;
- RigidBody* m_body;
- std::vector<CvPoint2D64f*> m_image_points;
- std::vector<int*> m_point_visibility;
- float noise;
-
-};
-
-Environment::Environment(void)
-{
- m_body = new RigidBody();
-}
-
-Environment::~Environment(void)
-{
- delete m_body;
-}
-
-int Environment::Capture()
-{
- //clear points
- for( size_t i = 0; i < m_image_points.size(); i++ )
- {
- if( m_image_points[i] )
- delete m_image_points[i];
- }
- m_image_points.clear();
-
- for( size_t i = 0; i < m_point_visibility.size(); i++ )
- {
- if( m_point_visibility[i] )
- delete m_point_visibility[i];
- }
- m_point_visibility.clear();
-
- CvPoint3D64f* board_pts = m_body->GetPoints3D(true);
- int num_points = m_body->NumPoints();
-
- //loop over cameras
- for( size_t i = 0; i < m_cameras.size(); i++ )
- {
- //get camera parameters
- //project points onto camera image
-
- double* rot = m_cameras[i]->GetRotation();
- double* trans = m_cameras[i]->GetTranslation();
- double* intr = m_cameras[i]->GetIntrinsics();
- double* dist = m_cameras[i]->GetDistortion();
-
- CvPoint2D64f* image_points = new CvPoint2D64f[num_points];
- m_image_points.push_back(image_points);
-
- int* points_visibility = new int[num_points];
- m_point_visibility.push_back(points_visibility);
-
- cvProjectPointsSimple(num_points, board_pts, rot, trans, intr, dist, image_points);
-
- CvRNG rng;
-
- if( noise > 0)
- {
- CvMat* values = cvCreateMat( num_points, 1, CV_32FC2 );
-
- float stdev = noise;
-
- cvRandArr( &rng, values, CV_RAND_NORMAL,
- cvScalar(0.0, 0.0), // mean
- cvScalar(stdev, stdev) // deviation
- );
-
- //add gaussian noise to image points
-
- for( int j = 0; j < num_points; j++ )
- {
- CvPoint2D32f pt = *(CvPoint2D32f*)cvPtr1D( values, j, 0 );
-
- pt.x = min( pt.x, stdev);
- pt.x = max( pt.x, -stdev);
-
- pt.y = min( pt.y, stdev);
- pt.y = max( pt.y, -stdev);
-
- image_points[j].x += pt.x;
- image_points[j].y += pt.y;
- }
- cvReleaseMat( &values );
- }
-
- //decide if point visible to camera
- //loop over points and assign visibility flag to them
- for( int j = 0; j < num_points; j++ )
- {
- //generate random visibility of the point
- int visible = cvRandInt(&rng) % 2; //visibility 50%
-
- //check the point is in camera FOV (1-pixel border assumed invisible)
- if( image_points[j].x > 0 && image_points[j].x < m_cameras[i]->GetResolution().width-1
- && image_points[j].y > 0 && image_points[j].y < m_cameras[i]->GetResolution().height-1 )
- {
- if(!visible)
- points_visibility[j] = PT_INVISIBLE;
- else
- points_visibility[j] = PT_VISIBLE;
- }
- else
- points_visibility[j] = PT_OUTBORDER;
- }
- }
-
- //some points may become completely invisible for all cameras or visible only at one camera
- //we will forcely make them visible for at least 2 cameras
- for( int i = 0 ; i < num_points; i++ )
- {
- int numvis = 0;
- for( size_t j = 0; j < m_cameras.size(); j++ )
- {
- if( m_point_visibility[j][i] == PT_VISIBLE )
- numvis++;
- }
-
- if(numvis < 2)
- {
- for( size_t j = 0; j < m_cameras.size(); j++ )
- {
- if( m_point_visibility[j][i] == PT_INVISIBLE )
- {
- m_point_visibility[j][i] = PT_VISIBLE;
- numvis++;
- }
- if(numvis > 1)
- break;
- }
- assert(numvis > 1 );
- }
- }
-
- return 0;
-}
-
-/*void Environment::TestCamera(int camind)
-{
- CvPoint3D64f* board_pts = m_body->GetPoints3D(false);
-
- int count = 0;
- for( int j = 0; j < m_body->NumPoints(); j++ )
- {
- if( m_point_visibility[camind][j] == PT_VISIBLE )
- count++;
- }
-
- CvMat* object_points = cvCreateMat( 1, count, CV_64FC3 );
- CvMat* image_points = cvCreateMat( 1, count, CV_64FC2 );
- CvMat* intrinsic_matrix = cvCreateMatHeader( 3, 3, CV_64FC1 );
- cvSetData(intrinsic_matrix, m_cameras[camind]->GetIntrinsics(), 3*sizeof(double) );
-
- CvMat* distortion_coeffs = cvCreateMat( 4, 1, CV_64FC1 ); cvSetZero(distortion_coeffs);
- CvMat* rotation_vector = cvCreateMat( 3, 1, CV_64FC1 );
- CvMat* translation_vector = cvCreateMat( 3, 1, CV_64FC1 );
-
- CvMat* rotation_matrix = cvCreateMat( 3, 3, CV_64FC1 );
-
- //loop over points and assign visibility flag to them
- int ind = 0;
- for( int j = 0; j < m_body->NumPoints(); j++ )
- {
- if( m_point_visibility[camind][j] == PT_VISIBLE)
- {
- //add to matrix
- *((CvPoint3D64f*)(object_points->data.db + ind*3)) = board_pts[j];
- *((CvPoint2D64f*)(image_points->data.db + ind*2)) = m_image_points[camind][j];
- ind++;
- }
- }
-
-
- //find extrinsic parameters of the board
- cvFindExtrinsicCameraParams2( object_points,
- image_points,
- intrinsic_matrix,
- distortion_coeffs,
- rotation_vector,
- translation_vector );
-
- //cvRodrigues2( rotation_vector, rotation_matrix );
-
-
- //reproject points and see error of reprojection
-
- CvMat* image_points_repro = cvCloneMat( image_points );
-
- cvProjectPoints2( object_points, rotation_vector, translation_vector, intrinsic_matrix, distortion_coeffs,
- image_points_repro );
-
- for( int j = 0; j < image_points_repro->cols; j++ )
- {
- CvPoint2D64f pt_orig = *((CvPoint2D64f*)(image_points->data.db + j*2));
- CvPoint2D64f pt_repro = *((CvPoint2D64f*)(image_points_repro->data.db + j*2));
-
- CvPoint2D64f diff;
- diff.x = pt_repro.x - pt_orig.x;
- diff.y = pt_repro.y - pt_orig.y;
-
- }
-} */
-
-int Environment::Save(char* filename)
-{
- int* ind = m_body->GetPointsIds();
- FILE* saveFile = fopen( filename, "w" );
- if(saveFile)
- {
- for( size_t cam_index = 0; cam_index < m_cameras.size(); cam_index++ )
- {
- CvPoint2D64f* image_points = m_image_points[cam_index];
-
- int numPnt = 0; //no visible points by default
-
- //check points visibility
- //camera is visible, check individual points
- for(int i = 0; i < m_body->NumPoints(); i++ )
- {
- if( m_point_visibility[cam_index][i] == PT_VISIBLE)
- {
- //point is visible
- numPnt++;
- }
- }
-
- if(numPnt) //some points are visible
- {
- for( int i = 0; i < m_body->NumPoints(); i++)
- {
- if( m_point_visibility[cam_index][i] == PT_VISIBLE )
- {
- //point is visible
- fprintf(saveFile, "%d %d %d %.12f %.12f\n", 0 /*snapshot_id*/, (int)cam_index, ind[i], image_points[i].x, image_points[i].y );
- }
- }
- }
-
- }
- }
-
- //close file
- fclose(saveFile);
- return 0;
-}
-
-
-
-
-//input parameters for envirinment generation
-struct Params
-{
- int width; //width of images
- int height; //height of images
- float FOVx; //camera field of view in horizontal direction. vertical FOV is detected from aspect ratio
- float noise; //corners projection noise
- float k1, k2, k3; //radial distortion coeffs
- float p1,p2; //tangential distortion coeffs
-};
-
-int GenerateTestData2(Params& params)
-{
- //create environment
- Environment* env = new Environment();
- env->SetNoise(params.noise);
-
- CvSize im_res = cvSize(params.width,params.height);
-
- double FOVx = params.FOVx; // field of view relatively to width (in degrees)
- double fov_rad = FOVx * CV_PI / 180;
- double fx = im_res.width/2.0 / tan( fov_rad/2);
- double fy = fx;
- double cx = im_res.width/2.0-0.5;
- double cy = im_res.height/2.0-0.5;
-
- //model cube room of size 2x2x2 meters
- //8 cameras on the perimeter at the height 1 meter in corners and in the middle of walls
- // all they look to the center of the room
- //coordinate center in the center of the cube
- //Z coordinate is oriented up
-
- Camera* cam[8];
- for( int i = 0; i < 8; i++ )
- {
- cam[i] = new Camera();
- cam[i]->SetDistortion(params.k1, params.k2,0,0); //only radial distortion
- cam[i]->SetIntrinsics(fx,fy, cx, cy ); //fx,fy,cx,cy
- cam[i]->SetResolution(im_res);
- env->AddCamera(cam[i]);
- }
-
- //set positions
- cam[0]->SetPosition( 1.,1.,0);
- cam[1]->SetPosition( 0.,1.,0);
- cam[2]->SetPosition( -1.,1.,0);
- cam[3]->SetPosition( -1.,0.,0);
- cam[4]->SetPosition( -1.,-1.,0);
- cam[5]->SetPosition( 0.,-1.,0);
- cam[6]->SetPosition( 1.,-1.,0);
- cam[7]->SetPosition( 1.,0.,0);
-
- //set rotation matrices
- //they will be oriented strongly vertically and rotated only around vertical axis (Z coorinate in WCS)
-
- CvMat* camrot = cvCreateMat( 3, 3, CV_64FC1);
-
- for( int i = 0; i < 8; i++ )
- {
- //y of the camera is oriented along negative Z of WCS
- double yDirCamera[3] = {0,0,-1};
- double zDirCamera[3]; //oriented from camera center to WCS center
- double* pos = cam[i]->GetPosition();
- zDirCamera[0] = -pos[0];
- zDirCamera[1] = -pos[1];
- zDirCamera[2] = -pos[2];
-
- double xDirCamera[3]; //cross product Y*Z
- xDirCamera[0] = yDirCamera[1]*zDirCamera[2] - yDirCamera[2]*zDirCamera[1];
- xDirCamera[1] = yDirCamera[2]*zDirCamera[0] - yDirCamera[0]*zDirCamera[2];
- xDirCamera[2] = yDirCamera[0]*zDirCamera[1] - yDirCamera[1]*zDirCamera[0];
-
- //normalize z and x
- double inv_norm = 1.0/sqrt(xDirCamera[0]*xDirCamera[0] + xDirCamera[1]*xDirCamera[1] + xDirCamera[2]*xDirCamera[2]);
- xDirCamera[0]*=inv_norm;
- xDirCamera[1]*=inv_norm;
- xDirCamera[2]*=inv_norm;
-
- inv_norm = 1.0 / sqrt(zDirCamera[0]*zDirCamera[0] + zDirCamera[1]*zDirCamera[1] + zDirCamera[2]*zDirCamera[2]);
- zDirCamera[0] *= inv_norm;
- zDirCamera[1] *= inv_norm;
- zDirCamera[2] *= inv_norm;
-
- camrot->data.db[0] = xDirCamera[0];
- camrot->data.db[3] = xDirCamera[1];
- camrot->data.db[6] = xDirCamera[2];
-
- camrot->data.db[1] = yDirCamera[0];
- camrot->data.db[4] = yDirCamera[1];
- camrot->data.db[7] = yDirCamera[2];
-
- camrot->data.db[2] = zDirCamera[0];
- camrot->data.db[5] = zDirCamera[1];
- camrot->data.db[8] = zDirCamera[2];
-
- //get inverse matrix (equal to transposed)
- cvTranspose(camrot, camrot);
-
- cam[i]->SetRotation(camrot->data.db);
- cam[i]->ComputeTranslation();// compute translation after we set position and rotation matrix
- }
-
-#if defined WIN32 || defined _WIN32
- _mkdir(g_filepath);
-#else
- mkdir(g_filepath, S_IRWXU | S_IRWXG | S_IROTH | S_IXOTH);
-#endif
- char fname[2048];
- sprintf(fname, "%scameras.txt", g_filepath );
- FILE* clist = fopen(fname, "w");
- for(unsigned int i = 0; i < 8; i++)
- {
- sprintf(fname, "%scamera%d.calib", g_filepath, i );
- FILE *calibFile = fopen(fname,"w");
- cam[i]->saveCamParams(calibFile);
- fclose( calibFile );
- fprintf(clist, "%s\n", fname);
- }
- fclose(clist);
-
- std::vector<CvPoint3D64f> board_pos;
- board_pos.clear();
-
- //generate body position, set zero for now
- CvPoint3D64f pos;
- pos.x = 0; pos.y = 0; pos.z = 0;
- board_pos.push_back(pos);
-
- RigidBody* body = env->GetBody();
- body->generate_random(50, -0.25, 0.25, -0.25, 0.25, -0.25, 0.25 );
-
- CvRNG rng = cvRNG();
- int index = 0; //index of board's position to save, is used to enumerate snapshots
-
- for(size_t i = 0; i < board_pos.size(); i++ )
- {
- CvPoint3D64f point = board_pos[i];
- body->SetPosition(point.x,point.y,point.z);
-
- //generate random orientation of the board
- unsigned int rn = cvRandInt(&rng);
- //scale to 90 degrees
- rn = rn%90;
- double slant = (double)rn-45-90; //angle of slant of the bord relatively to its horizontal direction
-
- rn = cvRandInt(&rng);
- //scale to 360 degrees
- rn = rn%360;
- double azimuth = rn; //azimuth
-
-
- //set slant and azimuth to 0
- slant = azimuth = 0;
-
- double sn = sin(azimuth*CV_PI/180);
- double cs = cos(azimuth*CV_PI/180);
-
- //generate rotation matrix
- CvMat* mat_azimuth = cvCreateMat( 3, 3, CV_64FC1);
- mat_azimuth->data.db[0] = cs;
- mat_azimuth->data.db[1] = -sn;
- mat_azimuth->data.db[2] = 0;
-
- mat_azimuth->data.db[3] = sn;
- mat_azimuth->data.db[4] = cs;
- mat_azimuth->data.db[5] = 0;
-
- mat_azimuth->data.db[6] = 0;
- mat_azimuth->data.db[7] = 0;
- mat_azimuth->data.db[8] = 1;
-
- sn = sin(slant*CV_PI/180);
- cs = cos(slant*CV_PI/180);
- CvMat* mat_slant = cvCreateMat( 3, 3, CV_64FC1); //rotation around X axis
- mat_slant->data.db[0] = 1;
- mat_slant->data.db[1] = 0;
- mat_slant->data.db[2] = 0;
-
- mat_slant->data.db[3] = 0;
- mat_slant->data.db[4] = cs;
- mat_slant->data.db[5] = -sn;
-
- mat_slant->data.db[6] = 0;
- mat_slant->data.db[7] = sn;
- mat_slant->data.db[8] = cs;
-
- CvMat* rot = cvCreateMat( 3, 3, CV_64FC1); //rotation around X axis
- //create complete rotation matrix
- cvMatMul(mat_azimuth, mat_slant, rot);
-
- //these are coordinates of board's axis in WCS
- body->SetRotation(rot->data.db);
-
- //project images onto all cameras
- env->Capture();
-
- //save 3d points of corners into the file
- char fname[2048];
- sprintf(fname, "%sPoints%d.3d", g_filepath, index );
- body->Save(fname, true);
- //save shots from camera
-
- sprintf(fname, "%salldata.txt", g_filepath );
- env->Save(fname);
- }
- //destroy everything
- delete env;
- return 0;
-}
-
-int TestLevmar2()
-{
- //load data from file
-
- // 1. load ground truth 3D points
- RigidBody body;
-
- char fname[2048];
- sprintf(fname, "%sPoints0.3d", g_filepath );
- body.Load(fname);
- int num_points = body.NumPoints();
-
- // 2. load cameras
- int num_cams = 0;
- //int num_cam_param = 10;
- std::vector<Camera*> cams;
-
- sprintf(fname, "%scameras.txt", g_filepath );
- FILE* fp = fopen(fname, "r" );
- while( !feof(fp) )
- {
- char fname[MAX_PATH];
- fscanf(fp, "%s\n", fname );
- Camera* newcam = new Camera();
- FILE* fp2 = fopen( fname, "r" );
- newcam->readCamParams(fp2);
- cams.push_back(newcam);
- fclose(fp2);
- num_cams++;
- }
- fclose(fp);
-
- // 2. Load projection data
- CvMat* m = cvCreateMat( body.NumPoints(), num_cams, CV_64FC2 );
- //all invisible point will have (-1,-1) projection
- cvSet( m, cvScalar(-1,-1) );
-
- sprintf(fname, "%salldata.txt", g_filepath );
- fp = fopen( fname, "r");
-
- int counter = 0;
- while( !feof(fp) )
- {
- //read line
- int snapid, cameraid, pointid;
- double x,y;
- fscanf(fp, "%d %d %d %lf %lf\n", &snapid, &cameraid, &pointid, &x, &y);
- cvSet2D(m, pointid, cameraid, cvScalar(x,y) );
- counter++;
- }
-
- vector<vector<int> > visibility;
-
- //transform this matrix to measurement vector
- vector<vector<Point2d> > imagePoints;
-
- for(int j = 0; j < num_cams; j++ )
- {
- vector<Point2d> vec;
- vector<int> visvec;
- for(int i = 0; i < num_points; i++ )
- {
- CvScalar s = cvGet2D( m, i, j );
- if( s.val[0] != -1 ) //point is visible
- {
- vec.push_back(Point2d(s.val[0],s.val[1]));
- visvec.push_back(1);
- }
- else
- {
- vec.push_back(Point2d(DBL_MAX,DBL_MAX));
- visvec.push_back(0);
- }
- }
- imagePoints.push_back(vec);
- visibility.push_back(visvec);
- }
-
- //form initial params
- vector<Mat> cameraMatrix; //intrinsic matrices of all cameras (input and output)
- vector<Mat> R; //rotation matrices of all cameras (input and output)
- vector<Mat> T; //translation vector of all cameras (input and output)
- vector<Mat> distCoeffs; //distortion coefficients of all cameras (input and output)
-
- //store original camera positions
- vector<Mat> T_backup;
- //store original camera rotations
- vector<Mat> R_backup;
- //store original intrinsic matrix
- vector<Mat> cameraMatrix_backup;
- //store original distortion
- vector<Mat> distCoeffs_backup;
-
- for( int i = 0; i < (int)cams.size(); i++ )
- {
- //fill params
- Camera* c = cams[i];
- //rotation
- double* rotmat = c->GetRotation();
- Mat rm(3,3,CV_64F,rotmat);
- R_backup.push_back(rm);
- //generate small random rotation
- Mat rodr; Rodrigues(rm, rodr);
- double n = norm(rodr);
- //add small angle
- //add about 5 degrees to rotation
- rodr *= ((n+0.1)/n);
- Rodrigues(rodr, rm);
- R.push_back(rm);
-
- //translation
- double* tr = c->GetTranslation();
- Mat tv(Size(1,3), CV_64F, tr);
- T_backup.push_back(tv);
- //add random translation within 1 cm
- Mat t_(3,1,CV_64F);
- randu(t_, -0.01, 0.01);
- tv+=t_;
-
- T.push_back(tv);
- //intrinsic matrix
- double* intr = c->GetIntrinsics();
- cameraMatrix_backup.push_back(Mat(Size(3,3), CV_64F, intr));
- cameraMatrix.push_back(Mat(Size(3,3), CV_64F, intr));
-
- //distortion
- Mat d(4, 1, CV_64F, c->GetDistortion() );
- distCoeffs_backup.push_back(d);
-
- //variate distortion by 5%
- d*=1.05;
- distCoeffs.push_back(d);
-
- }
-
- //form input points
- const Point3d* ptptr = (const Point3d*)body.GetPoints3D(true);
- vector<Point3d> points(ptptr, ptptr + num_points);
- //store points
- vector<Point3d> points_backup(num_points);
- std::copy(points.begin(), points.end(), points_backup.begin());
-
- //variate initial points
- CvRNG rng;
- CvMat* values = cvCreateMat( num_points*3, 1, CV_64F );
- cvRandArr( &rng, values, CV_RAND_NORMAL,
- cvScalar(0.0), // mean
- cvScalar(0.02) // deviation (in meters)
- );
- CvMat tmp = cvMat(values->rows, values->cols, values->type, &points[0] );
- cvAdd( &tmp, values, &tmp );
- cvReleaseMat( &values );
-
- LevMarqSparse::bundleAdjust( points, //positions of points in global coordinate system (input and output)
- imagePoints, //projections of 3d points for every camera
- visibility, //visibility of 3d points for every camera
- cameraMatrix, //intrinsic matrices of all cameras (input and output)
- R, //rotation matrices of all cameras (input and output)
- T, //translation vector of all cameras (input and output)
- distCoeffs, //distortion coefficients of all cameras (input and output)
- TermCriteria(TermCriteria::COUNT|TermCriteria::EPS, 3000, DBL_EPSILON ));
- //,enum{MOTION_AND_STRUCTURE,MOTION,STRUCTURE})
-
- //compare input points and found points
- double maxdist = 0;
- for( size_t i = 0; i < points.size(); i++ )
- {
- Point3d in = points_backup[i];
- Point3d out = points[i];
- double dist = sqrt(in.dot(out));
- if(dist > maxdist)
- maxdist = dist;
- }
- printf("Maximal distance between points: %.12lf\n", maxdist );
-
- //compare camera positions
- maxdist = 0;
- for( size_t i = 0; i < T.size(); i++ )
- {
- double dist = norm(T[i], T_backup[i]);
-
- if(dist > maxdist)
- maxdist = dist;
- }
- printf("Maximal distance between cameras centers: %.12lf\n", maxdist );
-
- //compare rotation matrices
- maxdist = 0;
- for( size_t i = 0; i < R.size(); i++ )
- {
- double dist = norm(R[i], R_backup[i], NORM_INF);
-
- if(dist > maxdist)
- maxdist = dist;
- }
- printf("Maximal difference in rotation matrices elements: %.12lf\n", maxdist );
-
- //compare intrinsic matrices
- maxdist = 0;
- double total_diff = 0;
- for( size_t i = 0; i < cameraMatrix.size(); i++ )
- {
- double fx_ratio = cameraMatrix[i].at<double>(0,0)/
- cameraMatrix_backup[i].at<double>(0,0);
- double fy_ratio = cameraMatrix[i].at<double>(1,1)/
- cameraMatrix_backup[i].at<double>(1,1);
- double cx_diff = cameraMatrix[i].at<double>(0,2) -
- cameraMatrix_backup[i].at<double>(0,2);
- double cy_diff = cameraMatrix[i].at<double>(1,2) -
- cameraMatrix_backup[i].at<double>(1,2);
- total_diff += fabs(fx_ratio - 1) + fabs(fy_ratio - 1) + fabs(cx_diff) + fabs(cy_diff);
- }
- //ts->printf(CvTS::LOG, "total diff = %g\n", total_diff);
-
- return 1;
-}
-
-
-class CV_BundleAdjustmentTest : public CvTest
-{
-
-public:
- CV_BundleAdjustmentTest();
- ~CV_BundleAdjustmentTest();
- void clear();
- //int write_default_params(CvFileStorage* fs);
-
-protected:
- //int read_params( CvFileStorage* fs );
- int compare(double* val, double* ref_val, int len,
- double eps, const char* param_name);
-
- void run(int);
-};
-
-
-CV_BundleAdjustmentTest::CV_BundleAdjustmentTest():
- CvTest( "bundleadjust", "bundleAdjust" )
-{
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;
-}
-
-
-CV_BundleAdjustmentTest::~CV_BundleAdjustmentTest()
-{
- clear();
-}
-
-
-void CV_BundleAdjustmentTest::clear()
-{
- CvTest::clear();
-}
-
-
-int CV_BundleAdjustmentTest::compare(double* val, double* ref_val, int len,
- double eps, const char* param_name )
-{
- return cvTsCmpEps2_64f( ts, val, ref_val, len, eps, param_name );
-}
-
-void CV_BundleAdjustmentTest::run( int start_from )
-{
- int code = CvTS::OK;
- char filepath[100];
- char filename[100];
-
- CvSize imageSize;
- int numImages;
- CvSize etalonSize;
-
- CvPoint2D64f* imagePoints;
- CvPoint3D64f* objectPoints;
- CvPoint2D64f* reprojectPoints;
-
- double* transVects;
- double* rotMatrs;
-
- double* goodTransVects;
- double* goodRotMatrs;
-
- double cameraMatrix[3*3];
- double distortion[4];
-
- double goodDistortion[4];
-
- int* numbers;
- FILE* file = 0;
- FILE* datafile = 0;
- int i,j;
- int currImage;
- int currPoint;
-
- int calibFlags;
- char i_dat_file[100];
- int numPoints;
- int numTests;
- int currTest;
-
- imagePoints = 0;
- objectPoints = 0;
- reprojectPoints = 0;
- numbers = 0;
-
- transVects = 0;
- rotMatrs = 0;
- goodTransVects = 0;
- goodRotMatrs = 0;
- int progress = 0;
-
- //generate test data
- Params params;
- //set default params
-
- params.FOVx = 30;
- params.height = 480;
- params.width = 640;
- //params.noise = 0.25f;
- params.k1 = -0.5f;
- params.k2 = -0.5f;
- params.k3 = 0.0f;
- params.noise = 0.0f;
- params.p1 = 0;
- params.p2 = 0;
-
- sprintf( g_filepath, "%sSBA/", ts->get_data_path() );
-
- GenerateTestData2(params);
- TestLevmar2();
-
- sprintf( filepath, "%scameracalibration/", ts->get_data_path() );
- sprintf( filename, "%sdatafiles.txt", filepath );
- datafile = fopen( filename, "r" );
- if( datafile == 0 )
- {
- ts->printf( CvTS::LOG, "Could not open file with list of test files: %s\n", filename );
- code = CvTS::FAIL_MISSING_TEST_DATA;
- goto _exit_;
- }
-
- fscanf(datafile,"%d",&numTests);
-
- for( currTest = start_from; currTest < numTests; currTest++ )
- {
- progress = update_progress( progress, currTest, numTests, 0 );
- fscanf(datafile,"%s",i_dat_file);
- sprintf(filename, "%s%s", filepath, i_dat_file);
- file = fopen(filename,"r");
-
- ts->update_context( this, currTest, true );
-
- if( file == 0 )
- {
- ts->printf( CvTS::LOG,
- "Can't open current test file: %s\n",filename);
- if( numTests == 1 )
- {
- code = CvTS::FAIL_MISSING_TEST_DATA;
- goto _exit_;
- }
- continue; // if there is more than one test, just skip the test
- }
-
- fscanf(file,"%d %d\n",&(imageSize.width),&(imageSize.height));
- if( imageSize.width <= 0 || imageSize.height <= 0 )
- {
- ts->printf( CvTS::LOG, "Image size in test file is incorrect\n" );
- code = CvTS::FAIL_INVALID_TEST_DATA;
- goto _exit_;
- }
-
- /* Read etalon size */
- fscanf(file,"%d %d\n",&(etalonSize.width),&(etalonSize.height));
- if( etalonSize.width <= 0 || etalonSize.height <= 0 )
- {
- ts->printf( CvTS::LOG, "Pattern size in test file is incorrect\n" );
- code = CvTS::FAIL_INVALID_TEST_DATA;
- goto _exit_;
- }
-
- numPoints = etalonSize.width * etalonSize.height;
-
- /* Read number of images */
- fscanf(file,"%d\n",&numImages);
- if( numImages <=0 )
- {
- ts->printf( CvTS::LOG, "Number of images in test file is incorrect\n");
- code = CvTS::FAIL_INVALID_TEST_DATA;
- goto _exit_;
- }
-
- /* Need to allocate memory */
- imagePoints = (CvPoint2D64f*)cvAlloc( numPoints *
- numImages * sizeof(CvPoint2D64f));
-
- objectPoints = (CvPoint3D64f*)cvAlloc( numPoints *
- numImages * sizeof(CvPoint3D64f));
-
- reprojectPoints = (CvPoint2D64f*)cvAlloc( numPoints *
- numImages * sizeof(CvPoint2D64f));
-
- /* Alloc memory for numbers */
- numbers = (int*)cvAlloc( numImages * sizeof(int));
-
- /* Fill it by numbers of points of each image*/
- for( currImage = 0; currImage < numImages; currImage++ )
- {
- numbers[currImage] = etalonSize.width * etalonSize.height;
- }
-
- /* Allocate memory for translate vectors and rotmatrixs*/
- transVects = (double*)cvAlloc(3 * 1 * numImages * sizeof(double));
- rotMatrs = (double*)cvAlloc(3 * 3 * numImages * sizeof(double));
-
- goodTransVects = (double*)cvAlloc(3 * 1 * numImages * sizeof(double));
- goodRotMatrs = (double*)cvAlloc(3 * 3 * numImages * sizeof(double));
-
- /* Read object points */
- i = 0;/* shift for current point */
- for( currImage = 0; currImage < numImages; currImage++ )
- {
- for( currPoint = 0; currPoint < numPoints; currPoint++ )
- {
- double x,y,z;
- fscanf(file,"%lf %lf %lf\n",&x,&y,&z);
-
- (objectPoints+i)->x = x;
- (objectPoints+i)->y = y;
- (objectPoints+i)->z = z;
- i++;
- }
- }
-
- /* Read image points */
- i = 0;/* shift for current point */
- for( currImage = 0; currImage < numImages; currImage++ )
- {
- for( currPoint = 0; currPoint < numPoints; currPoint++ )
- {
- double x,y;
- fscanf(file,"%lf %lf\n",&x,&y);
-
- (imagePoints+i)->x = x;
- (imagePoints+i)->y = y;
- i++;
- }
- }
-
- /* Read good data computed before */
-
- /* Focal lengths */
- double goodFcx,goodFcy;
- fscanf(file,"%lf %lf",&goodFcx,&goodFcy);
-
- /* Principal points */
- double goodCx,goodCy;
- fscanf(file,"%lf %lf",&goodCx,&goodCy);
-
- /* Read distortion */
-
- fscanf(file,"%lf",goodDistortion+0);
- fscanf(file,"%lf",goodDistortion+1);
- fscanf(file,"%lf",goodDistortion+2);
- fscanf(file,"%lf",goodDistortion+3);
-
- /* Read good Rot matrixes */
- for( currImage = 0; currImage < numImages; currImage++ )
- {
- for( i = 0; i < 3; i++ )
- for( j = 0; j < 3; j++ )
- fscanf(file, "%lf", goodRotMatrs + currImage * 9 + j * 3 + i);
- }
-
- /* Read good Trans vectors */
- for( currImage = 0; currImage < numImages; currImage++ )
- {
- for( i = 0; i < 3; i++ )
- fscanf(file, "%lf", goodTransVects + currImage * 3 + i);
- }
-
- calibFlags =
- //CV_CALIB_FIX_PRINCIPAL_POINT +
- //CV_CALIB_ZERO_TANGENT_DIST +
- //CV_CALIB_FIX_ASPECT_RATIO +
- //CV_CALIB_USE_INTRINSIC_GUESS +
- 0;
- memset( cameraMatrix, 0, 9*sizeof(cameraMatrix[0]) );
- cameraMatrix[0] = cameraMatrix[4] = 807.;
- cameraMatrix[2] = (imageSize.width - 1)*0.5;
- cameraMatrix[5] = (imageSize.height - 1)*0.5;
- cameraMatrix[8] = 1.;
-
- /* Now we can calibrate camera */
- cvCalibrateCamera_64f( numImages,
- numbers,
- imageSize,
- imagePoints,
- objectPoints,
- distortion,
- cameraMatrix,
- transVects,
- rotMatrs,
- calibFlags );
-
- /* ---- Reproject points to the image ---- */
- for( currImage = 0; currImage < numImages; currImage++ )
- {
- int numPoints = etalonSize.width * etalonSize.height;
- cvProjectPointsSimple( numPoints,
- objectPoints + currImage * numPoints,
- rotMatrs + currImage * 9,
- transVects + currImage * 3,
- cameraMatrix,
- distortion,
- reprojectPoints + currImage * numPoints);
- }
-
-
- /* ----- Compute reprojection error ----- */
- i = 0;
- double dx,dy;
- double rx,ry;
- double meanDx,meanDy;
- double maxDx = 0.0;
- double maxDy = 0.0;
-
- meanDx = 0;
- meanDy = 0;
- for( currImage = 0; currImage < numImages; currImage++ )
- {
- for( currPoint = 0; currPoint < etalonSize.width * etalonSize.height; currPoint++ )
- {
- rx = reprojectPoints[i].x;
- ry = reprojectPoints[i].y;
- dx = rx - imagePoints[i].x;
- dy = ry - imagePoints[i].y;
-
- meanDx += dx;
- meanDy += dy;
-
- dx = fabs(dx);
- dy = fabs(dy);
-
- if( dx > maxDx )
- maxDx = dx;
-
- if( dy > maxDy )
- maxDy = dy;
- i++;
- }
- }
-
- meanDx /= numImages * etalonSize.width * etalonSize.height;
- meanDy /= numImages * etalonSize.width * etalonSize.height;
-
- /* ========= Compare parameters ========= */
-
- /* ----- Compare focal lengths ----- */
- code = compare(cameraMatrix+0,&goodFcx,1,0.01,"fx");
- if( code < 0 )
- goto _exit_;
-
- code = compare(cameraMatrix+4,&goodFcy,1,0.01,"fy");
- if( code < 0 )
- goto _exit_;
-
- /* ----- Compare principal points ----- */
- code = compare(cameraMatrix+2,&goodCx,1,0.01,"cx");
- if( code < 0 )
- goto _exit_;
-
- code = compare(cameraMatrix+5,&goodCy,1,0.01,"cy");
- if( code < 0 )
- goto _exit_;
-
- /* ----- Compare distortion ----- */
- code = compare(distortion,goodDistortion,4,0.01,"[k1,k2,p1,p2]");
- if( code < 0 )
- goto _exit_;
-
- /* ----- Compare rot matrixs ----- */
- code = compare(rotMatrs,goodRotMatrs, 9*numImages,0.05,"rotation matrices");
- if( code < 0 )
- goto _exit_;
-
- /* ----- Compare rot matrixs ----- */
- code = compare(transVects,goodTransVects, 3*numImages,0.05,"translation vectors");
- if( code < 0 )
- goto _exit_;
-
- if( maxDx > 1.0 )
- {
- ts->printf( CvTS::LOG,
- "Error in reprojection maxDx=%f > 1.0\n",maxDx);
- code = CvTS::FAIL_BAD_ACCURACY; goto _exit_;
- }
-
- if( maxDy > 1.0 )
- {
- ts->printf( CvTS::LOG,
- "Error in reprojection maxDy=%f > 1.0\n",maxDy);
- code = CvTS::FAIL_BAD_ACCURACY; goto _exit_;
- }
-
- cvFree(&imagePoints);
- cvFree(&objectPoints);
- cvFree(&reprojectPoints);
- cvFree(&numbers);
-
- cvFree(&transVects);
- cvFree(&rotMatrs);
- cvFree(&goodTransVects);
- cvFree(&goodRotMatrs);
-
- fclose(file);
- file = 0;
- }
-
-_exit_:
-
- if( file )
- fclose(file);
-
- if( datafile )
- fclose(datafile);
-
- /* Free all allocated memory */
- cvFree(&imagePoints);
- cvFree(&objectPoints);
- cvFree(&reprojectPoints);
- cvFree(&numbers);
-
- cvFree(&transVects);
- cvFree(&rotMatrs);
- cvFree(&goodTransVects);
- cvFree(&goodRotMatrs);
-
- if( code < 0 )
- ts->set_failed_test_info( code );
-}
-
-//CV_BundleAdjustmentTest bundleadjustment_test;
-
-#endif
-
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////\r
-//\r
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.\r
-//\r
-// By downloading, copying, installing or using the software you agree to this license.\r
-// If you do not agree to this license, do not download, install,\r
-// copy or use the software.\r
-//\r
-//\r
-// Intel License Agreement\r
-// For Open Source Computer Vision Library\r
-//\r
-// Copyright (C) 2000, Intel Corporation, all rights reserved.\r
-// Third party copyrights are property of their respective owners.\r
-//\r
-// Redistribution and use in source and binary forms, with or without modification,\r
-// are permitted provided that the following conditions are met:\r
-//\r
-// * Redistribution's of source code must retain the above copyright notice,\r
-// this list of conditions and the following disclaimer.\r
-//\r
-// * Redistribution's in binary form must reproduce the above copyright notice,\r
-// this list of conditions and the following disclaimer in the documentation\r
-// and/or other materials provided with the distribution.\r
-//\r
-// * The name of Intel Corporation may not be used to endorse or promote products\r
-// derived from this software without specific prior written permission.\r
-//\r
-// This software is provided by the copyright holders and contributors "as is" and\r
-// any express or implied warranties, including, but not limited to, the implied\r
-// warranties of merchantability and fitness for a particular purpose are disclaimed.\r
-// In no event shall the Intel Corporation or contributors be liable for any direct,\r
-// indirect, incidental, special, exemplary, or consequential damages\r
-// (including, but not limited to, procurement of substitute goods or services;\r
-// loss of use, data, or profits; or business interruption) however caused\r
-// and on any theory of liability, whether in contract, strict liability,\r
-// or tort (including negligence or otherwise) arising in any way out of\r
-// the use of this software, even if advised of the possibility of such damage.\r
-//\r
-//M*/\r
-\r
-#include "cvtest.h"\r
-#include <limits>\r
-\r
-#if 0\r
-class CV_ProjectPointsTest : public CvArrTest\r
-{\r
-public:\r
- CV_ProjectPointsTest();\r
-\r
-protected:\r
- int read_params( CvFileStorage* fs );\r
- void fill_array( int test_case_idx, int i, int j, CvMat* arr );\r
- int prepare_test_case( int test_case_idx );\r
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );\r
- double get_success_error_level( int test_case_idx, int i, int j );\r
- void run_func();\r
- void prepare_to_validation( int );\r
-\r
- bool calc_jacobians;\r
-};\r
-\r
-\r
-CV_ProjectPointsTest::CV_ProjectPointsTest()\r
- : CvArrTest( "3d-ProjectPoints", "cvProjectPoints2", "" )\r
-{\r
- test_array[INPUT].push(NULL); // rotation vector\r
- test_array[OUTPUT].push(NULL); // rotation matrix\r
- test_array[OUTPUT].push(NULL); // jacobian (J)\r
- test_array[OUTPUT].push(NULL); // rotation vector (backward transform result)\r
- test_array[OUTPUT].push(NULL); // inverse transform jacobian (J1)\r
- test_array[OUTPUT].push(NULL); // J*J1 (or J1*J) == I(3x3)\r
- test_array[REF_OUTPUT].push(NULL);\r
- test_array[REF_OUTPUT].push(NULL);\r
- test_array[REF_OUTPUT].push(NULL);\r
- test_array[REF_OUTPUT].push(NULL);\r
- test_array[REF_OUTPUT].push(NULL);\r
-\r
- element_wise_relative_error = false;\r
- calc_jacobians = false;\r
-\r
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;\r
- default_timing_param_names = 0;\r
-}\r
-\r
-\r
-int CV_ProjectPointsTest::read_params( CvFileStorage* fs )\r
-{\r
- int code = CvArrTest::read_params( fs );\r
- return code;\r
-}\r
-\r
-\r
-void CV_ProjectPointsTest::get_test_array_types_and_sizes(\r
- int /*test_case_idx*/, CvSize** sizes, int** types )\r
-{\r
- CvRNG* rng = ts->get_rng();\r
- int depth = cvTsRandInt(rng) % 2 == 0 ? CV_32F : CV_64F;\r
- int i, code;\r
-\r
- code = cvTsRandInt(rng) % 3;\r
- types[INPUT][0] = CV_MAKETYPE(depth, 1);\r
-\r
- if( code == 0 )\r
- {\r
- sizes[INPUT][0] = cvSize(1,1);\r
- types[INPUT][0] = CV_MAKETYPE(depth, 3);\r
- }\r
- else if( code == 1 )\r
- sizes[INPUT][0] = cvSize(3,1);\r
- else\r
- sizes[INPUT][0] = cvSize(1,3);\r
-\r
- sizes[OUTPUT][0] = cvSize(3, 3);\r
- types[OUTPUT][0] = CV_MAKETYPE(depth, 1);\r
-\r
- types[OUTPUT][1] = CV_MAKETYPE(depth, 1);\r
-\r
- if( cvTsRandInt(rng) % 2 )\r
- sizes[OUTPUT][1] = cvSize(3,9);\r
- else\r
- sizes[OUTPUT][1] = cvSize(9,3);\r
-\r
- types[OUTPUT][2] = types[INPUT][0];\r
- sizes[OUTPUT][2] = sizes[INPUT][0];\r
-\r
- types[OUTPUT][3] = types[OUTPUT][1];\r
- sizes[OUTPUT][3] = cvSize(sizes[OUTPUT][1].height, sizes[OUTPUT][1].width);\r
-\r
- types[OUTPUT][4] = types[OUTPUT][1];\r
- sizes[OUTPUT][4] = cvSize(3,3);\r
-\r
- calc_jacobians = 1;//cvTsRandInt(rng) % 3 != 0;\r
- if( !calc_jacobians )\r
- sizes[OUTPUT][1] = sizes[OUTPUT][3] = sizes[OUTPUT][4] = cvSize(0,0);\r
-\r
- for( i = 0; i < 5; i++ )\r
- {\r
- types[REF_OUTPUT][i] = types[OUTPUT][i];\r
- sizes[REF_OUTPUT][i] = sizes[OUTPUT][i];\r
- }\r
-}\r
-\r
-\r
-double CV_ProjectPointsTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int j )\r
-{\r
- return j == 4 ? 1e-2 : 1e-2;\r
-}\r
-\r
-\r
-void CV_ProjectPointsTest::fill_array( int /*test_case_idx*/, int /*i*/, int /*j*/, CvMat* arr )\r
-{\r
- double r[3], theta0, theta1, f;\r
- CvMat _r = cvMat( arr->rows, arr->cols, CV_MAKETYPE(CV_64F,CV_MAT_CN(arr->type)), r );\r
- CvRNG* rng = ts->get_rng();\r
-\r
- r[0] = cvTsRandReal(rng)*CV_PI*2;\r
- r[1] = cvTsRandReal(rng)*CV_PI*2;\r
- r[2] = cvTsRandReal(rng)*CV_PI*2;\r
-\r
- theta0 = sqrt(r[0]*r[0] + r[1]*r[1] + r[2]*r[2]);\r
- theta1 = fmod(theta0, CV_PI*2);\r
-\r
- if( theta1 > CV_PI )\r
- theta1 = -(CV_PI*2 - theta1);\r
-\r
- f = theta1/(theta0 ? theta0 : 1);\r
- r[0] *= f;\r
- r[1] *= f;\r
- r[2] *= f;\r
-\r
- cvTsConvert( &_r, arr );\r
-}\r
-\r
-\r
-int CV_ProjectPointsTest::prepare_test_case( int test_case_idx )\r
-{\r
- int code = CvArrTest::prepare_test_case( test_case_idx );\r
- return code;\r
-}\r
-\r
-\r
-void CV_ProjectPointsTest::run_func()\r
-{\r
- CvMat *v2m_jac = 0, *m2v_jac = 0;\r
- if( calc_jacobians )\r
- {\r
- v2m_jac = &test_mat[OUTPUT][1];\r
- m2v_jac = &test_mat[OUTPUT][3];\r
- }\r
-\r
- cvProjectPoints2( &test_mat[INPUT][0], &test_mat[OUTPUT][0], v2m_jac );\r
- cvProjectPoints2( &test_mat[OUTPUT][0], &test_mat[OUTPUT][2], m2v_jac );\r
-}\r
-\r
-\r
-void CV_ProjectPointsTest::prepare_to_validation( int /*test_case_idx*/ )\r
-{\r
- const CvMat* vec = &test_mat[INPUT][0];\r
- CvMat* m = &test_mat[REF_OUTPUT][0];\r
- CvMat* vec2 = &test_mat[REF_OUTPUT][2];\r
- CvMat* v2m_jac = 0, *m2v_jac = 0;\r
- double theta0, theta1;\r
-\r
- if( calc_jacobians )\r
- {\r
- v2m_jac = &test_mat[REF_OUTPUT][1];\r
- m2v_jac = &test_mat[REF_OUTPUT][3];\r
- }\r
-\r
-\r
- cvTsProjectPoints( vec, m, v2m_jac );\r
- cvTsProjectPoints( m, vec2, m2v_jac );\r
- cvTsCopy( vec, vec2 );\r
-\r
- theta0 = cvNorm( vec2, 0, CV_L2 );\r
- theta1 = fmod( theta0, CV_PI*2 );\r
-\r
- if( theta1 > CV_PI )\r
- theta1 = -(CV_PI*2 - theta1);\r
- cvScale( vec2, vec2, theta1/(theta0 ? theta0 : 1) );\r
-\r
- if( calc_jacobians )\r
- {\r
- //cvInvert( v2m_jac, m2v_jac, CV_SVD );\r
- if( cvNorm(&test_mat[OUTPUT][3],0,CV_C) < 1000 )\r
- {\r
- cvTsGEMM( &test_mat[OUTPUT][1], &test_mat[OUTPUT][3],\r
- 1, 0, 0, &test_mat[OUTPUT][4],\r
- v2m_jac->rows == 3 ? 0 : CV_GEMM_A_T + CV_GEMM_B_T );\r
- }\r
- else\r
- {\r
- cvTsSetIdentity( &test_mat[OUTPUT][4], cvScalarAll(1.) );\r
- cvTsCopy( &test_mat[REF_OUTPUT][2], &test_mat[OUTPUT][2] );\r
- }\r
- cvTsSetIdentity( &test_mat[REF_OUTPUT][4], cvScalarAll(1.) );\r
- }\r
-}\r
-\r
-\r
-CV_ProjectPointsTest ProjectPoints_test;\r
-\r
-#endif\r
-\r
-using namespace cv;\r
-\r
-// --------------------------------- CV_CameraCalibrationTest --------------------------------------------\r
-\r
-class CV_CameraCalibrationTest : public CvTest\r
-{\r
-public:\r
- CV_CameraCalibrationTest( const char* testName, const char* testFuncs );\r
- ~CV_CameraCalibrationTest();\r
- void clear();\r
-protected:\r
- int compare(double* val, double* refVal, int len,\r
- double eps, const char* paramName);\r
- virtual void calibrate( int imageCount, int* pointCounts,\r
- CvSize imageSize, CvPoint2D64f* imagePoints, CvPoint3D64f* objectPoints,\r
- double* distortionCoeffs, double* cameraMatrix, double* translationVectors,\r
- double* rotationMatrices, int flags ) = 0;\r
- virtual void project( int pointCount, CvPoint3D64f* objectPoints,\r
- double* rotationMatrix, double* translationVector,\r
- double* cameraMatrix, double* distortion, CvPoint2D64f* imagePoints ) = 0;\r
-\r
- void run(int);\r
-};\r
-\r
-CV_CameraCalibrationTest::CV_CameraCalibrationTest( const char* testName, const char* testFuncs ):\r
- CvTest( testName, testFuncs )\r
-{\r
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;\r
-}\r
-\r
-CV_CameraCalibrationTest::~CV_CameraCalibrationTest()\r
-{\r
- clear();\r
-}\r
-\r
-void CV_CameraCalibrationTest::clear()\r
-{\r
- CvTest::clear();\r
-}\r
-\r
-int CV_CameraCalibrationTest::compare(double* val, double* ref_val, int len,\r
- double eps, const char* param_name )\r
-{\r
- return cvTsCmpEps2_64f( ts, val, ref_val, len, eps, param_name );\r
-}\r
-\r
-void CV_CameraCalibrationTest::run( int start_from )\r
-{\r
- int code = CvTS::OK;\r
- char filepath[200];\r
- char filename[200];\r
-\r
- CvSize imageSize;\r
- CvSize etalonSize;\r
- int numImages;\r
-\r
- CvPoint2D64f* imagePoints;\r
- CvPoint3D64f* objectPoints;\r
- CvPoint2D64f* reprojectPoints;\r
-\r
- double* transVects;\r
- double* rotMatrs;\r
-\r
- double* goodTransVects;\r
- double* goodRotMatrs;\r
-\r
- double cameraMatrix[3*3];\r
- double distortion[5]={0,0,0,0,0};\r
-\r
- double goodDistortion[4];\r
-\r
- int* numbers;\r
- FILE* file = 0;\r
- FILE* datafile = 0;\r
- int i,j;\r
- int currImage;\r
- int currPoint;\r
-\r
- int calibFlags;\r
- char i_dat_file[100];\r
- int numPoints;\r
- int numTests;\r
- int currTest;\r
-\r
- imagePoints = 0;\r
- objectPoints = 0;\r
- reprojectPoints = 0;\r
- numbers = 0;\r
-\r
- transVects = 0;\r
- rotMatrs = 0;\r
- goodTransVects = 0;\r
- goodRotMatrs = 0;\r
- int progress = 0;\r
-\r
- sprintf( filepath, "%scameracalibration/", ts->get_data_path() );\r
- sprintf( filename, "%sdatafiles.txt", filepath );\r
- datafile = fopen( filename, "r" );\r
- if( datafile == 0 )\r
- {\r
- ts->printf( CvTS::LOG, "Could not open file with list of test files: %s\n", filename );\r
- code = CvTS::FAIL_MISSING_TEST_DATA;\r
- goto _exit_;\r
- }\r
-\r
- fscanf(datafile,"%d",&numTests);\r
-\r
- for( currTest = start_from; currTest < numTests; currTest++ )\r
- {\r
- fscanf(datafile,"%s",i_dat_file);\r
- sprintf(filename, "%s%s", filepath, i_dat_file);\r
- file = fopen(filename,"r");\r
-\r
- ts->update_context( this, currTest, true );\r
-\r
- if( file == 0 )\r
- {\r
- ts->printf( CvTS::LOG,\r
- "Can't open current test file: %s\n",filename);\r
- if( numTests == 1 )\r
- {\r
- code = CvTS::FAIL_MISSING_TEST_DATA;\r
- goto _exit_;\r
- }\r
- continue; // if there is more than one test, just skip the test\r
- }\r
-\r
- fscanf(file,"%d %d\n",&(imageSize.width),&(imageSize.height));\r
- if( imageSize.width <= 0 || imageSize.height <= 0 )\r
- {\r
- ts->printf( CvTS::LOG, "Image size in test file is incorrect\n" );\r
- code = CvTS::FAIL_INVALID_TEST_DATA;\r
- goto _exit_;\r
- }\r
-\r
- /* Read etalon size */\r
- fscanf(file,"%d %d\n",&(etalonSize.width),&(etalonSize.height));\r
- if( etalonSize.width <= 0 || etalonSize.height <= 0 )\r
- {\r
- ts->printf( CvTS::LOG, "Pattern size in test file is incorrect\n" );\r
- code = CvTS::FAIL_INVALID_TEST_DATA;\r
- goto _exit_;\r
- }\r
-\r
- numPoints = etalonSize.width * etalonSize.height;\r
-\r
- /* Read number of images */\r
- fscanf(file,"%d\n",&numImages);\r
- if( numImages <=0 )\r
- {\r
- ts->printf( CvTS::LOG, "Number of images in test file is incorrect\n");\r
- code = CvTS::FAIL_INVALID_TEST_DATA;\r
- goto _exit_;\r
- }\r
-\r
- /* Need to allocate memory */\r
- imagePoints = (CvPoint2D64f*)cvAlloc( numPoints *\r
- numImages * sizeof(CvPoint2D64f));\r
-\r
- objectPoints = (CvPoint3D64f*)cvAlloc( numPoints *\r
- numImages * sizeof(CvPoint3D64f));\r
-\r
- reprojectPoints = (CvPoint2D64f*)cvAlloc( numPoints *\r
- numImages * sizeof(CvPoint2D64f));\r
-\r
- /* Alloc memory for numbers */\r
- numbers = (int*)cvAlloc( numImages * sizeof(int));\r
-\r
- /* Fill it by numbers of points of each image*/\r
- for( currImage = 0; currImage < numImages; currImage++ )\r
- {\r
- numbers[currImage] = etalonSize.width * etalonSize.height;\r
- }\r
-\r
- /* Allocate memory for translate vectors and rotmatrixs*/\r
- transVects = (double*)cvAlloc(3 * 1 * numImages * sizeof(double));\r
- rotMatrs = (double*)cvAlloc(3 * 3 * numImages * sizeof(double));\r
-\r
- goodTransVects = (double*)cvAlloc(3 * 1 * numImages * sizeof(double));\r
- goodRotMatrs = (double*)cvAlloc(3 * 3 * numImages * sizeof(double));\r
-\r
- /* Read object points */\r
- i = 0;/* shift for current point */\r
- for( currImage = 0; currImage < numImages; currImage++ )\r
- {\r
- for( currPoint = 0; currPoint < numPoints; currPoint++ )\r
- {\r
- double x,y,z;\r
- fscanf(file,"%lf %lf %lf\n",&x,&y,&z);\r
-\r
- (objectPoints+i)->x = x;\r
- (objectPoints+i)->y = y;\r
- (objectPoints+i)->z = z;\r
- i++;\r
- }\r
- }\r
-\r
- /* Read image points */\r
- i = 0;/* shift for current point */\r
- for( currImage = 0; currImage < numImages; currImage++ )\r
- {\r
- for( currPoint = 0; currPoint < numPoints; currPoint++ )\r
- {\r
- double x,y;\r
- fscanf(file,"%lf %lf\n",&x,&y);\r
-\r
- (imagePoints+i)->x = x;\r
- (imagePoints+i)->y = y;\r
- i++;\r
- }\r
- }\r
-\r
- /* Read good data computed before */\r
-\r
- /* Focal lengths */\r
- double goodFcx,goodFcy;\r
- fscanf(file,"%lf %lf",&goodFcx,&goodFcy);\r
-\r
- /* Principal points */\r
- double goodCx,goodCy;\r
- fscanf(file,"%lf %lf",&goodCx,&goodCy);\r
-\r
- /* Read distortion */\r
-\r
- fscanf(file,"%lf",goodDistortion+0);\r
- fscanf(file,"%lf",goodDistortion+1);\r
- fscanf(file,"%lf",goodDistortion+2);\r
- fscanf(file,"%lf",goodDistortion+3);\r
-\r
- /* Read good Rot matrixes */\r
- for( currImage = 0; currImage < numImages; currImage++ )\r
- {\r
- for( i = 0; i < 3; i++ )\r
- for( j = 0; j < 3; j++ )\r
- fscanf(file, "%lf", goodRotMatrs + currImage * 9 + j * 3 + i);\r
- }\r
-\r
- /* Read good Trans vectors */\r
- for( currImage = 0; currImage < numImages; currImage++ )\r
- {\r
- for( i = 0; i < 3; i++ )\r
- fscanf(file, "%lf", goodTransVects + currImage * 3 + i);\r
- }\r
-\r
- calibFlags = 0\r
- // + CV_CALIB_FIX_PRINCIPAL_POINT\r
- // + CV_CALIB_ZERO_TANGENT_DIST\r
- // + CV_CALIB_FIX_ASPECT_RATIO\r
- // + CV_CALIB_USE_INTRINSIC_GUESS\r
- + CV_CALIB_FIX_K3\r
- + CV_CALIB_FIX_K4+CV_CALIB_FIX_K5\r
- + CV_CALIB_FIX_K6\r
- ;\r
- memset( cameraMatrix, 0, 9*sizeof(cameraMatrix[0]) );\r
- cameraMatrix[0] = cameraMatrix[4] = 807.;\r
- cameraMatrix[2] = (imageSize.width - 1)*0.5;\r
- cameraMatrix[5] = (imageSize.height - 1)*0.5;\r
- cameraMatrix[8] = 1.;\r
-\r
- /* Now we can calibrate camera */\r
- calibrate( numImages,\r
- numbers,\r
- imageSize,\r
- imagePoints,\r
- objectPoints,\r
- distortion,\r
- cameraMatrix,\r
- transVects,\r
- rotMatrs,\r
- calibFlags );\r
-\r
- /* ---- Reproject points to the image ---- */\r
- for( currImage = 0; currImage < numImages; currImage++ )\r
- {\r
- int numPoints = etalonSize.width * etalonSize.height;\r
- project( numPoints,\r
- objectPoints + currImage * numPoints,\r
- rotMatrs + currImage * 9,\r
- transVects + currImage * 3,\r
- cameraMatrix,\r
- distortion,\r
- reprojectPoints + currImage * numPoints);\r
- }\r
-\r
- /* ----- Compute reprojection error ----- */\r
- i = 0;\r
- double dx,dy;\r
- double rx,ry;\r
- double meanDx,meanDy;\r
- double maxDx = 0.0;\r
- double maxDy = 0.0;\r
-\r
- meanDx = 0;\r
- meanDy = 0;\r
- for( currImage = 0; currImage < numImages; currImage++ )\r
- {\r
- for( currPoint = 0; currPoint < etalonSize.width * etalonSize.height; currPoint++ )\r
- {\r
- rx = reprojectPoints[i].x;\r
- ry = reprojectPoints[i].y;\r
- dx = rx - imagePoints[i].x;\r
- dy = ry - imagePoints[i].y;\r
-\r
- meanDx += dx;\r
- meanDy += dy;\r
-\r
- dx = fabs(dx);\r
- dy = fabs(dy);\r
-\r
- if( dx > maxDx )\r
- maxDx = dx;\r
-\r
- if( dy > maxDy )\r
- maxDy = dy;\r
- i++;\r
- }\r
- }\r
-\r
- meanDx /= numImages * etalonSize.width * etalonSize.height;\r
- meanDy /= numImages * etalonSize.width * etalonSize.height;\r
-\r
- /* ========= Compare parameters ========= */\r
-\r
- /* ----- Compare focal lengths ----- */\r
- code = compare(cameraMatrix+0,&goodFcx,1,0.1,"fx");\r
- if( code < 0 )\r
- goto _exit_;\r
-\r
- code = compare(cameraMatrix+4,&goodFcy,1,0.1,"fy");\r
- if( code < 0 )\r
- goto _exit_;\r
-\r
- /* ----- Compare principal points ----- */\r
- code = compare(cameraMatrix+2,&goodCx,1,0.1,"cx");\r
- if( code < 0 )\r
- goto _exit_;\r
-\r
- code = compare(cameraMatrix+5,&goodCy,1,0.1,"cy");\r
- if( code < 0 )\r
- goto _exit_;\r
-\r
- /* ----- Compare distortion ----- */\r
- code = compare(distortion,goodDistortion,4,0.1,"[k1,k2,p1,p2]");\r
- if( code < 0 )\r
- goto _exit_;\r
-\r
- /* ----- Compare rot matrixs ----- */\r
- code = compare(rotMatrs,goodRotMatrs, 9*numImages,0.05,"rotation matrices");\r
- if( code < 0 )\r
- goto _exit_;\r
-\r
- /* ----- Compare rot matrixs ----- */\r
- code = compare(transVects,goodTransVects, 3*numImages,0.1,"translation vectors");\r
- if( code < 0 )\r
- goto _exit_;\r
-\r
- if( maxDx > 1.0 )\r
- {\r
- ts->printf( CvTS::LOG,\r
- "Error in reprojection maxDx=%f > 1.0\n",maxDx);\r
- code = CvTS::FAIL_BAD_ACCURACY; goto _exit_;\r
- }\r
-\r
- if( maxDy > 1.0 )\r
- {\r
- ts->printf( CvTS::LOG,\r
- "Error in reprojection maxDy=%f > 1.0\n",maxDy);\r
- code = CvTS::FAIL_BAD_ACCURACY; goto _exit_;\r
- }\r
-\r
- progress = update_progress( progress, currTest, numTests, 0 );\r
-\r
- cvFree(&imagePoints);\r
- cvFree(&objectPoints);\r
- cvFree(&reprojectPoints);\r
- cvFree(&numbers);\r
-\r
- cvFree(&transVects);\r
- cvFree(&rotMatrs);\r
- cvFree(&goodTransVects);\r
- cvFree(&goodRotMatrs);\r
-\r
- fclose(file);\r
- file = 0;\r
- }\r
-\r
-_exit_:\r
-\r
- if( file )\r
- fclose(file);\r
-\r
- if( datafile )\r
- fclose(datafile);\r
-\r
- /* Free all allocated memory */\r
- cvFree(&imagePoints);\r
- cvFree(&objectPoints);\r
- cvFree(&reprojectPoints);\r
- cvFree(&numbers);\r
-\r
- cvFree(&transVects);\r
- cvFree(&rotMatrs);\r
- cvFree(&goodTransVects);\r
- cvFree(&goodRotMatrs);\r
-\r
- if( code < 0 )\r
- ts->set_failed_test_info( code );\r
-}\r
-\r
-// --------------------------------- CV_CameraCalibrationTest_C --------------------------------------------\r
-\r
-class CV_CameraCalibrationTest_C : public CV_CameraCalibrationTest\r
-{\r
-public:\r
- CV_CameraCalibrationTest_C() : CV_CameraCalibrationTest( "calibrate-camera-c", "cvCalibrateCamera2" ) {}\r
-protected:\r
- virtual void calibrate( int imageCount, int* pointCounts,\r
- CvSize imageSize, CvPoint2D64f* imagePoints, CvPoint3D64f* objectPoints,\r
- double* distortionCoeffs, double* cameraMatrix, double* translationVectors,\r
- double* rotationMatrices, int flags );\r
- virtual void project( int pointCount, CvPoint3D64f* objectPoints,\r
- double* rotationMatrix, double* translationVector,\r
- double* cameraMatrix, double* distortion, CvPoint2D64f* imagePoints );\r
-};\r
-\r
-void CV_CameraCalibrationTest_C::calibrate( int imageCount, int* pointCounts,\r
- CvSize imageSize, CvPoint2D64f* imagePoints, CvPoint3D64f* objectPoints,\r
- double* distortionCoeffs, double* cameraMatrix, double* translationVectors,\r
- double* rotationMatrices, int flags )\r
-{\r
- cvCalibrateCamera_64d( imageCount,\r
- pointCounts,\r
- imageSize,\r
- imagePoints,\r
- objectPoints,\r
- distortionCoeffs,\r
- cameraMatrix,\r
- translationVectors,\r
- rotationMatrices,\r
- flags );\r
-}\r
-\r
-void CV_CameraCalibrationTest_C::project( int pointCount, CvPoint3D64f* objectPoints,\r
- double* rotationMatrix, double* translationVector,\r
- double* cameraMatrix, double* distortion, CvPoint2D64f* imagePoints )\r
-{\r
- cvProjectPointsSimple( pointCount,\r
- objectPoints,\r
- rotationMatrix,\r
- translationVector,\r
- cameraMatrix,\r
- distortion,\r
- imagePoints );\r
-}\r
-\r
-CV_CameraCalibrationTest_C calibrate_test_c;\r
-\r
-// --------------------------------- CV_CameraCalibrationTest_CPP --------------------------------------------\r
-\r
-class CV_CameraCalibrationTest_CPP : public CV_CameraCalibrationTest\r
-{\r
-public:\r
- CV_CameraCalibrationTest_CPP() : CV_CameraCalibrationTest( "calibrate-camera-cpp", "cv::calibrateCamera" ) {}\r
-protected:\r
- virtual void calibrate( int imageCount, int* pointCounts,\r
- CvSize imageSize, CvPoint2D64f* imagePoints, CvPoint3D64f* objectPoints,\r
- double* distortionCoeffs, double* cameraMatrix, double* translationVectors,\r
- double* rotationMatrices, int flags );\r
- virtual void project( int pointCount, CvPoint3D64f* objectPoints,\r
- double* rotationMatrix, double* translationVector,\r
- double* cameraMatrix, double* distortion, CvPoint2D64f* imagePoints );\r
-};\r
-\r
-void CV_CameraCalibrationTest_CPP::calibrate( int imageCount, int* pointCounts,\r
- CvSize _imageSize, CvPoint2D64f* _imagePoints, CvPoint3D64f* _objectPoints,\r
- double* _distortionCoeffs, double* _cameraMatrix, double* translationVectors,\r
- double* rotationMatrices, int flags )\r
-{\r
- vector<vector<Point3f> > objectPoints( imageCount );\r
- vector<vector<Point2f> > imagePoints( imageCount );\r
- Size imageSize = _imageSize;\r
- Mat cameraMatrix, distCoeffs(1,4,CV_64F,Scalar::all(0));\r
- vector<Mat> rvecs, tvecs;\r
-\r
- CvPoint3D64f* op = _objectPoints;\r
- CvPoint2D64f* ip = _imagePoints;\r
- vector<vector<Point3f> >::iterator objectPointsIt = objectPoints.begin();\r
- vector<vector<Point2f> >::iterator imagePointsIt = imagePoints.begin();\r
- for( int i = 0; i < imageCount; ++objectPointsIt, ++imagePointsIt, i++ )\r
- {\r
- int num = pointCounts[i];\r
- objectPointsIt->resize( num );\r
- imagePointsIt->resize( num );\r
- vector<Point3f>::iterator oIt = objectPointsIt->begin();\r
- vector<Point2f>::iterator iIt = imagePointsIt->begin();\r
- for( int j = 0; j < num; ++oIt, ++iIt, j++, op++, ip++)\r
- {\r
- oIt->x = (float)op->x, oIt->y = (float)op->y, oIt->z = (float)op->z;\r
- iIt->x = (float)ip->x, iIt->y = (float)ip->y;\r
- }\r
- }\r
-\r
- calibrateCamera( objectPoints,\r
- imagePoints,\r
- imageSize,\r
- cameraMatrix,\r
- distCoeffs,\r
- rvecs,\r
- tvecs,\r
- flags );\r
-\r
- assert( cameraMatrix.type() == CV_64FC1 );\r
- memcpy( _cameraMatrix, cameraMatrix.data, 9*sizeof(double) );\r
-\r
- assert( cameraMatrix.type() == CV_64FC1 );\r
- memcpy( _distortionCoeffs, distCoeffs.data, 4*sizeof(double) );\r
-\r
- vector<Mat>::iterator rvecsIt = rvecs.begin();\r
- vector<Mat>::iterator tvecsIt = tvecs.begin();\r
- double *rm = rotationMatrices,\r
- *tm = translationVectors;\r
- assert( rvecsIt->type() == CV_64FC1 );\r
- assert( tvecsIt->type() == CV_64FC1 );\r
- for( int i = 0; i < imageCount; ++rvecsIt, ++tvecsIt, i++, rm+=9, tm+=3 )\r
- {\r
- Mat r9( 3, 3, CV_64FC1 );\r
- Rodrigues( *rvecsIt, r9 );\r
- memcpy( rm, r9.data, 9*sizeof(double) );\r
- memcpy( tm, tvecsIt->data, 3*sizeof(double) );\r
- }\r
-}\r
-\r
-void CV_CameraCalibrationTest_CPP::project( int pointCount, CvPoint3D64f* _objectPoints,\r
- double* rotationMatrix, double* translationVector,\r
- double* _cameraMatrix, double* distortion, CvPoint2D64f* _imagePoints )\r
-{\r
- Mat objectPoints( pointCount, 3, CV_64FC1, _objectPoints );\r
- Mat rmat( 3, 3, CV_64FC1, rotationMatrix ),\r
- rvec( 1, 3, CV_64FC1 ),\r
- tvec( 1, 3, CV_64FC1, translationVector );\r
- Mat cameraMatrix( 3, 3, CV_64FC1, _cameraMatrix );\r
- Mat distCoeffs( 1, 4, CV_64FC1, distortion );\r
- vector<Point2f> imagePoints;\r
- Rodrigues( rmat, rvec );\r
-\r
- objectPoints.convertTo( objectPoints, CV_32FC1 );\r
- projectPoints( objectPoints, rvec, tvec,\r
- cameraMatrix, distCoeffs, imagePoints );\r
- vector<Point2f>::const_iterator it = imagePoints.begin();\r
- for( int i = 0; it != imagePoints.end(); ++it, i++ )\r
- {\r
- _imagePoints[i] = cvPoint2D64f( it->x, it->y );\r
- }\r
-}\r
-\r
-CV_CameraCalibrationTest_CPP calibrate_test_cpp;\r
-\r
-//----------------------------------------- CV_CalibrationMatrixValuesTest --------------------------------\r
-\r
-class CV_CalibrationMatrixValuesTest : public CvTest\r
-{\r
-public:\r
- CV_CalibrationMatrixValuesTest( const char* testName, const char* testFuncs ) :\r
- CvTest( testName, testFuncs ) {}\r
-protected:\r
- void run(int);\r
- virtual void calibMatrixValues( const Mat& cameraMatrix, Size imageSize,\r
- double apertureWidth, double apertureHeight, double& fovx, double& fovy, double& focalLength,\r
- Point2d& principalPoint, double& aspectRatio ) = 0;\r
-};\r
-\r
-void CV_CalibrationMatrixValuesTest::run(int)\r
-{\r
- int code = CvTS::OK;\r
- const double fcMinVal = 1e-5;\r
- const double fcMaxVal = 1000;\r
- const double apertureMaxVal = 0.01;\r
-\r
- RNG rng = *ts->get_rng();\r
-\r
- double fx, fy, cx, cy, nx, ny;\r
- Mat cameraMatrix( 3, 3, CV_64FC1 );\r
- cameraMatrix.setTo( Scalar(0) );\r
- fx = cameraMatrix.at<double>(0,0) = rng.uniform( fcMinVal, fcMaxVal );\r
- fy = cameraMatrix.at<double>(1,1) = rng.uniform( fcMinVal, fcMaxVal );\r
- cx = cameraMatrix.at<double>(0,2) = rng.uniform( fcMinVal, fcMaxVal );\r
- cy = cameraMatrix.at<double>(1,2) = rng.uniform( fcMinVal, fcMaxVal );\r
- cameraMatrix.at<double>(2,2) = 1;\r
-\r
- Size imageSize( 600, 400 );\r
-\r
- double apertureWidth = (double)rng * apertureMaxVal,\r
- apertureHeight = (double)rng * apertureMaxVal;\r
-\r
- double fovx, fovy, focalLength, aspectRatio,\r
- goodFovx, goodFovy, goodFocalLength, goodAspectRatio;\r
- Point2d principalPoint, goodPrincipalPoint;\r
-\r
-\r
- calibMatrixValues( cameraMatrix, imageSize, apertureWidth, apertureHeight,\r
- fovx, fovy, focalLength, principalPoint, aspectRatio );\r
-\r
- // calculate calibration matrix values\r
- goodAspectRatio = fy / fx;\r
-\r
- if( apertureWidth != 0.0 && apertureHeight != 0.0 )\r
- {\r
- nx = imageSize.width / apertureWidth;\r
- ny = imageSize.height / apertureHeight;\r
- }\r
- else\r
- {\r
- nx = 1.0;\r
- ny = goodAspectRatio;\r
- }\r
-\r
- goodFovx = 2 * atan( imageSize.width / (2 * fx)) * 180.0 / CV_PI;\r
- goodFovy = 2 * atan( imageSize.height / (2 * fy)) * 180.0 / CV_PI;\r
-\r
- goodFocalLength = fx / nx;\r
-\r
- goodPrincipalPoint.x = cx / nx;\r
- goodPrincipalPoint.y = cy / ny;\r
-\r
- // check results\r
- if( fabs(fovx - goodFovx) > FLT_EPSILON )\r
- {\r
- ts->printf( CvTS::LOG, "bad fovx (real=%f, good = %f\n", fovx, goodFovx );\r
- code = CvTS::FAIL_BAD_ACCURACY;\r
- goto _exit_;\r
- }\r
- if( fabs(fovy - goodFovy) > FLT_EPSILON )\r
- {\r
- ts->printf( CvTS::LOG, "bad fovy (real=%f, good = %f\n", fovy, goodFovy );\r
- code = CvTS::FAIL_BAD_ACCURACY;\r
- goto _exit_;\r
- }\r
- if( fabs(focalLength - goodFocalLength) > FLT_EPSILON )\r
- {\r
- ts->printf( CvTS::LOG, "bad focalLength (real=%f, good = %f\n", focalLength, goodFocalLength );\r
- code = CvTS::FAIL_BAD_ACCURACY;\r
- goto _exit_;\r
- }\r
- if( fabs(aspectRatio - goodAspectRatio) > FLT_EPSILON )\r
- {\r
- ts->printf( CvTS::LOG, "bad aspectRatio (real=%f, good = %f\n", aspectRatio, goodAspectRatio );\r
- code = CvTS::FAIL_BAD_ACCURACY;\r
- goto _exit_;\r
- }\r
- if( norm( principalPoint - goodPrincipalPoint ) > FLT_EPSILON )\r
- {\r
- ts->printf( CvTS::LOG, "bad principalPoint\n" );\r
- code = CvTS::FAIL_BAD_ACCURACY;\r
- goto _exit_;\r
- }\r
-\r
-_exit_:\r
- CvRNG* _rng = ts->get_rng();\r
- *_rng = rng.state;\r
- ts->set_failed_test_info( code );\r
-}\r
-\r
-//----------------------------------------- CV_CalibrationMatrixValuesTest_C --------------------------------\r
-\r
-class CV_CalibrationMatrixValuesTest_C : public CV_CalibrationMatrixValuesTest\r
-{\r
-public:\r
- CV_CalibrationMatrixValuesTest_C() :\r
- CV_CalibrationMatrixValuesTest( "calibMatrixValues-c", "cvCalibrationMatrixValues" ) {}\r
-protected:\r
- virtual void calibMatrixValues( const Mat& cameraMatrix, Size imageSize,\r
- double apertureWidth, double apertureHeight, double& fovx, double& fovy, double& focalLength,\r
- Point2d& principalPoint, double& aspectRatio );\r
-};\r
-\r
-void CV_CalibrationMatrixValuesTest_C::calibMatrixValues( const Mat& _cameraMatrix, Size imageSize,\r
- double apertureWidth, double apertureHeight,\r
- double& fovx, double& fovy, double& focalLength,\r
- Point2d& principalPoint, double& aspectRatio )\r
-{\r
- CvMat cameraMatrix = _cameraMatrix;\r
- CvPoint2D64f pp;\r
- cvCalibrationMatrixValues( &cameraMatrix, imageSize, apertureWidth, apertureHeight,\r
- &fovx, &fovy, &focalLength, &pp, &aspectRatio );\r
- principalPoint.x = pp.x;\r
- principalPoint.y = pp.y;\r
-}\r
-\r
-CV_CalibrationMatrixValuesTest_C calibMatrixValues_test_c;\r
-\r
-//----------------------------------------- CV_CalibrationMatrixValuesTest_CPP --------------------------------\r
-\r
-class CV_CalibrationMatrixValuesTest_CPP : public CV_CalibrationMatrixValuesTest\r
-{\r
-public:\r
- CV_CalibrationMatrixValuesTest_CPP() :\r
- CV_CalibrationMatrixValuesTest( "calibMatrixValues-cpp", "cv::calibrationMatrixValues" ) {}\r
-protected:\r
- virtual void calibMatrixValues( const Mat& cameraMatrix, Size imageSize,\r
- double apertureWidth, double apertureHeight, double& fovx, double& fovy, double& focalLength,\r
- Point2d& principalPoint, double& aspectRatio );\r
-};\r
-\r
-void CV_CalibrationMatrixValuesTest_CPP::calibMatrixValues( const Mat& cameraMatrix, Size imageSize,\r
- double apertureWidth, double apertureHeight,\r
- double& fovx, double& fovy, double& focalLength,\r
- Point2d& principalPoint, double& aspectRatio )\r
-{\r
- calibrationMatrixValues( cameraMatrix, imageSize, apertureWidth, apertureHeight,\r
- fovx, fovy, focalLength, principalPoint, aspectRatio );\r
-}\r
-\r
-CV_CalibrationMatrixValuesTest_CPP calibMatrixValues_test_cpp;\r
-\r
-//----------------------------------------- CV_ProjectPointsTest --------------------------------\r
-void calcdfdx( const vector<vector<Point2f> >& leftF, const vector<vector<Point2f> >& rightF, double eps, Mat& dfdx )\r
-{\r
- const int fdim = 2;\r
- CV_Assert( !leftF.empty() && !rightF.empty() && !leftF[0].empty() && !rightF[0].empty() );\r
- CV_Assert( leftF[0].size() == rightF[0].size() );\r
- CV_Assert( fabs(eps) > std::numeric_limits<double>::epsilon() );\r
- int fcount = (int)leftF[0].size(), xdim = (int)leftF.size();\r
-\r
- dfdx.create( fcount*fdim, xdim, CV_64FC1 );\r
-\r
- vector<vector<Point2f> >::const_iterator arrLeftIt = leftF.begin();\r
- vector<vector<Point2f> >::const_iterator arrRightIt = rightF.begin();\r
- for( int xi = 0; xi < xdim; xi++, ++arrLeftIt, ++arrRightIt )\r
- {\r
- CV_Assert( (int)arrLeftIt->size() == fcount );\r
- CV_Assert( (int)arrRightIt->size() == fcount );\r
- vector<Point2f>::const_iterator lIt = arrLeftIt->begin();\r
- vector<Point2f>::const_iterator rIt = arrRightIt->begin();\r
- for( int fi = 0; fi < dfdx.rows; fi+=fdim, ++lIt, ++rIt )\r
- {\r
- dfdx.at<double>(fi, xi ) = 0.5 * ((double)(rIt->x - lIt->x)) / eps;\r
- dfdx.at<double>(fi+1, xi ) = 0.5 * ((double)(rIt->y - lIt->y)) / eps;\r
- }\r
- }\r
-}\r
-\r
-class CV_ProjectPointsTest : public CvTest\r
-{\r
-public:\r
- CV_ProjectPointsTest( const char* testName, const char* testFuncs ) :\r
- CvTest( testName, testFuncs ) {}\r
-protected:\r
- void run(int);\r
- virtual void project( const Mat& objectPoints,\r
- const Mat& rvec, const Mat& tvec,\r
- const Mat& cameraMatrix,\r
- const Mat& distCoeffs,\r
- vector<Point2f>& imagePoints,\r
- Mat& dpdrot, Mat& dpdt, Mat& dpdf,\r
- Mat& dpdc, Mat& dpddist,\r
- double aspectRatio=0 ) = 0;\r
-};\r
-\r
-void CV_ProjectPointsTest::run(int)\r
-{\r
- //typedef float matType;\r
-\r
- int code = CvTS::OK;\r
- const int pointCount = 100;\r
-\r
- const float zMinVal = 10.0f, zMaxVal = 100.0f,\r
- rMinVal = -0.3f, rMaxVal = 0.3f,\r
- tMinVal = -2.0f, tMaxVal = 2.0f;\r
-\r
- const float imgPointErr = 1e-3f,\r
- dEps = 1e-3f;\r
- \r
- double err;\r
-\r
- Size imgSize( 600, 800 );\r
- Mat_<float> objPoints( pointCount, 3), rvec( 1, 3), rmat, tvec( 1, 3 ), cameraMatrix( 3, 3 ), distCoeffs( 1, 4 ),\r
- leftRvec, rightRvec, leftTvec, rightTvec, leftCameraMatrix, rightCameraMatrix, leftDistCoeffs, rightDistCoeffs;\r
-\r
- RNG rng = *ts->get_rng();\r
-\r
- // generate data\r
- cameraMatrix << 300.f, 0.f, imgSize.width/2.f,\r
- 0.f, 300.f, imgSize.height/2.f,\r
- 0.f, 0.f, 1.f;\r
- distCoeffs << 0.1, 0.01, 0.001, 0.001;\r
-\r
- rvec(0,0) = rng.uniform( rMinVal, rMaxVal );\r
- rvec(0,1) = rng.uniform( rMinVal, rMaxVal );\r
- rvec(0,2) = rng.uniform( rMinVal, rMaxVal );\r
- Rodrigues( rvec, rmat );\r
-\r
- tvec(0,0) = rng.uniform( tMinVal, tMaxVal );\r
- tvec(0,1) = rng.uniform( tMinVal, tMaxVal );\r
- tvec(0,2) = rng.uniform( tMinVal, tMaxVal );\r
-\r
- for( int y = 0; y < objPoints.rows; y++ )\r
- {\r
- Mat point(1, 3, CV_32FC1, objPoints.ptr(y) );\r
- float z = rng.uniform( zMinVal, zMaxVal );\r
- point.at<float>(0,2) = z;\r
- point.at<float>(0,0) = (rng.uniform(2.f,(float)(imgSize.width-2)) - cameraMatrix(0,2)) / cameraMatrix(0,0) * z;\r
- point.at<float>(0,1) = (rng.uniform(2.f,(float)(imgSize.height-2)) - cameraMatrix(1,2)) / cameraMatrix(1,1) * z;\r
- point = (point - tvec) * rmat;\r
- }\r
-\r
- vector<Point2f> imgPoints;\r
- vector<vector<Point2f> > leftImgPoints;\r
- vector<vector<Point2f> > rightImgPoints;\r
- Mat dpdrot, dpdt, dpdf, dpdc, dpddist,\r
- valDpdrot, valDpdt, valDpdf, valDpdc, valDpddist;\r
-\r
- project( objPoints, rvec, tvec, cameraMatrix, distCoeffs,\r
- imgPoints, dpdrot, dpdt, dpdf, dpdc, dpddist, 0 );\r
-\r
- // calculate and check image points\r
- assert( (int)imgPoints.size() == pointCount );\r
- vector<Point2f>::const_iterator it = imgPoints.begin();\r
- for( int i = 0; i < pointCount; i++, ++it )\r
- {\r
- Point3d p( objPoints(i,0), objPoints(i,1), objPoints(i,2) );\r
- double z = p.x*rmat(2,0) + p.y*rmat(2,1) + p.z*rmat(2,2) + tvec(0,2),\r
- x = (p.x*rmat(0,0) + p.y*rmat(0,1) + p.z*rmat(0,2) + tvec(0,0)) / z,\r
- y = (p.x*rmat(1,0) + p.y*rmat(1,1) + p.z*rmat(1,2) + tvec(0,1)) / z,\r
- r2 = x*x + y*y,\r
- r4 = r2*r2;\r
- Point2f validImgPoint;\r
- double a1 = 2*x*y,\r
- a2 = r2 + 2*x*x,\r
- a3 = r2 + 2*y*y,\r
- cdist = 1+distCoeffs(0,0)*r2+distCoeffs(0,1)*r4;\r
- validImgPoint.x = static_cast<float>((double)cameraMatrix(0,0)*(x*cdist + (double)distCoeffs(0,2)*a1 + (double)distCoeffs(0,3)*a2)\r
- + (double)cameraMatrix(0,2));\r
- validImgPoint.y = static_cast<float>((double)cameraMatrix(1,1)*(y*cdist + (double)distCoeffs(0,2)*a3 + distCoeffs(0,3)*a1)\r
- + (double)cameraMatrix(1,2));\r
-\r
- Point2f ssdfp = *it;\r
- if( fabs(it->x - validImgPoint.x) > imgPointErr ||\r
- fabs(it->y - validImgPoint.y) > imgPointErr )\r
- {\r
- ts->printf( CvTS::LOG, "bad image point\n" );\r
- code = CvTS::FAIL_BAD_ACCURACY;\r
- goto _exit_;\r
- }\r
- }\r
-\r
- // check derivatives\r
- // 1. rotation\r
- leftImgPoints.resize(3);\r
- rightImgPoints.resize(3);\r
- for( int i = 0; i < 3; i++ )\r
- {\r
- rvec.copyTo( leftRvec ); leftRvec(0,i) -= dEps;\r
- project( objPoints, leftRvec, tvec, cameraMatrix, distCoeffs,\r
- leftImgPoints[i], valDpdrot, valDpdt, valDpdf, valDpdc, valDpddist, 0 );\r
- rvec.copyTo( rightRvec ); rightRvec(0,i) += dEps;\r
- project( objPoints, rightRvec, tvec, cameraMatrix, distCoeffs,\r
- rightImgPoints[i], valDpdrot, valDpdt, valDpdf, valDpdc, valDpddist, 0 );\r
- }\r
- calcdfdx( leftImgPoints, rightImgPoints, dEps, valDpdrot );\r
- err = norm( dpdrot, valDpdrot, NORM_INF );\r
- if( err > 3 )\r
- {\r
- ts->printf( CvTS::LOG, "bad dpdrot: too big difference = %g\n", err );\r
- code = CvTS::FAIL_BAD_ACCURACY;\r
- }\r
-\r
- // 2. translation\r
- for( int i = 0; i < 3; i++ )\r
- {\r
- tvec.copyTo( leftTvec ); leftTvec(0,i) -= dEps;\r
- project( objPoints, rvec, leftTvec, cameraMatrix, distCoeffs,\r
- leftImgPoints[i], valDpdrot, valDpdt, valDpdf, valDpdc, valDpddist, 0 );\r
- tvec.copyTo( rightTvec ); rightTvec(0,i) += dEps;\r
- project( objPoints, rvec, rightTvec, cameraMatrix, distCoeffs,\r
- rightImgPoints[i], valDpdrot, valDpdt, valDpdf, valDpdc, valDpddist, 0 );\r
- }\r
- calcdfdx( leftImgPoints, rightImgPoints, dEps, valDpdt );\r
- if( norm( dpdt, valDpdt, NORM_INF ) > 0.2 )\r
- {\r
- ts->printf( CvTS::LOG, "bad dpdtvec\n" );\r
- code = CvTS::FAIL_BAD_ACCURACY;\r
- }\r
-\r
- // 3. camera matrix\r
- // 3.1. focus\r
- leftImgPoints.resize(2);\r
- rightImgPoints.resize(2);\r
- cameraMatrix.copyTo( leftCameraMatrix ); leftCameraMatrix(0,0) -= dEps;\r
- project( objPoints, rvec, tvec, leftCameraMatrix, distCoeffs,\r
- leftImgPoints[0], valDpdrot, valDpdt, valDpdf, valDpdc, valDpddist, 0 );\r
- cameraMatrix.copyTo( leftCameraMatrix ); leftCameraMatrix(1,1) -= dEps;\r
- project( objPoints, rvec, tvec, leftCameraMatrix, distCoeffs,\r
- leftImgPoints[1], valDpdrot, valDpdt, valDpdf, valDpdc, valDpddist, 0 );\r
- cameraMatrix.copyTo( rightCameraMatrix ); rightCameraMatrix(0,0) += dEps;\r
- project( objPoints, rvec, tvec, rightCameraMatrix, distCoeffs,\r
- rightImgPoints[0], valDpdrot, valDpdt, valDpdf, valDpdc, valDpddist, 0 );\r
- cameraMatrix.copyTo( rightCameraMatrix ); rightCameraMatrix(1,1) += dEps;\r
- project( objPoints, rvec, tvec, rightCameraMatrix, distCoeffs,\r
- rightImgPoints[1], valDpdrot, valDpdt, valDpdf, valDpdc, valDpddist, 0 );\r
- calcdfdx( leftImgPoints, rightImgPoints, dEps, valDpdf );\r
- if ( norm( dpdf, valDpdf ) > 0.2 )\r
- {\r
- ts->printf( CvTS::LOG, "bad dpdf\n" );\r
- code = CvTS::FAIL_BAD_ACCURACY;\r
- }\r
- // 3.2. principal point\r
- leftImgPoints.resize(2);\r
- rightImgPoints.resize(2);\r
- cameraMatrix.copyTo( leftCameraMatrix ); leftCameraMatrix(0,2) -= dEps;\r
- project( objPoints, rvec, tvec, leftCameraMatrix, distCoeffs,\r
- leftImgPoints[0], valDpdrot, valDpdt, valDpdf, valDpdc, valDpddist, 0 );\r
- cameraMatrix.copyTo( leftCameraMatrix ); leftCameraMatrix(1,2) -= dEps;\r
- project( objPoints, rvec, tvec, leftCameraMatrix, distCoeffs,\r
- leftImgPoints[1], valDpdrot, valDpdt, valDpdf, valDpdc, valDpddist, 0 );\r
- cameraMatrix.copyTo( rightCameraMatrix ); rightCameraMatrix(0,2) += dEps;\r
- project( objPoints, rvec, tvec, rightCameraMatrix, distCoeffs,\r
- rightImgPoints[0], valDpdrot, valDpdt, valDpdf, valDpdc, valDpddist, 0 );\r
- cameraMatrix.copyTo( rightCameraMatrix ); rightCameraMatrix(1,2) += dEps;\r
- project( objPoints, rvec, tvec, rightCameraMatrix, distCoeffs,\r
- rightImgPoints[1], valDpdrot, valDpdt, valDpdf, valDpdc, valDpddist, 0 );\r
- calcdfdx( leftImgPoints, rightImgPoints, dEps, valDpdc );\r
- if ( norm( dpdc, valDpdc ) > 0.2 )\r
- {\r
- ts->printf( CvTS::LOG, "bad dpdc\n" );\r
- code = CvTS::FAIL_BAD_ACCURACY;\r
- }\r
-\r
- // 4. distortion\r
- leftImgPoints.resize(distCoeffs.cols);\r
- rightImgPoints.resize(distCoeffs.cols);\r
- for( int i = 0; i < distCoeffs.cols; i++ )\r
- {\r
- distCoeffs.copyTo( leftDistCoeffs ); leftDistCoeffs(0,i) -= dEps;\r
- project( objPoints, rvec, tvec, cameraMatrix, leftDistCoeffs,\r
- leftImgPoints[i], valDpdrot, valDpdt, valDpdf, valDpdc, valDpddist, 0 );\r
- distCoeffs.copyTo( rightDistCoeffs ); rightDistCoeffs(0,i) += dEps;\r
- project( objPoints, rvec, tvec, cameraMatrix, rightDistCoeffs,\r
- rightImgPoints[i], valDpdrot, valDpdt, valDpdf, valDpdc, valDpddist, 0 );\r
- }\r
- calcdfdx( leftImgPoints, rightImgPoints, dEps, valDpddist );\r
- if( norm( dpddist, valDpddist ) > 0.3 )\r
- {\r
- ts->printf( CvTS::LOG, "bad dpddist\n" );\r
- code = CvTS::FAIL_BAD_ACCURACY;\r
- }\r
-\r
-_exit_:\r
- CvRNG* _rng = ts->get_rng();\r
- *_rng = rng.state;\r
- ts->set_failed_test_info( code );\r
-}\r
-\r
-//----------------------------------------- CV_ProjectPointsTest_C --------------------------------\r
-class CV_ProjectPointsTest_C : public CV_ProjectPointsTest\r
-{\r
-public:\r
- CV_ProjectPointsTest_C() :\r
- CV_ProjectPointsTest( "projectPoints-c", "cvProjectPoints" ) {}\r
-protected:\r
- virtual void project( const Mat& objectPoints,\r
- const Mat& rvec, const Mat& tvec,\r
- const Mat& cameraMatrix,\r
- const Mat& distCoeffs,\r
- vector<Point2f>& imagePoints,\r
- Mat& dpdrot, Mat& dpdt, Mat& dpdf,\r
- Mat& dpdc, Mat& dpddist,\r
- double aspectRatio=0 );\r
-};\r
-\r
-void CV_ProjectPointsTest_C::project( const Mat& opoints, const Mat& rvec, const Mat& tvec,\r
- const Mat& cameraMatrix, const Mat& distCoeffs, vector<Point2f>& ipoints,\r
- Mat& dpdrot, Mat& dpdt, Mat& dpdf, Mat& dpdc, Mat& dpddist, double aspectRatio)\r
-{\r
- int npoints = opoints.cols*opoints.rows*opoints.channels()/3;\r
- ipoints.resize(npoints);\r
- dpdrot.create(npoints*2, 3, CV_64F);\r
- dpdt.create(npoints*2, 3, CV_64F);\r
- dpdf.create(npoints*2, 2, CV_64F);\r
- dpdc.create(npoints*2, 2, CV_64F);\r
- dpddist.create(npoints*2, distCoeffs.rows + distCoeffs.cols - 1, CV_64F);\r
- CvMat _objectPoints = opoints, _imagePoints = Mat(ipoints);\r
- CvMat _rvec = rvec, _tvec = tvec, _cameraMatrix = cameraMatrix, _distCoeffs = distCoeffs;\r
- CvMat _dpdrot = dpdrot, _dpdt = dpdt, _dpdf = dpdf, _dpdc = dpdc, _dpddist = dpddist;\r
-\r
- cvProjectPoints2( &_objectPoints, &_rvec, &_tvec, &_cameraMatrix, &_distCoeffs,\r
- &_imagePoints, &_dpdrot, &_dpdt, &_dpdf, &_dpdc, &_dpddist, aspectRatio );\r
-}\r
-\r
-CV_ProjectPointsTest_C projectPointsTest_c;\r
-\r
-//----------------------------------------- CV_ProjectPointsTest_CPP --------------------------------\r
-class CV_ProjectPointsTest_CPP : public CV_ProjectPointsTest\r
-{\r
-public:\r
- CV_ProjectPointsTest_CPP() :\r
- CV_ProjectPointsTest( "projectPoints-cpp", "cv::projectPoints" ) {}\r
-protected:\r
- virtual void project( const Mat& objectPoints,\r
- const Mat& rvec, const Mat& tvec,\r
- const Mat& cameraMatrix,\r
- const Mat& distCoeffs,\r
- vector<Point2f>& imagePoints,\r
- Mat& dpdrot, Mat& dpdt, Mat& dpdf,\r
- Mat& dpdc, Mat& dpddist,\r
- double aspectRatio=0 );\r
-};\r
-\r
-void CV_ProjectPointsTest_CPP::project( const Mat& objectPoints, const Mat& rvec, const Mat& tvec,\r
- const Mat& cameraMatrix, const Mat& distCoeffs, vector<Point2f>& imagePoints,\r
- Mat& dpdrot, Mat& dpdt, Mat& dpdf, Mat& dpdc, Mat& dpddist, double aspectRatio)\r
-{\r
- projectPoints( objectPoints, rvec, tvec, cameraMatrix, distCoeffs, imagePoints,\r
- dpdrot, dpdt, dpdf, dpdc, dpddist, aspectRatio );\r
-}\r
-\r
-CV_ProjectPointsTest_CPP projectPointsTest_cpp;\r
-\r
-///////////////////////////////// Stereo Calibration /////////////////////////////////////\r
-\r
-class CV_StereoCalibrationTest : public CvTest\r
-{\r
-public:\r
- CV_StereoCalibrationTest( const char* test_name, const char* test_funcs );\r
- ~CV_StereoCalibrationTest();\r
- void clear();\r
-protected:\r
- bool checkPandROI( int test_case_idx,\r
- const Mat& M, const Mat& D, const Mat& R,\r
- const Mat& P, Size imgsize, Rect roi );\r
-\r
- // covers of tested functions\r
- virtual double calibrateStereoCamera( const vector<vector<Point3f> >& objectPoints,\r
- const vector<vector<Point2f> >& imagePoints1,\r
- const vector<vector<Point2f> >& imagePoints2,\r
- Mat& cameraMatrix1, Mat& distCoeffs1,\r
- Mat& cameraMatrix2, Mat& distCoeffs2,\r
- Size imageSize, Mat& R, Mat& T,\r
- Mat& E, Mat& F, TermCriteria criteria, int flags ) = 0;\r
- virtual void rectify( const Mat& cameraMatrix1, const Mat& distCoeffs1,\r
- const Mat& cameraMatrix2, const Mat& distCoeffs2,\r
- Size imageSize, const Mat& R, const Mat& T,\r
- Mat& R1, Mat& R2, Mat& P1, Mat& P2, Mat& Q,\r
- double alpha, Size newImageSize,\r
- Rect* validPixROI1, Rect* validPixROI2, int flags ) = 0;\r
- virtual bool rectifyUncalibrated( const Mat& points1,\r
- const Mat& points2, const Mat& F, Size imgSize,\r
- Mat& H1, Mat& H2, double threshold=5 ) = 0;\r
-\r
- void run(int);\r
-};\r
-\r
-\r
-CV_StereoCalibrationTest::CV_StereoCalibrationTest( const char* test_name, const char* test_funcs ):\r
-CvTest( test_name, test_funcs )\r
-{\r
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;\r
-}\r
-\r
-\r
-CV_StereoCalibrationTest::~CV_StereoCalibrationTest()\r
-{\r
- clear();\r
-}\r
-\r
-void CV_StereoCalibrationTest::clear()\r
-{\r
- CvTest::clear();\r
-}\r
-\r
-bool CV_StereoCalibrationTest::checkPandROI( int test_case_idx, const Mat& M, const Mat& D, const Mat& R,\r
- const Mat& P, Size imgsize, Rect roi )\r
-{\r
- const double eps = 0.05;\r
- const int N = 21;\r
- int x, y, k;\r
- vector<Point2f> pts, upts;\r
-\r
- // step 1. check that all the original points belong to the destination image\r
- for( y = 0; y < N; y++ )\r
- for( x = 0; x < N; x++ )\r
- pts.push_back(Point2f((float)x*imgsize.width/(N-1), (float)y*imgsize.height/(N-1)));\r
-\r
- undistortPoints(Mat(pts), upts, M, D, R, P );\r
- for( k = 0; k < N*N; k++ )\r
- if( upts[k].x < -imgsize.width*eps || upts[k].x > imgsize.width*(1+eps) ||\r
- upts[k].y < -imgsize.height*eps || upts[k].y > imgsize.height*(1+eps) )\r
- {\r
- ts->printf(CvTS::LOG, "Test #%d. The point (%g, %g) was mapped to (%g, %g) which is out of image\n",\r
- test_case_idx, pts[k].x, pts[k].y, upts[k].x, upts[k].y);\r
- return false;\r
- }\r
-\r
- // step 2. check that all the points inside ROI belong to the original source image\r
- Mat temp(imgsize, CV_8U), utemp, map1, map2;\r
- temp = Scalar::all(1);\r
- initUndistortRectifyMap(M, D, R, P, imgsize, CV_16SC2, map1, map2);\r
- remap(temp, utemp, map1, map2, INTER_LINEAR);\r
-\r
- if(roi.x < 0 || roi.y < 0 || roi.x + roi.width > imgsize.width || roi.y + roi.height > imgsize.height)\r
- {\r
- ts->printf(CvTS::LOG, "Test #%d. The ROI=(%d, %d, %d, %d) is outside of the imge rectangle\n",\r
- test_case_idx, roi.x, roi.y, roi.width, roi.height);\r
- return false;\r
- }\r
- double s = sum(utemp(roi))[0];\r
- if( s > roi.area() || roi.area() - s > roi.area()*(1-eps) )\r
- {\r
- ts->printf(CvTS::LOG, "Test #%d. The ratio of black pixels inside the valid ROI (~%g%%) is too large\n",\r
- test_case_idx, s*100./roi.area());\r
- return false;\r
- }\r
-\r
- return true;\r
-}\r
-\r
-void CV_StereoCalibrationTest::run( int )\r
-{\r
- const int ntests = 1;\r
- const double maxReprojErr = 2;\r
- const double maxScanlineDistErr_c = 3;\r
- const double maxScanlineDistErr_uc = 4;\r
- FILE* f = 0;\r
-\r
- for(int testcase = 1; testcase <= ntests; testcase++)\r
- {\r
- char filepath[1000];\r
- char buf[1000];\r
- sprintf( filepath, "%sstereo/case%d/stereo_calib.txt", ts->get_data_path(), testcase );\r
- f = fopen(filepath, "rt");\r
- Size patternSize;\r
- vector<string> imglist;\r
-\r
- if( !f || !fgets(buf, sizeof(buf)-3, f) || sscanf(buf, "%d%d", &patternSize.width, &patternSize.height) != 2 )\r
- {\r
- ts->printf( CvTS::LOG, "The file %s can not be opened or has invalid content\n", filepath );\r
- ts->set_failed_test_info( f ? CvTS::FAIL_INVALID_TEST_DATA : CvTS::FAIL_MISSING_TEST_DATA );\r
- return;\r
- }\r
-\r
- for(;;)\r
- {\r
- if( !fgets( buf, sizeof(buf)-3, f ))\r
- break;\r
- size_t len = strlen(buf);\r
- while( len > 0 && isspace(buf[len-1]))\r
- buf[--len] = '\0';\r
- if( buf[0] == '#')\r
- continue;\r
- sprintf(filepath, "%sstereo/case%d/%s", ts->get_data_path(), testcase, buf );\r
- imglist.push_back(string(filepath));\r
- }\r
- fclose(f);\r
-\r
- if( imglist.size() == 0 || imglist.size() % 2 != 0 )\r
- {\r
- ts->printf( CvTS::LOG, "The number of images is 0 or an odd number in the case #%d\n", testcase );\r
- ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA );\r
- return;\r
- }\r
-\r
- int nframes = (int)(imglist.size()/2);\r
- int npoints = patternSize.width*patternSize.height;\r
- vector<vector<Point3f> > objpt(nframes);\r
- vector<vector<Point2f> > imgpt1(nframes);\r
- vector<vector<Point2f> > imgpt2(nframes);\r
- Size imgsize;\r
- int total = 0;\r
-\r
- for( int i = 0; i < nframes; i++ )\r
- {\r
- Mat left = imread(imglist[i*2]);\r
- Mat right = imread(imglist[i*2+1]);\r
- if(!left.data || !right.data)\r
- {\r
- ts->printf( CvTS::LOG, "Can not load images %s and %s, testcase %d\n",\r
- imglist[i*2].c_str(), imglist[i*2+1].c_str(), testcase );\r
- ts->set_failed_test_info( CvTS::FAIL_MISSING_TEST_DATA );\r
- return;\r
- }\r
- imgsize = left.size();\r
- bool found1 = findChessboardCorners(left, patternSize, imgpt1[i]);\r
- bool found2 = findChessboardCorners(right, patternSize, imgpt2[i]);\r
- if(!found1 || !found2)\r
- {\r
- ts->printf( CvTS::LOG, "The function could not detect boards on the images %s and %s, testcase %d\n",\r
- imglist[i*2].c_str(), imglist[i*2+1].c_str(), testcase );\r
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );\r
- return;\r
- }\r
- total += (int)imgpt1[i].size();\r
- for( int j = 0; j < npoints; j++ )\r
- objpt[i].push_back(Point3f((float)(j%patternSize.width), (float)(j/patternSize.width), 0.f));\r
- }\r
-\r
- // rectify (calibrated)\r
- Mat M1 = Mat::eye(3,3,CV_64F), M2 = Mat::eye(3,3,CV_64F), D1(5,1,CV_64F), D2(5,1,CV_64F), R, T, E, F;\r
- M1.at<double>(0,2) = M2.at<double>(0,2)=(imgsize.width-1)*0.5;\r
- M1.at<double>(1,2) = M2.at<double>(1,2)=(imgsize.height-1)*0.5;\r
- D1 = Scalar::all(0);\r
- D2 = Scalar::all(0);\r
- double err = calibrateStereoCamera(objpt, imgpt1, imgpt2, M1, D1, M2, D2, imgsize, R, T, E, F,\r
- TermCriteria(TermCriteria::MAX_ITER+TermCriteria::EPS, 30, 1e-6),\r
- CV_CALIB_SAME_FOCAL_LENGTH\r
- //+ CV_CALIB_FIX_ASPECT_RATIO\r
- + CV_CALIB_FIX_PRINCIPAL_POINT\r
- + CV_CALIB_ZERO_TANGENT_DIST\r
- + CV_CALIB_FIX_K3\r
- + CV_CALIB_FIX_K4 + CV_CALIB_FIX_K5 //+ CV_CALIB_FIX_K6\r
- );\r
- err /= nframes*npoints;\r
- if( err > maxReprojErr )\r
- {\r
- ts->printf( CvTS::LOG, "The average reprojection error is too big (=%g), testcase %d\n", err, testcase);\r
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );\r
- return;\r
- }\r
-\r
- Mat R1, R2, P1, P2, Q;\r
- Rect roi1, roi2;\r
- rectify(M1, D1, M2, D2, imgsize, R, T, R1, R2, P1, P2, Q, 1, imgsize, &roi1, &roi2, 0);\r
- Mat eye33 = Mat::eye(3,3,CV_64F);\r
- Mat R1t = R1.t(), R2t = R2.t();\r
-\r
- if( norm(R1t*R1 - eye33) > 0.01 ||\r
- norm(R2t*R2 - eye33) > 0.01 ||\r
- abs(determinant(F)) > 0.01)\r
- {\r
- ts->printf( CvTS::LOG, "The computed (by rectify) R1 and R2 are not orthogonal,"\r
- "or the computed (by calibrate) F is not singular, testcase %d\n", testcase);\r
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );\r
- return;\r
- }\r
-\r
- if(!checkPandROI(testcase, M1, D1, R1, P1, imgsize, roi1))\r
- {\r
- ts->set_failed_test_info( CvTS::FAIL_BAD_ACCURACY );\r
- return;\r
- }\r
-\r
- if(!checkPandROI(testcase, M2, D2, R2, P2, imgsize, roi2))\r
- {\r
- ts->set_failed_test_info( CvTS::FAIL_BAD_ACCURACY );\r
- return;\r
- }\r
-\r
- // rectifyUncalibrated\r
- CV_Assert( imgpt1.size() == imgpt2.size() );\r
- Mat _imgpt1( total, 1, CV_32FC2 ), _imgpt2( total, 1, CV_32FC2 );\r
- vector<vector<Point2f> >::const_iterator iit1 = imgpt1.begin();\r
- vector<vector<Point2f> >::const_iterator iit2 = imgpt2.begin();\r
- for( int pi = 0; iit1 != imgpt1.end(); ++iit1, ++iit2 )\r
- {\r
- vector<Point2f>::const_iterator pit1 = iit1->begin();\r
- vector<Point2f>::const_iterator pit2 = iit2->begin();\r
- CV_Assert( iit1->size() == iit2->size() );\r
- for( ; pit1 != iit1->end(); ++pit1, ++pit2, pi++ )\r
- {\r
- _imgpt1.at<Point2f>(pi,0) = Point2f( pit1->x, pit1->y );\r
- _imgpt2.at<Point2f>(pi,0) = Point2f( pit2->x, pit2->y );\r
- }\r
- }\r
-\r
- Mat _M1, _M2, _D1, _D2;\r
- vector<Mat> _R1, _R2, _T1, _T2;\r
- calibrateCamera( objpt, imgpt1, imgsize, _M1, _D1, _R1, _T1, 0 );\r
- calibrateCamera( objpt, imgpt2, imgsize, _M2, _D2, _R2, _T1, 0 );\r
- undistortPoints( _imgpt1, _imgpt1, _M1, _D1, Mat(), _M1 );\r
- undistortPoints( _imgpt2, _imgpt2, _M2, _D2, Mat(), _M2 );\r
-\r
- Mat matF, _H1, _H2;\r
- matF = findFundamentalMat( _imgpt1, _imgpt2 );\r
- rectifyUncalibrated( _imgpt1, _imgpt2, matF, imgsize, _H1, _H2 );\r
-\r
- Mat rectifPoints1, rectifPoints2;\r
- perspectiveTransform( _imgpt1, rectifPoints1, _H1 );\r
- perspectiveTransform( _imgpt2, rectifPoints2, _H2 );\r
-\r
- bool verticalStereo = abs(P2.at<double>(0,3)) < abs(P2.at<double>(1,3));\r
- double maxDiff_c = 0, maxDiff_uc = 0;\r
- for( int i = 0, k = 0; i < nframes; i++ )\r
- {\r
- vector<Point2f> temp[2];\r
- undistortPoints(Mat(imgpt1[i]), temp[0], M1, D1, R1, P1);\r
- undistortPoints(Mat(imgpt2[i]), temp[1], M2, D2, R2, P2);\r
-\r
- for( int j = 0; j < npoints; j++, k++ )\r
- {\r
- double diff_c = verticalStereo ? abs(temp[0][j].x - temp[1][j].x) : abs(temp[0][j].y - temp[1][j].y);\r
- Point2f d = rectifPoints1.at<Point2f>(k,0) - rectifPoints2.at<Point2f>(k,0);\r
- double diff_uc = verticalStereo ? abs(d.x) : abs(d.y);\r
- maxDiff_c = max(maxDiff_c, diff_c);\r
- maxDiff_uc = max(maxDiff_uc, diff_uc);\r
- if( maxDiff_c > maxScanlineDistErr_c )\r
- {\r
- ts->printf( CvTS::LOG, "The distance between %s coordinates is too big(=%g) (used calibrated stereo), testcase %d\n",\r
- verticalStereo ? "x" : "y", diff_c, testcase);\r
- ts->set_failed_test_info( CvTS::FAIL_BAD_ACCURACY );\r
- return;\r
- }\r
- if( maxDiff_uc > maxScanlineDistErr_uc )\r
- {\r
- ts->printf( CvTS::LOG, "The distance between %s coordinates is too big(=%g) (used uncalibrated stereo), testcase %d\n",\r
- verticalStereo ? "x" : "y", diff_uc, testcase);\r
- ts->set_failed_test_info( CvTS::FAIL_BAD_ACCURACY );\r
- return;\r
- }\r
- }\r
- }\r
-\r
- ts->printf( CvTS::LOG, "Testcase %d. Max distance (calibrated) =%g\n"\r
- "Max distance (uncalibrated) =%g\n", testcase, maxDiff_c, maxDiff_uc );\r
- }\r
-}\r
-\r
-//-------------------------------- CV_StereoCalibrationTest_C ------------------------------\r
-\r
-class CV_StereoCalibrationTest_C : public CV_StereoCalibrationTest\r
-{\r
-public:\r
- CV_StereoCalibrationTest_C() : CV_StereoCalibrationTest( "calibrate-stereo-c",\r
- "cvStereoCalibrate, cvStereoRectify, cvStereoRectifyUncalibrated" ) {}\r
-protected:\r
- virtual double calibrateStereoCamera( const vector<vector<Point3f> >& objectPoints,\r
- const vector<vector<Point2f> >& imagePoints1,\r
- const vector<vector<Point2f> >& imagePoints2,\r
- Mat& cameraMatrix1, Mat& distCoeffs1,\r
- Mat& cameraMatrix2, Mat& distCoeffs2,\r
- Size imageSize, Mat& R, Mat& T,\r
- Mat& E, Mat& F, TermCriteria criteria, int flags );\r
- virtual void rectify( const Mat& cameraMatrix1, const Mat& distCoeffs1,\r
- const Mat& cameraMatrix2, const Mat& distCoeffs2,\r
- Size imageSize, const Mat& R, const Mat& T,\r
- Mat& R1, Mat& R2, Mat& P1, Mat& P2, Mat& Q,\r
- double alpha, Size newImageSize,\r
- Rect* validPixROI1, Rect* validPixROI2, int flags );\r
- virtual bool rectifyUncalibrated( const Mat& points1,\r
- const Mat& points2, const Mat& F, Size imgSize,\r
- Mat& H1, Mat& H2, double threshold=5 );\r
-};\r
-\r
-double CV_StereoCalibrationTest_C::calibrateStereoCamera( const vector<vector<Point3f> >& objectPoints,\r
- const vector<vector<Point2f> >& imagePoints1,\r
- const vector<vector<Point2f> >& imagePoints2,\r
- Mat& cameraMatrix1, Mat& distCoeffs1,\r
- Mat& cameraMatrix2, Mat& distCoeffs2,\r
- Size imageSize, Mat& R, Mat& T,\r
- Mat& E, Mat& F, TermCriteria criteria, int flags )\r
-{\r
- cameraMatrix1.create( 3, 3, CV_64F );\r
- cameraMatrix2.create( 3, 3, CV_64F);\r
- distCoeffs1.create( 1, 5, CV_64F);\r
- distCoeffs2.create( 1, 5, CV_64F);\r
- R.create(3, 3, CV_64F);\r
- T.create(3, 1, CV_64F);\r
- E.create(3, 3, CV_64F);\r
- F.create(3, 3, CV_64F);\r
-\r
- int nimages = (int)objectPoints.size(), total = 0;\r
- for( int i = 0; i < nimages; i++ )\r
- {\r
- total += (int)objectPoints[i].size();\r
- }\r
-\r
- Mat npoints( 1, nimages, CV_32S ),\r
- objPt( 1, total, DataType<Point3f>::type ),\r
- imgPt( 1, total, DataType<Point2f>::type ),\r
- imgPt2( 1, total, DataType<Point2f>::type );\r
-\r
- Point2f* imgPtData2 = imgPt2.ptr<Point2f>();\r
- Point3f* objPtData = objPt.ptr<Point3f>();\r
- Point2f* imgPtData = imgPt.ptr<Point2f>();\r
- for( int i = 0, ni = 0, j = 0; i < nimages; i++, j += ni )\r
- {\r
- ni = (int)objectPoints[i].size();\r
- ((int*)npoints.data)[i] = ni;\r
- std::copy(objectPoints[i].begin(), objectPoints[i].end(), objPtData + j);\r
- std::copy(imagePoints1[i].begin(), imagePoints1[i].end(), imgPtData + j);\r
- std::copy(imagePoints2[i].begin(), imagePoints2[i].end(), imgPtData2 + j);\r
- }\r
- CvMat _objPt = objPt, _imgPt = imgPt, _imgPt2 = imgPt2, _npoints = npoints;\r
- CvMat _cameraMatrix1 = cameraMatrix1, _distCoeffs1 = distCoeffs1;\r
- CvMat _cameraMatrix2 = cameraMatrix2, _distCoeffs2 = distCoeffs2;\r
- CvMat matR = R, matT = T, matE = E, matF = F;\r
-\r
- return cvStereoCalibrate(&_objPt, &_imgPt, &_imgPt2, &_npoints, &_cameraMatrix1,\r
- &_distCoeffs1, &_cameraMatrix2, &_distCoeffs2, imageSize,\r
- &matR, &matT, &matE, &matF, criteria, flags );\r
-}\r
-\r
-void CV_StereoCalibrationTest_C::rectify( const Mat& cameraMatrix1, const Mat& distCoeffs1,\r
- const Mat& cameraMatrix2, const Mat& distCoeffs2,\r
- Size imageSize, const Mat& R, const Mat& T,\r
- Mat& R1, Mat& R2, Mat& P1, Mat& P2, Mat& Q,\r
- double alpha, Size newImageSize,\r
- Rect* validPixROI1, Rect* validPixROI2, int flags )\r
-{\r
- int rtype = CV_64F;\r
- R1.create(3, 3, rtype);\r
- R2.create(3, 3, rtype);\r
- P1.create(3, 4, rtype);\r
- P2.create(3, 4, rtype);\r
- Q.create(4, 4, rtype);\r
- CvMat _cameraMatrix1 = cameraMatrix1, _distCoeffs1 = distCoeffs1;\r
- CvMat _cameraMatrix2 = cameraMatrix2, _distCoeffs2 = distCoeffs2;\r
- CvMat matR = R, matT = T, _R1 = R1, _R2 = R2, _P1 = P1, _P2 = P2, matQ = Q;\r
- cvStereoRectify( &_cameraMatrix1, &_cameraMatrix2, &_distCoeffs1, &_distCoeffs2,\r
- imageSize, &matR, &matT, &_R1, &_R2, &_P1, &_P2, &matQ, flags,\r
- alpha, newImageSize, (CvRect*)validPixROI1, (CvRect*)validPixROI2);\r
-}\r
-\r
-bool CV_StereoCalibrationTest_C::rectifyUncalibrated( const Mat& points1,\r
- const Mat& points2, const Mat& F, Size imgSize, Mat& H1, Mat& H2, double threshold )\r
-{\r
- H1.create(3, 3, CV_64F);\r
- H2.create(3, 3, CV_64F);\r
- CvMat _pt1 = points1, _pt2 = points2, matF, *pF=0, _H1 = H1, _H2 = H2;\r
- if( F.size() == Size(3, 3) )\r
- pF = &(matF = F);\r
- return cvStereoRectifyUncalibrated(&_pt1, &_pt2, pF, imgSize, &_H1, &_H2, threshold) > 0;\r
-}\r
-\r
-CV_StereoCalibrationTest_C stereocalib_test_c;\r
-\r
-//-------------------------------- CV_StereoCalibrationTest_CPP ------------------------------\r
-\r
-class CV_StereoCalibrationTest_CPP : public CV_StereoCalibrationTest\r
-{\r
-public:\r
- CV_StereoCalibrationTest_CPP() : CV_StereoCalibrationTest( "calibrate-stereo-cpp",\r
- "stereoCalibrate, stereoRectify, stereoRectifyUncalibrated" ) {}\r
-protected:\r
- virtual double calibrateStereoCamera( const vector<vector<Point3f> >& objectPoints,\r
- const vector<vector<Point2f> >& imagePoints1,\r
- const vector<vector<Point2f> >& imagePoints2,\r
- Mat& cameraMatrix1, Mat& distCoeffs1,\r
- Mat& cameraMatrix2, Mat& distCoeffs2,\r
- Size imageSize, Mat& R, Mat& T,\r
- Mat& E, Mat& F, TermCriteria criteria, int flags );\r
- virtual void rectify( const Mat& cameraMatrix1, const Mat& distCoeffs1,\r
- const Mat& cameraMatrix2, const Mat& distCoeffs2,\r
- Size imageSize, const Mat& R, const Mat& T,\r
- Mat& R1, Mat& R2, Mat& P1, Mat& P2, Mat& Q,\r
- double alpha, Size newImageSize,\r
- Rect* validPixROI1, Rect* validPixROI2, int flags );\r
- virtual bool rectifyUncalibrated( const Mat& points1,\r
- const Mat& points2, const Mat& F, Size imgSize,\r
- Mat& H1, Mat& H2, double threshold=5 );\r
-};\r
-\r
-double CV_StereoCalibrationTest_CPP::calibrateStereoCamera( const vector<vector<Point3f> >& objectPoints,\r
- const vector<vector<Point2f> >& imagePoints1,\r
- const vector<vector<Point2f> >& imagePoints2,\r
- Mat& cameraMatrix1, Mat& distCoeffs1,\r
- Mat& cameraMatrix2, Mat& distCoeffs2,\r
- Size imageSize, Mat& R, Mat& T,\r
- Mat& E, Mat& F, TermCriteria criteria, int flags )\r
-{\r
- return stereoCalibrate( objectPoints, imagePoints1, imagePoints2,\r
- cameraMatrix1, distCoeffs1, cameraMatrix2, distCoeffs2,\r
- imageSize, R, T, E, F, criteria, flags );\r
-}\r
-\r
-void CV_StereoCalibrationTest_CPP::rectify( const Mat& cameraMatrix1, const Mat& distCoeffs1,\r
- const Mat& cameraMatrix2, const Mat& distCoeffs2,\r
- Size imageSize, const Mat& R, const Mat& T,\r
- Mat& R1, Mat& R2, Mat& P1, Mat& P2, Mat& Q,\r
- double alpha, Size newImageSize,\r
- Rect* validPixROI1, Rect* validPixROI2, int flags )\r
-{\r
- stereoRectify( cameraMatrix1, distCoeffs1, cameraMatrix2, distCoeffs2,\r
- imageSize, R, T, R1, R2, P1, P2, Q, alpha, newImageSize,validPixROI1, validPixROI2, flags );\r
-}\r
-\r
-bool CV_StereoCalibrationTest_CPP::rectifyUncalibrated( const Mat& points1,\r
- const Mat& points2, const Mat& F, Size imgSize, Mat& H1, Mat& H2, double threshold )\r
-{\r
- return stereoRectifyUncalibrated( points1, points2, F, imgSize, H1, H2, threshold );\r
-}\r
-\r
-CV_StereoCalibrationTest_CPP stereocalib_test_cpp;\r
-\r
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////\r
-//\r
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.\r
-//\r
-// By downloading, copying, installing or using the software you agree to this license.\r
-// If you do not agree to this license, do not download, install,\r
-// copy or use the software.\r
-//\r
-//\r
-// License Agreement\r
-// For Open Source Computer Vision Library\r
-//\r
-// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.\r
-// Copyright (C) 2009, Willow Garage Inc., all rights reserved.\r
-// Third party copyrights are property of their respective owners.\r
-//\r
-// Redistribution and use in source and binary forms, with or without modification,\r
-// are permitted provided that the following conditions are met:\r
-//\r
-// * Redistribution's of source code must retain the above copyright notice,\r
-// this list of conditions and the following disclaimer.\r
-//\r
-// * Redistribution's in binary form must reproduce the above copyright notice,\r
-// this list of conditions and the following disclaimer in the documentation\r
-// and/or other materials provided with the distribution.\r
-//\r
-// * The name of the copyright holders may not be used to endorse or promote products\r
-// derived from this software without specific prior written permission.\r
-//\r
-// This software is provided by the copyright holders and contributors "as is" and\r
-// any express or implied warranties, including, but not limited to, the implied\r
-// warranties of merchantability and fitness for a particular purpose are disclaimed.\r
-// In no event shall the Intel Corporation or contributors be liable for any direct,\r
-// indirect, incidental, special, exemplary, or consequential damages\r
-// (including, but not limited to, procurement of substitute goods or services;\r
-// loss of use, data, or profits; or business interruption) however caused\r
-// and on any theory of liability, whether in contract, strict liability,\r
-// or tort (including negligence or otherwise) arising in any way out of\r
-// the use of this software, even if advised of the possibility of such damage.\r
-//\r
-//M*/\r
-\r
-#include "cvtest.h"\r
-#include <string>\r
-#include <limits>\r
-#include <vector>\r
-#include <iostream>\r
-#include <sstream>\r
-#include <iomanip>\r
-\r
-#include "cvchessboardgenerator.h"\r
-\r
-using namespace cv;\r
-using namespace std;\r
-\r
-//template<class T> ostream& operator<<(ostream& out, const Mat_<T>& mat)\r
-//{ \r
-// for(Mat_<T>::const_iterator pos = mat.begin(), end = mat.end(); pos != end; ++pos)\r
-// out << *pos << " ";\r
-// return out;\r
-//}\r
-//ostream& operator<<(ostream& out, const Mat& mat) { return out << Mat_<double>(mat); } \r
-\r
-Mat calcRvec(const vector<Point3f>& points, const Size& cornerSize)\r
-{ \r
- Point3f p00 = points[0];\r
- Point3f p10 = points[1];\r
- Point3f p01 = points[cornerSize.width]; \r
-\r
- Vec3d ex(p10.x - p00.x, p10.y - p00.y, p10.z - p00.z);\r
- Vec3d ey(p01.x - p00.x, p01.y - p00.y, p01.z - p00.z); \r
- Vec3d ez = ex.cross(ey); \r
-\r
- Mat rot(3, 3, CV_64F);\r
- *rot.ptr<Vec3d>(0) = ex;\r
- *rot.ptr<Vec3d>(1) = ey;\r
- *rot.ptr<Vec3d>(2) = ez * (1.0/norm(ez));\r
-\r
- Mat res;\r
- Rodrigues(rot.t(), res);\r
- return res.reshape(1, 1);\r
-}\r
-\r
-class CV_CalibrateCameraArtificialTest : public CvTest\r
-{\r
-public:\r
- CV_CalibrateCameraArtificialTest() : CvTest( "calibrate-camera-artificial", "cvCalibrateCamera2")\r
- {\r
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE; \r
- }\r
- ~CV_CalibrateCameraArtificialTest() {}\r
-protected: \r
- int r;\r
-\r
- const static int JUST_FIND_CORNERS = 0;\r
- const static int USE_CORNERS_SUBPIX = 1;\r
- const static int USE_4QUAD_CORNERS = 2;\r
- const static int ARTIFICIAL_CORNERS = 4;\r
-\r
-\r
- bool checkErr(double a, double a0, double eps, double delta)\r
- {\r
- return fabs(a - a0) > eps * (fabs(a0) + delta);\r
- }\r
-\r
- void compareCameraMatrs(const Mat_<double>& camMat, const Mat& camMat_est)\r
- {\r
- if ( camMat_est.at<double>(0, 1) != 0 || camMat_est.at<double>(1, 0) != 0 ||\r
- camMat_est.at<double>(2, 0) != 0 || camMat_est.at<double>(2, 1) != 0 ||\r
- camMat_est.at<double>(2, 2) != 1)\r
- {\r
- ts->printf( CvTS::LOG, "Bad shape of camera matrix returned \n");\r
- ts->set_failed_test_info(CvTS::FAIL_MISMATCH);\r
- } \r
-\r
- double fx_e = camMat_est.at<double>(0, 0), fy_e = camMat_est.at<double>(1, 1);\r
- double cx_e = camMat_est.at<double>(0, 2), cy_e = camMat_est.at<double>(1, 2);\r
-\r
- double fx = camMat(0, 0), fy = camMat(1, 1), cx = camMat(0, 2), cy = camMat(1, 2);\r
-\r
- const double eps = 1e-2;\r
- const double dlt = 1e-5;\r
-\r
- bool fail = checkErr(fx_e, fx, eps, dlt) || checkErr(fy_e, fy, eps, dlt) || \r
- checkErr(cx_e, cx, eps, dlt) || checkErr(cy_e, cy, eps, dlt); \r
-\r
- if (fail)\r
- {\r
- ts->set_failed_test_info(CvTS::FAIL_BAD_ACCURACY); \r
- } \r
- ts->printf( CvTS::LOG, "%d) Expected [Fx Fy Cx Cy] = [%.3f %.3f %.3f %.3f]\n", r, fx, fy, cx, cy);\r
- ts->printf( CvTS::LOG, "%d) Estimated [Fx Fy Cx Cy] = [%.3f %.3f %.3f %.3f]\n", r, fx_e, fy_e, cx_e, cy_e); \r
- }\r
-\r
- void compareDistCoeffs(const Mat_<double>& distCoeffs, const Mat& distCoeffs_est)\r
- { \r
- const double *dt_e = distCoeffs_est.ptr<double>();\r
-\r
- double k1_e = dt_e[0], k2_e = dt_e[1], k3_e = dt_e[4];\r
- double p1_e = dt_e[2], p2_e = dt_e[3];\r
-\r
- double k1 = distCoeffs(0, 0), k2 = distCoeffs(0, 1), k3 = distCoeffs(0, 4);\r
- double p1 = distCoeffs(0, 2), p2 = distCoeffs(0, 3);\r
-\r
- const double eps = 5e-2;\r
- const double dlt = 1e-3; \r
-\r
- const double eps_k3 = 5;\r
- const double dlt_k3 = 1e-3; \r
-\r
- bool fail = checkErr(k1_e, k1, eps, dlt) || checkErr(k2_e, k2, eps, dlt) || checkErr(k3_e, k3, eps_k3, dlt_k3) || \r
- checkErr(p1_e, p1, eps, dlt) || checkErr(p2_e, p2, eps, dlt); \r
-\r
- if (fail)\r
- {\r
- // commented according to vp123's recomendation. TODO - improve accuaracy\r
- //ts->set_failed_test_info(CvTS::FAIL_BAD_ACCURACY); ss \r
- } \r
- ts->printf( CvTS::LOG, "%d) DistCoeff exp=(%.2f, %.2f, %.4f, %.4f %.2f)\n", r, k1, k2, p1, p2, k3);\r
- ts->printf( CvTS::LOG, "%d) DistCoeff est=(%.2f, %.2f, %.4f, %.4f %.2f)\n", r, k1_e, k2_e, p1_e, p2_e, k3_e); \r
- ts->printf( CvTS::LOG, "%d) AbsError = [%.5f %.5f %.5f %.5f %.5f]\n", r, fabs(k1-k1_e), fabs(k2-k2_e), fabs(p1-p1_e), fabs(p2-p2_e), fabs(k3-k3_e));\r
- }\r
-\r
- void compareShiftVecs(const vector<Mat>& tvecs, const vector<Mat>& tvecs_est)\r
- {\r
- const double eps = 1e-2;\r
- const double dlt = 1e-4;\r
-\r
- int err_count = 0;\r
- const int errMsgNum = 4;\r
- for(size_t i = 0; i < tvecs.size(); ++i)\r
- {\r
- const Point3d& tvec = *tvecs[i].ptr<Point3d>();\r
- const Point3d& tvec_est = *tvecs_est[i].ptr<Point3d>();\r
-\r
- if (norm(tvec_est - tvec) > eps* (norm(tvec) + dlt)) \r
- {\r
- if (err_count++ < errMsgNum)\r
- {\r
- if (err_count == errMsgNum) \r
- ts->printf( CvTS::LOG, "%d) ...\n", r); \r
- else \r
- {\r
- ts->printf( CvTS::LOG, "%d) Bad accuracy in returned tvecs. Index = %d\n", r, i); \r
- ts->printf( CvTS::LOG, "%d) norm(tvec_est - tvec) = %f, norm(tvec_exp) = %f \n", r, norm(tvec_est - tvec), norm(tvec));\r
- }\r
- }\r
- ts->set_failed_test_info(CvTS::FAIL_BAD_ACCURACY);\r
- } \r
- }\r
- }\r
-\r
- void compareRotationVecs(const vector<Mat>& rvecs, const vector<Mat>& rvecs_est)\r
- {\r
- const double eps = 2e-2;\r
- const double dlt = 1e-4;\r
-\r
- Mat rmat, rmat_est;\r
- int err_count = 0;\r
- const int errMsgNum = 4;\r
- for(size_t i = 0; i < rvecs.size(); ++i)\r
- { \r
- Rodrigues(rvecs[i], rmat);\r
- Rodrigues(rvecs_est[i], rmat_est); \r
-\r
- if (norm(rmat_est, rmat) > eps* (norm(rmat) + dlt))\r
- {\r
- if (err_count++ < errMsgNum)\r
- {\r
- if (err_count == errMsgNum)\r
- ts->printf( CvTS::LOG, "%d) ...\n", r); \r
- else\r
- {\r
- ts->printf( CvTS::LOG, "%d) Bad accuracy in returned rvecs (rotation matrs). Index = %d\n", r, i); \r
- ts->printf( CvTS::LOG, "%d) norm(rot_mat_est - rot_mat_exp) = %f, norm(rot_mat_exp) = %f \n", r, norm(rmat_est, rmat), norm(rmat)); \r
-\r
- }\r
- }\r
- ts->set_failed_test_info(CvTS::FAIL_BAD_ACCURACY);\r
- }\r
- }\r
- }\r
-\r
- double reprojectErrorWithoutIntrinsics(const vector<Point3f>& cb3d, const vector<Mat>& rvecs_exp, const vector<Mat>& tvecs_exp,\r
- const vector<Mat>& rvecs_est, const vector<Mat>& tvecs_est)\r
- { \r
- const static Mat eye33 = Mat::eye(3, 3, CV_64F);\r
- const static Mat zero15 = Mat::zeros(1, 5, CV_64F);\r
- Mat chessboard3D(cb3d);\r
- vector<Point2f> uv_exp, uv_est;\r
- double res = 0; \r
-\r
- for(size_t i = 0; i < rvecs_exp.size(); ++i) \r
- { \r
- projectPoints(chessboard3D, rvecs_exp[i], tvecs_exp[i], eye33, zero15, uv_exp); \r
- projectPoints(chessboard3D, rvecs_est[i], tvecs_est[i], eye33, zero15, uv_est);\r
- for(size_t j = 0; j < cb3d.size(); ++j)\r
- res += norm(uv_exp[i] - uv_est[i]);\r
- }\r
- return res;\r
- }\r
-\r
- Size2f sqSile;\r
-\r
- vector<Point3f> chessboard3D;\r
- vector<Mat> boards, rvecs_exp, tvecs_exp, rvecs_spnp, tvecs_spnp; \r
- vector< vector<Point3f> > objectPoints;\r
- vector< vector<Point2f> > imagePoints_art;\r
- vector< vector<Point2f> > imagePoints_findCb;\r
-\r
-\r
- void prepareForTest(const Mat& bg, const Mat& camMat, const Mat& distCoeffs, size_t brdsNum, const ChessBoardGenerator& cbg)\r
- {\r
- sqSile = Size2f(1.f, 1.f);\r
- Size cornersSize = cbg.cornersSize();\r
-\r
- chessboard3D.clear();\r
- for(int j = 0; j < cornersSize.height; ++j)\r
- for(int i = 0; i < cornersSize.width; ++i)\r
- chessboard3D.push_back(Point3f(sqSile.width * i, sqSile.height * j, 0));\r
-\r
- boards.resize(brdsNum);\r
- rvecs_exp.resize(brdsNum);\r
- tvecs_exp.resize(brdsNum);\r
- objectPoints.clear();\r
- objectPoints.resize(brdsNum, chessboard3D);\r
- imagePoints_art.clear();\r
- imagePoints_findCb.clear();\r
-\r
- vector<Point2f> corners_art, corners_fcb;\r
- for(size_t i = 0; i < brdsNum; ++i) \r
- { \r
- for(;;)\r
- {\r
- boards[i] = cbg(bg, camMat, distCoeffs, sqSile, corners_art);\r
- if(findChessboardCorners(boards[i], cornersSize, corners_fcb)) \r
- break; \r
- } \r
-\r
- //cv::namedWindow("CB"); imshow("CB", boards[i]); cv::waitKey();\r
-\r
- imagePoints_art.push_back(corners_art); \r
- imagePoints_findCb.push_back(corners_fcb);\r
-\r
- tvecs_exp[i].create(1, 3, CV_64F);\r
- *tvecs_exp[i].ptr<Point3d>() = cbg.corners3d[0];\r
- rvecs_exp[i] = calcRvec(cbg.corners3d, cbg.cornersSize()); \r
- }\r
-\r
- }\r
-\r
- void runTest(const Size& imgSize, const Mat_<double>& camMat, const Mat_<double>& distCoeffs, size_t brdsNum, const Size& cornersSize, int flag = 0)\r
- { \r
- const TermCriteria tc(TermCriteria::EPS|TermCriteria::MAX_ITER, 30, 0.1);\r
-\r
- vector< vector<Point2f> > imagePoints;\r
-\r
- switch(flag)\r
- {\r
- case JUST_FIND_CORNERS: imagePoints = imagePoints_findCb; break;\r
- case ARTIFICIAL_CORNERS: imagePoints = imagePoints_art; break;\r
-\r
- case USE_CORNERS_SUBPIX: \r
- for(size_t i = 0; i < brdsNum; ++i)\r
- { \r
- Mat gray;\r
- cvtColor(boards[i], gray, CV_BGR2GRAY);\r
- vector<Point2f> tmp = imagePoints_findCb[i];\r
- cornerSubPix(gray, tmp, Size(5, 5), Size(-1,-1), tc);\r
- imagePoints.push_back(tmp);\r
- }\r
- break;\r
- case USE_4QUAD_CORNERS:\r
- for(size_t i = 0; i < brdsNum; ++i)\r
- { \r
- Mat gray;\r
- cvtColor(boards[i], gray, CV_BGR2GRAY); \r
- vector<Point2f> tmp = imagePoints_findCb[i];\r
- find4QuadCornerSubpix(gray, tmp, Size(5, 5));\r
- imagePoints.push_back(tmp);\r
- }\r
- break;\r
- default:\r
- throw std::exception();\r
- }\r
- \r
- Mat camMat_est = Mat::eye(3, 3, CV_64F), distCoeffs_est = Mat::zeros(1, 5, CV_64F);\r
- vector<Mat> rvecs_est, tvecs_est;\r
-\r
- int flags = /*CV_CALIB_FIX_K3|*/CV_CALIB_FIX_K4|CV_CALIB_FIX_K5|CV_CALIB_FIX_K6; //CALIB_FIX_K3; //CALIB_FIX_ASPECT_RATIO | | CALIB_ZERO_TANGENT_DIST;\r
- double rep_error = calibrateCamera(objectPoints, imagePoints, imgSize, camMat_est, distCoeffs_est, rvecs_est, tvecs_est, flags);\r
- rep_error /= brdsNum * cornersSize.area();\r
-\r
- const double thres = 1;\r
- if (rep_error > thres)\r
- {\r
- ts->printf( CvTS::LOG, "%d) Too big reproject error = %f\n", r, rep_error);\r
- ts->set_failed_test_info(CvTS::FAIL_BAD_ACCURACY);\r
- }\r
-\r
- compareCameraMatrs(camMat, camMat_est);\r
- compareDistCoeffs(distCoeffs, distCoeffs_est);\r
- compareShiftVecs(tvecs_exp, tvecs_est);\r
- compareRotationVecs(rvecs_exp, rvecs_est); \r
-\r
- double rep_errorWOI = reprojectErrorWithoutIntrinsics(chessboard3D, rvecs_exp, tvecs_exp, rvecs_est, tvecs_est); \r
- rep_errorWOI /= brdsNum * cornersSize.area();\r
-\r
- const double thres2 = 0.01;\r
- if (rep_errorWOI > thres2)\r
- {\r
- ts->printf( CvTS::LOG, "%d) Too big reproject error without intrinsics = %f\n", r, rep_errorWOI);\r
- ts->set_failed_test_info(CvTS::FAIL_BAD_ACCURACY);\r
- } \r
- \r
- ts->printf( CvTS::LOG, "%d) Testing solvePnP...\n", r);\r
- rvecs_spnp.resize(brdsNum);\r
- tvecs_spnp.resize(brdsNum);\r
- for(size_t i = 0; i < brdsNum; ++i)\r
- solvePnP(Mat(objectPoints[i]), Mat(imagePoints[i]), camMat, distCoeffs, rvecs_spnp[i], tvecs_spnp[i]);\r
-\r
- compareShiftVecs(tvecs_exp, tvecs_spnp);\r
- compareRotationVecs(rvecs_exp, rvecs_spnp); \r
- }\r
-\r
- void run(int)\r
- { \r
-\r
- ts->set_failed_test_info(CvTS::OK);\r
- RNG& rng = theRNG();\r
-\r
- int progress = 0;\r
- int repeat_num = 3;\r
- for(r = 0; r < repeat_num; ++r)\r
- { \r
- const int brds_num = 20; \r
-\r
- Mat bg(Size(640, 480), CV_8UC3); \r
- randu(bg, Scalar::all(32), Scalar::all(255)); \r
- GaussianBlur(bg, bg, Size(5, 5), 2);\r
-\r
- double fx = 300 + (20 * (double)rng - 10);\r
- double fy = 300 + (20 * (double)rng - 10);\r
-\r
- double cx = bg.cols/2 + (40 * (double)rng - 20);\r
- double cy = bg.rows/2 + (40 * (double)rng - 20);\r
-\r
- Mat_<double> camMat(3, 3);\r
- camMat << fx, 0., cx, 0, fy, cy, 0., 0., 1.;\r
-\r
- double k1 = 0.5 + (double)rng/5;\r
- double k2 = (double)rng/5;\r
- double k3 = (double)rng/5;\r
-\r
- double p1 = 0.001 + (double)rng/10;\r
- double p2 = 0.001 + (double)rng/10;\r
-\r
- Mat_<double> distCoeffs(1, 5, 0.0);\r
- distCoeffs << k1, k2, p1, p2, k3;\r
-\r
- ChessBoardGenerator cbg(Size(9, 8)); \r
- cbg.min_cos = 0.9;\r
- cbg.cov = 0.8;\r
-\r
- progress = update_progress(progress, r, repeat_num, 0);\r
- ts->printf( CvTS::LOG, "\n"); \r
- prepareForTest(bg, camMat, distCoeffs, brds_num, cbg);\r
-\r
- ts->printf( CvTS::LOG, "artificial corners\n"); \r
- runTest(bg.size(), camMat, distCoeffs, brds_num, cbg.cornersSize(), ARTIFICIAL_CORNERS); \r
- progress = update_progress(progress, r, repeat_num, 0);\r
-\r
- ts->printf( CvTS::LOG, "findChessboard corners\n");\r
- runTest(bg.size(), camMat, distCoeffs, brds_num, cbg.cornersSize(), JUST_FIND_CORNERS); \r
- progress = update_progress(progress, r, repeat_num, 0);\r
-\r
- ts->printf( CvTS::LOG, "cornersSubPix corners\n");\r
- runTest(bg.size(), camMat, distCoeffs, brds_num, cbg.cornersSize(), USE_CORNERS_SUBPIX);\r
- progress = update_progress(progress, r, repeat_num, 0);\r
-\r
- ts->printf( CvTS::LOG, "4quad corners\n");\r
- runTest(bg.size(), camMat, distCoeffs, brds_num, cbg.cornersSize(), USE_4QUAD_CORNERS);\r
- progress = update_progress(progress, r, repeat_num, 0);\r
- }\r
- }\r
-}; \r
-\r
-CV_CalibrateCameraArtificialTest calibrateCameraArtificialTest;\r
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-
-class CV_TrackBaseTest : public CvTest
-{
-public:
- CV_TrackBaseTest( const char* test_name, const char* test_funcs );
- virtual ~CV_TrackBaseTest();
- void clear();
- int write_default_params(CvFileStorage* fs);
-
-protected:
- int read_params( CvFileStorage* fs );
- void run_func(void);
- int prepare_test_case( int test_case_idx );
- int validate_test_results( int test_case_idx );
- void generate_object();
-
- int min_log_size, max_log_size;
- CvMat* img;
- CvBox2D box0;
- CvSize img_size;
- CvTermCriteria criteria;
- int img_type;
-};
-
-
-CV_TrackBaseTest::CV_TrackBaseTest( const char* test_name, const char* test_funcs ):
- CvTest( test_name, test_funcs )
-{
- img = 0;
- test_case_count = 100;
- min_log_size = 5;
- max_log_size = 8;
-
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;
-}
-
-
-CV_TrackBaseTest::~CV_TrackBaseTest()
-{
- clear();
-}
-
-
-void CV_TrackBaseTest::clear()
-{
- cvReleaseMat( &img );
- CvTest::clear();
-}
-
-
-int CV_TrackBaseTest::write_default_params( CvFileStorage* fs )
-{
- CvTest::write_default_params( fs );
- if( ts->get_testing_mode() != CvTS::TIMING_MODE )
- {
- write_param( fs, "test_case_count", test_case_count );
- write_param( fs, "min_log_size", min_log_size );
- write_param( fs, "max_log_size", max_log_size );
- }
- return 0;
-}
-
-
-int CV_TrackBaseTest::read_params( CvFileStorage* fs )
-{
- int code = CvTest::read_params( fs );
- if( code < 0 )
- return code;
-
- test_case_count = cvReadInt( find_param( fs, "test_case_count" ), test_case_count );
- min_log_size = cvReadInt( find_param( fs, "min_log_size" ), min_log_size );
- max_log_size = cvReadInt( find_param( fs, "max_log_size" ), max_log_size );
-
- min_log_size = cvTsClipInt( min_log_size, 1, 10 );
- max_log_size = cvTsClipInt( max_log_size, 1, 10 );
- if( min_log_size > max_log_size )
- {
- int t;
- CV_SWAP( min_log_size, max_log_size, t );
- }
-
- return 0;
-}
-
-
-void CV_TrackBaseTest::generate_object()
-{
- int x, y;
- double cx = box0.center.x;
- double cy = box0.center.y;
- double width = box0.size.width*0.5;
- double height = box0.size.height*0.5;
- double angle = box0.angle*CV_PI/180.;
- double a = sin(angle), b = -cos(angle);
- double inv_ww = 1./(width*width), inv_hh = 1./(height*height);
-
- img = cvCreateMat( img_size.height, img_size.width, img_type );
- cvZero( img );
-
- // use the straightforward algorithm: for every pixel check if it is inside the ellipse
- for( y = 0; y < img_size.height; y++ )
- {
- uchar* ptr = img->data.ptr + img->step*y;
- float* fl = (float*)ptr;
- double x_ = (y - cy)*b, y_ = (y - cy)*a;
-
- for( x = 0; x < img_size.width; x++ )
- {
- double x1 = (x - cx)*a - x_;
- double y1 = (x - cx)*b + y_;
-
- if( x1*x1*inv_hh + y1*y1*inv_ww <= 1. )
- {
- if( img_type == CV_8U )
- ptr[x] = (uchar)1;
- else
- fl[x] = (float)1.f;
- }
- }
- }
-}
-
-
-int CV_TrackBaseTest::prepare_test_case( int test_case_idx )
-{
- CvRNG* rng = ts->get_rng();
- CvTest::prepare_test_case( test_case_idx );
- float m;
-
- clear();
-
- box0.size.width = (float)exp((cvTsRandReal(rng) * (max_log_size - min_log_size) + min_log_size)*CV_LOG2);
- box0.size.height = (float)exp((cvTsRandReal(rng) * (max_log_size - min_log_size) + min_log_size)*CV_LOG2);
- box0.angle = (float)(cvTsRandReal(rng)*180.);
-
- if( box0.size.width > box0.size.height )
- {
- float t;
- CV_SWAP( box0.size.width, box0.size.height, t );
- }
-
- m = MAX( box0.size.width, box0.size.height );
- img_size.width = cvRound(cvTsRandReal(rng)*m*0.5 + m + 1);
- img_size.height = cvRound(cvTsRandReal(rng)*m*0.5 + m + 1);
- img_type = cvTsRandInt(rng) % 2 ? CV_32F : CV_8U;
- img_type = CV_8U;
-
- box0.center.x = (float)(img_size.width*0.5 + (cvTsRandReal(rng)-0.5)*(img_size.width - m));
- box0.center.y = (float)(img_size.height*0.5 + (cvTsRandReal(rng)-0.5)*(img_size.height - m));
-
- criteria = cvTermCriteria( CV_TERMCRIT_EPS + CV_TERMCRIT_ITER, 10, 0.1 );
-
- generate_object();
-
- return 1;
-}
-
-
-void CV_TrackBaseTest::run_func(void)
-{
-}
-
-
-int CV_TrackBaseTest::validate_test_results( int /*test_case_idx*/ )
-{
- return 0;
-}
-
-
-CV_TrackBaseTest track_basetest( "track", "" );
-
-
-
-///////////////////////// CamShift //////////////////////////////
-
-class CV_CamShiftTest : public CV_TrackBaseTest
-{
-public:
- CV_CamShiftTest();
-
-protected:
- void run_func(void);
- int prepare_test_case( int test_case_idx );
- int validate_test_results( int test_case_idx );
- void generate_object();
-
- CvBox2D box;
- CvRect init_rect;
- CvConnectedComp comp;
- int area0;
-};
-
-
-CV_CamShiftTest::CV_CamShiftTest() :
- CV_TrackBaseTest( "track-camshift", "cvCamShift" )
-{
-}
-
-
-int CV_CamShiftTest::prepare_test_case( int test_case_idx )
-{
- CvRNG* rng = ts->get_rng();
- double m;
- int code = CV_TrackBaseTest::prepare_test_case( test_case_idx );
- int i, area;
-
- if( code <= 0 )
- return code;
-
- area0 = cvCountNonZero(img);
-
- for(i = 0; i < 100; i++)
- {
- CvMat temp;
-
- m = MAX(box0.size.width,box0.size.height)*0.8;
- init_rect.x = cvFloor(box0.center.x - m*(0.45 + cvTsRandReal(rng)*0.2));
- init_rect.y = cvFloor(box0.center.y - m*(0.45 + cvTsRandReal(rng)*0.2));
- init_rect.width = cvCeil(box0.center.x + m*(0.45 + cvTsRandReal(rng)*0.2) - init_rect.x);
- init_rect.height = cvCeil(box0.center.y + m*(0.45 + cvTsRandReal(rng)*0.2) - init_rect.y);
-
- if( init_rect.x < 0 || init_rect.y < 0 ||
- init_rect.x + init_rect.width >= img_size.width ||
- init_rect.y + init_rect.height >= img_size.height )
- continue;
-
- cvGetSubRect( img, &temp, init_rect );
- area = cvCountNonZero( &temp );
-
- if( area >= 0.1*area0 )
- break;
- }
-
- return i < 100 ? code : 0;
-}
-
-
-void CV_CamShiftTest::run_func(void)
-{
- cvCamShift( img, init_rect, criteria, &comp, &box );
-}
-
-
-int CV_CamShiftTest::validate_test_results( int /*test_case_idx*/ )
-{
- int code = CvTS::OK;
-
- double m = MAX(box0.size.width, box0.size.height), delta;
- double diff_angle;
-
- if( cvIsNaN(box.size.width) || cvIsInf(box.size.width) || box.size.width <= 0 ||
- cvIsNaN(box.size.height) || cvIsInf(box.size.height) || box.size.height <= 0 ||
- cvIsNaN(box.center.x) || cvIsInf(box.center.x) ||
- cvIsNaN(box.center.y) || cvIsInf(box.center.y) ||
- cvIsNaN(box.angle) || cvIsInf(box.angle) || box.angle < -180 || box.angle > 180 ||
- cvIsNaN(comp.area) || cvIsInf(comp.area) || comp.area <= 0 )
- {
- ts->printf( CvTS::LOG, "Invalid CvBox2D or CvConnectedComp was returned by cvCamShift\n" );
- code = CvTS::FAIL_INVALID_OUTPUT;
- goto _exit_;
- }
-
- box.angle = (float)(180 - box.angle);
-
- if( fabs(box.size.width - box0.size.width) > box0.size.width*0.2 ||
- fabs(box.size.height - box0.size.height) > box0.size.height*0.3 )
- {
- ts->printf( CvTS::LOG, "Incorrect CvBox2D size (=%.1f x %.1f, should be %.1f x %.1f)\n",
- box.size.width, box.size.height, box0.size.width, box0.size.height );
- code = CvTS::FAIL_BAD_ACCURACY;
- goto _exit_;
- }
-
- if( fabs(box.center.x - box0.center.x) > m*0.1 ||
- fabs(box.center.y - box0.center.y) > m*0.1 )
- {
- ts->printf( CvTS::LOG, "Incorrect CvBox2D position (=(%.1f, %.1f), should be (%.1f, %.1f))\n",
- box.center.x, box.center.y, box0.center.x, box0.center.y );
- code = CvTS::FAIL_BAD_ACCURACY;
- goto _exit_;
- }
-
- if( box.angle < 0 )
- box.angle += 180;
-
- diff_angle = fabs(box0.angle - box.angle);
- diff_angle = MIN( diff_angle, fabs(box0.angle - box.angle + 180));
-
- if( fabs(diff_angle) > 30 && box0.size.height > box0.size.width*1.2 )
- {
- ts->printf( CvTS::LOG, "Incorrect CvBox2D angle (=%1.f, should be %1.f)\n",
- box.angle, box0.angle );
- code = CvTS::FAIL_BAD_ACCURACY;
- goto _exit_;
- }
-
- delta = m*0.7;
-
- if( comp.rect.x < box0.center.x - delta ||
- comp.rect.y < box0.center.y - delta ||
- comp.rect.x + comp.rect.width > box0.center.x + delta ||
- comp.rect.y + comp.rect.height > box0.center.y + delta )
- {
- ts->printf( CvTS::LOG,
- "Incorrect CvConnectedComp ((%d,%d,%d,%d) is not within (%.1f,%.1f,%.1f,%.1f))\n",
- comp.rect.x, comp.rect.y, comp.rect.x + comp.rect.width, comp.rect.y + comp.rect.height,
- box0.center.x - delta, box0.center.y - delta, box0.center.x + delta, box0.center.y + delta );
- code = CvTS::FAIL_BAD_ACCURACY;
- goto _exit_;
- }
-
- if( fabs(comp.area - area0) > area0*0.15 )
- {
- ts->printf( CvTS::LOG,
- "Incorrect CvConnectedComp area (=%.1f, should be %d)\n", comp.area, area0 );
- code = CvTS::FAIL_BAD_ACCURACY;
- goto _exit_;
- }
-
-_exit_:
-
- if( code < 0 )
- {
-#if defined _DEBUG && defined WIN32
- IplImage* dst = cvCreateImage( img_size, 8, 3 );
- cvNamedWindow( "test", 1 );
- cvCmpS( img, 0, img, CV_CMP_GT );
- cvCvtColor( img, dst, CV_GRAY2BGR );
- cvRectangle( dst, cvPoint(init_rect.x, init_rect.y),
- cvPoint(init_rect.x + init_rect.width, init_rect.y + init_rect.height),
- CV_RGB(255,0,0), 3, 8, 0 );
- cvEllipseBox( dst, box, CV_RGB(0,255,0), 3, 8, 0 );
- cvShowImage( "test", dst );
- cvReleaseImage( &dst );
- cvWaitKey();
-#endif
- ts->set_failed_test_info( code );
- }
- return code;
-}
-
-
-CV_CamShiftTest camshift_test;
-
-
-///////////////////////// MeanShift //////////////////////////////
-
-class CV_MeanShiftTest : public CV_TrackBaseTest
-{
-public:
- CV_MeanShiftTest();
-
-protected:
- void run_func(void);
- int prepare_test_case( int test_case_idx );
- int validate_test_results( int test_case_idx );
- void generate_object();
-
- CvRect init_rect;
- CvConnectedComp comp;
- int area0, area;
-};
-
-
-CV_MeanShiftTest::CV_MeanShiftTest() :
- CV_TrackBaseTest( "track-meanshift", "cvMeanShift" )
-{
-}
-
-
-int CV_MeanShiftTest::prepare_test_case( int test_case_idx )
-{
- CvRNG* rng = ts->get_rng();
- double m;
- int code = CV_TrackBaseTest::prepare_test_case( test_case_idx );
- int i;
-
- if( code <= 0 )
- return code;
-
- area0 = cvCountNonZero(img);
-
- for(i = 0; i < 100; i++)
- {
- CvMat temp;
-
- m = (box0.size.width + box0.size.height)*0.5;
- init_rect.x = cvFloor(box0.center.x - m*(0.4 + cvTsRandReal(rng)*0.2));
- init_rect.y = cvFloor(box0.center.y - m*(0.4 + cvTsRandReal(rng)*0.2));
- init_rect.width = cvCeil(box0.center.x + m*(0.4 + cvTsRandReal(rng)*0.2) - init_rect.x);
- init_rect.height = cvCeil(box0.center.y + m*(0.4 + cvTsRandReal(rng)*0.2) - init_rect.y);
-
- if( init_rect.x < 0 || init_rect.y < 0 ||
- init_rect.x + init_rect.width >= img_size.width ||
- init_rect.y + init_rect.height >= img_size.height )
- continue;
-
- cvGetSubRect( img, &temp, init_rect );
- area = cvCountNonZero( &temp );
-
- if( area >= 0.5*area0 )
- break;
- }
-
- return i < 100 ? code : 0;
-}
-
-
-void CV_MeanShiftTest::run_func(void)
-{
- cvMeanShift( img, init_rect, criteria, &comp );
-}
-
-
-int CV_MeanShiftTest::validate_test_results( int /*test_case_idx*/ )
-{
- int code = CvTS::OK;
- CvPoint2D32f c;
- double m = MAX(box0.size.width, box0.size.height), delta;
-
- if( cvIsNaN(comp.area) || cvIsInf(comp.area) || comp.area <= 0 )
- {
- ts->printf( CvTS::LOG, "Invalid CvConnectedComp was returned by cvMeanShift\n" );
- code = CvTS::FAIL_INVALID_OUTPUT;
- goto _exit_;
- }
-
- c.x = (float)(comp.rect.x + comp.rect.width*0.5);
- c.y = (float)(comp.rect.y + comp.rect.height*0.5);
-
- if( fabs(c.x - box0.center.x) > m*0.1 ||
- fabs(c.y - box0.center.y) > m*0.1 )
- {
- ts->printf( CvTS::LOG, "Incorrect CvBox2D position (=(%.1f, %.1f), should be (%.1f, %.1f))\n",
- c.x, c.y, box0.center.x, box0.center.y );
- code = CvTS::FAIL_BAD_ACCURACY;
- goto _exit_;
- }
-
- delta = m*0.7;
-
- if( comp.rect.x < box0.center.x - delta ||
- comp.rect.y < box0.center.y - delta ||
- comp.rect.x + comp.rect.width > box0.center.x + delta ||
- comp.rect.y + comp.rect.height > box0.center.y + delta )
- {
- ts->printf( CvTS::LOG,
- "Incorrect CvConnectedComp ((%d,%d,%d,%d) is not within (%.1f,%.1f,%.1f,%.1f))\n",
- comp.rect.x, comp.rect.y, comp.rect.x + comp.rect.width, comp.rect.y + comp.rect.height,
- box0.center.x - delta, box0.center.y - delta, box0.center.x + delta, box0.center.y + delta );
- code = CvTS::FAIL_BAD_ACCURACY;
- goto _exit_;
- }
-
- if( fabs((double)(comp.area - area0)) > fabs((double)(area - area0)) + area0*0.05 )
- {
- ts->printf( CvTS::LOG,
- "Incorrect CvConnectedComp area (=%.1f, should be %d)\n", comp.area, area0 );
- code = CvTS::FAIL_BAD_ACCURACY;
- goto _exit_;
- }
-
-_exit_:
-
- if( code < 0 )
- {
-#if defined _DEBUG && defined WIN32
- IplImage* dst = cvCreateImage( img_size, 8, 3 );
- cvNamedWindow( "test", 1 );
- cvCmpS( img, 0, img, CV_CMP_GT );
- cvCvtColor( img, dst, CV_GRAY2BGR );
- cvRectangle( dst, cvPoint(init_rect.x, init_rect.y),
- cvPoint(init_rect.x + init_rect.width, init_rect.y + init_rect.height),
- CV_RGB(255,0,0), 3, 8, 0 );
- cvRectangle( dst, cvPoint(comp.rect.x, comp.rect.y),
- cvPoint(comp.rect.x + comp.rect.width, comp.rect.y + comp.rect.height),
- CV_RGB(0,255,0), 3, 8, 0 );
- cvShowImage( "test", dst );
- cvReleaseImage( &dst );
- cvWaitKey();
-#endif
- ts->set_failed_test_info( code );
- }
- return code;
-}
-
-
-CV_MeanShiftTest meanshift_test;
-
-/* End of file. */
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-class CV_CannyTest : public CvArrTest
-{
-public:
- CV_CannyTest();
-
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- double get_success_error_level( int test_case_idx, int i, int j );
- int prepare_test_case( int test_case_idx );
- void run_func();
- void prepare_to_validation( int );
- int validate_test_results( int /*test_case_idx*/ );
-
- int aperture_size, use_true_gradient;
- double threshold1, threshold2;
- bool test_cpp;
-};
-
-
-CV_CannyTest::CV_CannyTest()
- : CvArrTest( "canny", "cvCanny, cvSobel", "" )
-{
- test_array[INPUT].push(NULL);
- test_array[OUTPUT].push(NULL);
- test_array[REF_OUTPUT].push(NULL);
- element_wise_relative_error = true;
- aperture_size = use_true_gradient = 0;
- threshold1 = threshold2 = 0;
-
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;
- default_timing_param_names = 0;
- test_cpp = false;
-}
-
-
-void CV_CannyTest::get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- double thresh_range;
-
- CvArrTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- types[INPUT][0] = types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_8U;
-
- aperture_size = cvTsRandInt(rng) % 2 ? 5 : 3;
- thresh_range = aperture_size == 3 ? 300 : 1000;
-
- threshold1 = cvTsRandReal(rng)*thresh_range;
- threshold2 = cvTsRandReal(rng)*thresh_range*0.3;
-
- if( cvTsRandInt(rng) % 2 )
- CV_SWAP( threshold1, threshold2, thresh_range );
-
- use_true_gradient = cvTsRandInt(rng) % 2;
- test_cpp = (cvTsRandInt(rng) & 256) == 0;
-}
-
-
-int CV_CannyTest::prepare_test_case( int test_case_idx )
-{
- int code = CvArrTest::prepare_test_case( test_case_idx );
- if( code > 0 )
- {
- CvMat* src = &test_mat[INPUT][0];
- cvSmooth( src, src, CV_GAUSSIAN, 11, 11, 5, 5 );
- }
-
- return code;
-}
-
-
-double CV_CannyTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- return 0;
-}
-
-
-void CV_CannyTest::run_func()
-{
- if(!test_cpp)
- cvCanny( test_array[INPUT][0], test_array[OUTPUT][0], threshold1, threshold2,
- aperture_size + (use_true_gradient ? CV_CANNY_L2_GRADIENT : 0));
- else
- {
- cv::Mat _out = cv::cvarrToMat(test_array[OUTPUT][0]);
- cv::Canny(cv::cvarrToMat(test_array[INPUT][0]), _out, threshold1, threshold2,
- aperture_size + (use_true_gradient ? CV_CANNY_L2_GRADIENT : 0));
- }
-}
-
-
-static void
-icvTsCannyFollow( int x, int y, float lowThreshold, const CvMat* mag, CvMat* dst )
-{
- static const int ofs[][2] = {{1,0},{1,-1},{0,-1},{-1,-1},{-1,0},{-1,1},{0,1},{1,1}};
- int i;
-
- dst->data.ptr[dst->step*y + x] = (uchar)255;
-
- for( i = 0; i < 8; i++ )
- {
- int x1 = x + ofs[i][0];
- int y1 = y + ofs[i][1];
- if( (unsigned)x1 < (unsigned)mag->cols &&
- (unsigned)y1 < (unsigned)mag->rows &&
- mag->data.fl[y1*mag->cols+x1] > lowThreshold &&
- !dst->data.ptr[dst->step*y1+x1] )
- icvTsCannyFollow( x1, y1, lowThreshold, mag, dst );
- }
-}
-
-
-static void
-icvTsCanny( const CvMat* src, CvMat* dst,
- double threshold1, double threshold2,
- int aperture_size, int use_true_gradient )
-{
- int m = aperture_size;
- CvMat* _src = cvCreateMat( src->rows + m - 1, src->cols + m - 1, CV_16S );
- CvMat* dx = cvCreateMat( src->rows, src->cols, CV_16S );
- CvMat* dy = cvCreateMat( src->rows, src->cols, CV_16S );
- CvMat* kernel = cvCreateMat( m, m, CV_32F );
- CvPoint anchor = {m/2, m/2};
- CvMat* mag = cvCreateMat( src->rows, src->cols, CV_32F );
- const double tan_pi_8 = tan(CV_PI/8.);
- const double tan_3pi_8 = tan(CV_PI*3/8);
- float lowThreshold = (float)MIN(threshold1, threshold2);
- float highThreshold = (float)MAX(threshold1, threshold2);
-
- int x, y, width = src->cols, height = src->rows;
-
- cvTsConvert( src, dx );
- cvTsPrepareToFilter( dx, _src, anchor, CV_TS_BORDER_REPLICATE );
- cvTsCalcSobelKernel2D( 1, 0, m, 0, kernel );
- cvTsConvolve2D( _src, dx, kernel, anchor );
- cvTsCalcSobelKernel2D( 0, 1, m, 0, kernel );
- cvTsConvolve2D( _src, dy, kernel, anchor );
-
- /* estimate magnitude and angle */
- for( y = 0; y < height; y++ )
- {
- const short* _dx = (short*)(dx->data.ptr + dx->step*y);
- const short* _dy = (short*)(dy->data.ptr + dy->step*y);
- float* _mag = (float*)(mag->data.ptr + mag->step*y);
-
- for( x = 0; x < width; x++ )
- {
- float mval = use_true_gradient ?
- (float)sqrt((double)(_dx[x]*_dx[x] + _dy[x]*_dy[x])) :
- (float)(abs(_dx[x]) + abs(_dy[x]));
- _mag[x] = mval;
- }
- }
-
- /* nonmaxima suppression */
- for( y = 0; y < height; y++ )
- {
- const short* _dx = (short*)(dx->data.ptr + dx->step*y);
- const short* _dy = (short*)(dy->data.ptr + dy->step*y);
- float* _mag = (float*)(mag->data.ptr + mag->step*y);
-
- for( x = 0; x < width; x++ )
- {
- int y1 = 0, y2 = 0, x1 = 0, x2 = 0;
- double tg;
- float a = _mag[x], b = 0, c = 0;
-
- if( a <= lowThreshold )
- continue;
-
- if( _dx[x] )
- tg = (double)_dy[x]/_dx[x];
- else
- tg = DBL_MAX*CV_SIGN(_dy[x]);
-
- if( fabs(tg) < tan_pi_8 )
- {
- y1 = y2 = y; x1 = x + 1; x2 = x - 1;
- }
- else if( tan_pi_8 <= tg && tg <= tan_3pi_8 )
- {
- y1 = y + 1; y2 = y - 1; x1 = x + 1; x2 = x - 1;
- }
- else if( -tan_3pi_8 <= tg && tg <= -tan_pi_8 )
- {
- y1 = y - 1; y2 = y + 1; x1 = x + 1; x2 = x - 1;
- }
- else
- {
- assert( fabs(tg) > tan_3pi_8 );
- x1 = x2 = x; y1 = y + 1; y2 = y - 1;
- }
-
- if( (unsigned)y1 < (unsigned)height && (unsigned)x1 < (unsigned)width )
- b = (float)fabs((double)mag->data.fl[y1*width+x1]);
-
- if( (unsigned)y2 < (unsigned)height && (unsigned)x2 < (unsigned)width )
- c = (float)fabs((double)mag->data.fl[y2*width+x2]);
-
- if( (a > b || (a == b && ((x1 == x+1 && y1 == y) || (x1 == x && y1 == y+1)))) && a > c )
- ;
- else
- _mag[x] = -a;
- }
- }
-
- cvTsZero( dst );
-
- /* hysteresis threshold */
- for( y = 0; y < height; y++ )
- {
- const float* _mag = (float*)(mag->data.ptr + mag->step*y);
- uchar* _dst = dst->data.ptr + dst->step*y;
-
- for( x = 0; x < width; x++ )
- if( _mag[x] > highThreshold && !_dst[x] )
- icvTsCannyFollow( x, y, lowThreshold, mag, dst );
- }
-
- cvReleaseMat( &_src );
- cvReleaseMat( &dx );
- cvReleaseMat( &dy );
- cvReleaseMat( &kernel );
- cvReleaseMat( &mag );
-}
-
-
-void CV_CannyTest::prepare_to_validation( int )
-{
- icvTsCanny( &test_mat[INPUT][0], &test_mat[REF_OUTPUT][0],
- threshold1, threshold2, aperture_size, use_true_gradient );
-
- /*cv::Mat output(&test_mat[OUTPUT][0]);
- cv::Mat ref_output(&test_mat[REF_OUTPUT][0]);
-
- cv::absdiff(output, ref_output, output);
- cv::namedWindow("ref test", 0);
- cv::imshow("ref test", ref_output);
- cv::namedWindow("test", 0);
- cv::imshow("test", output);
- cv::waitKey();*/
-}
-
-
-int CV_CannyTest::validate_test_results( int test_case_idx )
-{
- int code = CvTS::OK, nz0;
- prepare_to_validation(test_case_idx);
-
- double err = cvNorm(&test_mat[OUTPUT][0], &test_mat[REF_OUTPUT][0], CV_L1);
- if( err == 0 )
- goto _exit_;
-
- if( err != cvRound(err) || cvRound(err)%255 != 0 )
- {
- ts->printf( CvTS::LOG, "Some of the pixels, produced by Canny, are not 0's or 255's; the difference is %g\n", err );
- code = CvTS::FAIL_INVALID_OUTPUT;
- goto _exit_;
- }
-
- nz0 = cvCountNonZero(&test_mat[REF_OUTPUT][0]);
- err = (err/255/MAX(nz0,100))*100;
- if( err > 1 )
- {
- ts->printf( CvTS::LOG, "Too high percentage of non-matching edge pixels = %g%%\n", err);
- code = CvTS::FAIL_BAD_ACCURACY;
- goto _exit_;
- }
-
-_exit_:
- if( code < 0 )
- ts->set_failed_test_info( code );
- return code;
-}
-
-
-CV_CannyTest canny_test;
-
-/* End of file. */
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-using namespace cv;
-using namespace std;
-
-//#define GET_STAT
-
-#define DIST_E "distE"
-#define S_E "sE"
-#define NO_PAIR_E "noPairE"
-//#define TOTAL_NO_PAIR_E "totalNoPairE"
-
-#define DETECTOR_NAMES "detector_names"
-#define DETECTORS "detectors"
-#define IMAGE_FILENAMES "image_filenames"
-#define VALIDATION "validation"
-#define FILENAME "fn"
-
-#define C_SCALE_CASCADE "scale_cascade"
-
-class CV_DetectorTest : public CvTest
-{
-public:
- CV_DetectorTest( const char* test_name );
- virtual int init( CvTS* system );
-protected:
- virtual int prepareData( FileStorage& fs );
- virtual void run( int startFrom );
- virtual string& getValidationFilename();
-
- virtual void readDetector( const FileNode& fn ) = 0;
- virtual void writeDetector( FileStorage& fs, int di ) = 0;
- int runTestCase( int detectorIdx, vector<vector<Rect> >& objects );
- virtual int detectMultiScale( int di, const Mat& img, vector<Rect>& objects ) = 0;
- int validate( int detectorIdx, vector<vector<Rect> >& objects );
-
- struct
- {
- float dist;
- float s;
- float noPair;
- //float totalNoPair;
- } eps;
- vector<string> detectorNames;
- vector<string> detectorFilenames;
- vector<string> imageFilenames;
- vector<Mat> images;
- string validationFilename;
- FileStorage validationFS;
-};
-
-CV_DetectorTest::CV_DetectorTest( const char* test_name ) : CvTest( test_name, "detectMultiScale" )
-{
-}
-
-int CV_DetectorTest::init(CvTS *system)
-{
- clear();
- ts = system;
- string dataPath = ts->get_data_path();
- validationFS.open( dataPath + getValidationFilename(), FileStorage::READ );
- return prepareData( validationFS );
-}
-
-string& CV_DetectorTest::getValidationFilename()
-{
- return validationFilename;
-}
-
-int CV_DetectorTest::prepareData( FileStorage& _fs )
-{
- if( !_fs.isOpened() )
- test_case_count = -1;
- else
- {
- FileNode fn = _fs.getFirstTopLevelNode();
-
- fn[DIST_E] >> eps.dist;
- fn[S_E] >> eps.s;
- fn[NO_PAIR_E] >> eps.noPair;
-// fn[TOTAL_NO_PAIR_E] >> eps.totalNoPair;
-
- // read detectors
- if( fn[DETECTOR_NAMES].node->data.seq != 0 )
- {
- FileNodeIterator it = fn[DETECTOR_NAMES].begin();
- for( ; it != fn[DETECTOR_NAMES].end(); )
- {
- string name;
- it >> name;
- detectorNames.push_back(name);
- readDetector(fn[DETECTORS][name]);
- }
- }
- test_case_count = (int)detectorNames.size();
-
- // read images filenames and images
- string dataPath = ts->get_data_path();
- if( fn[IMAGE_FILENAMES].node->data.seq != 0 )
- {
- for( FileNodeIterator it = fn[IMAGE_FILENAMES].begin(); it != fn[IMAGE_FILENAMES].end(); )
- {
- string filename;
- it >> filename;
- imageFilenames.push_back(filename);
- Mat img = imread( dataPath+filename, 1 );
- images.push_back( img );
- }
- }
- }
- return CvTS::OK;
-}
-
-void CV_DetectorTest::run( int start_from )
-{
- int code = CvTS::OK;
- start_from = 0;
-
-#ifdef GET_STAT
- validationFS.release();
- string filename = ts->get_data_path();
- filename += getValidationFilename();
- validationFS.open( filename, FileStorage::WRITE );
- validationFS << FileStorage::getDefaultObjectName(validationFilename) << "{";
-
- validationFS << DIST_E << eps.dist;
- validationFS << S_E << eps.s;
- validationFS << NO_PAIR_E << eps.noPair;
-// validationFS << TOTAL_NO_PAIR_E << eps.totalNoPair;
-
- // write detector names
- validationFS << DETECTOR_NAMES << "[";
- vector<string>::const_iterator nit = detectorNames.begin();
- for( ; nit != detectorNames.end(); ++nit )
- {
- validationFS << *nit;
- }
- validationFS << "]"; // DETECTOR_NAMES
-
- // write detectors
- validationFS << DETECTORS << "{";
- assert( detectorNames.size() == detectorFilenames.size() );
- nit = detectorNames.begin();
- for( int di = 0; di < detectorNames.size(), nit != detectorNames.end(); ++nit, di++ )
- {
- validationFS << *nit << "{";
- writeDetector( validationFS, di );
- validationFS << "}";
- }
- validationFS << "}";
-
- // write image filenames
- validationFS << IMAGE_FILENAMES << "[";
- vector<string>::const_iterator it = imageFilenames.begin();
- for( int ii = 0; it != imageFilenames.end(); ++it, ii++ )
- {
- char buf[10];
- sprintf( buf, "%s%d", "img_", ii );
- cvWriteComment( validationFS.fs, buf, 0 );
- validationFS << *it;
- }
- validationFS << "]"; // IMAGE_FILENAMES
-
- validationFS << VALIDATION << "{";
-#endif
-
- int progress = 0;
- for( int di = 0; di < test_case_count; di++ )
- {
- progress = update_progress( progress, di, test_case_count, 0 );
-#ifdef GET_STAT
- validationFS << detectorNames[di] << "{";
-#endif
- vector<vector<Rect> > objects;
- int temp_code = runTestCase( di, objects );
-#ifndef GET_STAT
- if (temp_code == CvTS::OK)
- temp_code = validate( di, objects );
-#endif
- if (temp_code != CvTS::OK)
- code = temp_code;
-#ifdef GET_STAT
- validationFS << "}"; // detectorNames[di]
-#endif
- }
-
-#ifdef GET_STAT
- validationFS << "}"; // VALIDATION
- validationFS << "}"; // getDefaultObjectName
-#endif
- if ( test_case_count <= 0 || imageFilenames.size() <= 0 )
- {
- ts->printf( CvTS::LOG, "validation file is not determined or not correct" );
- code = CvTS::FAIL_INVALID_TEST_DATA;
- }
- ts->set_failed_test_info( code );
-}
-
-int CV_DetectorTest::runTestCase( int detectorIdx, vector<vector<Rect> >& objects )
-{
- string dataPath = ts->get_data_path(), detectorFilename;
- if( !detectorFilenames[detectorIdx].empty() )
- detectorFilename = dataPath + detectorFilenames[detectorIdx];
-
- for( int ii = 0; ii < (int)imageFilenames.size(); ++ii )
- {
- vector<Rect> imgObjects;
- Mat image = images[ii];
- if( image.empty() )
- {
- char msg[30];
- sprintf( msg, "%s %d %s", "image ", ii, " can not be read" );
- ts->printf( CvTS::LOG, msg );
- return CvTS::FAIL_INVALID_TEST_DATA;
- }
- int code = detectMultiScale( detectorIdx, image, imgObjects );
- if( code != CvTS::OK )
- return code;
-
- objects.push_back( imgObjects );
-
-#ifdef GET_STAT
- char buf[10];
- sprintf( buf, "%s%d", "img_", ii );
- string imageIdxStr = buf;
- validationFS << imageIdxStr << "[:";
- for( vector<Rect>::const_iterator it = imgObjects.begin();
- it != imgObjects.end(); ++it )
- {
- validationFS << it->x << it->y << it->width << it->height;
- }
- validationFS << "]"; // imageIdxStr
-#endif
- }
- return CvTS::OK;
-}
-
-
-bool isZero( uchar i ) {return i == 0;}
-
-int CV_DetectorTest::validate( int detectorIdx, vector<vector<Rect> >& objects )
-{
- assert( imageFilenames.size() == objects.size() );
- int imageIdx = 0;
- int totalNoPair = 0, totalValRectCount = 0;
-
- for( vector<vector<Rect> >::const_iterator it = objects.begin();
- it != objects.end(); ++it, imageIdx++ ) // for image
- {
- Size imgSize = images[imageIdx].size();
- float dist = min(imgSize.height, imgSize.width) * eps.dist;
- float wDiff = imgSize.width * eps.s;
- float hDiff = imgSize.height * eps.s;
-
- int noPair = 0;
-
- // read validation rectangles
- char buf[10];
- sprintf( buf, "%s%d", "img_", imageIdx );
- string imageIdxStr = buf;
- FileNode node = validationFS.getFirstTopLevelNode()[VALIDATION][detectorNames[detectorIdx]][imageIdxStr];
- vector<Rect> valRects;
- if( node.node->data.seq != 0 )
- {
- for( FileNodeIterator it = node.begin(); it != node.end(); )
- {
- Rect r;
- it >> r.x >> r.y >> r.width >> r.height;
- valRects.push_back(r);
- }
- }
- totalValRectCount += (int)valRects.size();
-
- // compare rectangles
- vector<uchar> map(valRects.size(), 0);
- for( vector<Rect>::const_iterator cr = it->begin();
- cr != it->end(); ++cr )
- {
- // find nearest rectangle
- Point2f cp1 = Point2f( cr->x + (float)cr->width/2.0f, cr->y + (float)cr->height/2.0f );
- int minIdx = -1, vi = 0;
- float minDist = (float)norm( Point(imgSize.width, imgSize.height) );
- for( vector<Rect>::const_iterator vr = valRects.begin();
- vr != valRects.end(); ++vr, vi++ )
- {
- Point2f cp2 = Point2f( vr->x + (float)vr->width/2.0f, vr->y + (float)vr->height/2.0f );
- float curDist = (float)norm(cp1-cp2);
- if( curDist < minDist )
- {
- minIdx = vi;
- minDist = curDist;
- }
- }
- if( minIdx == -1 )
- {
- noPair++;
- }
- else
- {
- Rect vr = valRects[minIdx];
- if( map[minIdx] != 0 || (minDist > dist) || (abs(cr->width - vr.width) > wDiff) ||
- (abs(cr->height - vr.height) > hDiff) )
- noPair++;
- else
- map[minIdx] = 1;
- }
- }
- noPair += (int)count_if( map.begin(), map.end(), isZero );
- totalNoPair += noPair;
- if( noPair > cvRound(valRects.size()*eps.noPair)+1 )
- break;
- }
- if( imageIdx < (int)imageFilenames.size() )
- {
- char msg[500];
- sprintf( msg, "detector %s has overrated count of rectangles without pair on %s-image\n",
- detectorNames[detectorIdx].c_str(), imageFilenames[imageIdx].c_str() );
- ts->printf( CvTS::LOG, msg );
- return CvTS::FAIL_BAD_ACCURACY;
- }
- if ( totalNoPair > cvRound(totalValRectCount*eps./*total*/noPair)+1 )
- {
- ts->printf( CvTS::LOG, "overrated count of rectangles without pair on all images set" );
- return CvTS::FAIL_BAD_ACCURACY;
- }
-
- return CvTS::OK;
-}
-
-//----------------------------------------------- CascadeDetectorTest -----------------------------------
-class CV_CascadeDetectorTest : public CV_DetectorTest
-{
-public:
- CV_CascadeDetectorTest( const char* test_name );
-protected:
- virtual void readDetector( const FileNode& fn );
- virtual void writeDetector( FileStorage& fs, int di );
- virtual int detectMultiScale( int di, const Mat& img, vector<Rect>& objects );
- vector<int> flags;
-};
-
-CV_CascadeDetectorTest::CV_CascadeDetectorTest(const char *test_name)
- : CV_DetectorTest( test_name )
-{
- validationFilename = "cascadeandhog/cascade.xml";
-}
-
-void CV_CascadeDetectorTest::readDetector( const FileNode& fn )
-{
- string filename;
- int flag;
- fn[FILENAME] >> filename;
- detectorFilenames.push_back(filename);
- fn[C_SCALE_CASCADE] >> flag;
- if( flag )
- flags.push_back( 0 );
- else
- flags.push_back( CV_HAAR_SCALE_IMAGE );
-}
-
-void CV_CascadeDetectorTest::writeDetector( FileStorage& fs, int di )
-{
- int sc = flags[di] & CV_HAAR_SCALE_IMAGE ? 0 : 1;
- fs << FILENAME << detectorFilenames[di];
- fs << C_SCALE_CASCADE << sc;
-}
-
-int CV_CascadeDetectorTest::detectMultiScale( int di, const Mat& img,
- vector<Rect>& objects)
-{
- string dataPath = ts->get_data_path(), filename;
- filename = dataPath + detectorFilenames[di];
- CascadeClassifier cascade( filename );
- if( cascade.empty() )
- {
- ts->printf( CvTS::LOG, "cascade %s can not be opened");
- return CvTS::FAIL_INVALID_TEST_DATA;
- }
- Mat grayImg;
- cvtColor( img, grayImg, CV_BGR2GRAY );
- equalizeHist( grayImg, grayImg );
- cascade.detectMultiScale( grayImg, objects, 1.1, 3, flags[di] );
- return CvTS::OK;
-}
-
-//----------------------------------------------- HOGDetectorTest -----------------------------------
-class CV_HOGDetectorTest : public CV_DetectorTest
-{
-public:
- CV_HOGDetectorTest( const char* test_name );
-protected:
- virtual void readDetector( const FileNode& fn );
- virtual void writeDetector( FileStorage& fs, int di );
- virtual int detectMultiScale( int di, const Mat& img, vector<Rect>& objects );
-};
-
-CV_HOGDetectorTest::CV_HOGDetectorTest(const char *test_name)
-: CV_DetectorTest( test_name )
-{
- validationFilename = "cascadeandhog/hog.xml";
-}
-
-void CV_HOGDetectorTest::readDetector( const FileNode& fn )
-{
- string filename;
- if( fn[FILENAME].node->data.seq != 0 )
- fn[FILENAME] >> filename;
- detectorFilenames.push_back( filename);
-}
-
-void CV_HOGDetectorTest::writeDetector( FileStorage& fs, int di )
-{
- fs << FILENAME << detectorFilenames[di];
-}
-
-int CV_HOGDetectorTest::detectMultiScale( int di, const Mat& img,
- vector<Rect>& objects)
-{
- HOGDescriptor hog;
- if( detectorFilenames[di].empty() )
- hog.setSVMDetector(HOGDescriptor::getDefaultPeopleDetector());
- else
- assert(0);
- hog.detectMultiScale(img, objects);
- return CvTS::OK;
-}
-
-CV_CascadeDetectorTest cascadeTest("cascade-detector");
-CV_HOGDetectorTest hogTest("hog-detector");
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-#include "cvchessboardgenerator.h"
-
-#include <limits>
-#include <numeric>
-
-using namespace std;
-using namespace cv;
-
-#define _L2_ERR
-
-void show_points( const Mat& gray, const Mat& u, const vector<Point2f>& v, Size pattern_size, bool was_found )
-{
- Mat rgb( gray.size(), CV_8U);
- merge(vector<Mat>(3, gray), rgb);
-
- for(size_t i = 0; i < v.size(); i++ )
- circle( rgb, v[i], 3, CV_RGB(255, 0, 0), CV_FILLED);
-
- if( !u.empty() )
- {
- const Point2f* u_data = u.ptr<Point2f>();
- size_t count = u.cols * u.rows;
- for(size_t i = 0; i < count; i++ )
- circle( rgb, u_data[i], 3, CV_RGB(0, 255, 0), CV_FILLED);
- }
- if (!v.empty())
- {
- Mat corners((int)v.size(), 1, CV_32FC2, (void*)&v[0]);
- drawChessboardCorners( rgb, pattern_size, corners, was_found );
- }
- //namedWindow( "test", 0 ); imshow( "test", rgb ); waitKey(0);
-}
-
-
-enum Pattern { CHESSBOARD, CIRCLES_GRID, ASYMMETRIC_CIRCLES_GRID };
-
-class CV_ChessboardDetectorTest : public CvTest
-{
-public:
- CV_ChessboardDetectorTest( Pattern pattern, const char* testName, const char* funcName );
-protected:
- void run(int);
- void run_batch(const string& filename);
- bool checkByGenerator();
-
- Pattern pattern;
-};
-
-CV_ChessboardDetectorTest::CV_ChessboardDetectorTest( Pattern _pattern, const char* testName, const char* funcName ):
- CvTest( testName, funcName )
-{
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;
- pattern = _pattern;
-}
-
-double calcError(const vector<Point2f>& v, const Mat& u)
-{
- int count_exp = u.cols * u.rows;
- const Point2f* u_data = u.ptr<Point2f>();
-
- double err = numeric_limits<double>::max();
- for( int k = 0; k < 2; ++k )
- {
- double err1 = 0;
- for( int j = 0; j < count_exp; ++j )
- {
- int j1 = k == 0 ? j : count_exp - j - 1;
- double dx = fabs( v[j].x - u_data[j1].x );
- double dy = fabs( v[j].y - u_data[j1].y );
-
-#if defined(_L2_ERR)
- err1 += dx*dx + dy*dy;
-#else
- dx = MAX( dx, dy );
- if( dx > err1 )
- err1 = dx;
-#endif //_L2_ERR
- //printf("dx = %f\n", dx);
- }
- //printf("\n");
- err = min(err, err1);
- }
-
-#if defined(_L2_ERR)
- err = sqrt(err/count_exp);
-#endif //_L2_ERR
-
- return err;
-}
-
-const double rough_success_error_level = 2.5;
-const double precise_success_error_level = 2;
-
-
-/* ///////////////////// chess_corner_test ///////////////////////// */
-void CV_ChessboardDetectorTest::run( int /*start_from */)
-{
- /*if (!checkByGenerator())
- return;*/
- switch( pattern )
- {
- case CHESSBOARD:
- checkByGenerator();
- run_batch("chessboard_list.dat");
- run_batch("chessboard_list_subpixel.dat");
- break;
- case CIRCLES_GRID:
- run_batch("circles_list.dat");
- break;
- case ASYMMETRIC_CIRCLES_GRID:
- run_batch("acircles_list.dat");
- break;
- }
-}
-
-void CV_ChessboardDetectorTest::run_batch( const string& filename )
-{
- CvTS& ts = *this->ts;
- ts.set_failed_test_info( CvTS::OK );
-
- ts.printf(CvTS::LOG, "\nRunning batch %s\n", filename.c_str());
-//#define WRITE_POINTS 1
-#ifndef WRITE_POINTS
- double max_rough_error = 0, max_precise_error = 0;
-#endif
- string folder;
- switch( pattern )
- {
- case CHESSBOARD:
- folder = string(ts.get_data_path()) + "cameracalibration/";
- break;
- case CIRCLES_GRID:
- folder = string(ts.get_data_path()) + "cameracalibration/circles/";
- break;
- case ASYMMETRIC_CIRCLES_GRID:
- folder = string(ts.get_data_path()) + "cameracalibration/asymmetric_circles/";
- break;
- }
-
- FileStorage fs( folder + filename, FileStorage::READ );
- FileNode board_list = fs["boards"];
-
- if( !fs.isOpened() || board_list.empty() || !board_list.isSeq() || board_list.size() % 2 != 0 )
- {
- ts.printf( CvTS::LOG, "%s can not be readed or is not valid\n", (folder + filename).c_str() );
- ts.printf( CvTS::LOG, "fs.isOpened=%d, board_list.empty=%d, board_list.isSeq=%d,board_list.size()%2=%d\n",
- fs.isOpened(), (int)board_list.empty(), board_list.isSeq(), board_list.size()%2);
- ts.set_failed_test_info( CvTS::FAIL_MISSING_TEST_DATA );
- return;
- }
-
- int progress = 0;
- int max_idx = board_list.node->data.seq->total/2;
- double sum_error = 0.0;
- int count = 0;
-
- for(int idx = 0; idx < max_idx; ++idx )
- {
- ts.update_context( this, idx, true );
-
- /* read the image */
- string img_file = board_list[idx * 2];
- Mat gray = imread( folder + img_file, 0);
-
- if( gray.empty() )
- {
- ts.printf( CvTS::LOG, "one of chessboard images can't be read: %s\n", img_file.c_str() );
- ts.set_failed_test_info( CvTS::FAIL_MISSING_TEST_DATA );
- continue;
- }
-
- string filename = folder + (string)board_list[idx * 2 + 1];
- Mat expected;
- {
- CvMat *u = (CvMat*)cvLoad( filename.c_str() );
- if(!u )
- {
- ts.printf( CvTS::LOG, "one of chessboard corner files can't be read: %s\n", filename.c_str() );
- ts.set_failed_test_info( CvTS::FAIL_MISSING_TEST_DATA );
- continue;
- }
- expected = Mat(u, true);
- cvReleaseMat( &u );
- }
- size_t count_exp = static_cast<size_t>(expected.cols * expected.rows);
- Size pattern_size = expected.size();
-
- vector<Point2f> v;
- bool result = false;
- switch( pattern )
- {
- case CHESSBOARD:
- result = findChessboardCorners(gray, pattern_size, v, CV_CALIB_CB_ADAPTIVE_THRESH | CV_CALIB_CB_NORMALIZE_IMAGE);
- break;
- case CIRCLES_GRID:
- result = findCirclesGrid(gray, pattern_size, v, CALIB_CB_SYMMETRIC_GRID);
- break;
- case ASYMMETRIC_CIRCLES_GRID:
- result = findCirclesGrid(gray, pattern_size, v, CALIB_CB_ASYMMETRIC_GRID);
- break;
- }
- show_points( gray, Mat(), v, pattern_size, result );
- if( !result || v.size() != count_exp )
- {
- ts.printf( CvTS::LOG, "chessboard is not found in %s\n", img_file.c_str() );
- ts.set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- continue;
- }
-
-#ifndef WRITE_POINTS
- double err = calcError(v, expected);
-#if 0
- if( err > rough_success_error_level )
- {
- ts.printf( CvTS::LOG, "bad accuracy of corner guesses\n" );
- ts.set_failed_test_info( CvTS::FAIL_BAD_ACCURACY );
- continue;
- }
-#endif
- max_rough_error = MAX( max_rough_error, err );
-#endif
- if( pattern == CHESSBOARD )
- cornerSubPix( gray, v, Size(5, 5), Size(-1,-1), TermCriteria(TermCriteria::EPS|TermCriteria::MAX_ITER, 30, 0.1));
- //find4QuadCornerSubpix(gray, v, Size(5, 5));
- show_points( gray, expected, v, pattern_size, result );
-
-#ifndef WRITE_POINTS
-// printf("called find4QuadCornerSubpix\n");
- err = calcError(v, expected);
- sum_error += err;
- count++;
-#if 1
- if( err > precise_success_error_level )
- {
- ts.printf( CvTS::LOG, "Image %s: bad accuracy of adjusted corners %f\n", img_file.c_str(), err );
- ts.set_failed_test_info( CvTS::FAIL_BAD_ACCURACY );
- continue;
- }
-#endif
- ts.printf(CvTS::LOG, "Error on %s is %f\n", img_file.c_str(), err);
- max_precise_error = MAX( max_precise_error, err );
-#else
- Mat mat_v(pattern_size, CV_32FC2, (void*)&v[0]);
- CvMat cvmat_v = mat_v;
- cvSave( filename.c_str(), &cvmat_v );
-#endif
- progress = update_progress( progress, idx, max_idx, 0 );
- }
-
- sum_error /= count;
- ts.printf(CvTS::LOG, "Average error is %f\n", sum_error);
-}
-
-double calcErrorMinError(const Size& cornSz, const vector<Point2f>& corners_found, const vector<Point2f>& corners_generated)
-{
- Mat m1(cornSz, CV_32FC2, (Point2f*)&corners_generated[0]);
- Mat m2; flip(m1, m2, 0);
-
- Mat m3; flip(m1, m3, 1); m3 = m3.t(); flip(m3, m3, 1);
-
- Mat m4 = m1.t(); flip(m4, m4, 1);
-
- double min1 = min(calcError(corners_found, m1), calcError(corners_found, m2));
- double min2 = min(calcError(corners_found, m3), calcError(corners_found, m4));
- return min(min1, min2);
-}
-
-bool validateData(const ChessBoardGenerator& cbg, const Size& imgSz,
- const vector<Point2f>& corners_generated)
-{
- Size cornersSize = cbg.cornersSize();
- Mat_<Point2f> mat(cornersSize.height, cornersSize.width, (Point2f*)&corners_generated[0]);
-
- double minNeibDist = std::numeric_limits<double>::max();
- double tmp = 0;
- for(int i = 1; i < mat.rows - 2; ++i)
- for(int j = 1; j < mat.cols - 2; ++j)
- {
- const Point2f& cur = mat(i, j);
-
- tmp = norm( cur - mat(i + 1, j + 1) );
- if (tmp < minNeibDist)
- tmp = minNeibDist;
-
- tmp = norm( cur - mat(i - 1, j + 1 ) );
- if (tmp < minNeibDist)
- tmp = minNeibDist;
-
- tmp = norm( cur - mat(i + 1, j - 1) );
- if (tmp < minNeibDist)
- tmp = minNeibDist;
-
- tmp = norm( cur - mat(i - 1, j - 1) );
- if (tmp < minNeibDist)
- tmp = minNeibDist;
- }
-
- const double threshold = 0.25;
- double cbsize = (max(cornersSize.width, cornersSize.height) + 1) * minNeibDist;
- int imgsize = min(imgSz.height, imgSz.width);
- return imgsize * threshold < cbsize;
-}
-
-bool CV_ChessboardDetectorTest::checkByGenerator()
-{
- bool res = true;
- //theRNG() = 0x58e6e895b9913160;
- //cv::DefaultRngAuto dra;
- //theRNG() = *ts->get_rng();
-
- Mat bg(Size(800, 600), CV_8UC3, Scalar::all(255));
- randu(bg, Scalar::all(0), Scalar::all(255));
- GaussianBlur(bg, bg, Size(7,7), 3.0);
-
- Mat_<float> camMat(3, 3);
- camMat << 300.f, 0.f, bg.cols/2.f, 0, 300.f, bg.rows/2.f, 0.f, 0.f, 1.f;
-
- Mat_<float> distCoeffs(1, 5);
- distCoeffs << 1.2f, 0.2f, 0.f, 0.f, 0.f;
-
- const Size sizes[] = { Size(6, 6), Size(8, 6), Size(11, 12), Size(5, 4) };
- const size_t sizes_num = sizeof(sizes)/sizeof(sizes[0]);
- const int test_num = 16;
- int progress = 0;
- for(int i = 0; i < test_num; ++i)
- {
- progress = update_progress( progress, i, test_num, 0 );
- ChessBoardGenerator cbg(sizes[i % sizes_num]);
-
- vector<Point2f> corners_generated;
-
- Mat cb = cbg(bg, camMat, distCoeffs, corners_generated);
-
- if(!validateData(cbg, cb.size(), corners_generated))
- {
- ts->printf( CvTS::LOG, "Chess board skipped - too small" );
- continue;
- }
-
- /*cb = cb * 0.8 + Scalar::all(30);
- GaussianBlur(cb, cb, Size(3, 3), 0.8); */
- //cv::addWeighted(cb, 0.8, bg, 0.2, 20, cb);
- //cv::namedWindow("CB"); cv::imshow("CB", cb); cv::waitKey();
-
- vector<Point2f> corners_found;
- int flags = i % 8; // need to check branches for all flags
- bool found = findChessboardCorners(cb, cbg.cornersSize(), corners_found, flags);
- if (!found)
- {
- ts->printf( CvTS::LOG, "Chess board corners not found\n" );
- ts->set_failed_test_info( CvTS::FAIL_BAD_ACCURACY );
- res = false;
- continue;
- }
-
- double err = calcErrorMinError(cbg.cornersSize(), corners_found, corners_generated);
- if( err > rough_success_error_level )
- {
- ts->printf( CvTS::LOG, "bad accuracy of corner guesses" );
- ts->set_failed_test_info( CvTS::FAIL_BAD_ACCURACY );
- res = false;
- continue;
- }
- }
-
- /* ***** negative ***** */
- {
- vector<Point2f> corners_found;
- bool found = findChessboardCorners(bg, Size(8, 7), corners_found);
- if (found)
- res = false;
-
- ChessBoardGenerator cbg(Size(8, 7));
-
- vector<Point2f> cg;
- Mat cb = cbg(bg, camMat, distCoeffs, cg);
-
- found = findChessboardCorners(cb, Size(3, 4), corners_found);
- if (found)
- res = false;
-
- Point2f c = std::accumulate(cg.begin(), cg.end(), Point2f(), plus<Point2f>()) * (1.f/cg.size());
-
- Mat_<double> aff(2, 3);
- aff << 1.0, 0.0, -(double)c.x, 0.0, 1.0, 0.0;
- Mat sh;
- warpAffine(cb, sh, aff, cb.size());
-
- found = findChessboardCorners(sh, cbg.cornersSize(), corners_found);
- if (found)
- res = false;
-
- vector< vector<Point> > cnts(1);
- vector<Point>& cnt = cnts[0];
- cnt.push_back(cg[ 0]); cnt.push_back(cg[0+2]);
- cnt.push_back(cg[7+0]); cnt.push_back(cg[7+2]);
- cv::drawContours(cb, cnts, -1, Scalar::all(128), CV_FILLED);
-
- found = findChessboardCorners(cb, cbg.cornersSize(), corners_found);
- if (found)
- res = false;
-
- cv::drawChessboardCorners(cb, cbg.cornersSize(), Mat(corners_found), found);
- }
-
- return res;
-}
-
-CV_ChessboardDetectorTest chessboard_detector_test ( CHESSBOARD, "chessboard-detector", "cvFindChessboardCorners" );
-CV_ChessboardDetectorTest circlesgrid_detector_test ( CIRCLES_GRID, "circlesgrid-detector", "findCirclesGrid" );
-CV_ChessboardDetectorTest asymmetric_circlesgrid_detector_test ( ASYMMETRIC_CIRCLES_GRID, "asymmetric-circlesgrid-detector", "findCirclesGrid" );
-
-/* End of file. */
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-
-/////////////////////////// base test class for color transformations /////////////////////////
-
-static const char* cvtcolor_param_names[] = { "op", "size", "depth", 0 };
-static const int cvtcolor_depths_8_16_32[] = { CV_8U, CV_16U, CV_32F, -1 };
-static const int cvtcolor_depths_8_32[] = { CV_8U, CV_32F, -1 };
-static const int cvtcolor_depths_8[] = { CV_8U, -1 };
-
-static const CvSize cvtcolor_sizes[] = {{30,30}, {320, 240}, {720,480}, {-1,-1}};
-static const CvSize cvtcolor_whole_sizes[] = {{320,240}, {320, 240}, {720,480}, {-1,-1}};
-
-class CV_ColorCvtBaseTestImpl : public CvArrTest
-{
-public:
- CV_ColorCvtBaseTestImpl( const char* test_name, const char* test_funcs,
- bool custom_inv_transform, bool allow_32f, bool allow_16u );
-
-protected:
- int prepare_test_case( int test_case_idx );
- void prepare_to_validation( int /*test_case_idx*/ );
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void get_timing_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types,
- CvSize** whole_sizes, bool *are_images );
- void get_minmax_bounds( int i, int j, int type, CvScalar* low, CvScalar* high );
- int write_default_params(CvFileStorage* fs);
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
-
- // input --- fwd_transform -> ref_output[0]
- virtual void convert_forward( const CvMat* src, CvMat* dst );
- // ref_output[0] --- inv_transform ---> ref_output[1] (or input -- copy --> ref_output[1])
- virtual void convert_backward( const CvMat* src, const CvMat* dst, CvMat* dst2 );
-
- // called from default implementation of convert_forward
- virtual void convert_row_bgr2abc_32f_c3( const float* src_row, float* dst_row, int n );
-
- // called from default implementation of convert_backward
- virtual void convert_row_abc2bgr_32f_c3( const float* src_row, float* dst_row, int n );
-
- const char* fwd_code_str;
- const char* inv_code_str;
-
- void run_func();
- bool allow_16u, allow_32f;
- int blue_idx;
- bool inplace;
- bool custom_inv_transform;
- int fwd_code, inv_code;
- int timing_code;
- bool test_cpp;
- bool hue_channel;
-};
-
-
-CV_ColorCvtBaseTestImpl::CV_ColorCvtBaseTestImpl( const char* test_name, const char* test_funcs,
- bool _custom_inv_transform, bool _allow_32f, bool _allow_16u )
- : CvArrTest( test_name, test_funcs, "" )
-{
- test_array[INPUT].push(NULL);
- test_array[OUTPUT].push(NULL);
- test_array[OUTPUT].push(NULL);
- test_array[REF_OUTPUT].push(NULL);
- test_array[REF_OUTPUT].push(NULL);
- allow_16u = _allow_16u;
- allow_32f = _allow_32f;
- custom_inv_transform = _custom_inv_transform;
- fwd_code = inv_code = timing_code = -1;
- element_wise_relative_error = false;
-
- size_list = cvtcolor_sizes;
- whole_size_list = cvtcolor_whole_sizes;
- depth_list = cvtcolor_depths_8_16_32;
-
- fwd_code_str = inv_code_str = 0;
-
- default_timing_param_names = 0;
- test_cpp = false;
- hue_channel = false;
-}
-
-
-int CV_ColorCvtBaseTestImpl::write_default_params( CvFileStorage* fs )
-{
- int code = CvArrTest::write_default_params( fs );
- if( code >= 0 && ts->get_testing_mode() == CvTS::TIMING_MODE && fwd_code_str != 0 )
- {
- start_write_param( fs );
- cvStartWriteStruct( fs, "op", CV_NODE_SEQ+CV_NODE_FLOW );
- if( strcmp( fwd_code_str, "" ) != 0 )
- cvWriteString( fs, 0, fwd_code_str );
- if( strcmp( inv_code_str, "" ) != 0 )
- cvWriteString( fs, 0, inv_code_str );
- cvEndWriteStruct(fs);
- }
- return code;
-}
-
-
-void CV_ColorCvtBaseTestImpl::get_minmax_bounds( int i, int j, int type, CvScalar* low, CvScalar* high )
-{
- CvArrTest::get_minmax_bounds( i, j, type, low, high );
- if( i == INPUT )
- {
- int depth = CV_MAT_DEPTH(type);
- *low = cvScalarAll(0.);
- *high = cvScalarAll( depth == CV_8U ? 256 : depth == CV_16U ? 65536 : 1. );
- }
-}
-
-
-void CV_ColorCvtBaseTestImpl::get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- int depth, cn;
- CvArrTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
-
- if( allow_16u && allow_32f )
- {
- depth = cvTsRandInt(rng) % 3;
- depth = depth == 0 ? CV_8U : depth == 1 ? CV_16U : CV_32F;
- }
- else if( allow_16u || allow_32f )
- {
- depth = cvTsRandInt(rng) % 2;
- depth = depth == 0 ? CV_8U : allow_16u ? CV_16U : CV_32F;
- }
- else
- depth = CV_8U;
-
- cn = (cvTsRandInt(rng) & 1) + 3;
- blue_idx = cvTsRandInt(rng) & 1 ? 2 : 0;
-
- types[INPUT][0] = CV_MAKETYPE(depth, cn);
- types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_MAKETYPE(depth, 3);
- if( test_array[OUTPUT].size() > 1 )
- types[OUTPUT][1] = types[REF_OUTPUT][1] = CV_MAKETYPE(depth, cn);
-
- inplace = cn == 3 && cvTsRandInt(rng) % 2 != 0;
- test_cpp = (cvTsRandInt(rng) & 256) == 0;
-}
-
-
-void CV_ColorCvtBaseTestImpl::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images )
-{
- CvArrTest::get_timing_test_array_types_and_sizes( test_case_idx, sizes, types,
- whole_sizes, are_images );
- int depth = CV_MAT_DEPTH(types[INPUT][0]);
- const char* op_str = cvReadString( find_timing_param( "op" ), "none" );
- timing_code = strcmp( op_str, inv_code_str ) == 0 ? inv_code : fwd_code;
- types[INPUT][0] = types[OUTPUT][0] = CV_MAKETYPE(depth, 3);
- if( test_array[OUTPUT].size() > 1 )
- types[OUTPUT][1] = types[OUTPUT][0];
-}
-
-
-int CV_ColorCvtBaseTestImpl::prepare_test_case( int test_case_idx )
-{
- int code = CvArrTest::prepare_test_case( test_case_idx );
- if( code > 0 )
- {
- if( inplace )
- cvTsCopy( &test_mat[INPUT][0], &test_mat[OUTPUT][0] );
- if( ts->get_testing_mode() == CvTS::TIMING_MODE && timing_code != fwd_code )
- {
- int save_timing_code = timing_code;
- timing_code = fwd_code;
- run_func(); // initialize the intermediate image for backward color space transformation
- timing_code = save_timing_code;
- }
- }
- return code;
-}
-
-
-void CV_ColorCvtBaseTestImpl::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- sprintf( ptr, "%s,", cvReadString( find_timing_param( "op" ), fwd_code_str ));
- ptr += strlen(ptr);
- params_left--;
-
- CvArrTest::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-
-void CV_ColorCvtBaseTestImpl::run_func()
-{
- if( ts->get_testing_mode() == CvTS::CORRECTNESS_CHECK_MODE )
- {
- CvArr* out0 = test_array[OUTPUT][0];
- cv::Mat _out0 = cv::cvarrToMat(out0), _out1 = cv::cvarrToMat(test_array[OUTPUT][1]);
-
- if(!test_cpp)
- cvCvtColor( inplace ? out0 : test_array[INPUT][0], out0, fwd_code );
- else
- cv::cvtColor( cv::cvarrToMat(inplace ? out0 : test_array[INPUT][0]), _out0, fwd_code, _out0.channels());
-
- if( inplace )
- {
- cvCopy( out0, test_array[OUTPUT][1] );
- out0 = test_array[OUTPUT][1];
- }
- if(!test_cpp)
- cvCvtColor( out0, test_array[OUTPUT][1], inv_code );
- else
- cv::cvtColor(cv::cvarrToMat(out0), _out1, inv_code, _out1.channels());
- }
- else if( timing_code == fwd_code )
- cvCvtColor( test_array[INPUT][0], test_array[OUTPUT][0], timing_code );
- else
- cvCvtColor( test_array[OUTPUT][0], test_array[OUTPUT][1], timing_code );
-}
-
-
-void CV_ColorCvtBaseTestImpl::prepare_to_validation( int /*test_case_idx*/ )
-{
- convert_forward( &test_mat[INPUT][0], &test_mat[REF_OUTPUT][0] );
- convert_backward( &test_mat[INPUT][0], &test_mat[REF_OUTPUT][0],
- &test_mat[REF_OUTPUT][1] );
- int depth = CV_MAT_DEPTH(test_mat[REF_OUTPUT][0].type);
- if( depth == CV_8U && hue_channel )
- {
- for( int y = 0; y < test_mat[REF_OUTPUT][0].rows; y++ )
- for( int x = 0; x < test_mat[REF_OUTPUT][0].cols; x++ )
- {
- uchar* h0 = test_mat[REF_OUTPUT][0].data.ptr + test_mat[REF_OUTPUT][0].step*y + x*3;
- uchar* h = test_mat[OUTPUT][0].data.ptr + test_mat[OUTPUT][0].step*y + x*3;
- if( abs(*h - *h0) == 180 )
- if( *h == 0 ) *h = 180;
- }
- }
-}
-
-
-void CV_ColorCvtBaseTestImpl::convert_forward( const CvMat* src, CvMat* dst )
-{
- const float c8u = 0.0039215686274509803f; // 1./255
- const float c16u = 1.5259021896696422e-005f; // 1./65535
- int depth = CV_MAT_DEPTH(src->type);
- int cn = CV_MAT_CN(src->type), dst_cn = CV_MAT_CN(dst->type);
- int cols = src->cols, dst_cols_n = dst->cols*dst_cn;
- float* src_buf = (float*)cvAlloc( src->cols*3*sizeof(src_buf[0]) );
- float* dst_buf = (float*)cvAlloc( dst->cols*3*sizeof(dst_buf[0]) );
- int i, j;
-
- assert( (cn == 3 || cn == 4) && (dst_cn == 3 || dst_cn == 1) );
-
- for( i = 0; i < src->rows; i++ )
- {
- switch( depth )
- {
- case CV_8U:
- {
- const uchar* src_row = (const uchar*)(src->data.ptr + i*src->step);
- uchar* dst_row = (uchar*)(dst->data.ptr + i*dst->step);
-
- for( j = 0; j < cols; j++ )
- {
- src_buf[j*3] = src_row[j*cn + blue_idx]*c8u;
- src_buf[j*3+1] = src_row[j*cn + 1]*c8u;
- src_buf[j*3+2] = src_row[j*cn + (blue_idx^2)]*c8u;
- }
-
- convert_row_bgr2abc_32f_c3( src_buf, dst_buf, cols );
-
- for( j = 0; j < dst_cols_n; j++ )
- {
- int t = cvRound( dst_buf[j] );
- dst_row[j] = CV_CAST_8U(t);
- }
- }
- break;
- case CV_16U:
- {
- const ushort* src_row = (const ushort*)(src->data.ptr + i*src->step);
- ushort* dst_row = (ushort*)(dst->data.ptr + i*dst->step);
-
- for( j = 0; j < cols; j++ )
- {
- src_buf[j*3] = src_row[j*cn + blue_idx]*c16u;
- src_buf[j*3+1] = src_row[j*cn + 1]*c16u;
- src_buf[j*3+2] = src_row[j*cn + (blue_idx^2)]*c16u;
- }
-
- convert_row_bgr2abc_32f_c3( src_buf, dst_buf, cols );
-
- for( j = 0; j < dst_cols_n; j++ )
- {
- int t = cvRound( dst_buf[j] );
- dst_row[j] = CV_CAST_16U(t);
- }
- }
- break;
- case CV_32F:
- {
- const float* src_row = (const float*)(src->data.ptr + i*src->step);
- float* dst_row = (float*)(dst->data.ptr + i*dst->step);
-
- for( j = 0; j < cols; j++ )
- {
- src_buf[j*3] = src_row[j*cn + blue_idx];
- src_buf[j*3+1] = src_row[j*cn + 1];
- src_buf[j*3+2] = src_row[j*cn + (blue_idx^2)];
- }
-
- convert_row_bgr2abc_32f_c3( src_buf, dst_row, cols );
- }
- break;
- default:
- assert(0);
- }
- }
-
- cvFree( &src_buf );
- cvFree( &dst_buf );
-}
-
-
-void CV_ColorCvtBaseTestImpl::convert_row_bgr2abc_32f_c3( const float* /*src_row*/,
- float* /*dst_row*/, int /*n*/ )
-{
-}
-
-
-void CV_ColorCvtBaseTestImpl::convert_row_abc2bgr_32f_c3( const float* /*src_row*/,
- float* /*dst_row*/, int /*n*/ )
-{
-}
-
-
-void CV_ColorCvtBaseTestImpl::convert_backward( const CvMat* src, const CvMat* dst, CvMat* dst2 )
-{
- if( custom_inv_transform )
- {
- int depth = CV_MAT_DEPTH(src->type);
- int src_cn = CV_MAT_CN(dst->type), cn = CV_MAT_CN(dst2->type);
- int cols_n = src->cols*src_cn, dst_cols = dst->cols;
- float* src_buf = (float*)cvAlloc( src->cols*3*sizeof(src_buf[0]) );
- float* dst_buf = (float*)cvAlloc( dst->cols*3*sizeof(dst_buf[0]) );
- int i, j;
-
- assert( cn == 3 || cn == 4 );
-
- for( i = 0; i < src->rows; i++ )
- {
- switch( depth )
- {
- case CV_8U:
- {
- const uchar* src_row = (const uchar*)(dst->data.ptr + i*dst->step);
- uchar* dst_row = (uchar*)(dst2->data.ptr + i*dst2->step);
-
- for( j = 0; j < cols_n; j++ )
- src_buf[j] = src_row[j];
-
- convert_row_abc2bgr_32f_c3( src_buf, dst_buf, dst_cols );
-
- for( j = 0; j < dst_cols; j++ )
- {
- int b = cvRound( dst_buf[j*3]*255. );
- int g = cvRound( dst_buf[j*3+1]*255. );
- int r = cvRound( dst_buf[j*3+2]*255. );
- dst_row[j*cn + blue_idx] = CV_CAST_8U(b);
- dst_row[j*cn + 1] = CV_CAST_8U(g);
- dst_row[j*cn + (blue_idx^2)] = CV_CAST_8U(r);
- if( cn == 4 )
- dst_row[j*cn + 3] = 255;
- }
- }
- break;
- case CV_16U:
- {
- const ushort* src_row = (const ushort*)(dst->data.ptr + i*dst->step);
- ushort* dst_row = (ushort*)(dst2->data.ptr + i*dst2->step);
-
- for( j = 0; j < cols_n; j++ )
- src_buf[j] = src_row[j];
-
- convert_row_abc2bgr_32f_c3( src_buf, dst_buf, dst_cols );
-
- for( j = 0; j < dst_cols; j++ )
- {
- int b = cvRound( dst_buf[j*3]*65535. );
- int g = cvRound( dst_buf[j*3+1]*65535. );
- int r = cvRound( dst_buf[j*3+2]*65535. );
- dst_row[j*cn + blue_idx] = CV_CAST_16U(b);
- dst_row[j*cn + 1] = CV_CAST_16U(g);
- dst_row[j*cn + (blue_idx^2)] = CV_CAST_16U(r);
- if( cn == 4 )
- dst_row[j*cn + 3] = 65535;
- }
- }
- break;
- case CV_32F:
- {
- const float* src_row = (const float*)(dst->data.ptr + i*dst->step);
- float* dst_row = (float*)(dst2->data.ptr + i*dst2->step);
-
- convert_row_abc2bgr_32f_c3( src_row, dst_buf, dst_cols );
-
- for( j = 0; j < dst_cols; j++ )
- {
- float b = dst_buf[j*3];
- float g = dst_buf[j*3+1];
- float r = dst_buf[j*3+2];
- dst_row[j*cn + blue_idx] = b;
- dst_row[j*cn + 1] = g;
- dst_row[j*cn + (blue_idx^2)] = r;
- if( cn == 4 )
- dst_row[j*cn + 3] = 1.f;
- }
- }
- break;
- default:
- assert(0);
- }
- }
-
- cvFree( &src_buf );
- cvFree( &dst_buf );
- }
- else
- {
- int i, j, k;
- int elem_size = CV_ELEM_SIZE(src->type), elem_size1 = CV_ELEM_SIZE(src->type & CV_MAT_DEPTH_MASK);
- int width_n = src->cols*elem_size;
-
- for( i = 0; i < src->rows; i++ )
- {
- memcpy( dst2->data.ptr + i*dst2->step, src->data.ptr + i*src->step, width_n );
- if( CV_MAT_CN(src->type) == 4 )
- {
- // clear the alpha channel
- uchar* ptr = dst2->data.ptr + i*dst2->step + elem_size1*3;
- for( j = 0; j < width_n; j += elem_size )
- {
- for( k = 0; k < elem_size1; k++ )
- ptr[j + k] = 0;
- }
- }
- }
- }
-}
-
-
-CV_ColorCvtBaseTestImpl cvtcolor( "color", "", false, false, false );
-
-
-class CV_ColorCvtBaseTest : public CV_ColorCvtBaseTestImpl
-{
-public:
- CV_ColorCvtBaseTest( const char* test_name, const char* test_funcs,
- bool custom_inv_transform, bool allow_32f, bool allow_16u );
-};
-
-
-CV_ColorCvtBaseTest::CV_ColorCvtBaseTest( const char* test_name, const char* test_funcs,
- bool _custom_inv_transform, bool _allow_32f, bool _allow_16u )
- : CV_ColorCvtBaseTestImpl( test_name, test_funcs, _custom_inv_transform, _allow_32f, _allow_16u )
-{
- default_timing_param_names = cvtcolor_param_names;
- depth_list = 0;
- cn_list = 0;
- size_list = whole_size_list = 0;
-}
-
-#undef INIT_FWD_INV_CODES
-#define INIT_FWD_INV_CODES( fwd, inv ) \
- fwd_code = CV_##fwd; inv_code = CV_##inv; \
- fwd_code_str = #fwd; inv_code_str = #inv
-
-//// rgb <=> gray
-class CV_ColorGrayTest : public CV_ColorCvtBaseTest
-{
-public:
- CV_ColorGrayTest();
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void get_timing_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types,
- CvSize** whole_sizes, bool *are_images );
- void convert_row_bgr2abc_32f_c3( const float* src_row, float* dst_row, int n );
- void convert_row_abc2bgr_32f_c3( const float* src_row, float* dst_row, int n );
- double get_success_error_level( int test_case_idx, int i, int j );
-};
-
-
-CV_ColorGrayTest::CV_ColorGrayTest()
- : CV_ColorCvtBaseTest( "color-gray", "cvCvtColor", true, true, true )
-{
- INIT_FWD_INV_CODES( BGR2GRAY, GRAY2BGR );
-}
-
-
-void CV_ColorGrayTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CV_ColorCvtBaseTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- int cn = CV_MAT_CN(types[INPUT][0]);
- types[OUTPUT][0] = types[REF_OUTPUT][0] = types[INPUT][0] & CV_MAT_DEPTH_MASK;
- inplace = false;
-
- if( cn == 3 )
- {
- if( blue_idx == 0 )
- fwd_code = CV_BGR2GRAY, inv_code = CV_GRAY2BGR;
- else
- fwd_code = CV_RGB2GRAY, inv_code = CV_GRAY2RGB;
- }
- else
- {
- if( blue_idx == 0 )
- fwd_code = CV_BGRA2GRAY, inv_code = CV_GRAY2BGRA;
- else
- fwd_code = CV_RGBA2GRAY, inv_code = CV_GRAY2RGBA;
- }
-}
-
-
-void CV_ColorGrayTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images )
-{
- CV_ColorCvtBaseTest::get_timing_test_array_types_and_sizes( test_case_idx, sizes, types,
- whole_sizes, are_images );
- types[OUTPUT][0] &= CV_MAT_DEPTH_MASK;
-}
-
-
-double CV_ColorGrayTest::get_success_error_level( int /*test_case_idx*/, int i, int j )
-{
- int depth = CV_MAT_DEPTH(test_mat[i][j].type);
- return depth == CV_8U ? 2 : depth == CV_16U ? 16 : 1e-5;
-}
-
-
-void CV_ColorGrayTest::convert_row_bgr2abc_32f_c3( const float* src_row, float* dst_row, int n )
-{
- int depth = CV_MAT_DEPTH(test_mat[INPUT][0].type);
- double scale = depth == CV_8U ? 255 : depth == CV_16U ? 65535 : 1;
- double cr = 0.299*scale;
- double cg = 0.587*scale;
- double cb = 0.114*scale;
- int j;
-
- for( j = 0; j < n; j++ )
- dst_row[j] = (float)(src_row[j*3]*cb + src_row[j*3+1]*cg + src_row[j*3+2]*cr);
-}
-
-
-void CV_ColorGrayTest::convert_row_abc2bgr_32f_c3( const float* src_row, float* dst_row, int n )
-{
- int j, depth = CV_MAT_DEPTH(test_mat[INPUT][0].type);
- float scale = depth == CV_8U ? (1.f/255) : depth == CV_16U ? 1.f/65535 : 1.f;
- for( j = 0; j < n; j++ )
- dst_row[j*3] = dst_row[j*3+1] = dst_row[j*3+2] = src_row[j]*scale;
-}
-
-
-CV_ColorGrayTest color_gray_test;
-
-
-//// rgb <=> ycrcb
-class CV_ColorYCrCbTest : public CV_ColorCvtBaseTest
-{
-public:
- CV_ColorYCrCbTest();
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- double get_success_error_level( int test_case_idx, int i, int j );
- void convert_row_bgr2abc_32f_c3( const float* src_row, float* dst_row, int n );
- void convert_row_abc2bgr_32f_c3( const float* src_row, float* dst_row, int n );
-};
-
-
-CV_ColorYCrCbTest::CV_ColorYCrCbTest()
- : CV_ColorCvtBaseTest( "color-ycc", "cvCvtColor", true, true, true )
-{
- INIT_FWD_INV_CODES( BGR2YCrCb, YCrCb2BGR );
-}
-
-
-void CV_ColorYCrCbTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CV_ColorCvtBaseTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
-
- if( blue_idx == 0 )
- fwd_code = CV_BGR2YCrCb, inv_code = CV_YCrCb2BGR;
- else
- fwd_code = CV_RGB2YCrCb, inv_code = CV_YCrCb2RGB;
-}
-
-
-double CV_ColorYCrCbTest::get_success_error_level( int /*test_case_idx*/, int i, int j )
-{
- int depth = CV_MAT_DEPTH(test_mat[i][j].type);
- return depth == CV_8U ? 2 : depth == CV_16U ? 32 : 1e-3;
-}
-
-
-void CV_ColorYCrCbTest::convert_row_bgr2abc_32f_c3( const float* src_row, float* dst_row, int n )
-{
- int depth = CV_MAT_DEPTH(test_mat[INPUT][0].type);
- double scale = depth == CV_8U ? 255 : depth == CV_16U ? 65535 : 1;
- double bias = depth == CV_8U ? 128 : depth == CV_16U ? 32768 : 0.5;
-
- double M[] = { 0.299, 0.587, 0.114,
- 0.49981, -0.41853, -0.08128,
- -0.16864, -0.33107, 0.49970 };
- int j;
- for( j = 0; j < 9; j++ )
- M[j] *= scale;
-
- for( j = 0; j < n*3; j += 3 )
- {
- double r = src_row[j+2];
- double g = src_row[j+1];
- double b = src_row[j];
- double y = M[0]*r + M[1]*g + M[2]*b;
- double cr = M[3]*r + M[4]*g + M[5]*b + bias;
- double cb = M[6]*r + M[7]*g + M[8]*b + bias;
- dst_row[j] = (float)y;
- dst_row[j+1] = (float)cr;
- dst_row[j+2] = (float)cb;
- }
-}
-
-
-void CV_ColorYCrCbTest::convert_row_abc2bgr_32f_c3( const float* src_row, float* dst_row, int n )
-{
- int depth = CV_MAT_DEPTH(test_mat[INPUT][0].type);
- double bias = depth == CV_8U ? 128 : depth == CV_16U ? 32768 : 0.5;
- double scale = depth == CV_8U ? 1./255 : depth == CV_16U ? 1./65535 : 1;
- double M[] = { 1, 1.40252, 0,
- 1, -0.71440, -0.34434,
- 1, 0, 1.77305 };
- int j;
- for( j = 0; j < 9; j++ )
- M[j] *= scale;
-
- for( j = 0; j < n*3; j += 3 )
- {
- double y = src_row[j];
- double cr = src_row[j+1] - bias;
- double cb = src_row[j+2] - bias;
- double r = M[0]*y + M[1]*cr + M[2]*cb;
- double g = M[3]*y + M[4]*cr + M[5]*cb;
- double b = M[6]*y + M[7]*cr + M[8]*cb;
- dst_row[j] = (float)b;
- dst_row[j+1] = (float)g;
- dst_row[j+2] = (float)r;
- }
-}
-
-
-CV_ColorYCrCbTest color_ycrcb_test;
-
-
-
-//// rgb <=> hsv
-class CV_ColorHSVTest : public CV_ColorCvtBaseTest
-{
-public:
- CV_ColorHSVTest();
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- double get_success_error_level( int test_case_idx, int i, int j );
- void convert_row_bgr2abc_32f_c3( const float* src_row, float* dst_row, int n );
- void convert_row_abc2bgr_32f_c3( const float* src_row, float* dst_row, int n );
-};
-
-
-CV_ColorHSVTest::CV_ColorHSVTest()
- : CV_ColorCvtBaseTest( "color-hsv", "cvCvtColor", true, true, false )
-{
- INIT_FWD_INV_CODES( BGR2HSV, HSV2BGR );
- depth_list = cvtcolor_depths_8_32;
- hue_channel = true;
-}
-
-
-void CV_ColorHSVTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CV_ColorCvtBaseTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
-
- if( blue_idx == 0 )
- fwd_code = CV_BGR2HSV, inv_code = CV_HSV2BGR;
- else
- fwd_code = CV_RGB2HSV, inv_code = CV_HSV2RGB;
-}
-
-
-double CV_ColorHSVTest::get_success_error_level( int /*test_case_idx*/, int i, int j )
-{
- int depth = CV_MAT_DEPTH(test_mat[i][j].type);
- return depth == CV_8U ? (j == 0 ? 4 : 16) : depth == CV_16U ? 32 : 1e-3;
-}
-
-
-void CV_ColorHSVTest::convert_row_bgr2abc_32f_c3( const float* src_row, float* dst_row, int n )
-{
- int depth = CV_MAT_DEPTH(test_mat[INPUT][0].type);
- float h_scale = depth == CV_8U ? 30.f : 60.f;
- float scale = depth == CV_8U ? 255.f : depth == CV_16U ? 65535.f : 1.f;
- int j;
-
- for( j = 0; j < n*3; j += 3 )
- {
- float r = src_row[j+2];
- float g = src_row[j+1];
- float b = src_row[j];
- float vmin = MIN(r,g);
- float v = MAX(r,g);
- float s, h, diff;
- vmin = MIN(vmin,b);
- v = MAX(v,b);
- diff = v - vmin;
- if( diff == 0 )
- s = h = 0;
- else
- {
- s = diff/(v + FLT_EPSILON);
- diff = 1.f/diff;
-
- h = r == v ? (g - b)*diff :
- g == v ? 2 + (b - r)*diff : 4 + (r - g)*diff;
-
- if( h < 0 )
- h += 6;
- }
-
- dst_row[j] = h*h_scale;
- dst_row[j+1] = s*scale;
- dst_row[j+2] = v*scale;
- }
-}
-
-// taken from http://www.cs.rit.edu/~ncs/color/t_convert.html
-void CV_ColorHSVTest::convert_row_abc2bgr_32f_c3( const float* src_row, float* dst_row, int n )
-{
- int depth = CV_MAT_DEPTH(test_mat[INPUT][0].type);
- float h_scale = depth == CV_8U ? 1.f/30 : 1.f/60;
- float scale = depth == CV_8U ? 1.f/255 : depth == CV_16U ? 1.f/65535 : 1;
- int j;
-
- for( j = 0; j < n*3; j += 3 )
- {
- float h = src_row[j]*h_scale;
- float s = src_row[j+1]*scale;
- float v = src_row[j+2]*scale;
- float r = v, g = v, b = v;
-
- if( h < 0 )
- h += 6;
- else if( h >= 6 )
- h -= 6;
-
- if( s != 0 )
- {
- int i = cvFloor(h);
- float f = h - i;
- float p = v*(1 - s);
- float q = v*(1 - s*f);
- float t = v*(1 - s*(1 - f));
-
- if( i == 0 )
- r = v, g = t, b = p;
- else if( i == 1 )
- r = q, g = v, b = p;
- else if( i == 2 )
- r = p, g = v, b = t;
- else if( i == 3 )
- r = p, g = q, b = v;
- else if( i == 4 )
- r = t, g = p, b = v;
- else
- r = v, g = p, b = q;
- }
-
- dst_row[j] = b;
- dst_row[j+1] = g;
- dst_row[j+2] = r;
- }
-}
-
-
-CV_ColorHSVTest color_hsv_test;
-
-
-
-//// rgb <=> hls
-class CV_ColorHLSTest : public CV_ColorCvtBaseTest
-{
-public:
- CV_ColorHLSTest();
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- double get_success_error_level( int test_case_idx, int i, int j );
- void convert_row_bgr2abc_32f_c3( const float* src_row, float* dst_row, int n );
- void convert_row_abc2bgr_32f_c3( const float* src_row, float* dst_row, int n );
-};
-
-
-CV_ColorHLSTest::CV_ColorHLSTest()
- : CV_ColorCvtBaseTest( "color-hls", "cvCvtColor", true, true, false )
-{
- INIT_FWD_INV_CODES( BGR2HLS, HLS2BGR );
- depth_list = cvtcolor_depths_8_32;
- hue_channel = true;
-}
-
-
-void CV_ColorHLSTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CV_ColorCvtBaseTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
-
- if( blue_idx == 0 )
- fwd_code = CV_BGR2HLS, inv_code = CV_HLS2BGR;
- else
- fwd_code = CV_RGB2HLS, inv_code = CV_HLS2RGB;
-}
-
-
-double CV_ColorHLSTest::get_success_error_level( int /*test_case_idx*/, int i, int j )
-{
- int depth = CV_MAT_DEPTH(test_mat[i][j].type);
- return depth == CV_8U ? (j == 0 ? 4 : 16) : depth == CV_16U ? 32 : 1e-4;
-}
-
-
-void CV_ColorHLSTest::convert_row_bgr2abc_32f_c3( const float* src_row, float* dst_row, int n )
-{
- int depth = CV_MAT_DEPTH(test_mat[INPUT][0].type);
- float h_scale = depth == CV_8U ? 30.f : 60.f;
- float scale = depth == CV_8U ? 255.f : depth == CV_16U ? 65535.f : 1.f;
- int j;
-
- for( j = 0; j < n*3; j += 3 )
- {
- float r = src_row[j+2];
- float g = src_row[j+1];
- float b = src_row[j];
- float vmin = MIN(r,g);
- float v = MAX(r,g);
- float s, h, l, diff;
- vmin = MIN(vmin,b);
- v = MAX(v,b);
- diff = v - vmin;
-
- if( diff == 0 )
- s = h = 0, l = v;
- else
- {
- l = (v + vmin)*0.5f;
- s = l <= 0.5f ? diff / (v + vmin) : diff / (2 - v - vmin);
- diff = 1.f/diff;
-
- h = r == v ? (g - b)*diff :
- g == v ? 2 + (b - r)*diff : 4 + (r - g)*diff;
-
- if( h < 0 )
- h += 6;
- }
-
- dst_row[j] = h*h_scale;
- dst_row[j+1] = l*scale;
- dst_row[j+2] = s*scale;
- }
-}
-
-
-void CV_ColorHLSTest::convert_row_abc2bgr_32f_c3( const float* src_row, float* dst_row, int n )
-{
- int depth = CV_MAT_DEPTH(test_mat[INPUT][0].type);
- float h_scale = depth == CV_8U ? 1.f/30 : 1.f/60;
- float scale = depth == CV_8U ? 1.f/255 : depth == CV_16U ? 1.f/65535 : 1;
- int j;
-
- for( j = 0; j < n*3; j += 3 )
- {
- float h = src_row[j]*h_scale;
- float l = src_row[j+1]*scale;
- float s = src_row[j+2]*scale;
- float r = l, g = l, b = l;
-
- if( h < 0 )
- h += 6;
- else if( h >= 6 )
- h -= 6;
-
- if( s != 0 )
- {
- float m2 = l <= 0.5f ? l*(1.f + s) : l + s - l*s;
- float m1 = 2*l - m2;
- float h1 = h + 2;
-
- if( h1 >= 6 )
- h1 -= 6;
- if( h1 < 1 )
- r = m1 + (m2 - m1)*h1;
- else if( h1 < 3 )
- r = m2;
- else if( h1 < 4 )
- r = m1 + (m2 - m1)*(4 - h1);
- else
- r = m1;
-
- h1 = h;
-
- if( h1 < 1 )
- g = m1 + (m2 - m1)*h1;
- else if( h1 < 3 )
- g = m2;
- else if( h1 < 4 )
- g = m1 + (m2 - m1)*(4 - h1);
- else
- g = m1;
-
- h1 = h - 2;
- if( h1 < 0 )
- h1 += 6;
-
- if( h1 < 1 )
- b = m1 + (m2 - m1)*h1;
- else if( h1 < 3 )
- b = m2;
- else if( h1 < 4 )
- b = m1 + (m2 - m1)*(4 - h1);
- else
- b = m1;
- }
-
- dst_row[j] = b;
- dst_row[j+1] = g;
- dst_row[j+2] = r;
- }
-}
-
-
-CV_ColorHLSTest color_hls_test;
-
-
-static const double RGB2XYZ[] =
-{
- 0.412453, 0.357580, 0.180423,
- 0.212671, 0.715160, 0.072169,
- 0.019334, 0.119193, 0.950227
-};
-
-
-static const double XYZ2RGB[] =
-{
- 3.240479, -1.53715, -0.498535,
- -0.969256, 1.875991, 0.041556,
- 0.055648, -0.204043, 1.057311
-};
-
-static const float Xn = 0.950456f;
-static const float Zn = 1.088754f;
-
-
-//// rgb <=> xyz
-class CV_ColorXYZTest : public CV_ColorCvtBaseTest
-{
-public:
- CV_ColorXYZTest();
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- double get_success_error_level( int test_case_idx, int i, int j );
- void convert_row_bgr2abc_32f_c3( const float* src_row, float* dst_row, int n );
- void convert_row_abc2bgr_32f_c3( const float* src_row, float* dst_row, int n );
-};
-
-
-CV_ColorXYZTest::CV_ColorXYZTest()
- : CV_ColorCvtBaseTest( "color-xyz", "cvCvtColor", true, true, true )
-{
- INIT_FWD_INV_CODES( BGR2XYZ, XYZ2BGR );
-}
-
-
-void CV_ColorXYZTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CV_ColorCvtBaseTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
-
- if( blue_idx == 0 )
- fwd_code = CV_BGR2XYZ, inv_code = CV_XYZ2BGR;
- else
- fwd_code = CV_RGB2XYZ, inv_code = CV_XYZ2RGB;
-}
-
-
-double CV_ColorXYZTest::get_success_error_level( int /*test_case_idx*/, int i, int j )
-{
- int depth = CV_MAT_DEPTH(test_mat[i][j].type);
- return depth == CV_8U ? (j == 0 ? 2 : 8) : depth == CV_16U ? (j == 0 ? 64 : 128) : 1e-1;
-}
-
-
-void CV_ColorXYZTest::convert_row_bgr2abc_32f_c3( const float* src_row, float* dst_row, int n )
-{
- int depth = CV_MAT_DEPTH(test_mat[INPUT][0].type);
- double scale = depth == CV_8U ? 255 : depth == CV_16U ? 65535 : 1;
-
- double M[9];
- int j;
- for( j = 0; j < 9; j++ )
- M[j] = RGB2XYZ[j]*scale;
-
- for( j = 0; j < n*3; j += 3 )
- {
- double r = src_row[j+2];
- double g = src_row[j+1];
- double b = src_row[j];
- double x = M[0]*r + M[1]*g + M[2]*b;
- double y = M[3]*r + M[4]*g + M[5]*b;
- double z = M[6]*r + M[7]*g + M[8]*b;
- dst_row[j] = (float)x;
- dst_row[j+1] = (float)y;
- dst_row[j+2] = (float)z;
- }
-}
-
-
-void CV_ColorXYZTest::convert_row_abc2bgr_32f_c3( const float* src_row, float* dst_row, int n )
-{
- int depth = CV_MAT_DEPTH(test_mat[INPUT][0].type);
- double scale = depth == CV_8U ? 1./255 : depth == CV_16U ? 1./65535 : 1;
-
- double M[9];
- int j;
- for( j = 0; j < 9; j++ )
- M[j] = XYZ2RGB[j]*scale;
-
- for( j = 0; j < n*3; j += 3 )
- {
- double x = src_row[j];
- double y = src_row[j+1];
- double z = src_row[j+2];
- double r = M[0]*x + M[1]*y + M[2]*z;
- double g = M[3]*x + M[4]*y + M[5]*z;
- double b = M[6]*x + M[7]*y + M[8]*z;
- dst_row[j] = (float)b;
- dst_row[j+1] = (float)g;
- dst_row[j+2] = (float)r;
- }
-}
-
-
-CV_ColorXYZTest color_xyz_test;
-
-
-//// rgb <=> L*a*b*
-class CV_ColorLabTest : public CV_ColorCvtBaseTest
-{
-public:
- CV_ColorLabTest();
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- double get_success_error_level( int test_case_idx, int i, int j );
- void convert_row_bgr2abc_32f_c3( const float* src_row, float* dst_row, int n );
- void convert_row_abc2bgr_32f_c3( const float* src_row, float* dst_row, int n );
-};
-
-
-CV_ColorLabTest::CV_ColorLabTest()
- : CV_ColorCvtBaseTest( "color-lab", "cvCvtColor", true, true, false )
-{
- INIT_FWD_INV_CODES( BGR2Lab, Lab2BGR );
- depth_list = cvtcolor_depths_8_32;
-}
-
-
-void CV_ColorLabTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CV_ColorCvtBaseTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
-
- if( blue_idx == 0 )
- fwd_code = CV_LBGR2Lab, inv_code = CV_Lab2LBGR;
- else
- fwd_code = CV_LRGB2Lab, inv_code = CV_Lab2LRGB;
-}
-
-
-double CV_ColorLabTest::get_success_error_level( int /*test_case_idx*/, int i, int j )
-{
- int depth = CV_MAT_DEPTH(test_mat[i][j].type);
- return depth == CV_8U ? 16 : depth == CV_16U ? 32 : 1e-3;
-}
-
-
-static const double _1_3 = 0.333333333333;
-
-void CV_ColorLabTest::convert_row_bgr2abc_32f_c3( const float* src_row, float* dst_row, int n )
-{
- int depth = CV_MAT_DEPTH(test_mat[INPUT][0].type);
- float Lscale = depth == CV_8U ? 255.f/100.f : depth == CV_16U ? 65535.f/100.f : 1.f;
- float ab_bias = depth == CV_8U ? 128.f : depth == CV_16U ? 32768.f : 0.f;
- int j;
- float M[9];
-
- for( j = 0; j < 9; j++ )
- M[j] = (float)RGB2XYZ[j];
-
- for( j = 0; j < n*3; j += 3 )
- {
- float r = src_row[j+2];
- float g = src_row[j+1];
- float b = src_row[j];
-
- float X = (r*M[0] + g*M[1] + b*M[2])*(1.f/Xn);
- float Y = r*M[3] + g*M[4] + b*M[5];
- float Z = (r*M[6] + g*M[7] + b*M[8])*(1.f/Zn);
- float fX, fY, fZ;
-
- float L, a;
-
- if( Y > 0.008856 )
- {
- fY = (float)pow((double)Y,_1_3);
- L = 116.f*fY - 16.f;
- }
- else
- {
- fY = 7.787f*Y + 16.f/116.f;
- L = 903.3f*Y;
- }
-
- if( X > 0.008856 )
- fX = (float)pow((double)X,_1_3);
- else
- fX = 7.787f*X + 16.f/116.f;
-
- if( Z > 0.008856 )
- fZ = (float)pow((double)Z,_1_3);
- else
- fZ = 7.787f*Z + 16.f/116.f;
-
- a = 500.f*(fX - fY);
- b = 200.f*(fY - fZ);
-
- dst_row[j] = L*Lscale;
- dst_row[j+1] = a + ab_bias;
- dst_row[j+2] = b + ab_bias;
- }
-}
-
-
-void CV_ColorLabTest::convert_row_abc2bgr_32f_c3( const float* src_row, float* dst_row, int n )
-{
- int depth = CV_MAT_DEPTH(test_mat[INPUT][0].type);
- float Lscale = depth == CV_8U ? 100.f/255.f : depth == CV_16U ? 100.f/65535.f : 1.f;
- float ab_bias = depth == CV_8U ? 128.f : depth == CV_16U ? 32768.f : 0.f;
- int j;
- float M[9];
-
- for( j = 0; j < 9; j++ )
- M[j] = (float)XYZ2RGB[j];
-
- for( j = 0; j < n*3; j += 3 )
- {
- float L = src_row[j]*Lscale;
- float a = src_row[j+1] - ab_bias;
- float b = src_row[j+2] - ab_bias;
-
- float P = (L + 16.f)*(1.f/116.f);
- float X = (P + a*0.002f);
- float Z = (P - b*0.005f);
- float Y = P*P*P;
- X = Xn*X*X*X;
- Z = Zn*Z*Z*Z;
-
- float r = M[0]*X + M[1]*Y + M[2]*Z;
- float g = M[3]*X + M[4]*Y + M[5]*Z;
- b = M[6]*X + M[7]*Y + M[8]*Z;
-
- dst_row[j] = b;
- dst_row[j+1] = g;
- dst_row[j+2] = r;
- }
-}
-
-
-CV_ColorLabTest color_lab_test;
-
-
-//// rgb <=> L*u*v*
-class CV_ColorLuvTest : public CV_ColorCvtBaseTest
-{
-public:
- CV_ColorLuvTest();
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- double get_success_error_level( int test_case_idx, int i, int j );
- void convert_row_bgr2abc_32f_c3( const float* src_row, float* dst_row, int n );
- void convert_row_abc2bgr_32f_c3( const float* src_row, float* dst_row, int n );
-};
-
-
-CV_ColorLuvTest::CV_ColorLuvTest()
- : CV_ColorCvtBaseTest( "color-luv", "cvCvtColor", true, true, false )
-{
- INIT_FWD_INV_CODES( BGR2Luv, Luv2BGR );
- depth_list = cvtcolor_depths_8_32;
-}
-
-
-void CV_ColorLuvTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CV_ColorCvtBaseTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
-
- if( blue_idx == 0 )
- fwd_code = CV_LBGR2Luv, inv_code = CV_Luv2LBGR;
- else
- fwd_code = CV_LRGB2Luv, inv_code = CV_Luv2LRGB;
-}
-
-
-double CV_ColorLuvTest::get_success_error_level( int /*test_case_idx*/, int i, int j )
-{
- int depth = CV_MAT_DEPTH(test_mat[i][j].type);
- return depth == CV_8U ? 48 : depth == CV_16U ? 32 : 5e-2;
-}
-
-
-void CV_ColorLuvTest::convert_row_bgr2abc_32f_c3( const float* src_row, float* dst_row, int n )
-{
- int depth = CV_MAT_DEPTH(test_mat[INPUT][0].type);
- float Lscale = depth == CV_8U ? 255.f/100.f : depth == CV_16U ? 65535.f/100.f : 1.f;
- int j;
-
- float M[9];
- float un = 4.f*Xn/(Xn + 15.f*1.f + 3*Zn);
- float vn = 9.f*1.f/(Xn + 15.f*1.f + 3*Zn);
- float u_scale = 1.f, u_bias = 0.f;
- float v_scale = 1.f, v_bias = 0.f;
-
- for( j = 0; j < 9; j++ )
- M[j] = (float)RGB2XYZ[j];
-
- if( depth == CV_8U )
- {
- u_scale = 0.720338983f;
- u_bias = 96.5254237f;
- v_scale = 0.99609375f;
- v_bias = 139.453125f;
- }
-
- for( j = 0; j < n*3; j += 3 )
- {
- float r = src_row[j+2];
- float g = src_row[j+1];
- float b = src_row[j];
-
- float X = r*M[0] + g*M[1] + b*M[2];
- float Y = r*M[3] + g*M[4] + b*M[5];
- float Z = r*M[6] + g*M[7] + b*M[8];
- float d = X + 15*Y + 3*Z, L, u, v;
-
- if( d == 0 )
- L = u = v = 0;
- else
- {
- if( Y > 0.008856f )
- L = (float)(116.*pow((double)Y,_1_3) - 16.);
- else
- L = 903.3f * Y;
-
- d = 1.f/d;
- u = 13*L*(4*X*d - un);
- v = 13*L*(9*Y*d - vn);
- }
- dst_row[j] = L*Lscale;
- dst_row[j+1] = u*u_scale + u_bias;
- dst_row[j+2] = v*v_scale + v_bias;
- }
-}
-
-
-void CV_ColorLuvTest::convert_row_abc2bgr_32f_c3( const float* src_row, float* dst_row, int n )
-{
- int depth = CV_MAT_DEPTH(test_mat[INPUT][0].type);
- float Lscale = depth == CV_8U ? 100.f/255.f : depth == CV_16U ? 100.f/65535.f : 1.f;
- int j;
- float M[9];
- float un = 4.f*Xn/(Xn + 15.f*1.f + 3*Zn);
- float vn = 9.f*1.f/(Xn + 15.f*1.f + 3*Zn);
- float u_scale = 1.f, u_bias = 0.f;
- float v_scale = 1.f, v_bias = 0.f;
-
- for( j = 0; j < 9; j++ )
- M[j] = (float)XYZ2RGB[j];
-
- if( depth == CV_8U )
- {
- u_scale = 1.f/0.720338983f;
- u_bias = 96.5254237f;
- v_scale = 1.f/0.99609375f;
- v_bias = 139.453125f;
- }
-
- for( j = 0; j < n*3; j += 3 )
- {
- float L = src_row[j]*Lscale;
- float u = (src_row[j+1] - u_bias)*u_scale;
- float v = (src_row[j+2] - v_bias)*v_scale;
- float X, Y, Z;
-
- if( L >= 8 )
- {
- Y = (L + 16.f)*(1.f/116.f);
- Y = Y*Y*Y;
- }
- else
- {
- Y = L * (1.f/903.3f);
- if( L == 0 )
- L = 0.001f;
- }
-
- u = u/(13*L) + un;
- v = v/(13*L) + vn;
-
- X = -9*Y*u/((u - 4)*v - u*v);
- Z = (9*Y - 15*v*Y - v*X)/(3*v);
-
- float r = M[0]*X + M[1]*Y + M[2]*Z;
- float g = M[3]*X + M[4]*Y + M[5]*Z;
- float b = M[6]*X + M[7]*Y + M[8]*Z;
-
- dst_row[j] = b;
- dst_row[j+1] = g;
- dst_row[j+2] = r;
- }
-}
-
-
-CV_ColorLuvTest color_luv_test;
-
-
-
-//// rgb <=> another rgb
-class CV_ColorRGBTest : public CV_ColorCvtBaseTest
-{
-public:
- CV_ColorRGBTest();
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- double get_success_error_level( int test_case_idx, int i, int j );
- void convert_forward( const CvMat* src, CvMat* dst );
- void convert_backward( const CvMat* src, const CvMat* dst, CvMat* dst2 );
- int dst_bits;
-};
-
-
-CV_ColorRGBTest::CV_ColorRGBTest()
- : CV_ColorCvtBaseTest( "color-rgb", "cvCvtColor", true, true, true )
-{
- dst_bits = 0;
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;
-}
-
-
-void CV_ColorRGBTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- CV_ColorCvtBaseTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- int cn = CV_MAT_CN(types[INPUT][0]);
-
- dst_bits = 24;
-
- if( cvTsRandInt(rng) % 3 == 0 )
- {
- types[INPUT][0] = types[OUTPUT][1] = types[REF_OUTPUT][1] = CV_MAKETYPE(CV_8U,cn);
- types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_MAKETYPE(CV_8U,2);
- if( cvTsRandInt(rng) & 1 )
- {
- if( blue_idx == 0 )
- fwd_code = CV_BGR2BGR565, inv_code = CV_BGR5652BGR;
- else
- fwd_code = CV_RGB2BGR565, inv_code = CV_BGR5652RGB;
- dst_bits = 16;
- }
- else
- {
- if( blue_idx == 0 )
- fwd_code = CV_BGR2BGR555, inv_code = CV_BGR5552BGR;
- else
- fwd_code = CV_RGB2BGR555, inv_code = CV_BGR5552RGB;
- dst_bits = 15;
- }
- }
- else
- {
- if( cn == 3 )
- {
- fwd_code = CV_RGB2BGR, inv_code = CV_BGR2RGB;
- blue_idx = 2;
- }
- else if( blue_idx == 0 )
- fwd_code = CV_BGRA2BGR, inv_code = CV_BGR2BGRA;
- else
- fwd_code = CV_RGBA2BGR, inv_code = CV_BGR2RGBA;
- }
-
- if( CV_MAT_CN(types[INPUT][0]) != CV_MAT_CN(types[OUTPUT][0]) )
- inplace = false;
-}
-
-
-double CV_ColorRGBTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- return 0;
-}
-
-
-void CV_ColorRGBTest::convert_forward( const CvMat* src, CvMat* dst )
-{
- int depth = CV_MAT_DEPTH(src->type);
- int cn = CV_MAT_CN(src->type);
-/*#if defined _DEBUG || defined DEBUG
- int dst_cn = CV_MAT_CN(dst->type);
-#endif*/
- int i, j, cols = src->cols;
- int g_rshift = dst_bits == 16 ? 2 : 3;
- int r_lshift = dst_bits == 16 ? 11 : 10;
-
- //assert( (cn == 3 || cn == 4) && (dst_cn == 3 || (dst_cn == 2 && depth == CV_8U)) );
-
- for( i = 0; i < src->rows; i++ )
- {
- switch( depth )
- {
- case CV_8U:
- {
- const uchar* src_row = (const uchar*)(src->data.ptr + i*src->step);
- uchar* dst_row = (uchar*)(dst->data.ptr + i*dst->step);
-
- if( dst_bits == 24 )
- {
- for( j = 0; j < cols; j++ )
- {
- uchar b = src_row[j*cn + blue_idx];
- uchar g = src_row[j*cn + 1];
- uchar r = src_row[j*cn + (blue_idx^2)];
- dst_row[j*3] = b;
- dst_row[j*3+1] = g;
- dst_row[j*3+2] = r;
- }
- }
- else
- {
- for( j = 0; j < cols; j++ )
- {
- int b = src_row[j*cn + blue_idx] >> 3;
- int g = src_row[j*cn + 1] >> g_rshift;
- int r = src_row[j*cn + (blue_idx^2)] >> 3;
- ((ushort*)dst_row)[j] = (ushort)(b | (g << 5) | (r << r_lshift));
- if( cn == 4 && src_row[j*4+3] )
- ((ushort*)dst_row)[j] |= 1 << (r_lshift+5);
- }
- }
- }
- break;
- case CV_16U:
- {
- const ushort* src_row = (const ushort*)(src->data.ptr + i*src->step);
- ushort* dst_row = (ushort*)(dst->data.ptr + i*dst->step);
-
- for( j = 0; j < cols; j++ )
- {
- ushort b = src_row[j*cn + blue_idx];
- ushort g = src_row[j*cn + 1];
- ushort r = src_row[j*cn + (blue_idx^2)];
- dst_row[j*3] = b;
- dst_row[j*3+1] = g;
- dst_row[j*3+2] = r;
- }
- }
- break;
- case CV_32F:
- {
- const float* src_row = (const float*)(src->data.ptr + i*src->step);
- float* dst_row = (float*)(dst->data.ptr + i*dst->step);
-
- for( j = 0; j < cols; j++ )
- {
- float b = src_row[j*cn + blue_idx];
- float g = src_row[j*cn + 1];
- float r = src_row[j*cn + (blue_idx^2)];
- dst_row[j*3] = b;
- dst_row[j*3+1] = g;
- dst_row[j*3+2] = r;
- }
- }
- break;
- default:
- assert(0);
- }
- }
-}
-
-
-void CV_ColorRGBTest::convert_backward( const CvMat* /*src*/, const CvMat* src, CvMat* dst )
-{
- int depth = CV_MAT_DEPTH(src->type);
- int cn = CV_MAT_CN(dst->type);
-/*#if defined _DEBUG || defined DEBUG
- int src_cn = CV_MAT_CN(src->type);
-#endif*/
- int i, j, cols = src->cols;
- int g_lshift = dst_bits == 16 ? 2 : 3;
- int r_rshift = dst_bits == 16 ? 11 : 10;
-
- //assert( (cn == 3 || cn == 4) && (src_cn == 3 || (src_cn == 2 && depth == CV_8U)) );
-
- for( i = 0; i < src->rows; i++ )
- {
- switch( depth )
- {
- case CV_8U:
- {
- const uchar* src_row = (const uchar*)(src->data.ptr + i*src->step);
- uchar* dst_row = (uchar*)(dst->data.ptr + i*dst->step);
-
- if( dst_bits == 24 )
- {
- for( j = 0; j < cols; j++ )
- {
- uchar b = src_row[j*3];
- uchar g = src_row[j*3 + 1];
- uchar r = src_row[j*3 + 2];
-
- dst_row[j*cn + blue_idx] = b;
- dst_row[j*cn + 1] = g;
- dst_row[j*cn + (blue_idx^2)] = r;
-
- if( cn == 4 )
- dst_row[j*cn + 3] = 255;
- }
- }
- else
- {
- for( j = 0; j < cols; j++ )
- {
- ushort val = ((ushort*)src_row)[j];
- uchar b = (uchar)(val << 3);
- uchar g = (uchar)((val >> 5) << g_lshift);
- uchar r = (uchar)((val >> r_rshift) << 3);
-
- dst_row[j*cn + blue_idx] = b;
- dst_row[j*cn + 1] = g;
- dst_row[j*cn + (blue_idx^2)] = r;
-
- if( cn == 4 )
- {
- uchar alpha = r_rshift == 11 || (val & 0x8000) != 0 ? 255 : 0;
- dst_row[j*cn + 3] = alpha;
- }
- }
- }
- }
- break;
- case CV_16U:
- {
- const ushort* src_row = (const ushort*)(src->data.ptr + i*src->step);
- ushort* dst_row = (ushort*)(dst->data.ptr + i*dst->step);
-
- for( j = 0; j < cols; j++ )
- {
- ushort b = src_row[j*3];
- ushort g = src_row[j*3 + 1];
- ushort r = src_row[j*3 + 2];
-
- dst_row[j*cn + blue_idx] = b;
- dst_row[j*cn + 1] = g;
- dst_row[j*cn + (blue_idx^2)] = r;
-
- if( cn == 4 )
- dst_row[j*cn + 3] = 65535;
- }
- }
- break;
- case CV_32F:
- {
- const float* src_row = (const float*)(src->data.ptr + i*src->step);
- float* dst_row = (float*)(dst->data.ptr + i*dst->step);
-
- for( j = 0; j < cols; j++ )
- {
- float b = src_row[j*3];
- float g = src_row[j*3 + 1];
- float r = src_row[j*3 + 2];
-
- dst_row[j*cn + blue_idx] = b;
- dst_row[j*cn + 1] = g;
- dst_row[j*cn + (blue_idx^2)] = r;
-
- if( cn == 4 )
- dst_row[j*cn + 3] = 1.f;
- }
- }
- break;
- default:
- assert(0);
- }
- }
-}
-
-
-CV_ColorRGBTest color_rgb_test;
-
-
-//// rgb <=> bayer
-
-static const char* cvtcolor_bayer_param_names[] = { "size", "depth", 0 };
-
-class CV_ColorBayerTest : public CV_ColorCvtBaseTest
-{
-public:
- CV_ColorBayerTest();
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void get_timing_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types,
- CvSize** whole_sizes, bool *are_images );
- double get_success_error_level( int test_case_idx, int i, int j );
- void run_func();
- void prepare_to_validation( int test_case_idx );
-};
-
-
-CV_ColorBayerTest::CV_ColorBayerTest()
- : CV_ColorCvtBaseTest( "color-bayer", "cvCvtColor", false, false, false )
-{
- test_array[OUTPUT].pop();
- test_array[REF_OUTPUT].pop();
-
- fwd_code_str = "BayerBG2BGR";
- inv_code_str = "";
- fwd_code = CV_BayerBG2BGR;
- inv_code = -1;
-
- default_timing_param_names = cvtcolor_bayer_param_names;
- depth_list = cvtcolor_depths_8;
-}
-
-
-void CV_ColorBayerTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- CV_ColorCvtBaseTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
-
- types[INPUT][0] = CV_8UC1;
- types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_8UC3;
- inplace = false;
-
- fwd_code = cvTsRandInt(rng)%4 + CV_BayerBG2BGR;
-}
-
-
-void CV_ColorBayerTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images )
-{
- CV_ColorCvtBaseTest::get_timing_test_array_types_and_sizes( test_case_idx, sizes, types,
- whole_sizes, are_images );
- types[INPUT][0] &= CV_MAT_DEPTH_MASK;
-}
-
-
-double CV_ColorBayerTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- return 1;
-}
-
-
-void CV_ColorBayerTest::run_func()
-{
- if(!test_cpp)
- cvCvtColor( test_array[INPUT][0], test_array[OUTPUT][0], fwd_code );
- else
- {
- cv::Mat _out = cv::cvarrToMat(test_array[OUTPUT][0]);
- cv::cvtColor(cv::cvarrToMat(test_array[INPUT][0]), _out, fwd_code, _out.channels());
- }
-}
-
-
-void CV_ColorBayerTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- const CvMat* src = &test_mat[INPUT][0];
- CvMat* dst = &test_mat[REF_OUTPUT][0];
- int i, j, cols = src->cols - 2;
- int code = fwd_code;
- int bi = 0;
- int step = src->step;
-
- if( fwd_code == CV_BayerRG2BGR || fwd_code == CV_BayerGR2BGR )
- bi ^= 2;
-
- for( i = 1; i < src->rows - 1; i++ )
- {
- const uchar* ptr = src->data.ptr + i*step + 1;
- uchar* dst_row = dst->data.ptr + i*dst->step + 3;
- int save_code = code;
- if( cols <= 0 )
- {
- dst_row[-3] = dst_row[-2] = dst_row[-1] = 0;
- dst_row[cols*3] = dst_row[cols*3+1] = dst_row[cols*3+2] = 0;
- continue;
- }
-
- for( j = 0; j < cols; j++ )
- {
- int b, g, r;
- if( !(code & 1) )
- {
- b = ptr[j];
- g = (ptr[j-1] + ptr[j+1] + ptr[j-step] + ptr[j+step])>>2;
- r = (ptr[j-step-1] + ptr[j-step+1] + ptr[j+step-1] + ptr[j+step+1]) >> 2;
- }
- else
- {
- b = (ptr[j-1] + ptr[j+1]) >> 1;
- g = ptr[j];
- r = (ptr[j-step] + ptr[j+step]) >> 1;
- }
- code ^= 1;
- dst_row[j*3 + bi] = (uchar)b;
- dst_row[j*3 + 1] = (uchar)g;
- dst_row[j*3 + (bi^2)] = (uchar)r;
- }
-
- dst_row[-3] = dst_row[0];
- dst_row[-2] = dst_row[1];
- dst_row[-1] = dst_row[2];
- dst_row[cols*3] = dst_row[cols*3-3];
- dst_row[cols*3+1] = dst_row[cols*3-2];
- dst_row[cols*3+2] = dst_row[cols*3-1];
-
- code = save_code ^ 1;
- bi ^= 2;
- }
-
- if( src->rows <= 2 )
- {
- memset( dst->data.ptr, 0, (cols+2)*3 );
- memset( dst->data.ptr + (dst->rows-1)*dst->step, 0, (cols+2)*3 );
- }
- else
- {
- uchar* top_row = dst->data.ptr;
- uchar* bottom_row = dst->data.ptr + dst->step*(dst->rows-1);
- int dstep = dst->step;
-
- for( j = 0; j < (cols+2)*3; j++ )
- {
- top_row[j] = top_row[j + dstep];
- bottom_row[j] = bottom_row[j - dstep];
- }
- }
-}
-
-CV_ColorBayerTest color_bayer_test;
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////\r
-//\r
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.\r
-//\r
-// By downloading, copying, installing or using the software you agree to this license.\r
-// If you do not agree to this license, do not download, install,\r
-// copy or use the software.\r
-//\r
-//\r
-// License Agreement\r
-// For Open Source Computer Vision Library\r
-//\r
-// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.\r
-// Copyright (C) 2009, Willow Garage Inc., all rights reserved.\r
-// Third party copyrights are property of their respective owners.\r
-//\r
-// Redistribution and use in source and binary forms, with or without modification,\r
-// are permitted provided that the following conditions are met:\r
-//\r
-// * Redistribution's of source code must retain the above copyright notice,\r
-// this list of conditions and the following disclaimer.\r
-//\r
-// * Redistribution's in binary form must reproduce the above copyright notice,\r
-// this list of conditions and the following disclaimer in the documentation\r
-// and/or other materials provided with the distribution.\r
-//\r
-// * The name of the copyright holders may not be used to endorse or promote products\r
-// derived from this software without specific prior written permission.\r
-//\r
-// This software is provided by the copyright holders and contributors "as is" and\r
-// any express or implied warranties, including, but not limited to, the implied\r
-// warranties of merchantability and fitness for a particular purpose are disclaimed.\r
-// In no event shall the Intel Corporation or contributors be liable for any direct,\r
-// indirect, incidental, special, exemplary, or consequential damages\r
-// (including, but not limited to, procurement of substitute goods or services;\r
-// loss of use, data, or profits; or business interruption) however caused\r
-// and on any theory of liability, whether in contract, strict liability,\r
-// or tort (including negligence or otherwise) arising in any way out of\r
-// the use of this software, even if advised of the possibility of such damage.\r
-//\r
-//M*/\r
-\r
-#include "cvtest.h"\r
-\r
-using namespace cv;\r
-using namespace std;\r
-\r
-\r
-class Differential\r
-{\r
-public: \r
- typedef Mat_<double> mat_t; \r
-\r
- Differential(double eps_, const mat_t& rv1_, const mat_t& tv1_, const mat_t& rv2_, const mat_t& tv2_) \r
- : rv1(rv1_), tv1(tv1_), rv2(rv2_), tv2(tv2_), eps(eps_), ev(3, 1) {}\r
-\r
- void dRv1(mat_t& dr3_dr1, mat_t& dt3_dr1)\r
- { \r
- dr3_dr1.create(3, 3); dt3_dr1.create(3, 3);\r
- \r
- for(int i = 0; i < 3; ++i) \r
- {\r
- ev.setTo(Scalar(0)); ev(i, 0) = eps; \r
- \r
- composeRT( rv1 + ev, tv1, rv2, tv2, rv3_p, tv3_p); \r
- composeRT( rv1 - ev, tv1, rv2, tv2, rv3_m, tv3_m);\r
-\r
- dr3_dr1.col(i) = rv3_p - rv3_m; \r
- dt3_dr1.col(i) = tv3_p - tv3_m; \r
- }\r
- dr3_dr1 /= 2 * eps; dt3_dr1 /= 2 * eps;\r
- }\r
-\r
- void dRv2(mat_t& dr3_dr2, mat_t& dt3_dr2)\r
- { \r
- dr3_dr2.create(3, 3); dt3_dr2.create(3, 3);\r
- \r
- for(int i = 0; i < 3; ++i) \r
- {\r
- ev.setTo(Scalar(0)); ev(i, 0) = eps; \r
- \r
- composeRT( rv1, tv1, rv2 + ev, tv2, rv3_p, tv3_p); \r
- composeRT( rv1, tv1, rv2 - ev, tv2, rv3_m, tv3_m);\r
-\r
- dr3_dr2.col(i) = rv3_p - rv3_m; \r
- dt3_dr2.col(i) = tv3_p - tv3_m; \r
- }\r
- dr3_dr2 /= 2 * eps; dt3_dr2 /= 2 * eps;\r
- }\r
-\r
- void dTv1(mat_t& drt3_dt1, mat_t& dt3_dt1)\r
- { \r
- drt3_dt1.create(3, 3); dt3_dt1.create(3, 3);\r
- \r
- for(int i = 0; i < 3; ++i) \r
- {\r
- ev.setTo(Scalar(0)); ev(i, 0) = eps; \r
- \r
- composeRT( rv1, tv1 + ev, rv2, tv2, rv3_p, tv3_p); \r
- composeRT( rv1, tv1 - ev, rv2, tv2, rv3_m, tv3_m);\r
-\r
- drt3_dt1.col(i) = rv3_p - rv3_m; \r
- dt3_dt1.col(i) = tv3_p - tv3_m; \r
- }\r
- drt3_dt1 /= 2 * eps; dt3_dt1 /= 2 * eps;\r
- }\r
-\r
- void dTv2(mat_t& dr3_dt2, mat_t& dt3_dt2)\r
- { \r
- dr3_dt2.create(3, 3); dt3_dt2.create(3, 3);\r
- \r
- for(int i = 0; i < 3; ++i) \r
- {\r
- ev.setTo(Scalar(0)); ev(i, 0) = eps; \r
- \r
- composeRT( rv1, tv1, rv2, tv2 + ev, rv3_p, tv3_p); \r
- composeRT( rv1, tv1, rv2, tv2 - ev, rv3_m, tv3_m);\r
-\r
- dr3_dt2.col(i) = rv3_p - rv3_m; \r
- dt3_dt2.col(i) = tv3_p - tv3_m; \r
- }\r
- dr3_dt2 /= 2 * eps; dt3_dt2 /= 2 * eps;\r
- }\r
- \r
-private:\r
- const mat_t& rv1, tv1, rv2, tv2;\r
- double eps;\r
- Mat_<double> ev;\r
- \r
- Differential& operator=(const Differential&);\r
- Mat rv3_m, tv3_m, rv3_p, tv3_p; \r
-};\r
-\r
-class CV_composeRT_Test : public CvTest\r
-{\r
-public:\r
- CV_composeRT_Test()\r
- : CvTest( "composeRT", "cvComposeRT")\r
- {\r
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE; \r
- }\r
- ~CV_composeRT_Test() {}\r
-protected: \r
- \r
- void run(int)\r
- {\r
- CvTS& ts = *this->ts;\r
- ts.set_failed_test_info(CvTS::OK);\r
- \r
- Mat_<double> rvec1(3, 1), tvec1(3, 1), rvec2(3, 1), tvec2(3, 1); \r
-\r
- randu(rvec1, Scalar(0), Scalar(6.29));\r
- randu(rvec2, Scalar(0), Scalar(6.29));\r
-\r
- randu(tvec1, Scalar(-2), Scalar(2));\r
- randu(tvec2, Scalar(-2), Scalar(2));\r
- \r
- Mat rvec3, tvec3;\r
- composeRT(rvec1, tvec1, rvec2, tvec2, rvec3, tvec3);\r
- \r
- Mat rvec3_exp, tvec3_exp;\r
-\r
- Mat rmat1, rmat2;\r
- Rodrigues(rvec1, rmat1);\r
- Rodrigues(rvec2, rmat2);\r
- Rodrigues(rmat2 * rmat1, rvec3_exp);\r
-\r
- tvec3_exp = rmat2 * tvec1 + tvec2;\r
-\r
- const double thres = 1e-5;\r
- if (norm(rvec3_exp, rvec3) > thres || norm(tvec3_exp, tvec3) > thres)\r
- ts.set_failed_test_info(CvTS::FAIL_BAD_ACCURACY);\r
-\r
- const double eps = 1e-3;\r
- Differential diff(eps, rvec1, tvec1, rvec2, tvec2);\r
- \r
- Mat dr3dr1, dr3dt1, dr3dr2, dr3dt2, dt3dr1, dt3dt1, dt3dr2, dt3dt2;\r
-\r
- composeRT(rvec1, tvec1, rvec2, tvec2, rvec3, tvec3, \r
- dr3dr1, dr3dt1, dr3dr2, dr3dt2, dt3dr1, dt3dt1, dt3dr2, dt3dt2);\r
- \r
- Mat_<double> dr3_dr1, dt3_dr1;\r
- diff.dRv1(dr3_dr1, dt3_dr1);\r
-\r
- if (norm(dr3_dr1, dr3dr1) > thres || norm(dt3_dr1, dt3dr1) > thres)\r
- { \r
- ts.printf( CvTS::LOG, "Invalid derivates by r1\n" );\r
- ts.set_failed_test_info(CvTS::FAIL_BAD_ACCURACY);\r
- }\r
-\r
- Mat_<double> dr3_dr2, dt3_dr2;\r
- diff.dRv2(dr3_dr2, dt3_dr2);\r
-\r
- if (norm(dr3_dr2, dr3dr2) > thres || norm(dt3_dr2, dt3dr2) > thres)\r
- { \r
- ts.printf( CvTS::LOG, "Invalid derivates by r2\n" );\r
- ts.set_failed_test_info(CvTS::FAIL_BAD_ACCURACY);\r
- }\r
-\r
- Mat_<double> dr3_dt1, dt3_dt1;\r
- diff.dTv1(dr3_dt1, dt3_dt1);\r
-\r
- if (norm(dr3_dt1, dr3dt1) > thres || norm(dt3_dt1, dt3dt1) > thres)\r
- { \r
- ts.printf( CvTS::LOG, "Invalid derivates by t1\n" );\r
- ts.set_failed_test_info(CvTS::FAIL_BAD_ACCURACY);\r
- }\r
- \r
- Mat_<double> dr3_dt2, dt3_dt2;\r
- diff.dTv2(dr3_dt2, dt3_dt2);\r
-\r
- if (norm(dr3_dt2, dr3dt2) > thres || norm(dt3_dt2, dt3dt2) > thres)\r
- { \r
- ts.printf( CvTS::LOG, "Invalid derivates by t2\n" );\r
- ts.set_failed_test_info(CvTS::FAIL_BAD_ACCURACY);\r
- }\r
- } \r
-}; \r
- \r
-CV_composeRT_Test composeRT_test;\r
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-#if 0
-
-/* Testing parameters */
-static char TestName[] = "State estimation of linear system by means of ConDens Algorithm";
-static char TestClass[] = "Algorithm";
-static int Dim;
-static int Steps;
-static int SamplesNum;
-
-static int read_param = 0;
-static double EPSILON = 1.000;
-
-static void CondProbDens(CvConDensation* CD, float* Measurement)
-{
- float Prob = 1;
- for(int i = 0; i < CD->SamplesNum;i++)
- {
-
- Prob =1;
- for(int j =0; j < CD->DP;j++)
- {
- Prob*=(float)exp(-0.05*(Measurement[j] - CD->flSamples[i][j])*(Measurement[j]-CD->flSamples[i][j]));
- }
-
- CD->flConfidence[i] = Prob;
- }
-
-}
-static int fcaConDens( void )
-{
- AtsRandState noisegen;
- AtsRandState dynam;
- double Error = 0;
- CvConDensation* ConDens;
-
- /* Initialization global parameters */
- if( !read_param )
- {
- read_param = 1;
- /* Reading test-parameters */
- trsiRead( &Dim,"7","Dimension of dynamical system");
- trsiRead( &Steps,"100","Length of trajectory to track");
- trsiRead( &SamplesNum,"64","Length of trajectory to track");
- }
- CvMat Sample = cvMat(Dim,1,CV_MAT32F,NULL);
- CvMat Temp = cvMat(Dim,1,CV_MAT32F,NULL);
- CvMat LB = cvMat(Dim,1,CV_MAT32F,NULL);
- CvMat UB = cvMat(Dim,1,CV_MAT32F,NULL);
- cvmAlloc(&LB);
- cvmAlloc(&UB);
- cvmAlloc(&Sample);
- cvmAlloc(&Temp);
- ConDens = cvCreateConDensation(Dim, Dim,SamplesNum);
- CvMat Dyn = cvMat(Dim,Dim,CV_MAT32F,ConDens->DynamMatr);
- atsRandInit(&dynam,-1.0, 1.0, 1);
- atsRandInit(&noisegen,-0.1, 0.1, 2);
- cvmSetIdentity(&Dyn);
- atsbRand32f(&dynam,Sample.data.fl,Dim);
- int i;
- for(i = 0; i<Dim; i++)
- {
- LB.data.fl[i] = -1.0f;
- UB.data.fl[i] = 1.0f;
- }
- cvConDensInitSampleSet(ConDens,&LB,&UB);
- CondProbDens(ConDens,Sample.data.fl);
- for( i = 0; i<Steps; i++)
- {
- cvConDensUpdateByTime(ConDens);
- int j;
- for(j = 0; j<Dim; j++)
- {
- float t = 0;
- for(int k=0; k<Dim; k++)
- {
- t += Dyn.data.fl[j*Dim+k]*Sample.data.fl[k];
- }
- Temp.data.fl[j]= t+atsRand32f(&noisegen);
- }
-
- for(j = 0; j<Dim; j++)
- {
- Sample.data.fl[j] = Temp.data.fl[j];
- }
- CondProbDens(ConDens,Temp.data.fl);
- }
- Error = atsCompSinglePrec(Sample.data.fl,ConDens->State,Dim,EPSILON);
- cvmFree(&Sample);
- cvmFree(&Temp);
- cvmFree(&LB);
- cvmFree(&UB);
- cvReleaseConDensation(&ConDens);
- if(Error>=EPSILON)return TRS_FAIL;
- return TRS_OK;
-} /* fcaSobel8uC1R */
-void InitAConDens(void)
-{
- trsReg( "Condensation Algorithm", TestName, TestClass, fcaConDens);
-
-} /* InitASobel */
-
-/* End of file. */
-
-#endif
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-
-/* End of file. */
-
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-class CV_FindContourTest : public CvTest
-{
-public:
- enum { NUM_IMG = 4 };
-
- CV_FindContourTest();
- ~CV_FindContourTest();
- int write_default_params(CvFileStorage* fs);
- void clear();
-
-protected:
- int read_params( CvFileStorage* fs );
- int prepare_test_case( int test_case_idx );
- int validate_test_results( int test_case_idx );
- void run_func();
-
- int min_blob_size, max_blob_size;
- int blob_count, max_log_blob_count;
- int retr_mode, approx_method;
-
- int min_log_img_size, max_log_img_size;
- CvSize img_size;
- int count, count2;
-
- IplImage* img[NUM_IMG];
- CvMemStorage* storage;
- CvSeq *contours, *contours2, *chain;
-};
-
-
-CV_FindContourTest::CV_FindContourTest() :
- CvTest( "contour-find", "cvFindContours, cvDrawContours, cvApproxChains" )
-{
- int i;
-
- test_case_count = 300;
- min_blob_size = 1;
- max_blob_size = 50;
- max_log_blob_count = 10;
-
- min_log_img_size = 3;
- max_log_img_size = 10;
-
- for( i = 0; i < NUM_IMG; i++ )
- img[i] = 0;
-
- storage = 0;
-}
-
-
-CV_FindContourTest::~CV_FindContourTest()
-{
- clear();
-}
-
-
-void CV_FindContourTest::clear()
-{
- int i;
-
- CvTest::clear();
-
- for( i = 0; i < NUM_IMG; i++ )
- cvReleaseImage( &img[i] );
-
- cvReleaseMemStorage( &storage );
-}
-
-
-int CV_FindContourTest::write_default_params( CvFileStorage* fs )
-{
- CvTest::write_default_params( fs );
- if( ts->get_testing_mode() != CvTS::TIMING_MODE )
- {
- write_param( fs, "test_case_count", test_case_count );
- write_param( fs, "min_blob_size", min_blob_size );
- write_param( fs, "max_blob_size", max_blob_size );
- write_param( fs, "max_log_blob_count", max_log_blob_count );
- write_param( fs, "min_log_img_size", min_log_img_size );
- write_param( fs, "max_log_img_size", max_log_img_size );
- }
- return 0;
-}
-
-
-int CV_FindContourTest::read_params( CvFileStorage* fs )
-{
- int t;
- int code = CvTest::read_params( fs );
-
- if( code < 0 )
- return code;
-
- min_blob_size = cvReadInt( find_param( fs, "min_blob_size" ), min_blob_size );
- max_blob_size = cvReadInt( find_param( fs, "max_blob_size" ), max_blob_size );
- max_log_blob_count = cvReadInt( find_param( fs, "max_log_blob_count" ), max_log_blob_count );
- min_log_img_size = cvReadInt( find_param( fs, "min_log_img_size" ), min_log_img_size );
- max_log_img_size = cvReadInt( find_param( fs, "max_log_img_size" ), max_log_img_size );
-
- min_blob_size = cvTsClipInt( min_blob_size, 1, 100 );
- max_blob_size = cvTsClipInt( max_blob_size, 1, 100 );
-
- if( min_blob_size > max_blob_size )
- CV_SWAP( min_blob_size, max_blob_size, t );
-
- max_log_blob_count = cvTsClipInt( max_log_blob_count, 1, 10 );
-
- min_log_img_size = cvTsClipInt( min_log_img_size, 1, 10 );
- max_log_img_size = cvTsClipInt( max_log_img_size, 1, 10 );
-
- if( min_log_img_size > max_log_img_size )
- CV_SWAP( min_log_img_size, max_log_img_size, t );
-
- return 0;
-}
-
-
-static void
-cvTsGenerateBlobImage( IplImage* img, int min_blob_size, int max_blob_size,
- int blob_count, int min_brightness, int max_brightness,
- CvRNG* rng )
-{
- int i;
- CvSize size;
-
- assert( img->depth == IPL_DEPTH_8U && img->nChannels == 1 );
-
- cvZero( img );
-
- // keep the border clear
- cvSetImageROI( img, cvRect(1,1,img->width-2,img->height-2) );
- size = cvGetSize( img );
-
- for( i = 0; i < blob_count; i++ )
- {
- CvPoint center;
- CvSize axes;
- int angle = cvTsRandInt(rng) % 180;
- int brightness = cvTsRandInt(rng) %
- (max_brightness - min_brightness) + min_brightness;
- center.x = cvTsRandInt(rng) % size.width;
- center.y = cvTsRandInt(rng) % size.height;
-
- axes.width = (cvTsRandInt(rng) %
- (max_blob_size - min_blob_size) + min_blob_size + 1)/2;
- axes.height = (cvTsRandInt(rng) %
- (max_blob_size - min_blob_size) + min_blob_size + 1)/2;
-
- cvEllipse( img, center, axes, angle, 0, 360, cvScalar(brightness), CV_FILLED );
- }
-
- cvResetImageROI( img );
-}
-
-
-static void
-cvTsMarkContours( IplImage* img, int val )
-{
- int i, j;
- int step = img->widthStep;
-
- assert( img->depth == IPL_DEPTH_8U && img->nChannels == 1 && (val&1) != 0);
-
- for( i = 1; i < img->height - 1; i++ )
- for( j = 1; j < img->width - 1; j++ )
- {
- uchar* t = (uchar*)(img->imageData + img->widthStep*i + j);
- if( *t == 1 && (t[-step] == 0 || t[-1] == 0 || t[1] == 0 || t[step] == 0))
- *t = (uchar)val;
- }
-
- cvThreshold( img, img, val - 2, val, CV_THRESH_BINARY );
-}
-
-
-int CV_FindContourTest::prepare_test_case( int test_case_idx )
-{
- CvRNG* rng = ts->get_rng();
- const int min_brightness = 0, max_brightness = 2;
- int i, code = CvTest::prepare_test_case( test_case_idx );
-
- if( code < 0 )
- return code;
-
- clear();
-
- blob_count = cvRound(exp(cvTsRandReal(rng)*max_log_blob_count*CV_LOG2));
-
- img_size.width = cvRound(exp((cvTsRandReal(rng)*
- (max_log_img_size - min_log_img_size) + min_log_img_size)*CV_LOG2));
- img_size.height = cvRound(exp((cvTsRandReal(rng)*
- (max_log_img_size - min_log_img_size) + min_log_img_size)*CV_LOG2));
-
- approx_method = cvTsRandInt( rng ) % 4 + 1;
- retr_mode = cvTsRandInt( rng ) % 4;
-
- storage = cvCreateMemStorage( 1 << 10 );
-
- for( i = 0; i < NUM_IMG; i++ )
- img[i] = cvCreateImage( img_size, 8, 1 );
-
- cvTsGenerateBlobImage( img[0], min_blob_size, max_blob_size,
- blob_count, min_brightness, max_brightness, rng );
-
- cvCopy( img[0], img[1] );
- cvCopy( img[0], img[2] );
-
- cvTsMarkContours( img[1], 255 );
-
- return 1;
-}
-
-
-void CV_FindContourTest::run_func()
-{
- contours = contours2 = chain = 0;
- count = cvFindContours( img[2], storage, &contours, sizeof(CvContour), retr_mode, approx_method );
-
- cvZero( img[3] );
-
- if( contours && retr_mode != CV_RETR_EXTERNAL && approx_method < CV_CHAIN_APPROX_TC89_L1 )
- cvDrawContours( img[3], contours, cvScalar(255), cvScalar(255), INT_MAX, -1 );
-
- cvCopy( img[0], img[2] );
-
- count2 = cvFindContours( img[2], storage, &chain, sizeof(CvChain), retr_mode, CV_CHAIN_CODE );
-
- if( chain )
- contours2 = cvApproxChains( chain, storage, approx_method, 0, 0, 1 );
-
- cvZero( img[2] );
-
- if( contours && retr_mode != CV_RETR_EXTERNAL && approx_method < CV_CHAIN_APPROX_TC89_L1 )
- cvDrawContours( img[2], contours2, cvScalar(255), cvScalar(255), INT_MAX );
-}
-
-
-// the whole testing is done here, run_func() is not utilized in this test
-int CV_FindContourTest::validate_test_results( int /*test_case_idx*/ )
-{
- int i, code = CvTS::OK;
-
- cvCmpS( img[0], 0, img[0], CV_CMP_GT );
-
- if( count != count2 )
- {
- ts->printf( CvTS::LOG, "The number of contours retrieved with different "
- "approximation methods is not the same\n"
- "(%d contour(s) for method %d vs %d contour(s) for method %d)\n",
- count, approx_method, count2, CV_CHAIN_CODE );
- code = CvTS::FAIL_INVALID_OUTPUT;
- }
-
- if( retr_mode != CV_RETR_EXTERNAL && approx_method < CV_CHAIN_APPROX_TC89_L1 )
- {
- code = cvTsCmpEps2( ts, img[0], img[3], 0, true,
- "Comparing original image with the map of filled contours" );
-
- if( code < 0 )
- goto _exit_;
-
- code = cvTsCmpEps2( ts, img[1], img[2], 0, true,
- "Comparing contour outline vs manually produced edge map" );
-
- if( code < 0 )
- goto _exit_;
- }
-
- if( contours )
- {
- CvTreeNodeIterator iterator1;
- CvTreeNodeIterator iterator2;
- int count3;
-
- for( i = 0; i < 2; i++ )
- {
- CvTreeNodeIterator iterator;
- cvInitTreeNodeIterator( &iterator, i == 0 ? contours : contours2, INT_MAX );
-
- for( count3 = 0; cvNextTreeNode( &iterator ) != 0; count3++ )
- ;
-
- if( count3 != count )
- {
- ts->printf( CvTS::LOG,
- "The returned number of retrieved contours (using the approx_method = %d) does not match\n"
- "to the actual number of contours in the tree/list (returned %d, actual %d)\n",
- i == 0 ? approx_method : 0, count, count3 );
- code = CvTS::FAIL_INVALID_OUTPUT;
- goto _exit_;
- }
- }
-
- cvInitTreeNodeIterator( &iterator1, contours, INT_MAX );
- cvInitTreeNodeIterator( &iterator2, contours2, INT_MAX );
-
- for( count3 = 0; count3 < count; count3++ )
- {
- CvSeq* seq1 = (CvSeq*)cvNextTreeNode( &iterator1 );
- CvSeq* seq2 = (CvSeq*)cvNextTreeNode( &iterator2 );
- CvSeqReader reader1;
- CvSeqReader reader2;
-
- if( !seq1 || !seq2 )
- {
- ts->printf( CvTS::LOG,
- "There are NULL pointers in the original contour tree or the "
- "tree produced by cvApproxChains\n" );
- code = CvTS::FAIL_INVALID_OUTPUT;
- goto _exit_;
- }
-
- cvStartReadSeq( seq1, &reader1 );
- cvStartReadSeq( seq2, &reader2 );
-
- if( seq1->total != seq2->total )
- {
- ts->printf( CvTS::LOG,
- "The original contour #%d has %d points, while the corresponding contour has %d point\n",
- count3, seq1->total, seq2->total );
- code = CvTS::FAIL_INVALID_OUTPUT;
- goto _exit_;
- }
-
- for( i = 0; i < seq1->total; i++ )
- {
- CvPoint pt1;
- CvPoint pt2;
-
- CV_READ_SEQ_ELEM( pt1, reader1 );
- CV_READ_SEQ_ELEM( pt2, reader2 );
-
- if( pt1.x != pt2.x || pt1.y != pt2.y )
- {
- ts->printf( CvTS::LOG,
- "The point #%d in the contour #%d is different from the corresponding point "
- "in the approximated chain ((%d,%d) vs (%d,%d)", count3, i, pt1.x, pt1.y, pt2.x, pt2.y );
- code = CvTS::FAIL_INVALID_OUTPUT;
- goto _exit_;
- }
- }
- }
- }
-
-_exit_:
- if( code < 0 )
- {
-#if 0
- cvNamedWindow( "test", 0 );
- cvShowImage( "test", img[0] );
- cvWaitKey();
-#endif
- ts->set_failed_test_info( code );
- }
-
- return code;
-}
-
-
-CV_FindContourTest find_contour_test;
-
-/* End of file. */
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-#if 0
-/*#include "conio.h"*/
-
-static char cTestName[] = "Matching Contours";
-static char cTestClass[] = "Algorithm";
-static char cFuncName[] = "cvMatchContours";
-
-static int aMatchContours(void)
-{
- CvSeqBlock contour_blk1, contour_blk2;
- CvContour contour_h1, contour_h2;
- CvContoursMatchMethod method;
- int nPoints1 = 20, nPoints2 = 20;
- int xc,yc,a1 = 10, b1 = 20, a2 = 15, b2 =30, fi = 0;
- int xmin,ymin,xmax,ymax;
- int seq_type;
- double error_test,rezult, eps_rez = 0.1;
- double pi = 3.1415926;
- int i;
- int code = TRS_OK;
-
- int width=256,height=256;
- CvPoint *cp1,*cp2;
-
-/* read tests params */
-
- if (!trsiRead(&nPoints1,"20","Number of points first contour"))
- return TRS_UNDEF;
- if (!trsiRead(&nPoints2,"20","Number of points second contour"))
- return TRS_UNDEF;
-
- if(nPoints1>0&&nPoints2>0)
- {
- if (!trsiRead(&a1,"10","first radius of the first elipse"))
- return TRS_UNDEF;
- if (!trsiRead(&b1,"20","second radius of the first elipse"))
- return TRS_UNDEF;
- if (!trsiRead(&a2,"15","first radius of the second elipse"))
- return TRS_UNDEF;
- if (!trsiRead(&b2,"30","second radius of the second elipse"))
- return TRS_UNDEF;
- if (!trsiRead(&fi,"0","second radius of the second elipse"))
- return TRS_UNDEF;
-
- xc = (int)(width/2.);
- yc = (int)(height/2.);
- xmin = width;
- ymin = height;
- xmax = 0;
- ymax = 0;
-
- cp1 = (CvPoint*) trsmAlloc(nPoints1*sizeof(CvPoint));
- cp2 = (CvPoint*) trsmAlloc(nPoints2*sizeof(CvPoint));
-
- for(i=0;i<nPoints1;i++)
- {
- cp1[i].x = (int)(a1*cos(2*pi*i/nPoints1))+xc;
- cp1[i].y = (int)(b1*sin(2*pi*i/nPoints1))+yc;
- if(xmin> cp1[i].x) xmin = cp1[i].x;
- if(xmax< cp1[i].x) xmax = cp1[i].x;
- if(ymin> cp1[i].y) ymin = cp1[i].y;
- if(ymax< cp1[i].y) ymax = cp1[i].y;
- }
-
- if(xmax>width||xmin<0||ymax>height||ymin<0) return TRS_FAIL;
-
- for(i=0;i<nPoints2;i++)
- {
- cp2[i].x = (int)(a2*cos(2*pi*i/nPoints2)*cos(2*pi*fi/360.))-
- (int)(b2*sin(2*pi*i/nPoints2)*sin(2*pi*fi/360.))+xc;
-
- cp2[i].y = (int)(a2*cos(2*pi*i/nPoints2)*sin(2*pi*fi/360.))+
- (int)(b2*sin(2*pi*i/nPoints2)*cos(2*pi*fi/360.))+yc;
-
- if(xmin> cp2[i].x) xmin = cp2[i].x;
- if(xmax< cp2[i].x) xmax = cp2[i].x;
- if(ymin> cp2[i].y) ymin = cp2[i].y;
- if(ymax< cp2[i].y) ymax = cp2[i].y;
- }
- if(xmax>width||xmin<0||ymax>height||ymin<0) return TRS_FAIL;
-
-/* contours initialazing */
- seq_type = CV_SEQ_POLYGON;
- cvMakeSeqHeaderForArray( seq_type, sizeof(CvContour), sizeof(CvPoint),
- (char*)cp1, nPoints1, (CvSeq*)&contour_h1, &contour_blk1);
-
- cvMakeSeqHeaderForArray( seq_type, sizeof(CvContour), sizeof(CvPoint),
- (char*)cp2, nPoints2, (CvSeq*)&contour_h2, &contour_blk2);
-
-/* countours matchig */
- error_test = 0.;
-
- for (i=1;i<=3;i++)
- {
- method = (CvContoursMatchMethod)i;
- rezult = cvMatchContours((CvSeq*)&contour_h1, (CvSeq*)&contour_h2, method);
-
- error_test+=rezult;
- }
- error_test = error_test/3.;
-
- if(error_test > eps_rez) code = TRS_FAIL;
- else code = TRS_OK;
-
- trsWrite( ATS_CON | ATS_LST | ATS_SUM, "contours matching error_test =%f \n",
- error_test);
-
- trsFree (cp2);
- trsFree (cp1);
- }
-
-
-/* _getch(); */
- return code;
-}
-
-void InitAMatchContours( void )
-{
-/* Test Registartion */
- trsReg(cFuncName,cTestName,cTestClass,aMatchContours);
-
-} /* InitAMatchContours */
-
-/* End of file. */
-
-#endif
-
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-/*static int
-cvTsPointConvexPolygon( CvPoint2D32f pt, CvPoint2D32f* v, int n )
-{
- CvPoint2D32f v0 = v[n-1];
- int i, sign = 0;
-
- for( i = 0; i < n; i++ )
- {
- CvPoint2D32f v1 = v[i];
- float dx = pt.x - v0.x, dy = pt.y - v0.y;
- float dx1 = v1.x - v0.x, dy1 = v1.y - v0.y;
- double t = (double)dx*dy1 - (double)dx1*dy;
- if( fabs(t) > DBL_EPSILON )
- {
- if( t*sign < 0 )
- break;
- if( sign == 0 )
- sign = t < 0 ? -1 : 1;
- }
- else if( fabs(dx) + fabs(dy) < DBL_EPSILON )
- return i+1;
- v0 = v1;
- }
-
- return i < n ? -1 : 0;
-}*/
-
-CV_INLINE double
-cvTsDist( CvPoint2D32f a, CvPoint2D32f b )
-{
- double dx = a.x - b.x;
- double dy = a.y - b.y;
- return sqrt(dx*dx + dy*dy);
-}
-
-CV_INLINE double
-cvTsPtLineDist( CvPoint2D32f pt, CvPoint2D32f a, CvPoint2D32f b )
-{
- double d0 = cvTsDist( pt, a ), d1;
- double dd = cvTsDist( a, b );
- if( dd < FLT_EPSILON )
- return d0;
- d1 = cvTsDist( pt, b );
- dd = fabs((double)(pt.x - a.x)*(b.y - a.y) - (double)(pt.y - a.y)*(b.x - a.x))/dd;
- d0 = MIN( d0, d1 );
- return MIN( d0, dd );
-}
-
-static double
-cvTsPointPolygonTest( CvPoint2D32f pt, const CvPoint2D32f* vv, int n, int* _idx=0, int* _on_edge=0 )
-{
- int i;
- CvPoint2D32f v = vv[n-1], v0;
- double min_dist_num = FLT_MAX, min_dist_denom = 1;
- int min_dist_idx = -1, min_on_edge = 0;
- int counter = 0;
- double result;
-
- for( i = 0; i < n; i++ )
- {
- double dx, dy, dx1, dy1, dx2, dy2, dist_num, dist_denom = 1;
- int on_edge = 0, idx = i;
-
- v0 = v; v = vv[i];
- dx = v.x - v0.x; dy = v.y - v0.y;
- dx1 = pt.x - v0.x; dy1 = pt.y - v0.y;
- dx2 = pt.x - v.x; dy2 = pt.y - v.y;
-
- if( dx2*dx + dy2*dy >= 0 )
- dist_num = dx2*dx2 + dy2*dy2;
- else if( dx1*dx + dy1*dy <= 0 )
- {
- dist_num = dx1*dx1 + dy1*dy1;
- idx = i - 1;
- if( idx < 0 ) idx = n-1;
- }
- else
- {
- dist_num = (dy1*dx - dx1*dy);
- dist_num *= dist_num;
- dist_denom = dx*dx + dy*dy;
- on_edge = 1;
- }
-
- if( dist_num*min_dist_denom < min_dist_num*dist_denom )
- {
- min_dist_num = dist_num;
- min_dist_denom = dist_denom;
- min_dist_idx = idx;
- min_on_edge = on_edge;
- if( min_dist_num == 0 )
- break;
- }
-
- if( (v0.y <= pt.y && v.y <= pt.y) ||
- (v0.y > pt.y && v.y > pt.y) ||
- (v0.x < pt.x && v.x < pt.x) )
- continue;
-
- dist_num = dy1*dx - dx1*dy;
- if( dy < 0 )
- dist_num = -dist_num;
- counter += dist_num > 0;
- }
-
- result = sqrt(min_dist_num/min_dist_denom);
- if( counter % 2 == 0 )
- result = -result;
-
- if( _idx )
- *_idx = min_dist_idx;
- if( _on_edge )
- *_on_edge = min_on_edge;
-
- return result;
-}
-
-
-/****************************************************************************************\
-* Base class for shape descriptor tests *
-\****************************************************************************************/
-
-class CV_BaseShapeDescrTest : public CvTest
-{
-public:
- CV_BaseShapeDescrTest( const char* test_name, const char* test_funcs );
- virtual ~CV_BaseShapeDescrTest();
- void clear();
- int write_default_params(CvFileStorage* fs);
-
-protected:
- int read_params( CvFileStorage* fs );
- void run_func(void);
- int prepare_test_case( int test_case_idx );
- int validate_test_results( int test_case_idx );
- virtual void generate_point_set( void* points );
- virtual void extract_points();
-
- int min_log_size;
- int max_log_size;
- int dims;
- bool enable_flt_points;
-
- CvMemStorage* storage;
- CvSeq* points1;
- CvMat* points2;
- void* points;
- void* result;
- double low_high_range;
- CvScalar low, high;
-
- bool test_cpp;
-};
-
-
-CV_BaseShapeDescrTest::CV_BaseShapeDescrTest( const char* test_name, const char* test_funcs ):
- CvTest( test_name, test_funcs )
-{
- points1 = 0;
- points2 = 0;
- points = 0;
- storage = 0;
- test_case_count = 500;
- min_log_size = 0;
- max_log_size = 10;
- low = high = cvScalarAll(0);
- low_high_range = 50;
- dims = 2;
- enable_flt_points = true;
-
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;
-
- test_cpp = false;
-}
-
-
-CV_BaseShapeDescrTest::~CV_BaseShapeDescrTest()
-{
- clear();
-}
-
-
-void CV_BaseShapeDescrTest::clear()
-{
- CvTest::clear();
- cvReleaseMemStorage( &storage );
- cvReleaseMat( &points2 );
- points1 = 0;
- points = 0;
-}
-
-
-int CV_BaseShapeDescrTest::write_default_params( CvFileStorage* fs )
-{
- CvTest::write_default_params( fs );
- if( ts->get_testing_mode() != CvTS::TIMING_MODE )
- {
- write_param( fs, "test_case_count", test_case_count );
- write_param( fs, "min_log_size", min_log_size );
- write_param( fs, "max_log_size", max_log_size );
- }
- return 0;
-}
-
-
-int CV_BaseShapeDescrTest::read_params( CvFileStorage* fs )
-{
- int code = CvTest::read_params( fs );
- if( code < 0 )
- return code;
-
- test_case_count = cvReadInt( find_param( fs, "struct_count" ), test_case_count );
- min_log_size = cvReadInt( find_param( fs, "min_log_size" ), min_log_size );
- max_log_size = cvReadInt( find_param( fs, "max_log_size" ), max_log_size );
-
- min_log_size = cvTsClipInt( min_log_size, 0, 8 );
- max_log_size = cvTsClipInt( max_log_size, 0, 10 );
- if( min_log_size > max_log_size )
- {
- int t;
- CV_SWAP( min_log_size, max_log_size, t );
- }
-
- return 0;
-}
-
-
-void CV_BaseShapeDescrTest::generate_point_set( void* points )
-{
- CvRNG* rng = ts->get_rng();
- int i, k, n, total, point_type;
- CvSeqReader reader;
- uchar* data = 0;
- double a[4], b[4];
-
- for( k = 0; k < 4; k++ )
- {
- a[k] = high.val[k] - low.val[k];
- b[k] = low.val[k];
- }
- memset( &reader, 0, sizeof(reader) );
-
- if( CV_IS_SEQ(points) )
- {
- CvSeq* ptseq = (CvSeq*)points;
- total = ptseq->total;
- point_type = CV_SEQ_ELTYPE(ptseq);
- cvStartReadSeq( ptseq, &reader );
- }
- else
- {
- CvMat* ptm = (CvMat*)points;
- assert( CV_IS_MAT(ptm) && CV_IS_MAT_CONT(ptm->type) );
- total = ptm->rows + ptm->cols - 1;
- point_type = CV_MAT_TYPE(ptm->type);
- data = ptm->data.ptr;
- }
-
- n = CV_MAT_CN(point_type);
- point_type = CV_MAT_DEPTH(point_type);
-
- assert( (point_type == CV_32S || point_type == CV_32F) && n <= 4 );
-
- for( i = 0; i < total; i++ )
- {
- int* pi;
- float* pf;
- if( reader.ptr )
- {
- pi = (int*)reader.ptr;
- pf = (float*)reader.ptr;
- CV_NEXT_SEQ_ELEM( reader.seq->elem_size, reader );
- }
- else
- {
- pi = (int*)data + i*n;
- pf = (float*)data + i*n;
- }
- if( point_type == CV_32S )
- for( k = 0; k < n; k++ )
- pi[k] = cvRound(cvTsRandReal(rng)*a[k] + b[k]);
- else
- for( k = 0; k < n; k++ )
- pf[k] = (float)(cvTsRandReal(rng)*a[k] + b[k]);
- }
-}
-
-
-int CV_BaseShapeDescrTest::prepare_test_case( int test_case_idx )
-{
- int size;
- int use_storage = 0;
- int point_type;
- int i;
- CvRNG* rng = ts->get_rng();
-
- CvTest::prepare_test_case( test_case_idx );
-
- clear();
- size = cvRound( exp((cvTsRandReal(rng) * (max_log_size - min_log_size) + min_log_size)*CV_LOG2) );
- use_storage = cvTsRandInt(rng) % 2;
- point_type = CV_MAKETYPE(cvTsRandInt(rng) %
- (enable_flt_points ? 2 : 1) ? CV_32F : CV_32S, dims);
-
- if( use_storage )
- {
- storage = cvCreateMemStorage( (cvTsRandInt(rng)%10 + 1)*1024 );
- points1 = cvCreateSeq( point_type, sizeof(CvSeq), CV_ELEM_SIZE(point_type), storage );
- cvSeqPushMulti( points1, 0, size );
- points = points1;
- }
- else
- {
- int rows = 1, cols = size;
- if( cvTsRandInt(rng) % 2 )
- rows = size, cols = 1;
-
- points2 = cvCreateMat( rows, cols, point_type );
- points = points2;
- }
-
- for( i = 0; i < 4; i++ )
- {
- low.val[i] = (cvTsRandReal(rng)-0.5)*low_high_range*2;
- high.val[i] = (cvTsRandReal(rng)-0.5)*low_high_range*2;
- if( low.val[i] > high.val[i] )
- {
- double t;
- CV_SWAP( low.val[i], high.val[i], t );
- }
- if( high.val[i] < low.val[i] + 1 )
- high.val[i] += 1;
- }
-
- generate_point_set( points );
-
- test_cpp = (cvTsRandInt(rng) & 16) == 0;
- return 1;
-}
-
-
-void CV_BaseShapeDescrTest::extract_points()
-{
- if( points1 )
- {
- points2 = cvCreateMat( 1, points1->total, CV_SEQ_ELTYPE(points1) );
- cvCvtSeqToArray( points1, points2->data.ptr );
- }
-
- if( CV_MAT_DEPTH(points2->type) != CV_32F && enable_flt_points )
- {
- CvMat tmp = cvMat( points2->rows, points2->cols,
- (points2->type & ~CV_MAT_DEPTH_MASK) | CV_32F, points2->data.ptr );
- cvConvert( points2, &tmp );
- }
-}
-
-
-void CV_BaseShapeDescrTest::run_func(void)
-{
-}
-
-
-int CV_BaseShapeDescrTest::validate_test_results( int /*test_case_idx*/ )
-{
- extract_points();
- return 0;
-}
-
-
-CV_BaseShapeDescrTest shape_basetest( "shape", "" );
-
-
-/****************************************************************************************\
-* Convex Hull Test *
-\****************************************************************************************/
-
-class CV_ConvHullTest : public CV_BaseShapeDescrTest
-{
-public:
- CV_ConvHullTest();
- virtual ~CV_ConvHullTest();
- void clear();
-
-protected:
- void run_func(void);
- int prepare_test_case( int test_case_idx );
- int validate_test_results( int test_case_idx );
-
- CvSeq* hull1;
- CvMat* hull2;
- void* hull_storage;
- int orientation;
- int return_points;
-};
-
-
-CV_ConvHullTest::CV_ConvHullTest():
- CV_BaseShapeDescrTest( "shape-convhull", "cvConvexHull2" )
-{
- hull1 = 0;
- hull2 = 0;
- hull_storage = 0;
- orientation = return_points = 0;
-}
-
-
-CV_ConvHullTest::~CV_ConvHullTest()
-{
- clear();
-}
-
-
-void CV_ConvHullTest::clear()
-{
- CV_BaseShapeDescrTest::clear();
- cvReleaseMat( &hull2 );
- hull1 = 0;
- hull_storage = 0;
-}
-
-
-int CV_ConvHullTest::prepare_test_case( int test_case_idx )
-{
- int code = CV_BaseShapeDescrTest::prepare_test_case( test_case_idx );
- int use_storage_for_hull = 0;
- CvRNG* rng = ts->get_rng();
-
- if( code <= 0 )
- return code;
-
- orientation = cvTsRandInt(rng) % 2 ? CV_CLOCKWISE : CV_COUNTER_CLOCKWISE;
- return_points = cvTsRandInt(rng) % 2;
-
- use_storage_for_hull = (cvTsRandInt(rng) % 2) && !test_cpp;
- if( use_storage_for_hull )
- {
- if( !storage )
- storage = cvCreateMemStorage( (cvTsRandInt(rng)%10 + 1)*1024 );
- hull_storage = storage;
- }
- else
- {
- int rows, cols;
- int sz = points1 ? points1->total : points2->cols + points2->rows - 1;
- int point_type = points1 ? CV_SEQ_ELTYPE(points1) : CV_MAT_TYPE(points2->type);
-
- if( cvTsRandInt(rng) % 2 )
- rows = sz, cols = 1;
- else
- rows = 1, cols = sz;
-
- hull2 = cvCreateMat( rows, cols, return_points ? point_type : CV_32SC1 );
- hull_storage = hull2;
- }
-
- return code;
-}
-
-
-void CV_ConvHullTest::run_func()
-{
- if(!test_cpp)
- hull1 = cvConvexHull2( points, hull_storage, orientation, return_points );
- else
- {
- cv::Mat _points = cv::cvarrToMat(points);
- bool clockwise = orientation == CV_CLOCKWISE;
- size_t n = 0;
- if( !return_points )
- {
- std::vector<int> _hull;
- cv::convexHull(_points, _hull, clockwise);
- n = _hull.size();
- memcpy(hull2->data.ptr, &_hull[0], n*sizeof(_hull[0]));
- }
- else if(_points.type() == CV_32SC2)
- {
- std::vector<cv::Point> _hull;
- cv::convexHull(_points, _hull, clockwise);
- n = _hull.size();
- memcpy(hull2->data.ptr, &_hull[0], n*sizeof(_hull[0]));
- }
- else if(_points.type() == CV_32FC2)
- {
- std::vector<cv::Point2f> _hull;
- cv::convexHull(_points, _hull, clockwise);
- n = _hull.size();
- memcpy(hull2->data.ptr, &_hull[0], n*sizeof(_hull[0]));
- }
- if(hull2->rows > hull2->cols)
- hull2->rows = (int)n;
- else
- hull2->cols = (int)n;
- }
-}
-
-
-int CV_ConvHullTest::validate_test_results( int test_case_idx )
-{
- int code = CV_BaseShapeDescrTest::validate_test_results( test_case_idx );
- CvMat* hull = 0;
- CvMat* mask = 0;
- int i, point_count, hull_count;
- CvPoint2D32f *p, *h;
- CvSeq header, hheader, *ptseq, *hseq;
- CvSeqBlock block, hblock;
-
- if( points1 )
- ptseq = points1;
- else
- ptseq = cvMakeSeqHeaderForArray( CV_MAT_TYPE(points2->type),
- sizeof(CvSeq), CV_ELEM_SIZE(points2->type), points2->data.ptr,
- points2->rows + points2->cols - 1, &header, &block );
- point_count = ptseq->total;
- p = (CvPoint2D32f*)(points2->data.ptr);
-
- if( hull1 )
- hseq = hull1;
- else
- hseq = cvMakeSeqHeaderForArray( CV_MAT_TYPE(hull2->type),
- sizeof(CvSeq), CV_ELEM_SIZE(hull2->type), hull2->data.ptr,
- hull2->rows + hull2->cols - 1, &hheader, &hblock );
- hull_count = hseq->total;
- hull = cvCreateMat( 1, hull_count, CV_32FC2 );
- mask = cvCreateMat( 1, hull_count, CV_8UC1 );
- cvZero( mask );
- h = (CvPoint2D32f*)(hull->data.ptr);
-
- // extract convex hull points
- if( return_points )
- {
- cvCvtSeqToArray( hseq, hull->data.ptr );
- if( CV_SEQ_ELTYPE(hseq) != CV_32FC2 )
- {
- CvMat tmp = cvMat( hull->rows, hull->cols, CV_32SC2, hull->data.ptr );
- cvConvert( &tmp, hull );
- }
- }
- else
- {
- CvSeqReader reader;
- cvStartReadSeq( hseq, &reader );
-
- for( i = 0; i < hull_count; i++ )
- {
- schar* ptr = reader.ptr;
- int idx;
- CV_NEXT_SEQ_ELEM( hseq->elem_size, reader );
-
- if( hull1 )
- idx = cvSeqElemIdx( ptseq, *(uchar**)ptr );
- else
- idx = *(int*)ptr;
-
- if( idx < 0 || idx >= point_count )
- {
- ts->printf( CvTS::LOG, "Invalid convex hull point #%d\n", i );
- code = CvTS::FAIL_INVALID_OUTPUT;
- goto _exit_;
- }
- h[i] = p[idx];
- }
- }
-
- // check that the convex hull is a convex polygon
- if( hull_count >= 3 )
- {
- CvPoint2D32f pt0 = h[hull_count-1];
- for( i = 0; i < hull_count; i++ )
- {
- int j = i+1;
- CvPoint2D32f pt1 = h[i], pt2 = h[j < hull_count ? j : 0];
- float dx0 = pt1.x - pt0.x, dy0 = pt1.y - pt0.y;
- float dx1 = pt2.x - pt1.x, dy1 = pt2.y - pt1.y;
- double t = (double)dx0*dy1 - (double)dx1*dy0;
- if( (t < 0) ^ (orientation != CV_COUNTER_CLOCKWISE) )
- {
- ts->printf( CvTS::LOG, "The convex hull is not convex or has a wrong orientation (vtx %d)\n", i );
- code = CvTS::FAIL_INVALID_OUTPUT;
- goto _exit_;
- }
- pt0 = pt1;
- }
- }
-
- // check that all the points are inside the hull or on the hull edge
- // and at least hull_point points are at the hull vertices
- for( i = 0; i < point_count; i++ )
- {
- int idx = 0, on_edge = 0;
- double result = cvTsPointPolygonTest( p[i], h, hull_count, &idx, &on_edge );
-
- if( result < 0 )
- {
- ts->printf( CvTS::LOG, "The point #%d is outside of the convex hull\n", i );
- code = CvTS::FAIL_BAD_ACCURACY;
- goto _exit_;
- }
-
- if( result < FLT_EPSILON && !on_edge )
- mask->data.ptr[idx] = (uchar)1;
- }
-
- if( cvNorm( mask, 0, CV_L1 ) != hull_count )
- {
- ts->printf( CvTS::LOG, "Not every convex hull vertex coincides with some input point\n" );
- code = CvTS::FAIL_BAD_ACCURACY;
- goto _exit_;
- }
-
-_exit_:
-
- cvReleaseMat( &hull );
- cvReleaseMat( &mask );
- if( code < 0 )
- ts->set_failed_test_info( code );
- return code;
-}
-
-
-CV_ConvHullTest shape_convhull_test;
-
-
-/****************************************************************************************\
-* MinAreaRect Test *
-\****************************************************************************************/
-
-class CV_MinAreaRectTest : public CV_BaseShapeDescrTest
-{
-public:
- CV_MinAreaRectTest();
-
-protected:
- void run_func(void);
- int validate_test_results( int test_case_idx );
-
- CvBox2D box;
- CvPoint2D32f box_pt[4];
-};
-
-
-CV_MinAreaRectTest::CV_MinAreaRectTest():
- CV_BaseShapeDescrTest( "shape-minarearect", "cvMinAreaRect2, cvBoxPoints" )
-{
-}
-
-
-void CV_MinAreaRectTest::run_func()
-{
- if(!test_cpp)
- {
- box = cvMinAreaRect2( points, storage );
- cvBoxPoints( box, box_pt );
- }
- else
- {
- cv::RotatedRect r = cv::minAreaRect(cv::cvarrToMat(points));
- box = (CvBox2D)r;
- r.points((cv::Point2f*)box_pt);
- }
-}
-
-
-int CV_MinAreaRectTest::validate_test_results( int test_case_idx )
-{
- double eps = 1e-1;
- int code = CV_BaseShapeDescrTest::validate_test_results( test_case_idx );
- int i, j, point_count = points2->rows + points2->cols - 1;
- CvPoint2D32f *p = (CvPoint2D32f*)(points2->data.ptr);
- int mask[] = {0,0,0,0};
-
- // check that the bounding box is a rotated rectangle:
- // 1. diagonals should be equal
- // 2. they must intersect in their middle points
- {
- double d0 = cvTsDist( box_pt[0], box_pt[2] );
- double d1 = cvTsDist( box_pt[1], box_pt[3] );
-
- double x0 = (box_pt[0].x + box_pt[2].x)*0.5;
- double y0 = (box_pt[0].y + box_pt[2].y)*0.5;
- double x1 = (box_pt[1].x + box_pt[3].x)*0.5;
- double y1 = (box_pt[1].y + box_pt[3].y)*0.5;
-
- if( fabs(d0 - d1) + fabs(x0 - x1) + fabs(y0 - y1) > eps*MAX(d0,d1) )
- {
- ts->printf( CvTS::LOG, "The bounding box is not a rectangle\n" );
- code = CvTS::FAIL_INVALID_OUTPUT;
- goto _exit_;
- }
- }
-
-#if 0
- {
- int n = 4;
- double a = 8, c = 8, b = 100, d = 150;
- CvPoint bp[4], *bpp = bp;
- cvNamedWindow( "test", 1 );
- IplImage* img = cvCreateImage( cvSize(500,500), 8, 3 );
- cvZero(img);
- for( i = 0; i < point_count; i++ )
- cvCircle(img,cvPoint(cvRound(p[i].x*a+b),cvRound(p[i].y*c+d)), 3, CV_RGB(0,255,0), -1 );
- for( i = 0; i < n; i++ )
- bp[i] = cvPoint(cvRound(box_pt[i].x*a+b),cvRound(box_pt[i].y*c+d));
- cvPolyLine( img, &bpp, &n, 1, 1, CV_RGB(255,255,0), 1, CV_AA, 0 );
- cvShowImage( "test", img );
- cvWaitKey();
- cvReleaseImage(&img);
- }
-#endif
-
- // check that the box includes all the points
- // and there is at least one point at (or very close to) every box side
- for( i = 0; i < point_count; i++ )
- {
- int idx = 0, on_edge = 0;
- double result = cvTsPointPolygonTest( p[i], box_pt, 4, &idx, &on_edge );
- if( result < -eps )
- {
- ts->printf( CvTS::LOG, "The point #%d is outside of the box\n", i );
- code = CvTS::FAIL_BAD_ACCURACY;
- goto _exit_;
- }
-
- if( result < eps )
- {
- for( j = 0; j < 4; j++ )
- {
- double d = cvTsPtLineDist( p[i], box_pt[(j-1)&3], box_pt[j] );
- if( d < eps )
- mask[j] = (uchar)1;
- }
- }
- }
-
- if( mask[0] + mask[1] + mask[2] + mask[3] != 4 )
- {
- ts->printf( CvTS::LOG, "Not every box side has a point nearby\n" );
- code = CvTS::FAIL_BAD_ACCURACY;
- goto _exit_;
- }
-
-_exit_:
-
- if( code < 0 )
- ts->set_failed_test_info( code );
- return code;
-}
-
-
-CV_MinAreaRectTest shape_minarearect_test;
-
-
-/****************************************************************************************\
-* MinEnclosingCircle Test *
-\****************************************************************************************/
-
-class CV_MinCircleTest : public CV_BaseShapeDescrTest
-{
-public:
- CV_MinCircleTest();
-
-protected:
- void run_func(void);
- int validate_test_results( int test_case_idx );
-
- CvPoint2D32f center;
- float radius;
-};
-
-
-CV_MinCircleTest::CV_MinCircleTest():
- CV_BaseShapeDescrTest( "shape-mincircle", "cvMinEnclosingCircle" )
-{
-}
-
-
-void CV_MinCircleTest::run_func()
-{
- if(!test_cpp)
- cvMinEnclosingCircle( points, ¢er, &radius );
- else
- cv::minEnclosingCircle(cv::cvarrToMat(points), (cv::Point2f&)center, radius);
-}
-
-
-int CV_MinCircleTest::validate_test_results( int test_case_idx )
-{
- double eps = 1.03;
- int code = CV_BaseShapeDescrTest::validate_test_results( test_case_idx );
- int i, j = 0, point_count = points2->rows + points2->cols - 1;
- CvPoint2D32f *p = (CvPoint2D32f*)(points2->data.ptr);
- CvPoint2D32f v[3];
-
-#if 0
- {
- double a = 2, b = 200, d = 400;
- cvNamedWindow( "test", 1 );
- IplImage* img = cvCreateImage( cvSize(500,500), 8, 3 );
- cvZero(img);
- for( i = 0; i < point_count; i++ )
- cvCircle(img,cvPoint(cvRound(p[i].x*a+b),cvRound(p[i].y*a+d)), 3, CV_RGB(0,255,0), -1 );
- cvCircle( img, cvPoint(cvRound(center.x*a+b),cvRound(center.y*a+d)),
- cvRound(radius*a), CV_RGB(255,255,0), 1 );
- cvShowImage( "test", img );
- cvWaitKey();
- cvReleaseImage(&img);
- }
-#endif
-
- // check that the circle contains all the points inside and
- // remember at most 3 points that are close to the boundary
- for( i = 0; i < point_count; i++ )
- {
- double d = cvTsDist( p[i], center );
- if( d > radius )
- {
- ts->printf( CvTS::LOG, "The point #%d is outside of the circle\n", i );
- code = CvTS::FAIL_BAD_ACCURACY;
- goto _exit_;
- }
-
- if( radius - d < eps*radius && j < 3 )
- v[j++] = p[i];
- }
-
- if( point_count >= 2 && (j < 2 || (j == 2 && cvTsDist(v[0],v[1]) < (radius-1)*2/eps)) )
- {
- ts->printf( CvTS::LOG,
- "There should be at at least 3 points near the circle boundary or 2 points on the diameter\n" );
- code = CvTS::FAIL_BAD_ACCURACY;
- goto _exit_;
- }
-
-_exit_:
-
- if( code < 0 )
- ts->set_failed_test_info( code );
- return code;
-}
-
-
-CV_MinCircleTest shape_mincircle_test;
-
-
-/****************************************************************************************\
-* Perimeter Test *
-\****************************************************************************************/
-
-class CV_PerimeterTest : public CV_BaseShapeDescrTest
-{
-public:
- CV_PerimeterTest();
-
-protected:
- int prepare_test_case( int test_case_idx );
- void run_func(void);
- int validate_test_results( int test_case_idx );
- CvSlice slice;
- int is_closed;
- double result;
-};
-
-
-CV_PerimeterTest::CV_PerimeterTest():
- CV_BaseShapeDescrTest( "shape-perimeter", "cvArcLength" )
-{
-}
-
-
-int CV_PerimeterTest::prepare_test_case( int test_case_idx )
-{
- int code = CV_BaseShapeDescrTest::prepare_test_case( test_case_idx );
- CvRNG* rng = ts->get_rng();
- int total;
-
- if( code < 0 )
- return code;
-
- is_closed = cvTsRandInt(rng) % 2;
-
- if( points1 )
- {
- points1->flags |= CV_SEQ_KIND_CURVE;
- if( is_closed )
- points1->flags |= CV_SEQ_FLAG_CLOSED;
- total = points1->total;
- }
- else
- total = points2->cols + points2->rows - 1;
-
- if( (cvTsRandInt(rng) % 3) && !test_cpp )
- {
- slice.start_index = cvTsRandInt(rng) % total;
- slice.end_index = cvTsRandInt(rng) % total;
- }
- else
- slice = CV_WHOLE_SEQ;
-
- return 1;
-}
-
-
-void CV_PerimeterTest::run_func()
-{
- if(!test_cpp)
- result = cvArcLength( points, slice, points1 ? -1 : is_closed );
- else
- result = cv::arcLength(cv::cvarrToMat(points),
- !points1 ? is_closed != 0 : (points1->flags & CV_SEQ_FLAG_CLOSED) != 0);
-}
-
-
-int CV_PerimeterTest::validate_test_results( int test_case_idx )
-{
- int code = CV_BaseShapeDescrTest::validate_test_results( test_case_idx );
- int i, len = slice.end_index - slice.start_index, total = points2->cols + points2->rows - 1;
- double result0 = 0;
- CvPoint2D32f prev_pt, pt, *ptr;
-
- if( len < 0 )
- len += total;
-
- len = MIN( len, total );
- len -= !is_closed && len == total;
-
- ptr = (CvPoint2D32f*)points2->data.fl;
- prev_pt = ptr[slice.start_index % total];
-
- for( i = 1; i <= len; i++ )
- {
- pt = ptr[(i + slice.start_index) % total];
- double dx = pt.x - prev_pt.x, dy = pt.y - prev_pt.y;
- result0 += sqrt(dx*dx + dy*dy);
- prev_pt = pt;
- }
-
- if( cvIsNaN(result) || cvIsInf(result) )
- {
- ts->printf( CvTS::LOG, "cvArcLength() returned invalid value (%g)\n", result );
- code = CvTS::FAIL_INVALID_OUTPUT;
- }
- else if( fabs(result - result0) > FLT_EPSILON*100*result0 )
- {
- ts->printf( CvTS::LOG, "The function returned %g, while the correct result is %g\n", result, result0 );
- code = CvTS::FAIL_BAD_ACCURACY;
- }
-
- if( code < 0 )
- ts->set_failed_test_info( code );
- return code;
-}
-
-
-CV_PerimeterTest shape_perimeter_test;
-
-
-
-/****************************************************************************************\
-* FitEllipse Test *
-\****************************************************************************************/
-
-class CV_FitEllipseTest : public CV_BaseShapeDescrTest
-{
-public:
- CV_FitEllipseTest();
-
-protected:
- int prepare_test_case( int test_case_idx );
- void generate_point_set( void* points );
- void run_func(void);
- int validate_test_results( int test_case_idx );
- CvBox2D box0, box;
- double min_ellipse_size, max_noise;
-};
-
-
-CV_FitEllipseTest::CV_FitEllipseTest():
- CV_BaseShapeDescrTest( "shape-fit-ellipse", "cvFitEllipse" )
-{
- min_log_size = 5; // for robust ellipse fitting a dozen of points is needed at least
- max_log_size = 10;
- min_ellipse_size = 10;
- max_noise = 0.05;
-}
-
-
-void CV_FitEllipseTest::generate_point_set( void* points )
-{
- CvRNG* rng = ts->get_rng();
- int i, total, point_type;
- CvSeqReader reader;
- uchar* data = 0;
- double a, b;
-
- box0.center.x = (float)((low.val[0] + high.val[0])*0.5);
- box0.center.y = (float)((low.val[1] + high.val[1])*0.5);
- box0.size.width = (float)(MAX(high.val[0] - low.val[0], min_ellipse_size)*2);
- box0.size.height = (float)(MAX(high.val[1] - low.val[1], min_ellipse_size)*2);
- box0.angle = (float)(cvTsRandReal(rng)*180);
- a = cos(box0.angle*CV_PI/180.);
- b = sin(box0.angle*CV_PI/180.);
-
- if( box0.size.width > box0.size.height )
- {
- float t;
- CV_SWAP( box0.size.width, box0.size.height, t );
- }
- memset( &reader, 0, sizeof(reader) );
-
- if( CV_IS_SEQ(points) )
- {
- CvSeq* ptseq = (CvSeq*)points;
- total = ptseq->total;
- point_type = CV_SEQ_ELTYPE(ptseq);
- cvStartReadSeq( ptseq, &reader );
- }
- else
- {
- CvMat* ptm = (CvMat*)points;
- assert( CV_IS_MAT(ptm) && CV_IS_MAT_CONT(ptm->type) );
- total = ptm->rows + ptm->cols - 1;
- point_type = CV_MAT_TYPE(ptm->type);
- data = ptm->data.ptr;
- }
-
- assert( point_type == CV_32SC2 || point_type == CV_32FC2 );
-
- for( i = 0; i < total; i++ )
- {
- CvPoint* pp;
- CvPoint2D32f p;
- double angle = cvTsRandReal(rng)*CV_PI*2;
- double x = box0.size.height*0.5*(cos(angle) + (cvTsRandReal(rng)-0.5)*2*max_noise);
- double y = box0.size.width*0.5*(sin(angle) + (cvTsRandReal(rng)-0.5)*2*max_noise);
- p.x = (float)(box0.center.x + a*x + b*y);
- p.y = (float)(box0.center.y - b*x + a*y);
-
- if( reader.ptr )
- {
- pp = (CvPoint*)reader.ptr;
- CV_NEXT_SEQ_ELEM( sizeof(*pp), reader );
- }
- else
- pp = ((CvPoint*)data) + i;
- if( point_type == CV_32SC2 )
- {
- pp->x = cvRound(p.x);
- pp->y = cvRound(p.y);
- }
- else
- *(CvPoint2D32f*)pp = p;
- }
-}
-
-
-int CV_FitEllipseTest::prepare_test_case( int test_case_idx )
-{
- min_log_size = MAX(min_log_size,4);
- max_log_size = MAX(min_log_size,max_log_size);
- return CV_BaseShapeDescrTest::prepare_test_case( test_case_idx );
-}
-
-
-void CV_FitEllipseTest::run_func()
-{
- if(!test_cpp)
- box = cvFitEllipse2( points );
- else
- box = (CvBox2D)cv::fitEllipse(cv::cvarrToMat(points));
-}
-
-
-int CV_FitEllipseTest::validate_test_results( int test_case_idx )
-{
- int code = CV_BaseShapeDescrTest::validate_test_results( test_case_idx );
- double diff_angle;
-
- if( cvIsNaN(box.center.x) || cvIsInf(box.center.x) ||
- cvIsNaN(box.center.y) || cvIsInf(box.center.y) ||
- cvIsNaN(box.size.width) || cvIsInf(box.size.width) ||
- cvIsNaN(box.size.height) || cvIsInf(box.size.height) ||
- cvIsNaN(box.angle) || cvIsInf(box.angle) )
- {
- ts->printf( CvTS::LOG, "Some of the computed ellipse parameters are invalid (x=%g,y=%g,w=%g,h=%g,angle=%g)\n",
- box.center.x, box.center.y, box.size.width, box.size.height, box.angle );
- code = CvTS::FAIL_INVALID_OUTPUT;
- goto _exit_;
- }
-
- box.angle = (float)(90-box.angle);
- if( box.angle < 0 )
- box.angle += 360;
- if( box.angle > 360 )
- box.angle -= 360;
-
- if( fabs(box.center.x - box0.center.x) > 3 ||
- fabs(box.center.y - box0.center.y) > 3 ||
- fabs(box.size.width - box0.size.width) > 0.1*fabs(box0.size.width) ||
- fabs(box.size.height - box0.size.height) > 0.1*fabs(box0.size.height) )
- {
- ts->printf( CvTS::LOG, "The computed ellipse center and/or size are incorrect:\n\t"
- "(x=%.1f,y=%.1f,w=%.1f,h=%.1f), while it should be (x=%.1f,y=%.1f,w=%.1f,h=%.1f)\n",
- box.center.x, box.center.y, box.size.width, box.size.height,
- box0.center.x, box0.center.y, box0.size.width, box0.size.height );
- code = CvTS::FAIL_BAD_ACCURACY;
- goto _exit_;
- }
-
- diff_angle = fabs(box0.angle - box.angle);
- diff_angle = MIN( diff_angle, fabs(diff_angle - 360));
- diff_angle = MIN( diff_angle, fabs(diff_angle - 180));
-
- if( box0.size.height >= 1.3*box0.size.width && diff_angle > 30 )
- {
- ts->printf( CvTS::LOG, "Incorrect ellipse angle (=%1.f, should be %1.f)\n",
- box.angle, box0.angle );
- code = CvTS::FAIL_BAD_ACCURACY;
- goto _exit_;
- }
-
-_exit_:
-
-#if 0
- cvNamedWindow( "test", 0 );
- IplImage* img = cvCreateImage( cvSize(cvRound(low_high_range*4),
- cvRound(low_high_range*4)), 8, 3 );
- cvZero( img );
-
- box.center.x += (float)low_high_range*2;
- box.center.y += (float)low_high_range*2;
- cvEllipseBox( img, box, CV_RGB(255,0,0), 3, 8 );
-
- for( int i = 0; i < points2->rows + points2->cols - 1; i++ )
- {
- CvPoint pt;
- pt.x = cvRound(points2->data.fl[i*2] + low_high_range*2);
- pt.y = cvRound(points2->data.fl[i*2+1] + low_high_range*2);
- cvCircle( img, pt, 1, CV_RGB(255,255,255), -1, 8 );
- }
-
- cvShowImage( "test", img );
- cvReleaseImage( &img );
- cvWaitKey(0);
-#endif
-
- if( code < 0 )
- {
- ts->set_failed_test_info( code );
- }
- return code;
-}
-
-
-CV_FitEllipseTest fit_ellipse_test;
-
-
-
-/****************************************************************************************\
-* FitLine Test *
-\****************************************************************************************/
-
-class CV_FitLineTest : public CV_BaseShapeDescrTest
-{
-public:
- CV_FitLineTest();
-
-protected:
- int prepare_test_case( int test_case_idx );
- void generate_point_set( void* points );
- void run_func(void);
- int validate_test_results( int test_case_idx );
- double max_noise;
- float line[6], line0[6];
- int dist_type;
- double reps, aeps;
-};
-
-
-CV_FitLineTest::CV_FitLineTest():
- CV_BaseShapeDescrTest( "shape-fit-line", "cvFitLine" )
-{
- min_log_size = 5; // for robust ellipse fitting a dozen of points is needed at least
- max_log_size = 10;
- max_noise = 0.05;
-}
-
-
-void CV_FitLineTest::generate_point_set( void* points )
-{
- CvRNG* rng = ts->get_rng();
- int i, k, n, total, point_type;
- CvSeqReader reader;
- uchar* data = 0;
- double s = 0;
-
- n = dims;
- for( k = 0; k < n; k++ )
- {
- line0[k+n] = (float)((low.val[k] + high.val[k])*0.5);
- line0[k] = (float)(high.val[k] - low.val[k]);
- if( cvTsRandInt(rng) % 2 )
- line0[k] = -line0[k];
- s += (double)line0[k]*line0[k];
- }
-
- s = 1./sqrt(s);
- for( k = 0; k < n; k++ )
- line0[k] = (float)(line0[k]*s);
-
- memset( &reader, 0, sizeof(reader) );
-
- if( CV_IS_SEQ(points) )
- {
- CvSeq* ptseq = (CvSeq*)points;
- total = ptseq->total;
- point_type = CV_MAT_DEPTH(CV_SEQ_ELTYPE(ptseq));
- cvStartReadSeq( ptseq, &reader );
- }
- else
- {
- CvMat* ptm = (CvMat*)points;
- assert( CV_IS_MAT(ptm) && CV_IS_MAT_CONT(ptm->type) );
- total = ptm->rows + ptm->cols - 1;
- point_type = CV_MAT_DEPTH(CV_MAT_TYPE(ptm->type));
- data = ptm->data.ptr;
- }
-
- for( i = 0; i < total; i++ )
- {
- int* pi;
- float* pf;
- float p[4], t;
- if( reader.ptr )
- {
- pi = (int*)reader.ptr;
- pf = (float*)reader.ptr;
- CV_NEXT_SEQ_ELEM( reader.seq->elem_size, reader );
- }
- else
- {
- pi = (int*)data + i*n;
- pf = (float*)data + i*n;
- }
-
- t = (float)((cvTsRandReal(rng)-0.5)*low_high_range*2);
-
- for( k = 0; k < n; k++ )
- p[k] = (float)((cvTsRandReal(rng)-0.5)*max_noise*2 + t*line0[k] + line0[k+n]);
-
- if( point_type == CV_32S )
- for( k = 0; k < n; k++ )
- pi[k] = cvRound(p[k]);
- else
- for( k = 0; k < n; k++ )
- pf[k] = p[k];
- }
-}
-
-
-int CV_FitLineTest::prepare_test_case( int test_case_idx )
-{
- CvRNG* rng = ts->get_rng();
- dims = cvTsRandInt(rng) % 2 + 2;
- min_log_size = MAX(min_log_size,5);
- max_log_size = MAX(min_log_size,max_log_size);
- int code = CV_BaseShapeDescrTest::prepare_test_case( test_case_idx );
- dist_type = cvTsRandInt(rng) % 6 + 1;
- dist_type += dist_type == CV_DIST_C;
- reps = 0.1; aeps = 0.01;
- return code;
-}
-
-
-void CV_FitLineTest::run_func()
-{
- if(!test_cpp)
- cvFitLine( points, dist_type, 0, reps, aeps, line );
- else if(dims == 2)
- cv::fitLine(cv::cvarrToMat(points), (cv::Vec4f&)line[0], dist_type, 0, reps, aeps);
- else
- cv::fitLine(cv::cvarrToMat(points), (cv::Vec6f&)line[0], dist_type, 0, reps, aeps);
-}
-
-
-int CV_FitLineTest::validate_test_results( int test_case_idx )
-{
- int code = CV_BaseShapeDescrTest::validate_test_results( test_case_idx );
- int k, max_k = 0;
- double vec_diff = 0, t;
-
- for( k = 0; k < dims*2; k++ )
- {
- if( cvIsNaN(line[k]) || cvIsInf(line[k]) )
- {
- ts->printf( CvTS::LOG, "Some of the computed line parameters are invalid (line[%d]=%g)\n",
- k, line[k] );
- code = CvTS::FAIL_INVALID_OUTPUT;
- goto _exit_;
- }
- }
-
- if( fabs(line0[1]) > fabs(line0[0]) )
- max_k = 1;
- if( fabs(line0[dims-1]) > fabs(line0[max_k]) )
- max_k = dims-1;
- if( line0[max_k] < 0 )
- for( k = 0; k < dims; k++ )
- line0[k] = -line0[k];
- if( line[max_k] < 0 )
- for( k = 0; k < dims; k++ )
- line[k] = -line[k];
-
- for( k = 0; k < dims; k++ )
- {
- double dt = line[k] - line0[k];
- vec_diff += dt*dt;
- }
-
- if( sqrt(vec_diff) > 0.05 )
- {
- if( dims == 2 )
- ts->printf( CvTS::LOG,
- "The computed line vector (%.2f,%.2f) is different from the actual (%.2f,%.2f)\n",
- line[0], line[1], line0[0], line0[1] );
- else
- ts->printf( CvTS::LOG,
- "The computed line vector (%.2f,%.2f,%.2f) is different from the actual (%.2f,%.2f,%.2f)\n",
- line[0], line[1], line[2], line0[0], line0[1], line0[2] );
- code = CvTS::FAIL_BAD_ACCURACY;
- goto _exit_;
- }
-
- t = (line[max_k+dims] - line0[max_k+dims])/line0[max_k];
- for( k = 0; k < dims; k++ )
- {
- double p = line0[k+dims] + t*line0[k] - line[k+dims];
- vec_diff += p*p;
- }
-
- if( sqrt(vec_diff) > 1*MAX(fabs(t),1) )
- {
- if( dims == 2 )
- ts->printf( CvTS::LOG,
- "The computed line point (%.2f,%.2f) is too far from the actual line\n",
- line[2]+line0[2], line[3]+line0[3] );
- else
- ts->printf( CvTS::LOG,
- "The computed line point (%.2f,%.2f,%.2f) is too far from the actual line\n",
- line[3]+line0[3], line[4]+line0[4], line[5]+line0[5] );
- code = CvTS::FAIL_BAD_ACCURACY;
- goto _exit_;
- }
-
-_exit_:
-
- if( code < 0 )
- {
- ts->set_failed_test_info( code );
- }
- return code;
-}
-
-
-CV_FitLineTest fit_line_test;
-
-
-/****************************************************************************************\
-* ContourMoments Test *
-\****************************************************************************************/
-
-
-static void
-cvTsGenerateTousledBlob( CvPoint2D32f center, CvSize2D32f axes,
- double max_r_scale, double angle, CvArr* points, CvRNG* rng )
-{
- int i, total, point_type;
- uchar* data = 0;
- CvSeqReader reader;
- memset( &reader, 0, sizeof(reader) );
-
- if( CV_IS_SEQ(points) )
- {
- CvSeq* ptseq = (CvSeq*)points;
- total = ptseq->total;
- point_type = CV_SEQ_ELTYPE(ptseq);
- cvStartReadSeq( ptseq, &reader );
- }
- else
- {
- CvMat* ptm = (CvMat*)points;
- assert( CV_IS_MAT(ptm) && CV_IS_MAT_CONT(ptm->type) );
- total = ptm->rows + ptm->cols - 1;
- point_type = CV_MAT_TYPE(ptm->type);
- data = ptm->data.ptr;
- }
-
- assert( point_type == CV_32SC2 || point_type == CV_32FC2 );
-
- for( i = 0; i < total; i++ )
- {
- CvPoint* pp;
- CvPoint2D32f p;
-
- double phi0 = 2*CV_PI*i/total;
- double phi = CV_PI*angle/180.;
- double t = cvTsRandReal(rng)*max_r_scale + (1 - max_r_scale);
- double ta = axes.height*t;
- double tb = axes.width*t;
- double c0 = cos(phi0)*ta, s0 = sin(phi0)*tb;
- double c = cos(phi), s = sin(phi);
- p.x = (float)(c0*c - s0*s + center.x);
- p.y = (float)(c0*s + s0*c + center.y);
-
- if( reader.ptr )
- {
- pp = (CvPoint*)reader.ptr;
- CV_NEXT_SEQ_ELEM( sizeof(*pp), reader );
- }
- else
- pp = ((CvPoint*)data) + i;
-
- if( point_type == CV_32SC2 )
- {
- pp->x = cvRound(p.x);
- pp->y = cvRound(p.y);
- }
- else
- *(CvPoint2D32f*)pp = p;
- }
-}
-
-
-class CV_ContourMomentsTest : public CV_BaseShapeDescrTest
-{
-public:
- CV_ContourMomentsTest();
-
-protected:
- int prepare_test_case( int test_case_idx );
- void generate_point_set( void* points );
- void run_func(void);
- int validate_test_results( int test_case_idx );
- CvMoments moments0, moments;
- double area0, area;
- CvSize2D32f axes;
- CvPoint2D32f center;
- int max_max_r_scale;
- double max_r_scale, angle;
- CvSize img_size;
-};
-
-
-CV_ContourMomentsTest::CV_ContourMomentsTest():
- CV_BaseShapeDescrTest( "shape-moments", "cvMoments, cvContourArea" )
-{
- min_log_size = 3;
- max_log_size = 8;
- max_max_r_scale = 15;
- low_high_range = 200;
- enable_flt_points = false;
-}
-
-
-void CV_ContourMomentsTest::generate_point_set( void* points )
-{
- CvRNG* rng = ts->get_rng();
- float max_sz;
-
- axes.width = (float)((cvTsRandReal(rng)*0.9 + 0.1)*low_high_range);
- axes.height = (float)((cvTsRandReal(rng)*0.9 + 0.1)*low_high_range);
- max_sz = MAX(axes.width, axes.height);
-
- img_size.width = img_size.height = cvRound(low_high_range*2.2);
-
- center.x = (float)(img_size.width*0.5 + (cvTsRandReal(rng)-0.5)*(img_size.width - max_sz*2)*0.8);
- center.y = (float)(img_size.height*0.5 + (cvTsRandReal(rng)-0.5)*(img_size.height - max_sz*2)*0.8);
-
- assert( 0 < center.x - max_sz && center.x + max_sz < img_size.width &&
- 0 < center.y - max_sz && center.y + max_sz < img_size.height );
-
- max_r_scale = cvTsRandReal(rng)*max_max_r_scale*0.01;
- angle = cvTsRandReal(rng)*360;
-
- cvTsGenerateTousledBlob( center, axes, max_r_scale, angle, points, rng );
-
- if( points1 )
- points1->flags = CV_SEQ_MAGIC_VAL + CV_SEQ_POLYGON;
-}
-
-
-int CV_ContourMomentsTest::prepare_test_case( int test_case_idx )
-{
- min_log_size = MAX(min_log_size,3);
- max_log_size = MIN(max_log_size,8);
- max_log_size = MAX(min_log_size,max_log_size);
- int code = CV_BaseShapeDescrTest::prepare_test_case( test_case_idx );
- return code;
-}
-
-
-void CV_ContourMomentsTest::run_func()
-{
- if(!test_cpp)
- {
- cvMoments( points, &moments );
- area = cvContourArea( points );
- }
- else
- {
- moments = (CvMoments)cv::moments(cv::cvarrToMat(points));
- area = cv::contourArea(cv::cvarrToMat(points));
- }
-}
-
-
-int CV_ContourMomentsTest::validate_test_results( int test_case_idx )
-{
- int code = CV_BaseShapeDescrTest::validate_test_results( test_case_idx );
- int i, n = (int)(sizeof(moments)/sizeof(moments.inv_sqrt_m00));
- CvMat* img = cvCreateMat( img_size.height, img_size.width, CV_8UC1 );
- CvPoint* pt = (CvPoint*)points2->data.i;
- int count = points2->cols + points2->rows - 1;
- double max_v0 = 0;
-
- cvZero(img);
- cvFillPoly( img, &pt, &count, 1, cvScalarAll(1));
- cvMoments( img, &moments0 );
-
- for( i = 0; i < n; i++ )
- {
- double t = fabs((&moments0.m00)[i]);
- max_v0 = MAX(max_v0, t);
- }
-
- for( i = 0; i <= n; i++ )
- {
- double v = i < n ? (&moments.m00)[i] : area;
- double v0 = i < n ? (&moments0.m00)[i] : moments0.m00;
-
- if( cvIsNaN(v) || cvIsInf(v) )
- {
- ts->printf( CvTS::LOG,
- "The contour %s is invalid (=%g)\n", i < n ? "moment" : "area", v );
- code = CvTS::FAIL_INVALID_OUTPUT;
- break;
- }
-
- if( fabs(v - v0) > 0.1*max_v0 )
- {
- ts->printf( CvTS::LOG,
- "The computed contour %s is %g, while it should be %g\n",
- i < n ? "moment" : "area", v, v0 );
- code = CvTS::FAIL_BAD_ACCURACY;
- break;
- }
- }
-
- if( code < 0 )
- {
-#if 0
- cvCmpS( img, 0, img, CV_CMP_GT );
- cvNamedWindow( "test", 1 );
- cvShowImage( "test", img );
- cvWaitKey();
-#endif
- ts->set_failed_test_info( code );
- }
-
- cvReleaseMat( &img );
- return code;
-}
-
-
-CV_ContourMomentsTest contour_moments_test;
-
-
-/* End of file. */
-
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
- //
- // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
- //
- // By downloading, copying, installing or using the software you agree to this license.
- // If you do not agree to this license, do not download, install,
- // copy or use the software.
- //
- //
- // Intel License Agreement
- // For Open Source Computer Vision Library
- //
- // Copyright (C) 2000, Intel Corporation, all rights reserved.
- // Third party copyrights are property of their respective owners.
- //
- // Redistribution and use in source and binary forms, with or without modification,
- // are permitted provided that the following conditions are met:
- //
- // * Redistribution's of source code must retain the above copyright notice,
- // this list of conditions and the following disclaimer.
- //
- // * Redistribution's in binary form must reproduce the above copyright notice,
- // this list of conditions and the following disclaimer in the documentation
- // and/or other materials provided with the distribution.
- //
- // * The name of Intel Corporation may not be used to endorse or promote products
- // derived from this software without specific prior written permission.
- //
- // This software is provided by the copyright holders and contributors "as is" and
- // any express or implied warranties, including, but not limited to, the implied
- // warranties of merchantability and fitness for a particular purpose are disclaimed.
- // In no event shall the Intel Corporation or contributors be liable for any direct,
- // indirect, incidental, special, exemplary, or consequential damages
- // (including, but not limited to, procurement of substitute goods or services;
- // loss of use, data, or profits; or business interruption) however caused
- // and on any theory of liability, whether in contract, strict liability,
- // or tort (including negligence or otherwise) arising in any way out of
- // the use of this software, even if advised of the possibility of such damage.
- //
- //M*/
-
-#include <limits>
-
-#include "cvtest.h"
-#include "cvchessboardgenerator.h"
-
-using namespace cv;
-
-class CV_ChessboardSubpixelTest : public CvTest
-{
-public:
- CV_ChessboardSubpixelTest();
-
-protected:
- Mat intrinsic_matrix_;
- Mat distortion_coeffs_;
- Size image_size_;
-
- void run(int);
- void generateIntrinsicParams();
-};
-
-
-int calcDistance(const vector<Point2f>& set1, const vector<Point2f>& set2, double& mean_dist)
-{
- if(set1.size() != set2.size())
- {
- return 0;
- }
-
- std::vector<int> indices;
- double sum_dist = 0.0;
- for(size_t i = 0; i < set1.size(); i++)
- {
- double min_dist = std::numeric_limits<double>::max();
- int min_idx = -1;
-
- for(int j = 0; j < (int)set2.size(); j++)
- {
- double dist = norm(set1[i] - set2[j]);
- if(dist < min_dist)
- {
- min_idx = j;
- min_dist = dist;
- }
- }
-
- // check validity of min_idx
- if(min_idx == -1)
- {
- return 0;
- }
- std::vector<int>::iterator it = std::find(indices.begin(), indices.end(), min_idx);
- if(it != indices.end())
- {
- // there are two points in set1 corresponding to the same point in set2
- return 0;
- }
- indices.push_back(min_idx);
-
-// printf("dist %d = %f\n", (int)i, min_dist);
-
- sum_dist += min_dist*min_dist;
- }
-
- mean_dist = sqrt(sum_dist/set1.size());
-// printf("sum_dist = %f, set1.size() = %d, mean_dist = %f\n", sum_dist, (int)set1.size(), mean_dist);
-
- return 1;
-}
-
-CV_ChessboardSubpixelTest::CV_ChessboardSubpixelTest():
- CvTest( "chessboard-subpixel", "cvFindCornerSubPix" ),
- intrinsic_matrix_(Size(3, 3), CV_64FC1), distortion_coeffs_(Size(1, 4), CV_64FC1),
- image_size_(640, 480)
-{
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE | CvTS::TIMING_MODE;
-}
-
-/* ///////////////////// chess_corner_test ///////////////////////// */
-void CV_ChessboardSubpixelTest::run( int )
-{
- int code = CvTS::OK;
- int progress = 0;
-
- CvRNG* rng = ts->get_rng();
-
- const int runs_count = 20;
- const int max_pattern_size = 8;
- const int min_pattern_size = 5;
- Mat bg(image_size_, CV_8UC1);
- bg = Scalar(0);
-
- double sum_dist = 0.0;
- int count = 0;
- for(int i = 0; i < runs_count; i++)
- {
- const int pattern_width = min_pattern_size + cvRandInt(rng) % (max_pattern_size - min_pattern_size);
- const int pattern_height = min_pattern_size + cvRandInt(rng) % (max_pattern_size - min_pattern_size);
- Size pattern_size;
- if(pattern_width > pattern_height)
- {
- pattern_size = Size(pattern_height, pattern_width);
- }
- else
- {
- pattern_size = Size(pattern_width, pattern_height);
- }
- ChessBoardGenerator gen_chessboard(Size(pattern_size.width + 1, pattern_size.height + 1));
-
- // generates intrinsic camera and distortion matrices
- generateIntrinsicParams();
-
- vector<Point2f> corners;
- Mat chessboard_image = gen_chessboard(bg, intrinsic_matrix_, distortion_coeffs_, corners);
-
- vector<Point2f> test_corners;
- bool result = findChessboardCorners(chessboard_image, pattern_size, test_corners, 15);
- if(!result)
- {
-#if 0
- ts->printf(CvTS::LOG, "Warning: chessboard was not detected! Writing image to test.jpg\n");
- ts->printf(CvTS::LOG, "Size = %d, %d\n", pattern_size.width, pattern_size.height);
- ts->printf(CvTS::LOG, "Intrinsic params: fx = %f, fy = %f, cx = %f, cy = %f\n",
- intrinsic_matrix_.at<double>(0, 0), intrinsic_matrix_.at<double>(1, 1),
- intrinsic_matrix_.at<double>(0, 2), intrinsic_matrix_.at<double>(1, 2));
- ts->printf(CvTS::LOG, "Distortion matrix: %f, %f, %f, %f, %f\n",
- distortion_coeffs_.at<double>(0, 0), distortion_coeffs_.at<double>(0, 1),
- distortion_coeffs_.at<double>(0, 2), distortion_coeffs_.at<double>(0, 3),
- distortion_coeffs_.at<double>(0, 4));
-
- imwrite("test.jpg", chessboard_image);
-#endif
- continue;
- }
-
- double dist1 = 0.0;
- int ret = calcDistance(corners, test_corners, dist1);
- if(ret == 0)
- {
- ts->printf(CvTS::LOG, "findChessboardCorners returns invalid corner coordinates!\n");
- code = CvTS::FAIL_INVALID_OUTPUT;
- break;
- }
-
- IplImage chessboard_image_header = chessboard_image;
- cvFindCornerSubPix(&chessboard_image_header, (CvPoint2D32f*)&test_corners[0],
- (int)test_corners.size(), cvSize(3, 3), cvSize(1, 1), cvTermCriteria(CV_TERMCRIT_EPS|CV_TERMCRIT_ITER,300,0.1));
- find4QuadCornerSubpix(chessboard_image, test_corners, Size(5, 5));
-
- double dist2 = 0.0;
- ret = calcDistance(corners, test_corners, dist2);
- if(ret == 0)
- {
- ts->printf(CvTS::LOG, "findCornerSubpix returns invalid corner coordinates!\n");
- code = CvTS::FAIL_INVALID_OUTPUT;
- break;
- }
-
- ts->printf(CvTS::LOG, "Error after findChessboardCorners: %f, after findCornerSubPix: %f\n",
- dist1, dist2);
- sum_dist += dist2;
- count++;
-
- const double max_reduce_factor = 0.8;
- if(dist1 < dist2*max_reduce_factor)
- {
- ts->printf(CvTS::LOG, "findCornerSubPix increases average error!\n");
- code = CvTS::FAIL_INVALID_OUTPUT;
- break;
- }
-
- progress = update_progress( progress, i-1, runs_count, 0 );
- }
- sum_dist /= count;
- ts->printf(CvTS::LOG, "Average error after findCornerSubpix: %f\n", sum_dist);
-
- if( code < 0 )
- ts->set_failed_test_info( code );
-}
-
-void CV_ChessboardSubpixelTest::generateIntrinsicParams()
-{
- CvRNG* rng = ts->get_rng();
- const double max_focus_length = 1000.0;
- const double max_focus_diff = 5.0;
-
- double fx = cvRandReal(rng)*max_focus_length;
- double fy = fx + cvRandReal(rng)*max_focus_diff;
- double cx = image_size_.width/2;
- double cy = image_size_.height/2;
-
- double k1 = 0.5*cvRandReal(rng);
- double k2 = 0.05*cvRandReal(rng);
- double p1 = 0.05*cvRandReal(rng);
- double p2 = 0.05*cvRandReal(rng);
- double k3 = 0.0;
-
- intrinsic_matrix_ = (Mat_<double>(3, 3) << fx, 0.0, cx, 0.0, fy, cy, 0.0, 0.0, 1.0);
- distortion_coeffs_ = (Mat_<double>(1, 5) << k1, k2, p1, p2, k3);
-}
-
-CV_ChessboardSubpixelTest chessboard_subpixel_test;
-
-/* End of file. */
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-#if 0
-
-static char cTestName[] = "Binary tree create";
-static char cTestClass[] = "Algorithm";
-static char cFuncName[] = "cvCreateContourTree";
-
-static int aCreateContourTree(void)
-{
- CvSeqBlock contour_blk1;
- CvContour contour_h1; /* input contour */
- CvSeq *contour_h2; /* destination contour */
- CvContourTree *tree; /* created binary tree */
- CvMemStorage *storage; /* storage for contour and tree writing */
- CvTermCriteria criteria; /* criteria for the contour restoring */
-/* CvSeqReader reader; // points reader of contour */
-/* ippiTrianAttr vertex;*/
-
- int block_size = 10000;
- int nPoints1 = 20;
- int xc,yc,a1 = 10, b1 = 20, fi = 0;
- int xmin,ymin,xmax,ymax;
- double error_test;
- double pi = 3.1415926, eps_rez = 0.05;
- double threshold = 1.e-7;
- double rezult,error;
- int i, code = TRS_OK;
- int type_seq = 0;
- int width=256,height=256;
- CvPoint *cp1;
- CvPoint *cp2;
-
-/* read tests params */
-
- if (!trsiRead(&nPoints1,"20","Number of points first contour"))
- return TRS_UNDEF;
-
- if(nPoints1>0)
- {
- if (!trsiRead(&a1,"10","first radius of the first elipse"))
- return TRS_UNDEF;
- if (!trsiRead(&b1,"20","second radius of the first elipse"))
- return TRS_UNDEF;
-
- if (!trsiRead(&fi,"0","second radius of the second elipse"))
- return TRS_UNDEF;
-
- xc = (int)(width/2.);
- yc = (int)(height/2.);
- xmin = width;
- ymin = height;
- xmax = 0;
- ymax = 0;
-
- cp1 = (CvPoint*) trsmAlloc(nPoints1*sizeof(CvPoint));
- cp2 = (CvPoint*) trsmAlloc(nPoints1*sizeof(CvPoint));
-
- for(i=0;i<nPoints1;i++)
- {
- cp1[i].x = (int)(a1*cos(2*pi*i/nPoints1))+xc;
- cp1[i].y = (int)(b1*sin(2*pi*i/nPoints1))+yc;
- cp1[i].x = (int)(a1*cos(2*pi*i/nPoints1)*cos(2*pi*fi/360.))-
- (int)(b1*sin(2*pi*i/nPoints1)*sin(2*pi*fi/360.))+xc;
-
- cp1[i].y = (int)(a1*cos(2*pi*i/nPoints1)*sin(2*pi*fi/360.))+
- (int)(b1*sin(2*pi*i/nPoints1)*cos(2*pi*fi/360.))+yc;
-
- if(xmin> cp1[i].x) xmin = cp1[i].x;
- if(xmax< cp1[i].x) xmax = cp1[i].x;
- if(ymin> cp1[i].y) ymin = cp1[i].y;
- if(ymax< cp1[i].y) ymax = cp1[i].y;
- }
-
- if(xmax>width||xmin<0||ymax>height||ymin<0)
- return TRS_FAIL;
-
-
- storage = cvCreateMemStorage( block_size );
-/* contours initialazing */
-
- type_seq = CV_SEQ_POLYGON;
- cvMakeSeqHeaderForArray(type_seq, sizeof(CvContour), sizeof(CvPoint),
- (char*)cp1, nPoints1, (CvSeq*)&contour_h1, &contour_blk1);
-
-/* create countour's tree */
- error_test = 0.;
-
- tree = cvCreateContourTree ((CvSeq*)&contour_h1, storage, threshold);
-
- trsWrite( ATS_CON | ATS_LST | ATS_SUM, "Contour's binary tree is created \n");
-
- error = 0;
- criteria.type = CV_TERMCRIT_ITER;
- criteria.max_iter = 100;
- contour_h2 = cvContourFromContourTree (tree, storage, criteria);
- rezult = cvMatchContours ((CvSeq*)&contour_h1, contour_h2,CV_CONTOURS_MATCH_I1);
-
- error+=rezult;
-
- criteria.type = CV_TERMCRIT_EPS;
- criteria.epsilon = (float)0.00001;
- contour_h2 = cvContourFromContourTree (tree, storage, criteria);
- rezult = cvMatchContours ((CvSeq*)&contour_h1, contour_h2, CV_CONTOURS_MATCH_I1);
- error+=rezult;
-
- criteria.type = CV_TERMCRIT_ITER + CV_TERMCRIT_EPS;
- criteria.epsilon = (float)0.00001;
- criteria.max_iter = 1;
- contour_h2 = cvContourFromContourTree (tree, storage, criteria);
- rezult = cvMatchContours ((CvSeq*)&contour_h1, contour_h2, CV_CONTOURS_MATCH_I1);
- error+=rezult;
-
- criteria.type = CV_TERMCRIT_ITER + CV_TERMCRIT_EPS;
- criteria.epsilon = 1000.;
- criteria.max_iter = 100;
- contour_h2 = cvContourFromContourTree (tree, storage, criteria);
- rezult = cvMatchContours ((CvSeq*)&contour_h1, contour_h2, CV_CONTOURS_MATCH_I1);
- error+=rezult;
-
- if(error > eps_rez )
- code = TRS_FAIL;
- else
- code = TRS_OK;
-
- trsWrite( ATS_CON | ATS_LST | ATS_SUM, "contour from contour tree is restored rezult= %f \n",rezult);
-
- cvCvtSeqToArray(contour_h2, (char*)cp2 );
-
- cvReleaseMemStorage ( &storage );
-
- trsFree (cp2);
- trsFree (cp1);
-
- }
-
-
-/* _getch(); */
- return code;
-}
-
-void InitACreateContourTree( void )
-{
-/* Test Registartion */
- trsReg(cFuncName,cTestName,cTestClass,aCreateContourTree);
-
-} /* InitACreateContourTree */
-
-/* End of file. */
-
-#endif
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-#include <limits>
-#include <cstdio>
-#include <iostream>
-#include <fstream>
-
-using namespace std;
-using namespace cv;
-
-/****************************************************************************************\
-* Functions to evaluate affine covariant detectors and descriptors. *
-\****************************************************************************************/
-
-static inline Point2f applyHomography( const Mat_<double>& H, const Point2f& pt )
-{
- double z = H(2,0)*pt.x + H(2,1)*pt.y + H(2,2);
- if( z )
- {
- double w = 1./z;
- return Point2f( (float)((H(0,0)*pt.x + H(0,1)*pt.y + H(0,2))*w),
- (float)((H(1,0)*pt.x + H(1,1)*pt.y + H(1,2))*w) );
- }
- return Point2f( numeric_limits<float>::max(), numeric_limits<float>::max() );
-}
-
-static inline void linearizeHomographyAt( const Mat_<double>& H, const Point2f& pt, Mat_<double>& A )
-{
- A.create(2,2);
- double p1 = H(0,0)*pt.x + H(0,1)*pt.y + H(0,2),
- p2 = H(1,0)*pt.x + H(1,1)*pt.y + H(1,2),
- p3 = H(2,0)*pt.x + H(2,1)*pt.y + H(2,2),
- p3_2 = p3*p3;
- if( p3 )
- {
- A(0,0) = H(0,0)/p3 - p1*H(2,0)/p3_2; // fxdx
- A(0,1) = H(0,1)/p3 - p1*H(2,1)/p3_2; // fxdy
-
- A(1,0) = H(1,0)/p3 - p2*H(2,0)/p3_2; // fydx
- A(1,1) = H(1,1)/p3 - p2*H(2,1)/p3_2; // fydx
- }
- else
- A.setTo(Scalar::all(numeric_limits<double>::max()));
-}
-
-static void calcKeyPointProjections( const vector<KeyPoint>& src, const Mat_<double>& H, vector<KeyPoint>& dst )
-{
- if( !src.empty() )
- {
- assert( !H.empty() && H.cols == 3 && H.rows == 3);
- dst.resize(src.size());
- vector<KeyPoint>::const_iterator srcIt = src.begin();
- vector<KeyPoint>::iterator dstIt = dst.begin();
- for( ; srcIt != src.end(); ++srcIt, ++dstIt )
- {
- Point2f dstPt = applyHomography(H, srcIt->pt);
-
- float srcSize2 = srcIt->size * srcIt->size;
- Mat_<double> M(2, 2);
- M(0,0) = M(1,1) = 1./srcSize2;
- M(1,0) = M(0,1) = 0;
- Mat_<double> invM; invert(M, invM);
- Mat_<double> Aff; linearizeHomographyAt(H, srcIt->pt, Aff);
- Mat_<double> dstM; invert(Aff*invM*Aff.t(), dstM);
- Mat_<double> eval; eigen( dstM, eval );
- assert( eval(0,0) && eval(1,0) );
- float dstSize = (float)pow(1./(eval(0,0)*eval(1,0)), 0.25);
-
- // TODO: check angle projection
- float srcAngleRad = (float)(srcIt->angle*CV_PI/180);
- Point2f vec1(cos(srcAngleRad), sin(srcAngleRad)), vec2;
- vec2.x = (float)(Aff(0,0)*vec1.x + Aff(0,1)*vec1.y);
- vec2.y = (float)(Aff(1,0)*vec1.x + Aff(0,1)*vec1.y);
- float dstAngleGrad = fastAtan2(vec2.y, vec2.x);
-
- *dstIt = KeyPoint( dstPt, dstSize, dstAngleGrad, srcIt->response, srcIt->octave, srcIt->class_id );
- }
- }
-}
-
-static void filterKeyPointsByImageSize( vector<KeyPoint>& keypoints, const Size& imgSize )
-{
- if( !keypoints.empty() )
- {
- vector<KeyPoint> filtered;
- filtered.reserve(keypoints.size());
- Rect r(0, 0, imgSize.width, imgSize.height);
- vector<KeyPoint>::const_iterator it = keypoints.begin();
- for( int i = 0; it != keypoints.end(); ++it, i++ )
- if( r.contains(it->pt) )
- filtered.push_back(*it);
- keypoints.assign(filtered.begin(), filtered.end());
- }
-}
-
-/****************************************************************************************\
-* Detectors evaluation *
-\****************************************************************************************/
-const int DATASETS_COUNT = 8;
-const int TEST_CASE_COUNT = 5;
-
-const string IMAGE_DATASETS_DIR = "detectors_descriptors_evaluation/images_datasets/";
-const string DETECTORS_DIR = "detectors_descriptors_evaluation/detectors/";
-const string DESCRIPTORS_DIR = "detectors_descriptors_evaluation/descriptors/";
-const string KEYPOINTS_DIR = "detectors_descriptors_evaluation/keypoints_datasets/";
-
-const string PARAMS_POSTFIX = "_params.xml";
-const string RES_POSTFIX = "_res.xml";
-
-const string REPEAT = "repeatability";
-const string CORRESP_COUNT = "correspondence_count";
-
-string DATASET_NAMES[DATASETS_COUNT] = { "bark", "bikes", "boat", "graf", "leuven", "trees", "ubc", "wall"};
-
-string DEFAULT_PARAMS = "default";
-
-string IS_ACTIVE_PARAMS = "isActiveParams";
-string IS_SAVE_KEYPOINTS = "isSaveKeypoints";
-
-
-class BaseQualityTest : public CvTest
-{
-public:
- BaseQualityTest( const char* _algName, const char* _testName, const char* _testFuncs ) :
- CvTest( _testName, _testFuncs ), algName(_algName)
- {
- //TODO: change this
- isWriteGraphicsData = true;
- }
-
-protected:
- virtual string getRunParamsFilename() const = 0;
- virtual string getResultsFilename() const = 0;
- virtual string getPlotPath() const = 0;
-
- virtual void validQualityClear( int datasetIdx ) = 0;
- virtual void calcQualityClear( int datasetIdx ) = 0;
- virtual void validQualityCreate( int datasetIdx ) = 0;
- virtual bool isValidQualityEmpty( int datasetIdx ) const = 0;
- virtual bool isCalcQualityEmpty( int datasetIdx ) const = 0;
-
- void readAllDatasetsRunParams();
- virtual void readDatasetRunParams( FileNode& fn, int datasetIdx ) = 0;
- void writeAllDatasetsRunParams() const;
- virtual void writeDatasetRunParams( FileStorage& fs, int datasetIdx ) const = 0;
- void setDefaultAllDatasetsRunParams();
- virtual void setDefaultDatasetRunParams( int datasetIdx ) = 0;
- virtual void readDefaultRunParams( FileNode& /*fn*/ ) {}
- virtual void writeDefaultRunParams( FileStorage& /*fs*/ ) const {}
-
- virtual void readResults();
- virtual void readResults( FileNode& fn, int datasetIdx, int caseIdx ) = 0;
- void writeResults() const;
- virtual void writeResults( FileStorage& fs, int datasetIdx, int caseIdx ) const = 0;
-
- bool readDataset( const string& datasetName, vector<Mat>& Hs, vector<Mat>& imgs );
-
- virtual void readAlgorithm( ) {};
- virtual void processRunParamsFile () {};
- virtual void runDatasetTest( const vector<Mat>& /*imgs*/, const vector<Mat>& /*Hs*/, int /*di*/, int& /*progress*/ ) {}
- void run( int );
-
- virtual void processResults( int datasetIdx );
- virtual int processResults( int datasetIdx, int caseIdx ) = 0;
- virtual void processResults();
- virtual void writePlotData( int /*datasetIdx*/ ) const {}
- virtual void writeAveragePlotData() const {};
-
- string algName;
- bool isWriteParams, isWriteResults, isWriteGraphicsData;
-};
-
-void BaseQualityTest::readAllDatasetsRunParams()
-{
- string filename = getRunParamsFilename();
- FileStorage fs( filename, FileStorage::READ );
- if( !fs.isOpened() )
- {
- isWriteParams = true;
- setDefaultAllDatasetsRunParams();
- ts->printf(CvTS::LOG, "all runParams are default\n");
- }
- else
- {
- isWriteParams = false;
- FileNode topfn = fs.getFirstTopLevelNode();
-
- FileNode fn = topfn[DEFAULT_PARAMS];
- readDefaultRunParams(fn);
-
- for( int i = 0; i < DATASETS_COUNT; i++ )
- {
- FileNode fn = topfn[DATASET_NAMES[i]];
- if( fn.empty() )
- {
- ts->printf( CvTS::LOG, "%d-runParams is default\n", i);
- setDefaultDatasetRunParams(i);
- }
- else
- readDatasetRunParams(fn, i);
- }
- }
-}
-
-void BaseQualityTest::writeAllDatasetsRunParams() const
-{
- string filename = getRunParamsFilename();
- FileStorage fs( filename, FileStorage::WRITE );
- if( fs.isOpened() )
- {
- fs << "run_params" << "{"; // top file node
- fs << DEFAULT_PARAMS << "{";
- writeDefaultRunParams(fs);
- fs << "}";
- for( int i = 0; i < DATASETS_COUNT; i++ )
- {
- fs << DATASET_NAMES[i] << "{";
- writeDatasetRunParams(fs, i);
- fs << "}";
- }
- fs << "}";
- }
- else
- ts->printf(CvTS::LOG, "file %s for writing run params can not be opened\n", filename.c_str() );
-}
-
-void BaseQualityTest::setDefaultAllDatasetsRunParams()
-{
- for( int i = 0; i < DATASETS_COUNT; i++ )
- setDefaultDatasetRunParams(i);
-}
-
-bool BaseQualityTest::readDataset( const string& datasetName, vector<Mat>& Hs, vector<Mat>& imgs )
-{
- Hs.resize( TEST_CASE_COUNT );
- imgs.resize( TEST_CASE_COUNT+1 );
- string dirname = string(ts->get_data_path()) + IMAGE_DATASETS_DIR + datasetName + "/";
-
- for( int i = 0; i < (int)Hs.size(); i++ )
- {
- stringstream filename; filename << "H1to" << i+2 << "p.xml";
- FileStorage fs( dirname + filename.str(), FileStorage::READ );
- if( !fs.isOpened() )
- return false;
- fs.getFirstTopLevelNode() >> Hs[i];
- }
-
- for( int i = 0; i < (int)imgs.size(); i++ )
- {
- stringstream filename; filename << "img" << i+1 << ".png";
- imgs[i] = imread( dirname + filename.str(), 0 );
- if( imgs[i].empty() )
- return false;
- }
- return true;
-}
-
-void BaseQualityTest::readResults()
-{
- string filename = getResultsFilename();
- FileStorage fs( filename, FileStorage::READ );
- if( fs.isOpened() )
- {
- isWriteResults = false;
- FileNode topfn = fs.getFirstTopLevelNode();
- for( int di = 0; di < DATASETS_COUNT; di++ )
- {
- FileNode datafn = topfn[DATASET_NAMES[di]];
- if( datafn.empty() )
- {
- validQualityClear(di);
- ts->printf( CvTS::LOG, "results for %s dataset were not read\n",
- DATASET_NAMES[di].c_str() );
- }
- else
- {
- validQualityCreate(di);
- for( int ci = 0; ci < TEST_CASE_COUNT; ci++ )
- {
- stringstream ss; ss << "case" << ci;
- FileNode casefn = datafn[ss.str()];
- CV_Assert( !casefn.empty() );
- readResults( casefn , di, ci );
- }
- }
- }
- }
- else
- isWriteResults = true;
-}
-
-void BaseQualityTest::writeResults() const
-{
- string filename = getResultsFilename();;
- FileStorage fs( filename, FileStorage::WRITE );
- if( fs.isOpened() )
- {
- fs << "results" << "{";
- for( int di = 0; di < DATASETS_COUNT; di++ )
- {
- if( isCalcQualityEmpty(di) )
- {
- ts->printf(CvTS::LOG, "results on %s dataset were not write because of empty\n",
- DATASET_NAMES[di].c_str());
- }
- else
- {
- fs << DATASET_NAMES[di] << "{";
- for( int ci = 0; ci < TEST_CASE_COUNT; ci++ )
- {
- stringstream ss; ss << "case" << ci;
- fs << ss.str() << "{";
- writeResults( fs, di, ci );
- fs << "}"; //ss.str()
- }
- fs << "}"; //DATASET_NAMES[di]
- }
- }
- fs << "}"; //results
- }
- else
- ts->printf(CvTS::LOG, "results were not written because file %s can not be opened\n", filename.c_str() );
-}
-
-void BaseQualityTest::processResults( int datasetIdx )
-{
- if( isWriteGraphicsData )
- writePlotData( datasetIdx );
-}
-
-void BaseQualityTest::processResults()
-{
- if( isWriteParams )
- writeAllDatasetsRunParams();
-
- if( isWriteGraphicsData )
- writeAveragePlotData();
-
- int res = CvTS::OK;
- if( isWriteResults )
- writeResults();
- else
- {
- for( int di = 0; di < DATASETS_COUNT; di++ )
- {
- if( isValidQualityEmpty(di) || isCalcQualityEmpty(di) )
- continue;
-
- ts->printf(CvTS::LOG, "\nDataset: %s\n", DATASET_NAMES[di].c_str() );
-
- for( int ci = 0; ci < TEST_CASE_COUNT; ci++ )
- {
- ts->printf(CvTS::LOG, "case%d\n", ci);
- int currRes = processResults( di, ci );
- res = currRes == CvTS::OK ? res : currRes;
- }
- }
- }
-
- if( res != CvTS::OK )
- ts->printf(CvTS::LOG, "BAD ACCURACY\n");
- ts->set_failed_test_info( res );
-}
-
-void BaseQualityTest::run ( int )
-{
- readAlgorithm ();
- processRunParamsFile ();
- readResults();
-
- int notReadDatasets = 0;
- int progress = 0;
-
- FileStorage runParamsFS( getRunParamsFilename(), FileStorage::READ );
- isWriteParams = (! runParamsFS.isOpened());
- FileNode topfn = runParamsFS.getFirstTopLevelNode();
- FileNode defaultParams = topfn[DEFAULT_PARAMS];
- readDefaultRunParams (defaultParams);
-
- for(int di = 0; di < DATASETS_COUNT; di++ )
- {
- vector<Mat> imgs, Hs;
- if( !readDataset( DATASET_NAMES[di], Hs, imgs ) )
- {
- calcQualityClear (di);
- ts->printf( CvTS::LOG, "images or homography matrices of dataset named %s can not be read\n",
- DATASET_NAMES[di].c_str());
- notReadDatasets++;
- continue;
- }
-
- FileNode fn = topfn[DATASET_NAMES[di]];
- readDatasetRunParams(fn, di);
-
- runDatasetTest (imgs, Hs, di, progress);
- processResults( di );
- }
- if( notReadDatasets == DATASETS_COUNT )
- {
- ts->printf(CvTS::LOG, "All datasets were not be read\n");
- ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA );
- }
- else
- processResults();
- runParamsFS.release();
-}
-
-
-
-class DetectorQualityTest : public BaseQualityTest
-{
-public:
- DetectorQualityTest( const char* _detectorName, const char* _testName ) :
- BaseQualityTest( _detectorName, _testName, "quality-of-detector" )
- {
- validQuality.resize(DATASETS_COUNT);
- calcQuality.resize(DATASETS_COUNT);
- isSaveKeypoints.resize(DATASETS_COUNT);
- isActiveParams.resize(DATASETS_COUNT);
-
- isSaveKeypointsDefault = false;
- isActiveParamsDefault = false;
- }
-
-protected:
- using BaseQualityTest::readResults;
- using BaseQualityTest::writeResults;
- using BaseQualityTest::processResults;
-
- virtual string getRunParamsFilename() const;
- virtual string getResultsFilename() const;
- virtual string getPlotPath() const;
-
- virtual void validQualityClear( int datasetIdx );
- virtual void calcQualityClear( int datasetIdx );
- virtual void validQualityCreate( int datasetIdx );
- virtual bool isValidQualityEmpty( int datasetIdx ) const;
- virtual bool isCalcQualityEmpty( int datasetIdx ) const;
-
- virtual void readResults( FileNode& fn, int datasetIdx, int caseIdx );
- virtual void writeResults( FileStorage& fs, int datasetIdx, int caseIdx ) const;
-
- virtual void readDatasetRunParams( FileNode& fn, int datasetIdx );
- virtual void writeDatasetRunParams( FileStorage& fs, int datasetIdx ) const;
- virtual void setDefaultDatasetRunParams( int datasetIdx );
- virtual void readDefaultRunParams( FileNode &fn );
- virtual void writeDefaultRunParams( FileStorage &fs ) const;
-
- virtual void writePlotData( int di ) const;
- virtual void writeAveragePlotData() const;
-
- void openToWriteKeypointsFile( FileStorage& fs, int datasetIdx );
-
- virtual void readAlgorithm( );
- virtual void processRunParamsFile () {};
- virtual void runDatasetTest( const vector<Mat> &imgs, const vector<Mat> &Hs, int di, int &progress );
- virtual int processResults( int datasetIdx, int caseIdx );
-
- Ptr<FeatureDetector> specificDetector;
- Ptr<FeatureDetector> defaultDetector;
-
- struct Quality
- {
- float repeatability;
- int correspondenceCount;
- };
- vector<vector<Quality> > validQuality;
- vector<vector<Quality> > calcQuality;
-
- vector<bool> isSaveKeypoints;
- vector<bool> isActiveParams;
-
- bool isSaveKeypointsDefault;
- bool isActiveParamsDefault;
-};
-
-string DetectorQualityTest::getRunParamsFilename() const
-{
- return string(ts->get_data_path()) + DETECTORS_DIR + algName + PARAMS_POSTFIX;
-}
-
-string DetectorQualityTest::getResultsFilename() const
-{
- return string(ts->get_data_path()) + DETECTORS_DIR + algName + RES_POSTFIX;
-}
-
-string DetectorQualityTest::getPlotPath() const
-{
- return string(ts->get_data_path()) + DETECTORS_DIR + "plots/";
-}
-
-void DetectorQualityTest::validQualityClear( int datasetIdx )
-{
- validQuality[datasetIdx].clear();
-}
-
-void DetectorQualityTest::calcQualityClear( int datasetIdx )
-{
- calcQuality[datasetIdx].clear();
-}
-
-void DetectorQualityTest::validQualityCreate( int datasetIdx )
-{
- validQuality[datasetIdx].resize(TEST_CASE_COUNT);
-}
-
-bool DetectorQualityTest::isValidQualityEmpty( int datasetIdx ) const
-{
- return validQuality[datasetIdx].empty();
-}
-
-bool DetectorQualityTest::isCalcQualityEmpty( int datasetIdx ) const
-{
- return calcQuality[datasetIdx].empty();
-}
-
-void DetectorQualityTest::readResults( FileNode& fn, int datasetIdx, int caseIdx )
-{
- validQuality[datasetIdx][caseIdx].repeatability = fn[REPEAT];
- validQuality[datasetIdx][caseIdx].correspondenceCount = fn[CORRESP_COUNT];
-}
-
-void DetectorQualityTest::writeResults( FileStorage& fs, int datasetIdx, int caseIdx ) const
-{
- fs << REPEAT << calcQuality[datasetIdx][caseIdx].repeatability;
- fs << CORRESP_COUNT << calcQuality[datasetIdx][caseIdx].correspondenceCount;
-}
-
-void DetectorQualityTest::readDefaultRunParams (FileNode &fn)
-{
- if (! fn.empty() )
- {
- isSaveKeypointsDefault = (int)fn[IS_SAVE_KEYPOINTS] != 0;
- defaultDetector->read (fn);
- }
-}
-
-void DetectorQualityTest::writeDefaultRunParams (FileStorage &fs) const
-{
- fs << IS_SAVE_KEYPOINTS << isSaveKeypointsDefault;
- defaultDetector->write (fs);
-}
-
-void DetectorQualityTest::readDatasetRunParams( FileNode& fn, int datasetIdx )
-{
- isActiveParams[datasetIdx] = (int)fn[IS_ACTIVE_PARAMS] != 0;
- if (isActiveParams[datasetIdx])
- {
- isSaveKeypoints[datasetIdx] = (int)fn[IS_SAVE_KEYPOINTS] != 0;
- specificDetector->read (fn);
- }
- else
- {
- setDefaultDatasetRunParams(datasetIdx);
- }
-}
-
-void DetectorQualityTest::writeDatasetRunParams( FileStorage& fs, int datasetIdx ) const
-{
- fs << IS_ACTIVE_PARAMS << isActiveParams[datasetIdx];
- fs << IS_SAVE_KEYPOINTS << isSaveKeypoints[datasetIdx];
- defaultDetector->write (fs);
-}
-
-void DetectorQualityTest::setDefaultDatasetRunParams( int datasetIdx )
-{
- isSaveKeypoints[datasetIdx] = isSaveKeypointsDefault;
- isActiveParams[datasetIdx] = isActiveParamsDefault;
-}
-
-void DetectorQualityTest::writePlotData(int di ) const
-{
- int imgXVals[] = { 2, 3, 4, 5, 6 }; // if scale, blur or light changes
- int viewpointXVals[] = { 20, 30, 40, 50, 60 }; // if viewpoint changes
- int jpegXVals[] = { 60, 80, 90, 95, 98 }; // if jpeg compression
-
- int* xVals = 0;
- if( !DATASET_NAMES[di].compare("ubc") )
- {
- xVals = jpegXVals;
- }
- else if( !DATASET_NAMES[di].compare("graf") || !DATASET_NAMES[di].compare("wall") )
- {
- xVals = viewpointXVals;
- }
- else
- xVals = imgXVals;
-
- stringstream rFilename, cFilename;
- rFilename << getPlotPath() << algName << "_" << DATASET_NAMES[di] << "_repeatability.csv";
- cFilename << getPlotPath() << algName << "_" << DATASET_NAMES[di] << "_correspondenceCount.csv";
- ofstream rfile(rFilename.str().c_str()), cfile(cFilename.str().c_str());
- for( int ci = 0; ci < TEST_CASE_COUNT; ci++ )
- {
- rfile << xVals[ci] << ", " << calcQuality[di][ci].repeatability << endl;
- cfile << xVals[ci] << ", " << calcQuality[di][ci].correspondenceCount << endl;
- }
-}
-
-void DetectorQualityTest::writeAveragePlotData() const
-{
- stringstream rFilename, cFilename;
- rFilename << getPlotPath() << algName << "_average_repeatability.csv";
- cFilename << getPlotPath() << algName << "_average_correspondenceCount.csv";
- ofstream rfile(rFilename.str().c_str()), cfile(cFilename.str().c_str());
- float avRep = 0, avCorCount = 0;
- for( int di = 0; di < DATASETS_COUNT; di++ )
- {
- for( int ci = 0; ci < TEST_CASE_COUNT; ci++ )
- {
- avRep += calcQuality[di][ci].repeatability;
- avCorCount += calcQuality[di][ci].correspondenceCount;
- }
- }
- avRep /= DATASETS_COUNT*TEST_CASE_COUNT;
- avCorCount /= DATASETS_COUNT*TEST_CASE_COUNT;
- rfile << algName << ", " << avRep << endl;
- cfile << algName << ", " << cvRound(avCorCount) << endl;
-}
-
-void DetectorQualityTest::openToWriteKeypointsFile( FileStorage& fs, int datasetIdx )
-{
- string filename = string(ts->get_data_path()) + KEYPOINTS_DIR + algName + "_"+
- DATASET_NAMES[datasetIdx] + ".xml.gz" ;
-
- fs.open(filename, FileStorage::WRITE);
- if( !fs.isOpened() )
- ts->printf( CvTS::LOG, "keypoints can not be written in file %s because this file can not be opened\n",
- filename.c_str());
-}
-
-inline void writeKeypoints( FileStorage& fs, const vector<KeyPoint>& keypoints, int imgIdx )
-{
- if( fs.isOpened() )
- {
- stringstream imgName; imgName << "img" << imgIdx;
- write( fs, imgName.str(), keypoints );
- }
-}
-
-inline void readKeypoints( FileStorage& fs, vector<KeyPoint>& keypoints, int imgIdx )
-{
- assert( fs.isOpened() );
- stringstream imgName; imgName << "img" << imgIdx;
- read( fs[imgName.str()], keypoints);
-}
-
-void DetectorQualityTest::readAlgorithm ()
-{
- defaultDetector = FeatureDetector::create( algName );
- specificDetector = FeatureDetector::create( algName );
- if( defaultDetector == 0 )
- {
- ts->printf(CvTS::LOG, "Algorithm can not be read\n");
- ts->set_failed_test_info( CvTS::FAIL_GENERIC);
- }
-}
-
-void DetectorQualityTest::runDatasetTest (const vector<Mat> &imgs, const vector<Mat> &Hs, int di, int &progress)
-{
- Ptr<FeatureDetector> detector = isActiveParams[di] ? specificDetector : defaultDetector;
- FileStorage keypontsFS;
- if( isSaveKeypoints[di] )
- openToWriteKeypointsFile( keypontsFS, di );
-
- calcQuality[di].resize(TEST_CASE_COUNT);
-
- vector<KeyPoint> keypoints1;
- detector->detect( imgs[0], keypoints1 );
- writeKeypoints( keypontsFS, keypoints1, 0);
- int progressCount = DATASETS_COUNT*TEST_CASE_COUNT;
- for( int ci = 0; ci < TEST_CASE_COUNT; ci++ )
- {
- progress = update_progress( progress, di*TEST_CASE_COUNT + ci, progressCount, 0 );
- vector<KeyPoint> keypoints2;
- float rep;
- evaluateFeatureDetector( imgs[0], imgs[ci+1], Hs[ci], &keypoints1, &keypoints2,
- rep, calcQuality[di][ci].correspondenceCount,
- detector );
- calcQuality[di][ci].repeatability = rep == -1 ? rep : 100.f*rep;
- writeKeypoints( keypontsFS, keypoints2, ci+1);
- }
-}
-
-void testLog( CvTS* ts, bool isBadAccuracy )
-{
- if( isBadAccuracy )
- ts->printf(CvTS::LOG, " bad accuracy\n");
- else
- ts->printf(CvTS::LOG, "\n");
-}
-
-int DetectorQualityTest::processResults( int datasetIdx, int caseIdx )
-{
- int res = CvTS::OK;
- bool isBadAccuracy;
-
- Quality valid = validQuality[datasetIdx][caseIdx], calc = calcQuality[datasetIdx][caseIdx];
-
- const int countEps = 1 + cvRound( 0.005f*(float)valid.correspondenceCount );
- const float rltvEps = 0.5f;
-
- ts->printf(CvTS::LOG, "%s: calc=%f, valid=%f", REPEAT.c_str(), calc.repeatability, valid.repeatability );
- isBadAccuracy = (valid.repeatability - calc.repeatability) > rltvEps;
- testLog( ts, isBadAccuracy );
- res = isBadAccuracy ? CvTS::FAIL_BAD_ACCURACY : res;
-
- ts->printf(CvTS::LOG, "%s: calc=%d, valid=%d", CORRESP_COUNT.c_str(), calc.correspondenceCount, valid.correspondenceCount );
- isBadAccuracy = (valid.correspondenceCount - calc.correspondenceCount) > countEps;
- testLog( ts, isBadAccuracy );
- res = isBadAccuracy ? CvTS::FAIL_BAD_ACCURACY : res;
- return res;
-}
-
-/****************************************************************************************\
-* Descriptors evaluation *
-\****************************************************************************************/
-
-const string RECALL = "recall";
-const string PRECISION = "precision";
-
-const string KEYPOINTS_FILENAME = "keypointsFilename";
-const string PROJECT_KEYPOINTS_FROM_1IMAGE = "projectKeypointsFrom1Image";
-const string MATCH_FILTER = "matchFilter";
-const string RUN_PARAMS_IS_IDENTICAL = "runParamsIsIdentical";
-
-const string ONE_WAY_TRAIN_DIR = "detectors_descriptors_evaluation/one_way_train_images/";
-const string ONE_WAY_IMAGES_LIST = "one_way_train_images.txt";
-
-class DescriptorQualityTest : public BaseQualityTest
-{
-public:
- enum{ NO_MATCH_FILTER = 0 };
- DescriptorQualityTest( const char* _descriptorName, const char* _testName, const char* _matcherName = 0 ) :
- BaseQualityTest( _descriptorName, _testName, "quality-of-descriptor" )
- {
- validQuality.resize(DATASETS_COUNT);
- calcQuality.resize(DATASETS_COUNT);
- calcDatasetQuality.resize(DATASETS_COUNT);
- commRunParams.resize(DATASETS_COUNT);
-
- commRunParamsDefault.projectKeypointsFrom1Image = true;
- commRunParamsDefault.matchFilter = NO_MATCH_FILTER;
- commRunParamsDefault.isActiveParams = false;
-
- if( _matcherName )
- matcherName = _matcherName;
- }
-
-protected:
- using BaseQualityTest::readResults;
- using BaseQualityTest::writeResults;
- using BaseQualityTest::processResults;
-
- virtual string getRunParamsFilename() const;
- virtual string getResultsFilename() const;
- virtual string getPlotPath() const;
-
- virtual void validQualityClear( int datasetIdx );
- virtual void calcQualityClear( int datasetIdx );
- virtual void validQualityCreate( int datasetIdx );
- virtual bool isValidQualityEmpty( int datasetIdx ) const;
- virtual bool isCalcQualityEmpty( int datasetIdx ) const;
-
- virtual void readResults( FileNode& fn, int datasetIdx, int caseIdx );
- virtual void writeResults( FileStorage& fs, int datasetIdx, int caseIdx ) const;
-
- virtual void readDatasetRunParams( FileNode& fn, int datasetIdx ); //
- virtual void writeDatasetRunParams( FileStorage& fs, int datasetIdx ) const;
- virtual void setDefaultDatasetRunParams( int datasetIdx );
- virtual void readDefaultRunParams( FileNode &fn );
- virtual void writeDefaultRunParams( FileStorage &fs ) const;
-
- virtual void readAlgorithm( );
- virtual void processRunParamsFile () {};
- virtual void runDatasetTest( const vector<Mat> &imgs, const vector<Mat> &Hs, int di, int &progress );
-
- virtual int processResults( int datasetIdx, int caseIdx );
-
- virtual void writePlotData( int di ) const;
- void calculatePlotData( vector<vector<DMatch> > &allMatches, vector<vector<uchar> > &allCorrectMatchesMask, int di );
-
- struct Quality
- {
- float recall;
- float precision;
- };
- vector<vector<Quality> > validQuality;
- vector<vector<Quality> > calcQuality;
- vector<vector<Quality> > calcDatasetQuality;
-
- struct CommonRunParams
- {
- string keypontsFilename;
- bool projectKeypointsFrom1Image;
- int matchFilter; // not used now
- bool isActiveParams;
- };
- vector<CommonRunParams> commRunParams;
-
- Ptr<GenericDescriptorMatch> specificDescMatcher;
- Ptr<GenericDescriptorMatch> defaultDescMatcher;
-
- CommonRunParams commRunParamsDefault;
- string matcherName;
-};
-
-string DescriptorQualityTest::getRunParamsFilename() const
-{
- return string(ts->get_data_path()) + DESCRIPTORS_DIR + algName + PARAMS_POSTFIX;
-}
-
-string DescriptorQualityTest::getResultsFilename() const
-{
- return string(ts->get_data_path()) + DESCRIPTORS_DIR + algName + RES_POSTFIX;
-}
-
-string DescriptorQualityTest::getPlotPath() const
-{
- return string(ts->get_data_path()) + DESCRIPTORS_DIR + "plots/";
-}
-
-void DescriptorQualityTest::validQualityClear( int datasetIdx )
-{
- validQuality[datasetIdx].clear();
-}
-
-void DescriptorQualityTest::calcQualityClear( int datasetIdx )
-{
- calcQuality[datasetIdx].clear();
-}
-
-void DescriptorQualityTest::validQualityCreate( int datasetIdx )
-{
- validQuality[datasetIdx].resize(TEST_CASE_COUNT);
-}
-
-bool DescriptorQualityTest::isValidQualityEmpty( int datasetIdx ) const
-{
- return validQuality[datasetIdx].empty();
-}
-
-bool DescriptorQualityTest::isCalcQualityEmpty( int datasetIdx ) const
-{
- return calcQuality[datasetIdx].empty();
-}
-
-void DescriptorQualityTest::readResults( FileNode& fn, int datasetIdx, int caseIdx )
-{
- validQuality[datasetIdx][caseIdx].recall = fn[RECALL];
- validQuality[datasetIdx][caseIdx].precision = fn[PRECISION];
-}
-
-void DescriptorQualityTest::writeResults( FileStorage& fs, int datasetIdx, int caseIdx ) const
-{
- fs << RECALL << calcQuality[datasetIdx][caseIdx].recall;
- fs << PRECISION << calcQuality[datasetIdx][caseIdx].precision;
-}
-
-void DescriptorQualityTest::readDefaultRunParams (FileNode &fn)
-{
- if (! fn.empty() )
- {
- commRunParamsDefault.projectKeypointsFrom1Image = (int)fn[PROJECT_KEYPOINTS_FROM_1IMAGE] != 0;
- commRunParamsDefault.matchFilter = (int)fn[MATCH_FILTER];
- defaultDescMatcher->read (fn);
- }
-}
-
-void DescriptorQualityTest::writeDefaultRunParams (FileStorage &fs) const
-{
- fs << PROJECT_KEYPOINTS_FROM_1IMAGE << commRunParamsDefault.projectKeypointsFrom1Image;
- fs << MATCH_FILTER << commRunParamsDefault.matchFilter;
- defaultDescMatcher->write (fs);
-}
-
-void DescriptorQualityTest::readDatasetRunParams( FileNode& fn, int datasetIdx )
-{
- commRunParams[datasetIdx].isActiveParams = (int)fn[IS_ACTIVE_PARAMS] != 0;
- if (commRunParams[datasetIdx].isActiveParams)
- {
- commRunParams[datasetIdx].keypontsFilename = (string)fn[KEYPOINTS_FILENAME];
- commRunParams[datasetIdx].projectKeypointsFrom1Image = (int)fn[PROJECT_KEYPOINTS_FROM_1IMAGE] != 0;
- commRunParams[datasetIdx].matchFilter = (int)fn[MATCH_FILTER];
- specificDescMatcher->read (fn);
- }
- else
- {
- setDefaultDatasetRunParams(datasetIdx);
- }
-}
-
-void DescriptorQualityTest::writeDatasetRunParams( FileStorage& fs, int datasetIdx ) const
-{
- fs << IS_ACTIVE_PARAMS << commRunParams[datasetIdx].isActiveParams;
- fs << KEYPOINTS_FILENAME << commRunParams[datasetIdx].keypontsFilename;
- fs << PROJECT_KEYPOINTS_FROM_1IMAGE << commRunParams[datasetIdx].projectKeypointsFrom1Image;
- fs << MATCH_FILTER << commRunParams[datasetIdx].matchFilter;
-
- defaultDescMatcher->write (fs);
-}
-
-void DescriptorQualityTest::setDefaultDatasetRunParams( int datasetIdx )
-{
- commRunParams[datasetIdx] = commRunParamsDefault;
- commRunParams[datasetIdx].keypontsFilename = "SURF_" + DATASET_NAMES[datasetIdx] + ".xml.gz";
-}
-
-void DescriptorQualityTest::writePlotData( int di ) const
-{
- stringstream filename;
- filename << getPlotPath() << algName << "_" << DATASET_NAMES[di] << ".csv";
- FILE *file = fopen (filename.str().c_str(), "w");
- size_t size = calcDatasetQuality[di].size();
- for (size_t i=0;i<size;i++)
- {
- fprintf( file, "%f, %f\n", 1 - calcDatasetQuality[di][i].precision, calcDatasetQuality[di][i].recall);
- }
- fclose( file );
-}
-
-void DescriptorQualityTest::readAlgorithm( )
-{
- defaultDescMatcher = GenericDescriptorMatcher::create( algName );
- specificDescMatcher = GenericDescriptorMatcher::create( algName );
-
- if( defaultDescMatcher == 0 )
- {
- Ptr<DescriptorExtractor> extractor = DescriptorExtractor::create( algName );
- Ptr<DescriptorMatcher> matcher = DescriptorMatcher::create( matcherName );
- defaultDescMatcher = new VectorDescriptorMatch( extractor, matcher );
- specificDescMatcher = new VectorDescriptorMatch( extractor, matcher );
-
- if( extractor == 0 || matcher == 0 )
- {
- ts->printf(CvTS::LOG, "Algorithm can not be read\n");
- ts->set_failed_test_info( CvTS::FAIL_GENERIC);
- }
- }
-}
-
-void DescriptorQualityTest::calculatePlotData( vector<vector<DMatch> > &allMatches, vector<vector<uchar> > &allCorrectMatchesMask, int di )
-{
- vector<Point2f> recallPrecisionCurve;
- computeRecallPrecisionCurve( allMatches, allCorrectMatchesMask, recallPrecisionCurve );
-
- calcDatasetQuality[di].clear();
- const float resultPrecision = 0.5;
- bool isResultCalculated = false;
- const double eps = 1e-2;
-
- Quality initQuality;
- initQuality.recall = 0;
- initQuality.precision = 0;
- calcDatasetQuality[di].push_back( initQuality );
-
- for( size_t i=0;i<recallPrecisionCurve.size();i++ )
- {
- Quality quality;
- quality.recall = recallPrecisionCurve[i].y;
- quality.precision = 1 - recallPrecisionCurve[i].x;
- Quality back = calcDatasetQuality[di].back();
-
- if( fabs( quality.recall - back.recall ) < eps && fabs( quality.precision - back.precision ) < eps )
- continue;
-
- calcDatasetQuality[di].push_back( quality );
-
- if( !isResultCalculated && quality.precision < resultPrecision )
- {
- for(int ci=0;ci<TEST_CASE_COUNT;ci++)
- {
- calcQuality[di][ci].recall = quality.recall;
- calcQuality[di][ci].precision = quality.precision;
- }
- isResultCalculated = true;
- }
- }
-}
-
-void DescriptorQualityTest::runDatasetTest (const vector<Mat> &imgs, const vector<Mat> &Hs, int di, int &progress)
-{
- FileStorage keypontsFS( string(ts->get_data_path()) + KEYPOINTS_DIR + commRunParams[di].keypontsFilename,
- FileStorage::READ );
- if( !keypontsFS.isOpened())
- {
- calcQuality[di].clear();
- ts->printf( CvTS::LOG, "keypoints from file %s can not be read\n", commRunParams[di].keypontsFilename.c_str() );
- return;
- }
-
- Ptr<GenericDescriptorMatcher> descMatch = commRunParams[di].isActiveParams ? specificDescMatcher : defaultDescMatcher;
- calcQuality[di].resize(TEST_CASE_COUNT);
-
- vector<KeyPoint> keypoints1;
- readKeypoints( keypontsFS, keypoints1, 0);
-
- int progressCount = DATASETS_COUNT*TEST_CASE_COUNT;
-
- vector<vector<DMatch> > allMatches1to2;
- vector<vector<uchar> > allCorrectMatchesMask;
- for( int ci = 0; ci < TEST_CASE_COUNT; ci++ )
- {
- progress = update_progress( progress, di*TEST_CASE_COUNT + ci, progressCount, 0 );
-
- vector<KeyPoint> keypoints2;
- if( commRunParams[di].projectKeypointsFrom1Image )
- {
- // TODO need to test function calcKeyPointProjections
- calcKeyPointProjections( keypoints1, Hs[ci], keypoints2 );
- filterKeyPointsByImageSize( keypoints2, imgs[ci+1].size() );
- }
- else
- readKeypoints( keypontsFS, keypoints2, ci+1 );
- // TODO if( commRunParams[di].matchFilter )
-
- vector<vector<DMatch> > matches1to2;
- vector<vector<uchar> > correctMatchesMask;
- vector<Point2f> recallPrecisionCurve; // not used because we need recallPrecisionCurve for
- // all images in dataset
- evaluateGenericDescriptorMatcher( imgs[0], imgs[ci+1], Hs[ci], keypoints1, keypoints2,
- &matches1to2, &correctMatchesMask, recallPrecisionCurve,
- descMatch );
- allMatches1to2.insert( allMatches1to2.end(), matches1to2.begin(), matches1to2.end() );
- allCorrectMatchesMask.insert( allCorrectMatchesMask.end(), correctMatchesMask.begin(), correctMatchesMask.end() );
- }
-
- calculatePlotData( allMatches1to2, allCorrectMatchesMask, di );
-}
-
-int DescriptorQualityTest::processResults( int datasetIdx, int caseIdx )
-{
- const float rltvEps = 0.001f;
-
- int res = CvTS::OK;
- bool isBadAccuracy;
-
- Quality valid = validQuality[datasetIdx][caseIdx], calc = calcQuality[datasetIdx][caseIdx];
-
- ts->printf(CvTS::LOG, "%s: calc=%f, valid=%f", RECALL.c_str(), calc.recall, valid.recall );
- isBadAccuracy = (valid.recall - calc.recall) > rltvEps;
- testLog( ts, isBadAccuracy );
- res = isBadAccuracy ? CvTS::FAIL_BAD_ACCURACY : res;
-
- ts->printf(CvTS::LOG, "%s: calc=%f, valid=%f", PRECISION.c_str(), calc.precision, valid.precision );
- isBadAccuracy = (valid.precision - calc.precision) > rltvEps;
- testLog( ts, isBadAccuracy );
- res = isBadAccuracy ? CvTS::FAIL_BAD_ACCURACY : res;
-
- return res;
-}
-
-//--------------------------------- Calonder descriptor test --------------------------------------------
-class CalonderDescriptorQualityTest : public DescriptorQualityTest
-{
-public:
- CalonderDescriptorQualityTest() :
- DescriptorQualityTest( "Calonder", "quality-descriptor-calonder") {}
- virtual void readAlgorithm( )
- {
- string classifierFile = string(ts->get_data_path()) + "/features2d/calonder_classifier.rtc";
- defaultDescMatcher = new VectorDescriptorMatch( new CalonderDescriptorExtractor<float>( classifierFile ),
- new BruteForceMatcher<L2<float> > );
- specificDescMatcher = defaultDescMatcher;
- }
-};
-
-//--------------------------------- One Way descriptor test --------------------------------------------
-class OneWayDescriptorQualityTest : public DescriptorQualityTest
-{
-public:
- OneWayDescriptorQualityTest() :
- DescriptorQualityTest("ONEWAY", "quality-descriptor-one-way")
- {
- }
-protected:
- virtual void processRunParamsFile ();
- virtual void writeDatasetRunParams( FileStorage& fs, int datasetIdx ) const;
-};
-
-void OneWayDescriptorQualityTest::processRunParamsFile ()
-{
- string filename = getRunParamsFilename();
- FileStorage fs = FileStorage (filename, FileStorage::READ);
- FileNode fn = fs.getFirstTopLevelNode();
- fn = fn[DEFAULT_PARAMS];
-
- string pcaFilename = string(ts->get_data_path()) + (string)fn["pcaFilename"];
- string trainPath = string(ts->get_data_path()) + (string)fn["trainPath"];
- string trainImagesList = (string)fn["trainImagesList"];
- int patch_width = fn["patchWidth"];
- int patch_height = fn["patchHeight"];
- Size patchSize = cvSize (patch_width, patch_height);
- int poseCount = fn["poseCount"];
-
- if (trainImagesList.length () == 0 )
- return;
-
- fs.release ();
-
- readAllDatasetsRunParams();
-
- OneWayDescriptorBase *base = new OneWayDescriptorBase(patchSize, poseCount, pcaFilename,
- trainPath, trainImagesList);
-
- OneWayDescriptorMatch *match = new OneWayDescriptorMatch ();
- match->initialize( OneWayDescriptorMatch::Params (), base );
- defaultDescMatcher = match;
- writeAllDatasetsRunParams();
-}
-
-void OneWayDescriptorQualityTest::writeDatasetRunParams( FileStorage& fs, int datasetIdx ) const
-{
- fs << IS_ACTIVE_PARAMS << commRunParams[datasetIdx].isActiveParams;
- fs << KEYPOINTS_FILENAME << commRunParams[datasetIdx].keypontsFilename;
- fs << PROJECT_KEYPOINTS_FROM_1IMAGE << commRunParams[datasetIdx].projectKeypointsFrom1Image;
- fs << MATCH_FILTER << commRunParams[datasetIdx].matchFilter;
-}
-
-// Detectors
-//DetectorQualityTest fastDetectorQuality = DetectorQualityTest( "FAST", "quality-detector-fast" );
-//DetectorQualityTest gfttDetectorQuality = DetectorQualityTest( "GFTT", "quality-detector-gftt" );
-//DetectorQualityTest harrisDetectorQuality = DetectorQualityTest( "HARRIS", "quality-detector-harris" );
-//DetectorQualityTest mserDetectorQuality = DetectorQualityTest( "MSER", "quality-detector-mser" );
-//DetectorQualityTest starDetectorQuality = DetectorQualityTest( "STAR", "quality-detector-star" );
-//DetectorQualityTest siftDetectorQuality = DetectorQualityTest( "SIFT", "quality-detector-sift" );
-//DetectorQualityTest surfDetectorQuality = DetectorQualityTest( "SURF", "quality-detector-surf" );
-
-// Descriptors
-//DescriptorQualityTest siftDescriptorQuality = DescriptorQualityTest( "SIFT", "quality-descriptor-sift", "BruteForce" );
-//DescriptorQualityTest surfDescriptorQuality = DescriptorQualityTest( "SURF", "quality-descriptor-surf", "BruteForce" );
-//DescriptorQualityTest fernDescriptorQualityTest( "FERN", "quality-descriptor-fern");
-//CalonderDescriptorQualityTest calonderDescriptorQualityTest;
-
-
-
-// Don't run it because of bug in OneWayDescriptorBase many to many matching. TODO: fix this bug.
-//OneWayDescriptorQualityTest oneWayDescriptorQuality;
-
-// Don't run them (will validate and save results as "quality-descriptor-sift" and "quality-descriptor-surf" test data).
-// TODO: differ result filenames.
-//DescriptorQualityTest siftL1DescriptorQuality = DescriptorQualityTest( "SIFT", "quality-descriptor-sift-L1", "BruteForce-L1" );
-//DescriptorQualityTest surfL1DescriptorQuality = DescriptorQualityTest( "SURF", "quality-descriptor-surf-L1", "BruteForce-L1" );
-//DescriptorQualityTest oppSiftL1DescriptorQuality = DescriptorQualityTest( "SIFT", "quality-descriptor-opponent-sift-L1", "BruteForce-L1" );
-//DescriptorQualityTest oppSurfL1DescriptorQuality = DescriptorQualityTest( "SURF", "quality-descriptor-opponent-surf-L1", "BruteForce-L1" );
-
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-static const char* distrans_param_names[] = { "size", "dist_type", "labels", 0 };
-static const CvSize distrans_sizes[] = {{30,30}, {320, 240}, {720,480}, {-1,-1}};
-static const CvSize distrans_whole_sizes[] = {{320,240}, {320, 240}, {720,480}, {-1,-1}};
-static const char* distrans_types[] = { "c_3x3", "l1_3x3", "l2_3x3", "l2_5x5", 0 };
-static const int distrans_labels[] = { 0, 1, -1 };
-
-class CV_DisTransTest : public CvArrTest
-{
-public:
- CV_DisTransTest();
-
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- double get_success_error_level( int test_case_idx, int i, int j );
- void run_func();
- void prepare_to_validation( int );
-
- void get_minmax_bounds( int i, int j, int type, CvScalar* low, CvScalar* high );
- int prepare_test_case( int test_case_idx );
-
- int write_default_params(CvFileStorage* fs);
- void get_timing_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types,
- CvSize** whole_sizes, bool *are_images );
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
- int mask_size;
- int dist_type;
- int fill_labels;
- float mask[3];
-};
-
-
-CV_DisTransTest::CV_DisTransTest()
- : CvArrTest( "distrans", "cvDistTransform", "" )
-{
- test_array[INPUT].push(NULL);
- test_array[OUTPUT].push(NULL);
- test_array[OUTPUT].push(NULL);
- test_array[REF_OUTPUT].push(NULL);
- test_array[REF_OUTPUT].push(NULL);
- optional_mask = false;
- element_wise_relative_error = true;
-
- default_timing_param_names = distrans_param_names;
- depth_list = 0;
- size_list = distrans_sizes;
- whole_size_list = distrans_whole_sizes;
- cn_list = 0;
-}
-
-
-void CV_DisTransTest::get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- CvArrTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
-
- types[INPUT][0] = CV_8UC1;
- types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_32FC1;
- types[OUTPUT][1] = types[REF_OUTPUT][1] = CV_32SC1;
-
- if( cvTsRandInt(rng) & 1 )
- {
- mask_size = 3;
- dist_type = cvTsRandInt(rng) % 4;
- dist_type = dist_type == 0 ? CV_DIST_C : dist_type == 1 ? CV_DIST_L1 :
- dist_type == 2 ? CV_DIST_L2 : CV_DIST_USER;
- }
- else
- {
- mask_size = 5;
- dist_type = cvTsRandInt(rng) % 10;
- dist_type = dist_type == 0 ? CV_DIST_C : dist_type == 1 ? CV_DIST_L1 :
- dist_type < 6 ? CV_DIST_L2 : CV_DIST_USER;
- }
-
- // for now, check only the "labeled" distance transform mode
- fill_labels = 0;
-
- if( !fill_labels )
- sizes[OUTPUT][1] = sizes[REF_OUTPUT][1] = cvSize(0,0);
-
- if( dist_type == CV_DIST_USER )
- {
- mask[0] = (float)(1.1 - cvTsRandReal(rng)*0.2);
- mask[1] = (float)(1.9 - cvTsRandReal(rng)*0.8);
- mask[2] = (float)(3. - cvTsRandReal(rng));
- }
-}
-
-
-double CV_DisTransTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- CvSize sz = cvGetMatSize(&test_mat[INPUT][0]);
- return dist_type == CV_DIST_C || dist_type == CV_DIST_L1 ? 0 : 0.01*MAX(sz.width, sz.height);
-}
-
-
-void CV_DisTransTest::get_minmax_bounds( int i, int j, int type, CvScalar* low, CvScalar* high )
-{
- CvArrTest::get_minmax_bounds( i, j, type, low, high );
- if( i == INPUT && CV_MAT_DEPTH(type) == CV_8U )
- {
- *low = cvScalarAll(0);
- *high = cvScalarAll(10);
- }
-}
-
-int CV_DisTransTest::prepare_test_case( int test_case_idx )
-{
- int code = CvArrTest::prepare_test_case( test_case_idx );
- if( code > 0 )
- {
- // the function's response to an "all-nonzeros" image is not determined,
- // so put at least one zero point
- CvMat* mat = &test_mat[INPUT][0];
- CvRNG* rng = ts->get_rng();
- int i = cvTsRandInt(rng) % mat->rows;
- int j = cvTsRandInt(rng) % mat->cols;
- mat->data.ptr[mat->step*i + j] = 0;
- }
-
- return code;
-}
-
-
-void CV_DisTransTest::run_func()
-{
- cvDistTransform( test_array[INPUT][0], test_array[OUTPUT][0], dist_type, mask_size,
- dist_type == CV_DIST_USER ? mask : 0, test_array[OUTPUT][1] );
-}
-
-
-static void
-cvTsDistTransform( const CvMat* _src, CvMat* _dst, int dist_type,
- int mask_size, float* _mask, CvMat* /*_labels*/ )
-{
- int i, j, k;
- int width = _src->cols, height = _src->rows;
- const float init_val = 1e6;
- float mask[3];
- CvMat* temp;
- int ofs[16];
- float delta[16];
- int tstep, count;
-
- assert( mask_size == 3 || mask_size == 5 );
-
- if( dist_type == CV_DIST_USER )
- memcpy( mask, _mask, sizeof(mask) );
- else if( dist_type == CV_DIST_C )
- {
- mask_size = 3;
- mask[0] = mask[1] = 1.f;
- }
- else if( dist_type == CV_DIST_L1 )
- {
- mask_size = 3;
- mask[0] = 1.f;
- mask[1] = 2.f;
- }
- else if( mask_size == 3 )
- {
- mask[0] = 0.955f;
- mask[1] = 1.3693f;
- }
- else
- {
- mask[0] = 1.0f;
- mask[1] = 1.4f;
- mask[2] = 2.1969f;
- }
-
- temp = cvCreateMat( height + mask_size-1, width + mask_size-1, CV_32F );
- tstep = temp->step / sizeof(float);
-
- if( mask_size == 3 )
- {
- count = 4;
- ofs[0] = -1; delta[0] = mask[0];
- ofs[1] = -tstep-1; delta[1] = mask[1];
- ofs[2] = -tstep; delta[2] = mask[0];
- ofs[3] = -tstep+1; delta[3] = mask[1];
- }
- else
- {
- count = 8;
- ofs[0] = -1; delta[0] = mask[0];
- ofs[1] = -tstep-2; delta[1] = mask[2];
- ofs[2] = -tstep-1; delta[2] = mask[1];
- ofs[3] = -tstep; delta[3] = mask[0];
- ofs[4] = -tstep+1; delta[4] = mask[1];
- ofs[5] = -tstep+2; delta[5] = mask[2];
- ofs[6] = -tstep*2-1; delta[6] = mask[2];
- ofs[7] = -tstep*2+1; delta[7] = mask[2];
- }
-
- for( i = 0; i < mask_size/2; i++ )
- {
- float* t0 = (float*)(temp->data.ptr + i*temp->step);
- float* t1 = (float*)(temp->data.ptr + (temp->rows - i - 1)*temp->step);
-
- for( j = 0; j < width + mask_size - 1; j++ )
- t0[j] = t1[j] = init_val;
- }
-
- for( i = 0; i < height; i++ )
- {
- uchar* s = _src->data.ptr + i*_src->step;
- float* tmp = (float*)(temp->data.ptr + temp->step*(i + (mask_size/2))) + (mask_size/2);
-
- for( j = 0; j < mask_size/2; j++ )
- tmp[-j-1] = tmp[j + width] = init_val;
-
- for( j = 0; j < width; j++ )
- {
- if( s[j] == 0 )
- tmp[j] = 0;
- else
- {
- float min_dist = init_val;
- for( k = 0; k < count; k++ )
- {
- float t = tmp[j+ofs[k]] + delta[k];
- if( min_dist > t )
- min_dist = t;
- }
- tmp[j] = min_dist;
- }
- }
- }
-
- for( i = height - 1; i >= 0; i-- )
- {
- float* d = (float*)(_dst->data.ptr + i*_dst->step);
- float* tmp = (float*)(temp->data.ptr + temp->step*(i + (mask_size/2))) + (mask_size/2);
-
- for( j = width - 1; j >= 0; j-- )
- {
- float min_dist = tmp[j];
- if( min_dist > mask[0] )
- {
- for( k = 0; k < count; k++ )
- {
- float t = tmp[j-ofs[k]] + delta[k];
- if( min_dist > t )
- min_dist = t;
- }
- tmp[j] = min_dist;
- }
- d[j] = min_dist;
- }
- }
-
- cvReleaseMat( &temp );
-}
-
-
-void CV_DisTransTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- cvTsDistTransform( &test_mat[INPUT][0], &test_mat[REF_OUTPUT][0],
- dist_type, mask_size, mask, 0 );
-}
-
-
-int CV_DisTransTest::write_default_params( CvFileStorage* fs )
-{
- int code = CvArrTest::write_default_params( fs );
- if( code < 0 )
- return code;
-
- if( ts->get_testing_mode() == CvTS::TIMING_MODE )
- {
- start_write_param( fs );
- write_string_list( fs, "dist_type", distrans_types );
- write_int_list( fs, "labels", distrans_labels, -1, -1 );
- }
-
- return code;
-}
-
-
-void CV_DisTransTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images )
-{
- CvArrTest::get_timing_test_array_types_and_sizes( test_case_idx, sizes, types,
- whole_sizes, are_images );
- const char* distype_str = cvReadString( find_timing_param( "dist_type" ), "l2_5x5" );
- mask_size = strstr( distype_str, "3x3" ) ? 3 : 5;
- dist_type = distype_str[0] == 'c' ? CV_DIST_C : distype_str[1] == '1' ? CV_DIST_L1 : CV_DIST_L2;
- fill_labels = cvReadInt( find_timing_param( "labels" ), 0 );
-
- types[INPUT][0] = CV_8UC1;
- types[OUTPUT][0] = CV_32FC1;
- types[OUTPUT][1] = CV_32SC1;
-
- if( !fill_labels )
- sizes[OUTPUT][1] = whole_sizes[OUTPUT][1] = cvSize(0,0);
-}
-
-
-void CV_DisTransTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- sprintf( ptr, "%s,", cvReadString( find_timing_param( "dist_type" ), "l2_5x5" ) );
- ptr += strlen(ptr);
- sprintf( ptr, "%s,", fill_labels ? "labels" : "no_labels" );
- ptr += strlen(ptr);
- params_left -= 2;
-
- CvArrTest::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-
-CV_DisTransTest distrans_test;
-
-
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////\r
-//\r
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.\r
-//\r
-// By downloading, copying, installing or using the software you agree to this license.\r
-// If you do not agree to this license, do not download, install,\r
-// copy or use the software.\r
-//\r
-//\r
-// Intel License Agreement\r
-// For Open Source Computer Vision Library\r
-//\r
-// Copyright (C) 2000, Intel Corporation, all rights reserved.\r
-// Third party copyrights are property of their respective owners.\r
-//\r
-// Redistribution and use in source and binary forms, with or without modification,\r
-// are permitted provided that the following conditions are met:\r
-//\r
-// * Redistribution's of source code must retain the above copyright notice,\r
-// this list of conditions and the following disclaimer.\r
-//\r
-// * Redistribution's in binary form must reproduce the above copyright notice,\r
-// this list of conditions and the following disclaimer in the documentation\r
-// and/or other materials provided with the distribution.\r
-//\r
-// * The name of Intel Corporation may not be used to endorse or promote products\r
-// derived from this software without specific prior written permission.\r
-//\r
-// This software is provided by the copyright holders and contributors "as is" and\r
-// any express or implied warranties, including, but not limited to, the implied\r
-// warranties of merchantability and fitness for a particular purpose are disclaimed.\r
-// In no event shall the Intel Corporation or contributors be liable for any direct,\r
-// indirect, incidental, special, exemplary, or consequential damages\r
-// (including, but not limited to, procurement of substitute goods or services;\r
-// loss of use, data, or profits; or business interruption) however caused\r
-// and on any theory of liability, whether in contract, strict liability,\r
-// or tort (including negligence or otherwise) arising in any way out of\r
-// the use of this software, even if advised of the possibility of such damage.\r
-//\r
-//M*/\r
-\r
-#include "cvtest.h"\r
-#include "highgui.h"\r
-\r
-using namespace cv;\r
-\r
-//#define DRAW_TEST_IMAGE\r
-\r
-class CV_DrawingTest : public CvTest\r
-{\r
-public:\r
- CV_DrawingTest( const char* testName ) : CvTest( testName, "drawing funcs" ) {}\r
-protected:\r
- void run( int );\r
- virtual void draw( Mat& img ) = 0;\r
- virtual int checkLineIterator( Mat& img) = 0;\r
-};\r
-\r
-void CV_DrawingTest::run( int )\r
-{\r
- int code = CvTS::OK;\r
- Mat testImg, valImg;\r
- const string name = "drawing/image.jpg";\r
- string path = ts->get_data_path(), filename;\r
- filename = path + name;\r
- \r
- draw( testImg );\r
-\r
-#ifdef DRAW_TEST_IMAGE\r
- imwrite( filename, testImg );\r
-#else\r
- valImg = imread( filename );\r
- if( valImg.empty() )\r
- {\r
- ts->printf( CvTS::LOG, "test image can not be read");\r
- code = CvTS::FAIL_INVALID_TEST_DATA;\r
- }\r
- else\r
- {\r
- float err = (float)norm( testImg, valImg, CV_RELATIVE_L1 );\r
- float Eps = 0.9f;\r
- if( err > Eps)\r
- {\r
- ts->printf( CvTS::LOG, "CV_RELATIVE_L1 between testImg and valImg is equal %f (larger than %f)\n", err, Eps );\r
- code = CvTS::FAIL_BAD_ACCURACY;\r
- }\r
- else\r
- {\r
- code = checkLineIterator( testImg );\r
- }\r
- }\r
-#endif\r
- ts->set_failed_test_info( code );\r
-}\r
-\r
-class CV_DrawingTest_CPP : public CV_DrawingTest\r
-{\r
-public:\r
- CV_DrawingTest_CPP() : CV_DrawingTest( "drawing_cpp" ) {}\r
-protected:\r
- virtual void draw( Mat& img );\r
- virtual int checkLineIterator( Mat& img);\r
-};\r
-\r
-void CV_DrawingTest_CPP::draw( Mat& img )\r
-{\r
- Size imgSize( 600, 400 );\r
- img.create( imgSize, CV_8UC3 );\r
-\r
- vector<Point> polyline(4);\r
- polyline[0] = Point(0, 0);\r
- polyline[1] = Point(imgSize.width, 0);\r
- polyline[2] = Point(imgSize.width, imgSize.height);\r
- polyline[3] = Point(0, imgSize.height);\r
- const Point* pts = &polyline[0];\r
- int n = (int)polyline.size();\r
- fillPoly( img, &pts, &n, 1, Scalar::all(255) );\r
-\r
- Point p1(1,1), p2(3,3);\r
- if( clipLine(Rect(0,0,imgSize.width,imgSize.height), p1, p2) && clipLine(imgSize, p1, p2) )\r
- circle( img, Point(300,100), 40, Scalar(0,0,255), 3 ); // draw\r
-\r
- p2 = Point(3,imgSize.height+1000);\r
- if( clipLine(Rect(0,0,imgSize.width,imgSize.height), p1, p2) && clipLine(imgSize, p1, p2) )\r
- circle( img, Point(500,300), 50, cvColorToScalar(255,CV_8UC3), 5, 8, 1 ); // draw\r
-\r
- p1 = Point(imgSize.width,1), p2 = Point(imgSize.width,3);\r
- if( clipLine(Rect(0,0,imgSize.width,imgSize.height), p1, p2) && clipLine(imgSize, p1, p2) )\r
- circle( img, Point(390,100), 10, Scalar(0,0,255), 3 ); // not draw\r
-\r
- p1 = Point(imgSize.width-1,1), p2 = Point(imgSize.width,3);\r
- if( clipLine(Rect(0,0,imgSize.width,imgSize.height), p1, p2) && clipLine(imgSize, p1, p2) )\r
- ellipse( img, Point(390,100), Size(20,30), 60, 0, 220.0, Scalar(0,200,0), 4 ); //draw\r
-\r
- ellipse( img, RotatedRect(Point(100,200),Size(200,100),160), Scalar(200,200,255), 5 );\r
-\r
- polyline.clear();\r
- ellipse2Poly( Point(430,180), Size(100,150), 30, 0, 150, 20, polyline );\r
- pts = &polyline[0];\r
- n = (int)polyline.size();\r
- polylines( img, &pts, &n, 1, false, Scalar(0,0,150), 4, CV_AA );\r
- n = 0;\r
- for( vector<Point>::const_iterator it = polyline.begin(); n < (int)polyline.size()-1; ++it, n++ )\r
- {\r
- line( img, *it, *(it+1), Scalar(50,250,100));\r
- }\r
-\r
- polyline.clear();\r
- ellipse2Poly( Point(500,300), Size(50,80), 0, 0, 180, 10, polyline );\r
- pts = &polyline[0];\r
- n = (int)polyline.size();\r
- polylines( img, &pts, &n, 1, true, Scalar(100,200,100), 20 );\r
- fillConvexPoly( img, pts, n, Scalar(0, 80, 0) );\r
-\r
- polyline.resize(8);\r
- // external rectengular\r
- polyline[0] = Point(0, 0);\r
- polyline[1] = Point(80, 0);\r
- polyline[2] = Point(80, 80);\r
- polyline[3] = Point(0, 80);\r
- // internal rectangular\r
- polyline[4] = Point(20, 20);\r
- polyline[5] = Point(60, 20);\r
- polyline[6] = Point(60, 60);\r
- polyline[7] = Point(20, 60);\r
- const Point* ppts[] = {&polyline[0], &polyline[0]+4};\r
- int pn[] = {4, 4};\r
- fillPoly( img, ppts, pn, 2, Scalar(100, 100, 0), 8, 0, Point(500, 20) );\r
-\r
- rectangle( img, Point(0, 300), Point(50, 398), Scalar(0,0,255) );\r
-\r
- string text1 = "OpenCV";\r
- int baseline = 0, thickness = 3, fontFace = FONT_HERSHEY_SCRIPT_SIMPLEX;\r
- float fontScale = 2;\r
- Size textSize = getTextSize( text1, fontFace, fontScale, thickness, &baseline);\r
- baseline += thickness;\r
- Point textOrg((img.cols - textSize.width)/2, (img.rows + textSize.height)/2);\r
- rectangle(img, textOrg + Point(0, baseline), textOrg + Point(textSize.width, -textSize.height), Scalar(0,0,255));\r
- line(img, textOrg + Point(0, thickness), textOrg + Point(textSize.width, thickness), Scalar(0, 0, 255));\r
- putText(img, text1, textOrg, fontFace, fontScale, Scalar(150,0,150), thickness, 8);\r
-\r
- string text2 = "abcdefghijklmnopqrstuvwxyz1234567890";\r
- Scalar color(200,0,0);\r
- fontScale = 0.5, thickness = 1;\r
- int dist = 5;\r
-\r
- textSize = getTextSize( text2, FONT_HERSHEY_SIMPLEX, fontScale, thickness, &baseline);\r
- textOrg = Point(5,5)+Point(0,textSize.height+dist);\r
- putText(img, text2, textOrg, FONT_HERSHEY_SIMPLEX, fontScale, color, thickness, CV_AA);\r
- \r
- fontScale = 1;\r
- textSize = getTextSize( text2, FONT_HERSHEY_PLAIN, fontScale, thickness, &baseline);\r
- textOrg += Point(0,textSize.height+dist);\r
- putText(img, text2, textOrg, FONT_HERSHEY_PLAIN, fontScale, color, thickness, CV_AA);\r
-\r
- fontScale = 0.5;\r
- textSize = getTextSize( text2, FONT_HERSHEY_DUPLEX, fontScale, thickness, &baseline);\r
- textOrg += Point(0,textSize.height+dist);\r
- putText(img, text2, textOrg, FONT_HERSHEY_DUPLEX, fontScale, color, thickness, CV_AA);\r
-\r
- textSize = getTextSize( text2, FONT_HERSHEY_COMPLEX, fontScale, thickness, &baseline);\r
- textOrg += Point(0,textSize.height+dist);\r
- putText(img, text2, textOrg, FONT_HERSHEY_COMPLEX, fontScale, color, thickness, CV_AA);\r
-\r
- textSize = getTextSize( text2, FONT_HERSHEY_TRIPLEX, fontScale, thickness, &baseline);\r
- textOrg += Point(0,textSize.height+dist);\r
- putText(img, text2, textOrg, FONT_HERSHEY_TRIPLEX, fontScale, color, thickness, CV_AA);\r
-\r
- fontScale = 1;\r
- textSize = getTextSize( text2, FONT_HERSHEY_COMPLEX_SMALL, fontScale, thickness, &baseline);\r
- textOrg += Point(0,180) + Point(0,textSize.height+dist);\r
- putText(img, text2, textOrg, FONT_HERSHEY_COMPLEX_SMALL, fontScale, color, thickness, CV_AA);\r
-\r
- textSize = getTextSize( text2, FONT_HERSHEY_SCRIPT_SIMPLEX, fontScale, thickness, &baseline);\r
- textOrg += Point(0,textSize.height+dist);\r
- putText(img, text2, textOrg, FONT_HERSHEY_SCRIPT_SIMPLEX, fontScale, color, thickness, CV_AA);\r
-\r
- textSize = getTextSize( text2, FONT_HERSHEY_SCRIPT_COMPLEX, fontScale, thickness, &baseline);\r
- textOrg += Point(0,textSize.height+dist);\r
- putText(img, text2, textOrg, FONT_HERSHEY_SCRIPT_COMPLEX, fontScale, color, thickness, CV_AA);\r
-\r
- dist = 15, fontScale = 0.5;\r
- textSize = getTextSize( text2, FONT_ITALIC, fontScale, thickness, &baseline);\r
- textOrg += Point(0,textSize.height+dist);\r
- putText(img, text2, textOrg, FONT_ITALIC, fontScale, color, thickness, CV_AA);\r
-}\r
-\r
-int CV_DrawingTest_CPP::checkLineIterator( Mat& img )\r
-{\r
- LineIterator it( img, Point(0,300), Point(1000, 300) );\r
- for(int i = 0; i < it.count; ++it, i++ )\r
- {\r
- Vec3b v = (Vec3b)(*(*it)) - img.at<Vec3b>(300,i);\r
- float err = (float)norm( v );\r
- if( err != 0 )\r
- {\r
- ts->printf( CvTS::LOG, "LineIterator works incorrect" );\r
- return CvTS::FAIL_INVALID_OUTPUT;\r
- }\r
- }\r
- return CvTS::OK;\r
-}\r
-\r
-class CV_DrawingTest_C : public CV_DrawingTest\r
-{\r
-public:\r
- CV_DrawingTest_C() : CV_DrawingTest( "drawing_c" ) {}\r
-protected:\r
- virtual void draw( Mat& img );\r
- virtual int checkLineIterator( Mat& img);\r
-};\r
-\r
-void CV_DrawingTest_C::draw( Mat& _img )\r
-{\r
- CvSize imgSize = cvSize(600, 400);\r
- _img.create( imgSize, CV_8UC3 );\r
- CvMat img = _img;\r
- \r
- vector<CvPoint> polyline(4);\r
- polyline[0] = cvPoint(0, 0);\r
- polyline[1] = cvPoint(imgSize.width, 0);\r
- polyline[2] = cvPoint(imgSize.width, imgSize.height);\r
- polyline[3] = cvPoint(0, imgSize.height);\r
- CvPoint* pts = &polyline[0];\r
- int n = (int)polyline.size();\r
- cvFillPoly( &img, &pts, &n, 1, cvScalar(255,255,255) );\r
-\r
- CvPoint p1 = cvPoint(1,1), p2 = cvPoint(3,3);\r
- if( cvClipLine(imgSize, &p1, &p2) )\r
- cvCircle( &img, cvPoint(300,100), 40, cvScalar(0,0,255), 3 ); // draw\r
-\r
- p1 = cvPoint(1,1), p2 = cvPoint(3,imgSize.height+1000);\r
- if( cvClipLine(imgSize, &p1, &p2) )\r
- cvCircle( &img, cvPoint(500,300), 50, cvScalar(255,0,0), 5, 8, 1 ); // draw\r
-\r
- p1 = cvPoint(imgSize.width,1), p2 = cvPoint(imgSize.width,3);\r
- if( cvClipLine(imgSize, &p1, &p2) )\r
- cvCircle( &img, cvPoint(390,100), 10, cvScalar(0,0,255), 3 ); // not draw\r
-\r
- p1 = Point(imgSize.width-1,1), p2 = Point(imgSize.width,3);\r
- if( cvClipLine(imgSize, &p1, &p2) )\r
- cvEllipse( &img, cvPoint(390,100), cvSize(20,30), 60, 0, 220.0, cvScalar(0,200,0), 4 ); //draw\r
-\r
- CvBox2D box;\r
- box.center.x = 100;\r
- box.center.y = 200;\r
- box.size.width = 200;\r
- box.size.height = 100;\r
- box.angle = 160;\r
- cvEllipseBox( &img, box, Scalar(200,200,255), 5 );\r
-\r
- polyline.resize(9);\r
- pts = &polyline[0];\r
- n = (int)polyline.size();\r
- assert( cvEllipse2Poly( cvPoint(430,180), cvSize(100,150), 30, 0, 150, &polyline[0], 20 ) == n );\r
- cvPolyLine( &img, &pts, &n, 1, false, cvScalar(0,0,150), 4, CV_AA );\r
- n = 0;\r
- for( vector<CvPoint>::const_iterator it = polyline.begin(); n < (int)polyline.size()-1; ++it, n++ )\r
- {\r
- cvLine( &img, *it, *(it+1), cvScalar(50,250,100) );\r
- }\r
-\r
- polyline.resize(19);\r
- pts = &polyline[0];\r
- n = (int)polyline.size();\r
- assert( cvEllipse2Poly( cvPoint(500,300), cvSize(50,80), 0, 0, 180, &polyline[0], 10 ) == n );\r
- cvPolyLine( &img, &pts, &n, 1, true, Scalar(100,200,100), 20 );\r
- cvFillConvexPoly( &img, pts, n, cvScalar(0, 80, 0) );\r
-\r
- polyline.resize(8);\r
- // external rectengular\r
- polyline[0] = cvPoint(500, 20);\r
- polyline[1] = cvPoint(580, 20);\r
- polyline[2] = cvPoint(580, 100);\r
- polyline[3] = cvPoint(500, 100);\r
- // internal rectangular\r
- polyline[4] = cvPoint(520, 40);\r
- polyline[5] = cvPoint(560, 40);\r
- polyline[6] = cvPoint(560, 80);\r
- polyline[7] = cvPoint(520, 80);\r
- CvPoint* ppts[] = {&polyline[0], &polyline[0]+4};\r
- int pn[] = {4, 4};\r
- cvFillPoly( &img, ppts, pn, 2, cvScalar(100, 100, 0), 8, 0 );\r
-\r
- cvRectangle( &img, cvPoint(0, 300), cvPoint(50, 398), cvScalar(0,0,255) );\r
-\r
- string text1 = "OpenCV";\r
- CvFont font;\r
- cvInitFont( &font, FONT_HERSHEY_SCRIPT_SIMPLEX, 2, 2, 0, 3 );\r
- int baseline = 0;\r
- CvSize textSize;\r
- cvGetTextSize( text1.c_str(), &font, &textSize, &baseline );\r
- baseline += font.thickness;\r
- CvPoint textOrg = cvPoint((imgSize.width - textSize.width)/2, (imgSize.height + textSize.height)/2);\r
- cvRectangle( &img, cvPoint( textOrg.x, textOrg.y + baseline),\r
- cvPoint(textOrg.x + textSize.width, textOrg.y - textSize.height), cvScalar(0,0,255));\r
- cvLine( &img, cvPoint(textOrg.x, textOrg.y + font.thickness), \r
- cvPoint(textOrg.x + textSize.width, textOrg.y + font.thickness), cvScalar(0, 0, 255));\r
- cvPutText( &img, text1.c_str(), textOrg, &font, cvScalar(150,0,150) );\r
-\r
- int dist = 5;\r
- string text2 = "abcdefghijklmnopqrstuvwxyz1234567890";\r
- CvScalar color = cvScalar(200,0,0);\r
- cvInitFont( &font, FONT_HERSHEY_SIMPLEX, 0.5, 0.5, 0, 1, CV_AA );\r
- cvGetTextSize( text2.c_str(), &font, &textSize, &baseline );\r
- textOrg = cvPoint(5, 5+textSize.height+dist);\r
- cvPutText(&img, text2.c_str(), textOrg, &font, color );\r
- \r
- cvInitFont( &font, FONT_HERSHEY_PLAIN, 1, 1, 0, 1, CV_AA );\r
- cvGetTextSize( text2.c_str(), &font, &textSize, &baseline );\r
- textOrg = cvPoint(textOrg.x,textOrg.y+textSize.height+dist);\r
- cvPutText(&img, text2.c_str(), textOrg, &font, color );\r
-\r
- cvInitFont( &font, FONT_HERSHEY_DUPLEX, 0.5, 0.5, 0, 1, CV_AA );\r
- cvGetTextSize( text2.c_str(), &font, &textSize, &baseline );\r
- textOrg = cvPoint(textOrg.x,textOrg.y+textSize.height+dist);\r
- cvPutText(&img, text2.c_str(), textOrg, &font, color );\r
-\r
- cvInitFont( &font, FONT_HERSHEY_COMPLEX, 0.5, 0.5, 0, 1, CV_AA );\r
- cvGetTextSize( text2.c_str(), &font, &textSize, &baseline );\r
- textOrg = cvPoint(textOrg.x,textOrg.y+textSize.height+dist);\r
- cvPutText(&img, text2.c_str(), textOrg, &font, color );\r
-\r
- cvInitFont( &font, FONT_HERSHEY_TRIPLEX, 0.5, 0.5, 0, 1, CV_AA );\r
- cvGetTextSize( text2.c_str(), &font, &textSize, &baseline );\r
- textOrg = cvPoint(textOrg.x,textOrg.y+textSize.height+dist);\r
- cvPutText(&img, text2.c_str(), textOrg, &font, color );\r
-\r
- cvInitFont( &font, FONT_HERSHEY_COMPLEX_SMALL, 1, 1, 0, 1, CV_AA );\r
- cvGetTextSize( text2.c_str(), &font, &textSize, &baseline );\r
- textOrg = cvPoint(textOrg.x,textOrg.y+textSize.height+dist + 180);\r
- cvPutText(&img, text2.c_str(), textOrg, &font, color );\r
-\r
- cvInitFont( &font, FONT_HERSHEY_SCRIPT_SIMPLEX, 1, 1, 0, 1, CV_AA );\r
- cvGetTextSize( text2.c_str(), &font, &textSize, &baseline );\r
- textOrg = cvPoint(textOrg.x,textOrg.y+textSize.height+dist);\r
- cvPutText(&img, text2.c_str(), textOrg, &font, color );\r
-\r
- cvInitFont( &font, FONT_HERSHEY_SCRIPT_COMPLEX, 1, 1, 0, 1, CV_AA );\r
- cvGetTextSize( text2.c_str(), &font, &textSize, &baseline );\r
- textOrg = cvPoint(textOrg.x,textOrg.y+textSize.height+dist);\r
- cvPutText(&img, text2.c_str(), textOrg, &font, color );\r
-\r
- dist = 15;\r
- cvInitFont( &font, FONT_ITALIC, 0.5, 0.5, 0, 1, CV_AA );\r
- cvGetTextSize( text2.c_str(), &font, &textSize, &baseline );\r
- textOrg = cvPoint(textOrg.x,textOrg.y+textSize.height+dist);\r
- cvPutText(&img, text2.c_str(), textOrg, &font, color );\r
-}\r
-\r
-int CV_DrawingTest_C::checkLineIterator( Mat& _img )\r
-{\r
- CvLineIterator it;\r
- CvMat img = _img;\r
- int count = cvInitLineIterator( &img, cvPoint(0,300), cvPoint(1000, 300), &it );\r
- for(int i = 0; i < count; i++ )\r
- {\r
- Vec3b v = (Vec3b)(*(it.ptr)) - _img.at<Vec3b>(300,i);\r
- float err = (float)norm( v );\r
- if( err != 0 )\r
- {\r
- ts->printf( CvTS::LOG, "CvLineIterator works incorrect" );\r
- return CvTS::FAIL_INVALID_OUTPUT;\r
- }\r
- CV_NEXT_LINE_POINT(it);\r
- }\r
- return CvTS::OK;\r
-}\r
-\r
-CV_DrawingTest_CPP drawing_test_cpp;\r
-CV_DrawingTest_C drawing_test_c;\r
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-#if 0
-
-#include <string.h>
-#include "highgui.h"
-
-static char* funcs = "cvLine cvLineAA cvRectangle cvCircle cvCircleAA "
- "cvEllipse cvEllipseAA cvFillConvexPoly cvFillPoly"
- "cvPolyLine cvPolyLineAA cvPutText";
-static char* test_desc = "Drawing to image (regression test)";
-
-static char* filedir_ = "drawing";
-
-#ifndef RGB
-#define RGB(r,g,b) CV_RGB(b,g,r)
-#endif
-
-static int my_tolower( int c )
-{
- return 'A' <= c && c <= 'Z' ? c + ('a' - 'A') : c;
-}
-
-static int CheckImage(IplImage* image, char* file, char* /*funcname*/)
-{
- //printf("loading %s\n", file );
- IplImage* read = cvLoadImage( file, 1 );
-
- if( !read )
- {
- trsWrite( ATS_CON | ATS_LST, "can't read image\n" );
- return 1;
- }
-
- int err = 0;
-
-#if 0
- {
- IplImage* temp = cvCloneImage( read );
- cvAbsDiff( image, read, temp );
- cvThreshold( temp, temp, 0, 255, CV_THRESH_BINARY );
- cvvNamedWindow( "Original", 0 );
- cvvNamedWindow( "Diff", 0 );
- cvvShowImage( "Original", read );
- cvvShowImage( "Diff", temp );
- cvvWaitKey(0);
- cvvDestroyWindow( "Original" );
- cvvDestroyWindow( "Diff" );
- }
-#endif
-
- cvAbsDiff( image, read, read );
- cvThreshold( read, read, 0, 1, CV_THRESH_BINARY );
- err = cvRound( cvNorm( read, 0, CV_L1 ))/3;
-
- cvReleaseImage( &read );
- return err;
-}
-
-static int ProcessImage( IplImage* image, char* funcname, int read )
-{
- char name[1000];
- char lowername[1000];
- int i = 0, err;
-
- do
- {
- lowername[i] = (char)my_tolower(funcname[i]);
- }
- while( funcname[i++] != '\0' );
-
- if( read )
- {
- err = CheckImage( image,
- atsGetTestDataPath(name, filedir_, lowername, "bmp"),
- funcname );
- if( err )
- {
- trsWrite( ATS_CON | ATS_LST, "Error in %s: %d\n", funcname, err );
- }
- return 0; //err;
- }
- else
- {
- cvvSaveImage( atsGetTestDataPath(name, filedir_, lowername, "bmp"), image );
- return 0;
- }
-}
-
-static int drawing_test()
-{
- static int read_params = 0;
- static int read = 0;
- const int channel = 3;
- CvSize size = cvSize(600, 300);
-
- int i, j;
- int Errors = 0;
-
- if( !read_params )
- {
- read_params = 1;
-
- trsCaseRead( &read, "/n/y", "y", "Read from file ?" );
- }
- // Create image
- IplImage* image = cvCreateImage( size, IPL_DEPTH_8U, channel );
-
- // cvLine
- cvZero( image );
-
- for( i = 0; i < 100; i++ )
- {
- CvPoint p1 = cvPoint( i - 30, i * 4 + 10 );
- CvPoint p2 = cvPoint( size.width + 30 - i, size.height - 10 - i * 4 );
-
- cvLine( image, p1, p2, CV_RGB(178+i, 255-i, i), i % 10 );
- }
- Errors += ProcessImage( image, "cvLine", read );
-
- // cvLineAA
- cvZero( image );
-
- for( i = 0; i < 100; i++ )
- {
- CvPoint p1 = cvPoint( i - 30, i * 4 + 10 );
- CvPoint p2 = cvPoint( size.width + 30 - i, size.height - 10 - i * 4 );
-
- cvLine( image, p1, p2, CV_RGB(178+i, 255-i, i), 1, CV_AA, 0 );
- }
- //Errors += ProcessImage( image, "cvLineAA", read );
-
- // cvRectangle
- cvZero( image );
-
- for( i = 0; i < 100; i++ )
- {
- CvPoint p1 = cvPoint( i - 30, i * 4 + 10 );
- CvPoint p2 = cvPoint( size.width + 30 - i, size.height - 10 - i * 4 );
-
- cvRectangle( image, p1, p2, CV_RGB(178+i, 255-i, i), i % 10 );
- }
- Errors += ProcessImage( image, "cvRectangle", read );
-
-#if 0
- named_window( "Diff", 0 );
-#endif
-
- // cvCircle
- cvZero( image );
-
- for( i = 0; i < 100; i++ )
- {
- CvPoint p1 = cvPoint( i * 3, i * 2 );
- CvPoint p2 = cvPoint( size.width - i * 3, size.height - i * 2 );
-
- cvCircle( image, p1, i, CV_RGB(178+i, 255-i, i), i % 10 );
- cvCircle( image, p2, i, CV_RGB(178+i, 255-i, i), i % 10 );
-
-#if 0
- show_iplimage( "Diff", image );
- wait_key(0);
-#endif
- }
- Errors += ProcessImage( image, "cvCircle", read );
-
- // cvCircleAA
- cvZero( image );
-
- for( i = 0; i < 100; i++ )
- {
- CvPoint p1 = cvPoint( i * 3, i * 2 );
- CvPoint p2 = cvPoint( size.width - i * 3, size.height - i * 2 );
-
- cvCircleAA( image, p1, i, RGB(i, 255 - i, 178 + i), 0 );
- cvCircleAA( image, p2, i, RGB(i, 255 - i, 178 + i), 0 );
- }
- Errors += ProcessImage( image, "cvCircleAA", read );
-
- // cvEllipse
- cvZero( image );
-
- for( i = 10; i < 100; i += 10 )
- {
- CvPoint p1 = cvPoint( i * 6, i * 3 );
- CvSize axes = cvSize( i * 3, i * 2 );
-
- cvEllipse( image, p1, axes,
- 180 * i / 100, 90 * i / 100, 90 * (i - 100) / 100,
- CV_RGB(178+i, 255-i, i), i % 10 );
- }
- Errors += ProcessImage( image, "cvEllipse", read );
-
- // cvEllipseAA
- cvZero( image );
-
- for( i = 10; i < 100; i += 10 )
- {
- CvPoint p1 = cvPoint( i * 6, i * 3 );
- CvSize axes = cvSize( i * 3, i * 2 );
-
- cvEllipseAA( image, p1, axes,
- 180 * i / 100, 90 * i / 100, 90 * (i - 100) / 100,
- RGB(i, 255 - i, 178 + i), i % 10 );
- }
- Errors += ProcessImage( image, "cvEllipseAA", read );
-
- // cvFillConvexPoly
- cvZero( image );
-
- for( j = 0; j < 5; j++ )
- for( i = 0; i < 100; i += 10 )
- {
- CvPoint p[4] = {{ j * 100 - 10, i }, { j * 100 + 10, i },
- { j * 100 + 30, i * 2 }, { j * 100 + 170, i * 3 }};
- cvFillConvexPoly( image, p, 4, CV_RGB(178+i, 255-i, i) );
-
- }
- Errors += ProcessImage( image, "cvFillConvexPoly", read );
-
- // cvFillPoly
- cvZero( image );
-
- for( i = 0; i < 100; i += 10 )
- {
- CvPoint p0[] = {{-10, i}, { 10, i}, { 30, i * 2}, {170, i * 3}};
- CvPoint p1[] = {{ 90, i}, {110, i}, {130, i * 2}, {270, i * 3}};
- CvPoint p2[] = {{190, i}, {210, i}, {230, i * 2}, {370, i * 3}};
- CvPoint p3[] = {{290, i}, {310, i}, {330, i * 2}, {470, i * 3}};
- CvPoint p4[] = {{390, i}, {410, i}, {430, i * 2}, {570, i * 3}};
-
- CvPoint* p[] = {p0, p1, p2, p3, p4};
-
- int n[] = {4, 4, 4, 4, 4};
- cvFillPoly( image, p, n, 5, CV_RGB(178+i, 255-i, i) );
- }
- Errors += ProcessImage( image, "cvFillPoly", read );
-
- // cvPolyLine
- cvZero( image );
-
- for( i = 0; i < 100; i += 10 )
- {
- CvPoint p0[] = {{-10, i}, { 10, i}, { 30, i * 2}, {170, i * 3}};
- CvPoint p1[] = {{ 90, i}, {110, i}, {130, i * 2}, {270, i * 3}};
- CvPoint p2[] = {{190, i}, {210, i}, {230, i * 2}, {370, i * 3}};
- CvPoint p3[] = {{290, i}, {310, i}, {330, i * 2}, {470, i * 3}};
- CvPoint p4[] = {{390, i}, {410, i}, {430, i * 2}, {570, i * 3}};
-
- CvPoint* p[] = {p0, p1, p2, p3, p4};
-
- int n[] = {4, 4, 4, 4, 4};
- cvPolyLine( image, p, n, 5, 1, CV_RGB(178+i, 255-i, i), i % 10 );
- }
- Errors += ProcessImage( image, "cvPolyLine", read );
-
- // cvPolyLineAA
- cvZero( image );
-
- for( i = 0; i < 100; i += 10 )
- {
- CvPoint p0[] = {{-10, i}, { 10, i}, { 30, i * 2}, {170, i * 3}};
- CvPoint p1[] = {{ 90, i}, {110, i}, {130, i * 2}, {270, i * 3}};
- CvPoint p2[] = {{190, i}, {210, i}, {230, i * 2}, {370, i * 3}};
- CvPoint p3[] = {{290, i}, {310, i}, {330, i * 2}, {470, i * 3}};
- CvPoint p4[] = {{390, i}, {410, i}, {430, i * 2}, {570, i * 3}};
-
- CvPoint* p[] = {p0, p1, p2, p3, p4};
-
- int n[] = {4, 4, 4, 4, 4};
- cvPolyLineAA( image, p, n, 5, 1, RGB(i, 255 - i, 178 + i), 0 );
- }
- Errors += ProcessImage( image, "cvPolyLineAA", read );
-
- // cvPolyLineAA
- cvZero( image );
-
- for( i = 1; i < 10; i++ )
- {
- CvFont font;
- cvInitFont( &font, CV_FONT_VECTOR0,
- (double)i / 5, (double)i / 5, (double)i / 10, i );
- cvPutText( image, "privet. this is test. :)", cvPoint(0, i * 20), &font, CV_RGB(178+i, 255-i, i) );
- }
- Errors += ProcessImage( image, "cvPutText", read );
-
- cvReleaseImage( &image );
-
- return Errors ? trsResult( TRS_FAIL, "errors" ) : trsResult( TRS_OK, "ok" );
-}
-
-#if 0
-static int resize_test()
-{
- IplImage* src = load_iplimage( "d:/user/vp/archive/art/greatwave.jpg" );
- IplImage* image = cvCreateImage( cvGetSize( src ), 8, 1 );
-
- cvCvtColor( src, image, CV_BGR2GRAY );
-
- named_window( "image", 1 );
- show_iplimage( "image", image );
- wait_key( 0 );
-
- named_window( "result", 1 );
-
- for( int i = 0; i < 30; i++ )
- {
- IplImage* dst = cvCreateImage(
- cvSize( (rand() % 1000) + 1, (rand() % 1000) + 1),
- 8, image->nChannels );
-
- cvResize( image, dst, CV_INTER_LINEAR );
- show_iplimage( "result", dst );
-
- wait_key_ex( 0, 1000 );
- cvReleaseImage( &dst );
- }
-
- cvReleaseImage( &image );
- destroy_window( "image" );
- destroy_window( "result" );
-
- return CV_OK;
-}
-#endif
-
-void InitADrawingRegress()
-{
- /* Register test functions */
- trsReg( funcs, test_desc, atsAlgoClass, drawing_test );
- //trsReg( "cvResize", "", atsAlgoClass, resize_test );
-}
-
-#endif
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-#if 0
-
-#include "aeigenobjects.inc"
-
-#define __8U 8
-#define __32F 32
-#define MAXDIFF 1.01
-#define RELDIFF 1.0e-4
-
-typedef struct _UserData /* User data structure for callback mode */
-{
- void* addr1; /* Array of objects ROI start addresses */
- void* addr2;
- int step1; /* Step in bytes */
- int step2;
- CvSize size1; /* ROI or full size */
- CvSize size2;
-} UserData;
-
-/* Testing parameters */
-static char FuncName[] =
-"cvCalcCovarMatrixEx, cvCalcEigenObjects, cvCalcDecompCoeff, cvEigenDecomposite, cvEigenProjection";
-static char TestName[] = "Eigen objects functions group test";
-static char TestClass[] = "Algorithm";
-static int obj_number, obj_width, obj_height;
-static double rel_bufSize;
-
-/*-----------------------------=--=-=== Callback functions ===-=--=---------------------*/
-
-int read_callback_8u( int ind, void* buf, void* userData)
-{
- int i, j, k = 0;
- UserData* data = (UserData*)userData;
- uchar* start = ((uchar**)(data->addr1))[ind];
- uchar* buff = (uchar*)buf;
-
- if( ind<0 ) return CV_BADFACTOR_ERR;
- if( buf==NULL || userData==NULL ) return CV_NULLPTR_ERR;
-
- for( i=0; i<data->size1.height; i++, start+=data->step1 )
- for( j=0; j<data->size1.width; j++, k++ )
- buff[k] = start[j];
- return CV_NO_ERR;
-}
-/*----------------------*/
-int read_callback_32f( int ind, void* buf, void* userData)
-{
- int i, j, k = 0;
- UserData* data = (UserData*)userData;
- float* start = ((float**)(data->addr2))[ind];
- float* buff = (float*)buf;
-
- if( ind<0 ) return CV_BADFACTOR_ERR;
- if( buf==NULL || userData==NULL ) return CV_NULLPTR_ERR;
-
- for( i=0; i<data->size2.height; i++, start+=data->step2/4 )
- for( j=0; j<data->size2.width; j++, k++ )
- buff[k] = start[j];
- return CV_NO_ERR;
-}
-/*========================*/
-int write_callback_8u( int ind, void* buf, void* userData)
-{
- int i, j, k = 0;
- UserData* data = (UserData*)userData;
- uchar* start = ((uchar**)(data->addr1))[ind];
- uchar* buff = (uchar*)buf;
-
- if( ind<0 ) return CV_BADFACTOR_ERR;
- if( buf==NULL || userData==NULL ) return CV_NULLPTR_ERR;
-
- for( i=0; i<data->size1.height; i++, start+=data->step1 )
- for( j=0; j<data->size1.width; j++, k++ )
- start[j] = buff[k];
- return CV_NO_ERR;
-}
-/*----------------------*/
-int write_callback_32f( int ind, void* buf, void* userData)
-{
- int i, j, k = 0;
- UserData* data = (UserData*)userData;
- float* start = ((float**)(data->addr2))[ind];
- float* buff = (float*)buf;
-
- if( ind<0 ) return CV_BADFACTOR_ERR;
- if( buf==NULL || userData==NULL ) return CV_NULLPTR_ERR;
-
- for( i=0; i<data->size2.height; i++, start+=data->step2/4 )
- for( j=0; j<data->size2.width; j++, k++ )
- start[j] = buff[k];
- return CV_NO_ERR;
-}
-
-/*##########################################=-- Test body --=###########################*/
-static int fmaEigenObjects( void )
-{
- int n, n4, i, j, ie, m1, rep = 0, roi, roi4, bufSize;
- int roix=0, roiy=0, sizex, sizey, step, step4, step44;
- int err0, err1, err2, err3, err4, err5, err6, err7, err=0;
- uchar *pro, *pro0, *object;
- uchar** objs;
- float *covMatr, *covMatr0, *avg, *avg0, *eigVal, *eigVal0, *coeffs, *coeffs0,
- covMatrMax, coeffm, singleCoeff0;
- float **eigObjs, **eigObjs0;
- IplImage **Objs, **EigObjs, **EigObjs0, *Pro, *Pro0, *Object, *Avg, *Avg0;
- double eps0, amax=0, singleCoeff, p;
- AtsRandState state;
- CvSize size;
- int r;
- CvTermCriteria limit;
- UserData userData;
- int (*read_callback)( int ind, void* buf, void* userData)=
- read_callback_8u;
- int (*read2_callback)( int ind, void* buf, void* userData)=
- read_callback_32f;
- int (*write_callback)( int ind, void* buf, void* userData)=
- write_callback_32f;
- CvInput* u_r = (CvInput*)&read_callback;
- CvInput* u_r2= (CvInput*)&read2_callback;
- CvInput* u_w = (CvInput*)&write_callback;
- void* read_ = (u_r)->data;
- void* read_2 = (u_r2)->data;
- void* write_ = (u_w)->data;
-
- /* Reading test parameters */
- trsiRead( &obj_width, "100", "width of objects" );
- trsiRead( &obj_height, "100", "height of objects" );
- trsiRead( &obj_number, "11", "number of objects" );
- trsdRead( &rel_bufSize, "0.09", "relative i/o buffer size" );
-
- if( rel_bufSize < 0.0 ) rel_bufSize = 0.0;
- m1 = obj_number - 1;
- eps0= 1.0e-27;
- n = obj_width * obj_height;
- sizex = obj_width, sizey = obj_height;
-
- Objs = (IplImage**)cvAlloc(sizeof(IplImage*) * obj_number );
- EigObjs = (IplImage**)cvAlloc(sizeof(IplImage*) * m1 );
- EigObjs0 = (IplImage**)cvAlloc(sizeof(IplImage*) * m1 );
-
- objs = (uchar**)cvAlloc(sizeof(uchar*) * obj_number );
- eigObjs = (float**)cvAlloc(sizeof(float*) * m1 );
- eigObjs0 = (float**)cvAlloc(sizeof(float*) * m1 );
- covMatr = (float*) cvAlloc(sizeof(float) * obj_number * obj_number );
- covMatr0 = (float*) cvAlloc(sizeof(float) * obj_number * obj_number );
- coeffs = (float*) cvAlloc(sizeof(float*) * m1 );
- coeffs0 = (float*) cvAlloc(sizeof(float*) * m1 );
- eigVal = (float*) cvAlloc(sizeof(float) * obj_number );
- eigVal0 = (float*) cvAlloc(sizeof(float) * obj_number );
-
- size.width = obj_width; size.height = obj_height;
- atsRandInit( &state, 0, 255, 13 );
-
- Avg = cvCreateImage( size, IPL_DEPTH_32F, 1 );
- cvSetImageROI( Avg, cvRect(0, 0, Avg->width, Avg->height) );
- Avg0 = cvCreateImage( size, IPL_DEPTH_32F, 1 );
- cvSetImageROI( Avg0, cvRect(0, 0, Avg0->width, Avg0->height) );
- avg = (float*)Avg->imageData;
- avg0 = (float*)Avg0->imageData;
- Pro = cvCreateImage( size, IPL_DEPTH_8U, 1 );
- cvSetImageROI( Pro, cvRect(0, 0, Pro->width, Pro->height) );
- Pro0 = cvCreateImage( size, IPL_DEPTH_8U, 1 );
- cvSetImageROI( Pro0, cvRect(0, 0, Pro0->width, Pro0->height) );
- pro = (uchar*)Pro->imageData;
- pro0 = (uchar*)Pro0->imageData;
- Object = cvCreateImage( size, IPL_DEPTH_8U, 1 );
- cvSetImageROI( Object, cvRect(0, 0, Object->width, Object->height) );
- object = (uchar*)Object->imageData;
-
- step = Pro->widthStep; step4 = Avg->widthStep; step44 = step4/4;
- n = step*obj_height; n4= step44*obj_height;
- atsbRand8u ( &state, object, n );
-
- for( i=0; i<obj_number; i++ )
- {
- Objs[i] = cvCreateImage( size, IPL_DEPTH_8U, 1 );
- cvSetImageROI( Objs[i], cvRect(0, 0, Objs[i]->width, Objs[i]->height) );
- objs[i] = (uchar*)Objs[i]->imageData;
- atsbRand8u ( &state, objs[i], n );
- if( i < m1 )
- {
- EigObjs[i] = cvCreateImage( size, IPL_DEPTH_32F, 1 );
- cvSetImageROI( EigObjs[i], cvRect(0, 0, EigObjs[i]->width, EigObjs[i]->height) );
- EigObjs0[i] = cvCreateImage( size, IPL_DEPTH_32F, 1 );
- cvSetImageROI( EigObjs0[i], cvRect(0, 0, EigObjs0[i]->width, EigObjs0[i]->height) );
- }
- }
-
- limit.type = CV_TERMCRIT_ITER; limit.max_iter = m1; limit.epsilon = 1;//(float)eps0;
-
- bufSize = (int)(4*n*obj_number*rel_bufSize);
-trsWrite(TW_RUN|TW_CON, "\n i/o buffer size : %10d bytes\n", bufSize );
-
-trsWrite(TW_RUN|TW_CON, "\n ROI unsupported\n" );
-
-/* User data fill */
- userData.addr1 = (void*)objs;
- userData.addr2 = (void*)eigObjs;
- userData.step1 = step;
- userData.step2 = step4;
-
-
-repeat:
- roi = roiy*step + roix;
- roi4 = roiy*step44 + roix;
-
- Avg->roi->xOffset = roix; Avg->roi->yOffset = roiy;
- Avg->roi->height = size.height; Avg->roi->width = size.width;
- Avg0->roi->xOffset = roix; Avg0->roi->yOffset = roiy;
- Avg0->roi->height = size.height; Avg0->roi->width = size.width;
- Pro->roi->xOffset = roix; Pro->roi->yOffset = roiy;
- Pro->roi->height = size.height; Pro->roi->width = size.width;
- Pro0->roi->xOffset = roix; Pro0->roi->yOffset = roiy;
- Pro0->roi->height = size.height; Pro0->roi->width = size.width;
- Object->roi->xOffset = roix; Object->roi->yOffset = roiy;
- Object->roi->height = size.height; Object->roi->width = size.width;
-
- for( i=0; i<obj_number; i++ )
- {
- Objs[i]->roi->xOffset = roix; Objs[i]->roi->yOffset = roiy;
- Objs[i]->roi->height = size.height; Objs[i]->roi->width = size.width;
- objs[i] = (uchar*)Objs[i]->imageData + roi;
- if( i < m1 )
- {
- EigObjs[i]->roi->xOffset = roix; EigObjs[i]->roi->yOffset = roiy;
- EigObjs[i]->roi->height = size.height; EigObjs[i]->roi->width = size.width;
- EigObjs0[i]->roi->xOffset = roix; EigObjs0[i]->roi->yOffset = roiy;
- EigObjs0[i]->roi->height = size.height; EigObjs0[i]->roi->width = size.width;
- eigObjs[i] = (float*)EigObjs[i]->imageData + roi4;
- eigObjs0[i] = (float*)EigObjs0[i]->imageData + roi4;
- }
- }
-
- userData.size1 = userData.size2 = size;
-
-/* =================================== Test functions run ============================= */
-
- r = _cvCalcEigenObjects_8u32fR_q( obj_number, objs, step, eigObjs0, step4,
- size, eigVal0, avg0+roi4, step4, &m1, &eps0 );
-
- r = _cvEigenDecomposite_8u32fR_q( object+roi, step, m1, eigObjs0, step4,
- avg0+roi4, step4, size, coeffs0 );
-
- r = _cvEigenProjection_8u32fR_q( m1, eigObjs0, step4, coeffs0, avg0+roi4, step4,
- pro0+roi, step, size );
-
- r = _cvCalcCovarMatrix_8u32fR_q( obj_number, objs, step, avg0+roi4, step4,
- size, covMatr0 );
-
- singleCoeff0 = _cvCalcDecompCoeff_8u32fR_q( object+roi, step, eigObjs0[0], step4,
- avg0+roi4, step4, size );
-
- covMatrMax = 0.f;
- for( i=0; i<obj_number*obj_number; i++ )
- if( covMatrMax < (float)fabs( covMatr[i] ) )
- covMatrMax = (float)fabs( covMatr[i] );
-
- amax = 0;
- for( ie=0; ie<m1; ie++ )
- for( i=0; i<size.height; i++ )
- for( j=0; j<size.width; j++ )
- {
- int ij = i*obj_width + j;
- float e = eigObjs0[ie][ij];
- if( amax < fabs(e) ) amax = fabs(e);
- }
-
- coeffm = 0.f;
- for( i=0; i<m1; i++ )
- if( coeffm < (float)fabs(coeffs0[i]) ) coeffm = (float)fabs(coeffs0[i]);
-
-/*- - - - - - - - - - - - - - - - - - - - - without callbacks - - - - - - - - - - - - - */
- for( i=0; i<obj_number*obj_number; i++ ) covMatr[i] = covMatr0[i];
- for( i=0; i<size.height; i++ )
- for( j=0; j<size.width; j++ ) pro[i*step + j] = pro0[i*step + j];
- for( i=0; i<size.height; i++ )
- for( j=0; j<size.width; j++ ) avg[i*step44 + j] = avg0[i*step44 + j];
- for( i=0; i<m1; i++ ) { coeffs[i] = coeffs0[i]; eigVal[i] = eigVal0[i]; }
- for( ie=0; ie<m1; ie++ )
- for( i=0; i<size.height; i++ )
- for( j=0; j<size.width; j++ )
- eigObjs[ie][i*step44+j] = eigObjs0[ie][i*step44+j];
-
- err1 = err2 = err3 = err4 = err5 = err6 = err7 = 0;
-
- cvCalcCovarMatrixEx( obj_number,
- (void*)Objs,
- CV_EIGOBJ_NO_CALLBACK,
- bufSize,
- NULL,
- (void*)&userData,
- Avg,
- covMatr );
-
- cvCalcEigenObjects ( obj_number,
- (void*)Objs,
- (void*)EigObjs,
- CV_EIGOBJ_NO_CALLBACK,
- bufSize,
- (void*)&userData,
- &limit,
- Avg,
- eigVal );
-
- singleCoeff = cvCalcDecompCoeff( Object, EigObjs[0], Avg );
- if( fabs( (singleCoeff - singleCoeff0)/singleCoeff0 ) > RELDIFF ) err7++;
-
- cvEigenDecomposite( Object,
- m1,
- (void*)EigObjs,
- CV_EIGOBJ_NO_CALLBACK,
- (void*)&userData,
- Avg,
- coeffs );
- cvEigenProjection ( (void*)EigObjs,
- m1,
- CV_EIGOBJ_NO_CALLBACK,
- (void*)&userData,
- coeffs,
- Avg,
- Pro );
-
-/* Covariance matrix comparision */
- for( i=0; i<obj_number*obj_number; i++ )
- if( fabs(covMatr[i] - covMatr0[i]) > RELDIFF*fabs(covMatrMax) ) err6++;
-
-/* Averaged object comparision */
- for( i=0; i<size.height; i++ )
- for( j=0; j<size.width; j++ )
- {
- int ij = i*step44 + j;
- if( fabs( (avg+roi)[ij] - (avg0+roi)[ij] ) > MAXDIFF ) err1++;
- }
-
-/* Eigen objects comparision */
- for( ie=0; ie<m1; ie++ )
- for( i=0; i<size.height; i++ )
- for( j=0; j<size.width; j++ )
- {
- int ij = i*step44 + j;
- float e0 = (eigObjs0[ie])[ij], e = (eigObjs[ie])[ij];
- if( fabs( (e-e0)/amax ) > RELDIFF ) err2++;
- }
-
-/* Eigen values comparision */
- for( i=0; i<m1; i++ )
- {
- double e0 = eigVal0[i], e = eigVal[i];
- if(e0)
- if( fabs( (e-e0)/e0 ) > RELDIFF ) err3++;
- }
-
-/* Decomposition coefficients comparision */
- for( i=0; i<m1; i++ )
- if(coeffs0[i])
- if( fabs( (coeffs[i] - coeffs0[i])/coeffm ) > RELDIFF ) err4++;
-
-/* Projection comparision */
- for( i=0; i<size.height; i++ )
- for( j=0; j<size.width; j++ )
- {
- int ij = i*step + j;
- if( fabs( (double)((pro+roi)[ij] - (pro0+roi)[ij]) ) > MAXDIFF ) err5++;
- }
-
- err0 = 0;
- p = 100.f*err6/(float)(obj_number*obj_number);
- if( p>0.1 )
- {
- trsWrite(TW_RUN|TW_CON, " Covar. matrix - %d errors (%7.3f %% );\n", err6, p );
- err0 += err6;
- }
- p = 100.f*err1/(float)(size.height*size.width);
- if( p>0.1 )
- {
- trsWrite(TW_RUN|TW_CON, " Averaged obj. - %d errors (%7.3f %% );\n", err1, p );
- err0 += err1;
- }
- p = 100.f*err3/(float)(m1);
- if( p>0.1 )
- {
- trsWrite(TW_RUN|TW_CON, " Eigen values - %d errors (%7.3f %% );\n", err3, p );
- err0 += err3;
- }
- p = 100.f*err2/(float)(size.height*size.width*m1);
- if( p>0.1 )
- {
- trsWrite(TW_RUN|TW_CON, " Eigen objects - %d errors (%7.3f %% );\n", err2, p );
- err0 += err2;
- }
- p = 100.f*err4/(float)(m1);
- if( p>0.1 )
- {
- trsWrite(TW_RUN|TW_CON, " Decomp.coeffs - %d errors (%7.3f %% );\n", err4, p );
- err0 += err4;
- }
- if( ((float)err7)/m1 > 0.1 )
- {
- trsWrite(TW_RUN|TW_CON, " Single dec.c. - %d errors ;\n", err7);
- err0 += err7;
- }
- p = 100.f*err5/(float)(size.height*size.width);
- if( p>0.1 )
- {
- trsWrite(TW_RUN|TW_CON, " Projection - %d errors (%7.3f %% );\n", err5, p );
- err0 += err5;
- }
- trsWrite(TW_RUN|TW_CON, " without callbacks : %8d errors;\n", err0 );
-
- err += err0;
-
-/*- - - - - - - - - - - - - - - - - - - - - input callback - - - - - - - - - - - - - */
- for( i=0; i<size.height; i++ )
- for( j=0; j<size.width; j++ ) pro[i*step + j] = pro0[i*step + j];
- for( i=0; i<size.height; i++ )
- for( j=0; j<size.width; j++ ) avg[i*step44 + j] = avg0[i*step44 + j];
- for( i=0; i<m1; i++ ) { coeffs[i] = coeffs0[i]; eigVal[i] = eigVal0[i]; }
- for( ie=0; ie<m1; ie++ )
- for( i=0; i<size.height; i++ )
- for( j=0; j<size.width; j++ )
- eigObjs[ie][i*step44+j] = eigObjs0[ie][i*step44+j];
-
- err1 = err2 = err3 = err4 = err5 = err6 = err7 = 0;
-
- cvCalcEigenObjects ( obj_number,
- read_,
- (void*)EigObjs,
- CV_EIGOBJ_INPUT_CALLBACK,
- bufSize,
- (void*)&userData,
- &limit,
- Avg,
- eigVal );
-
- cvEigenDecomposite( Object,
- m1,
- read_2,
- CV_EIGOBJ_INPUT_CALLBACK,
- (void*)&userData,
- Avg,
- coeffs );
-
- cvEigenProjection ( read_2,
- m1,
- CV_EIGOBJ_INPUT_CALLBACK,
- (void*)&userData,
- coeffs,
- Avg,
- Pro );
-
-/* Averaged object comparision */
- for( i=0; i<size.height; i++ )
- for( j=0; j<size.width; j++ )
- {
- int ij = i*step44 + j;
- if( fabs( (avg+roi)[ij] - (avg0+roi)[ij] ) > MAXDIFF ) err1++;
- }
-
-/* Eigen objects comparision */
- for( ie=0; ie<m1; ie++ )
- for( i=0; i<size.height; i++ )
- for( j=0; j<size.width; j++ )
- {
- int ij = i*step44 + j;
- float e0 = (eigObjs0[ie])[ij], e = (eigObjs[ie])[ij];
- if( fabs( (e-e0)/amax ) > RELDIFF ) err2++;
- }
-
-/* Eigen values comparision */
- for( i=0; i<m1; i++ )
- {
- double e0 = eigVal0[i], e = eigVal[i];
- if(e0)
- if( fabs( (e-e0)/e0 ) > RELDIFF ) err3++;
- }
-
-/* Projection comparision */
- for( i=0; i<size.height; i++ )
- for( j=0; j<size.width; j++ )
- {
- int ij = i*step + j;
- if( fabs( (double)((pro+roi)[ij] - (pro0+roi)[ij]) ) > MAXDIFF ) err5++;
- }
-
-/* Decomposition coefficients comparision */
- for( i=0; i<m1; i++ )
- if(coeffs0[i])
- if( fabs( (coeffs[i] - coeffs0[i])/coeffm ) > RELDIFF ) err4++;
-
- err0 = 0;
- p = 100.f*err1/(float)(size.height*size.width);
- if( p>0.1 )
- {
- trsWrite(TW_RUN|TW_CON, " Averaged obj. - %d errors (%7.3f %% );\n", err1, p );
- err0 += err1;
- }
- p = 100.f*err3/(float)(m1);
- if( p>0.1 )
- {
- trsWrite(TW_RUN|TW_CON, " Eigen values - %d errors (%7.3f %% );\n", err3, p );
- err0 += err3;
- }
- p = 100.f*err2/(float)(size.height*size.width*m1);
- if( p>0.1 )
- {
- trsWrite(TW_RUN|TW_CON, " Eigen objects - %d errors (%7.3f %% );\n", err2, p );
- err0 += err2;
- }
- p = 100.f*err4/(float)(m1);
- if( p>0.1 )
- {
- trsWrite(TW_RUN|TW_CON, " Decomp.coeffs - %d errors (%7.3f %% );\n", err4, p );
- err0 += err4;
- }
- p = 100.f*err5/(float)(size.height*size.width);
- if( p>0.1 )
- {
- trsWrite(TW_RUN|TW_CON, " Projection - %d errors (%7.3f %% );\n", err5, p );
- err0 += err5;
- }
- trsWrite(TW_RUN|TW_CON, " input callback : %8d errors;\n", err0 );
-
- err += err0;
-
-/*- - - - - - - - - - - - - - - - - - - - - output callback - - - - - - - - - - - - - */
- for( i=0; i<size.height; i++ )
- for( j=0; j<size.width; j++ ) avg[i*step44 + j] = avg0[i*step44 + j];
- for( i=0; i<m1; i++ ) eigVal[i] = eigVal0[i];
- for( ie=0; ie<m1; ie++ )
- for( i=0; i<size.height; i++ )
- for( j=0; j<size.width; j++ )
- eigObjs[ie][i*step44+j] = eigObjs0[ie][i*step44+j];
-
- err1 = err2 = err3 = err4 = err5 = 0;
-
- cvCalcEigenObjects ( obj_number,
- (void*)Objs,
- write_,
- CV_EIGOBJ_OUTPUT_CALLBACK,
- bufSize,
- (void*)&userData,
- &limit,
- Avg,
- eigVal );
-
-/* Averaged object comparision */
- for( i=0; i<size.height; i++ )
- for( j=0; j<size.width; j++ )
- {
- int ij = i*step44 + j;
- if( fabs( (avg+roi)[ij] - (avg0+roi)[ij] ) > MAXDIFF ) err1++;
- }
-
-/* Eigen objects comparision */
- for( ie=0; ie<m1; ie++ )
- for( i=0; i<size.height; i++ )
- for( j=0; j<size.width; j++ )
- {
- int ij = i*step44 + j;
- float e0 = (eigObjs0[ie])[ij], e = (eigObjs[ie])[ij];
- if( fabs( (e-e0)/amax ) > RELDIFF ) err2++;
- }
-
-/* Eigen values comparision */
- for( i=0; i<m1; i++ )
- {
- double e0 = eigVal0[i], e = eigVal[i];
- if(e0)
- if( fabs( (e-e0)/e0 ) > RELDIFF ) err3++;
- }
-
- err0 = 0;
- p = 100.f*err1/(float)(size.height*size.width);
- if( p>0.1 )
- {
- trsWrite(TW_RUN|TW_CON, " Averaged obj. - %d errors (%7.3f %% );\n", err1, p );
- err0 += err1;
- }
- p = 100.f*err3/(float)(m1);
- if( p>0.1 )
- {
- trsWrite(TW_RUN|TW_CON, " Eigen values - %d errors (%7.3f %% );\n", err3, p );
- err0 += err3;
- }
- p = 100.f*err2/(float)(size.height*size.width*m1);
- if( p>0.1 )
- {
- trsWrite(TW_RUN|TW_CON, " Eigen objects - %d errors (%7.3f %% );\n", err2, p );
- err0 += err2;
- }
- trsWrite(TW_RUN|TW_CON, " output callback : %8d errors;\n", err0 );
-
- err += err0;
-
-/*- - - - - - - - - - - - - - - - - - - - - both callbacks - - - - - - - - - - - - - */
- for( i=0; i<size.height; i++ )
- for( j=0; j<size.width; j++ ) avg[i*step44 + j] = avg0[i*step44 + j];
- for( i=0; i<m1; i++ ) eigVal[i] = eigVal0[i];
- for( ie=0; ie<m1; ie++ )
- for( i=0; i<size.height; i++ )
- for( j=0; j<size.width; j++ )
- eigObjs[ie][i*step44+j] = eigObjs0[ie][i*step44+j];
-
- err1 = err2 = err3 = err4 = err5 = 0;
-
- cvCalcEigenObjects ( obj_number,
- read_,
- write_,
- CV_EIGOBJ_INPUT_CALLBACK | CV_EIGOBJ_OUTPUT_CALLBACK,
- bufSize,
- (void*)&userData,
- &limit,
- Avg,
- eigVal );
-
-/* Averaged object comparision */
- for( i=0; i<size.height; i++ )
- for( j=0; j<size.width; j++ )
- {
- int ij = i*step44 + j;
- if( fabs( (avg+roi)[ij] - (avg0+roi)[ij] ) > MAXDIFF ) err1++;
- }
-
-/* Eigen objects comparision */
- for( ie=0; ie<m1; ie++ )
- for( i=0; i<size.height; i++ )
- for( j=0; j<size.width; j++ )
- {
- int ij = i*step44 + j;
- float e0 = (eigObjs0[ie])[ij], e = (eigObjs[ie])[ij];
- if( fabs( (e-e0)/amax ) > RELDIFF ) err2++;
- }
-
-/* Eigen values comparision */
- for( i=0; i<m1; i++ )
- {
- double e0 = eigVal0[i], e = eigVal[i];
- if(e0)
- if( fabs( (e-e0)/e0 ) > RELDIFF ) err3++;
- }
-
- err0 = 0;
- p = 100.f*err1/(float)(size.height*size.width);
- if( p>0.1 )
- {
- trsWrite(TW_RUN|TW_CON, " Averaged obj. - %d errors (%7.3f %% );\n", err1, p );
- err0 += err1;
- }
- p = 100.f*err3/(float)(m1);
- if( p>0.1 )
- {
- trsWrite(TW_RUN|TW_CON, " Eigen values - %d errors (%7.3f %% );\n", err3, p );
- err0 += err3;
- }
- p = 100.f*err2/(float)(size.height*size.width*m1);
- if( p>0.1 )
- {
- trsWrite(TW_RUN|TW_CON, " Eigen objects - %d errors (%7.3f %% );\n", err2, p );
- err0 += err2;
- }
- trsWrite(TW_RUN|TW_CON, " both callbacks : %8d errors;\n", err0 );
-
- err += err0;
-
-
-/*================================-- test with ROI --===================================*/
-
- if(!rep)
- {
- roix = (int)(0.157f*obj_width);
- roiy = (int)(0.131f*obj_height);
- sizex = (int)(0.611f*obj_width);
- sizey = (int)(0.737f*obj_height);
- roi = roiy*obj_width + roix;
-
-trsWrite(TW_RUN|TW_CON, "\n ROI supported\n" );
- rep++;
- size.width = sizex; size.height = sizey;
-
- goto repeat;
- }
-
-/*^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ free memory ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^*/
- cvReleaseImage( &Avg );
- cvReleaseImage( &Avg0 );
- cvReleaseImage( &Pro );
- cvReleaseImage( &Pro0 );
- cvReleaseImage( &Object );
- for( i=0; i<obj_number; i++ )
- {
- cvReleaseImage( &Objs[i] );
- if( i < m1 )
- {
- cvReleaseImage( &EigObjs[i] );
- cvReleaseImage( &EigObjs0[i] );
- }
- }
-
- cvFree( &objs );
- cvFree( &eigObjs );
- cvFree( &eigObjs0 );
- cvFree( &coeffs );
- cvFree( &coeffs0 );
- cvFree( &eigVal );
- cvFree( &eigVal0 );
- cvFree( &Objs );
- cvFree( &EigObjs );
- cvFree( &EigObjs0 );
- cvFree( &covMatr );
- cvFree( &covMatr0 );
-
-trsWrite(TW_RUN|TW_CON, "\n Errors number: %d\n", err );
-
- if(err) return trsResult( TRS_FAIL, "Algorithm test has passed. %d errors.", err );
- else return trsResult( TRS_OK, "Algorithm test has passed successfully" );
-
-} /*fma*/
-
-/*------------------------------------------- Initialize function ------------------------ */
-void InitAEigenObjects( void )
-{
- /* Registering test function */
- trsReg( FuncName, TestName, TestClass, fmaEigenObjects );
-} /* InitAEigenObjects */
-
-#endif
-
-/* End of file */
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-/*______________________________________________________________________________________*/
-/* */
-/* Test functions for the Eigen Objects functions group */
-/*______________________________________________________________________________________*/
-
-#include "cvtest.h"
-
-static int _cvCalcCovarMatrix_8u32fR_q( int nObjects,
- uchar** objects,
- int objStep,
- float* avg,
- int avgStep,
- CvSize size,
- float* covarMatrix )
-{
- int i, j;
-
- if ( nObjects < 2 ) return CV_BADFACTOR_ERR;
- if ( size.width > objStep || 4*size.width > avgStep || size.height < 1)
- return CV_BADSIZE_ERR;
- if ( objects == NULL || avg == NULL || covarMatrix == NULL ) return CV_NULLPTR_ERR;
-
- avgStep /= 4;
-
- for(i=0; i<nObjects; i++)
- {
- uchar* bu = objects[i];
- for(j=i; j<nObjects; j++)
- {
- int ij = i*nObjects + j, k, l;
- float w = 0.f;
- float* a = avg;
- uchar* bu1 = bu;
- uchar* bu2 = objects[j];
-
- for(k=0; k<size.height; k++, bu1 += objStep, bu2 += objStep, a += avgStep)
- {
- for(l = 0; l < size.width-3; l+=4)
- {
- float f = a [l];
- uchar u1 = bu1[l];
- uchar u2 = bu2[l];
- w += ( u1 - f ) * ( u2 - f );
- f = a [l+1];
- u1 = bu1[l+1];
- u2 = bu2[l+1];
- w += ( u1 - f ) * ( u2 - f );
- f = a [l+2];
- u1 = bu1[l+2];
- u2 = bu2[l+2];
- w += ( u1 - f ) * ( u2 - f );
- f = a [l+3];
- u1 = bu1[l+3];
- u2 = bu2[l+3];
- w += ( u1 - f ) * ( u2 - f );
- }
- for(; l < size.width; l++)
- {
- float f = a [l];
- uchar u1 = bu1[l];
- uchar u2 = bu2[l];
- w += ( u1 - f ) * ( u2 - f );
- }
- }
-
- covarMatrix[ij] = w;
- ij = j*nObjects + i;
- covarMatrix[ij] = w;
- }
- }
-
- return CV_NO_ERR;
-} /* end of _cvCalcCovarMatrix_8u32fR */
-
-
-/* copy of _cvJacobiEigen_32f */
-int _cvJacobiEigens_32f ( float* A,
- float* V,
- float* E,
- int n,
- float eps )
-{
- int i, j, k, ind;
- float *AA = A, *VV = V;
- double Amax, anorm=0, ax;
-
- if ( A == NULL || V == NULL || E == NULL ) return CV_NULLPTR_ERR;
- if ( n <= 0 ) return CV_BADSIZE_ERR;
- if (eps < 1.0e-7f ) eps = 1.0e-7f;
-
- /*-------- Prepare --------*/
- for(i=0; i<n; i++, VV+=n, AA+=n)
- {
- for(j=0; j<i; j++)
- {
- double Am = AA[j];
- anorm += Am*Am;
- }
- for(j=0; j<n; j++) VV[j] = 0.f;
- VV[i] = 1.f;
- }
-
- anorm = sqrt( anorm + anorm );
- ax = anorm*eps/n;
- Amax = anorm;
-
- while ( Amax > ax )
- {
- Amax /= n;
- do /* while (ind) */
- {
- int p, q;
- float *V1 = V, *A1 = A;
- ind = 0;
- for(p=0; p<n-1; p++, A1+=n, V1+=n)
- {
- float *A2 = A + n*(p+1), *V2 = V + n*(p+1);
- for(q=p+1; q<n; q++, A2+=n, V2+=n)
- {
- double x, y, c, s, c2, s2, a;
- float *A3, Apq=A1[q], App, Aqq, Aip, Aiq, Vpi, Vqi;
- if( fabs( Apq ) < Amax ) continue;
-
- ind=1;
-
- /*---- Calculation of rotation angle's sine & cosine ----*/
- App = A1[p];
- Aqq = A2[q];
- y = 5.0e-1*(App - Aqq);
- x = -Apq / sqrt(Apq*Apq + y*y);
- if(y<0.0) x = -x;
- s = x / sqrt(2.0*(1.0 + sqrt(1.0 - x*x)));
- s2 = s*s;
- c = sqrt(1.0 - s2);
- c2 = c*c;
- a = 2.0*Apq*c*s;
-
- /*---- Apq annulation ----*/
- A3 = A;
- for(i=0; i<p; i++, A3+=n)
- {
- Aip = A3[p];
- Aiq = A3[q];
- Vpi = V1[i];
- Vqi = V2[i];
- A3[p] = (float)(Aip*c - Aiq*s);
- A3[q] = (float)(Aiq*c + Aip*s);
- V1[i] = (float)(Vpi*c - Vqi*s);
- V2[i] = (float)(Vqi*c + Vpi*s);
- }
- for(; i<q; i++, A3+=n)
- {
- Aip = A1[i];
- Aiq = A3[q];
- Vpi = V1[i];
- Vqi = V2[i];
- A1[i] = (float)(Aip*c - Aiq*s);
- A3[q] = (float)(Aiq*c + Aip*s);
- V1[i] = (float)(Vpi*c - Vqi*s);
- V2[i] = (float)(Vqi*c + Vpi*s);
- }
- for(; i<n; i++)
- {
- Aip = A1[i];
- Aiq = A2[i];
- Vpi = V1[i];
- Vqi = V2[i];
- A1[i] = (float)(Aip*c - Aiq*s);
- A2[i] = (float)(Aiq*c + Aip*s);
- V1[i] = (float)(Vpi*c - Vqi*s);
- V2[i] = (float)(Vqi*c + Vpi*s);
- }
- A1[p] = (float)(App*c2 + Aqq*s2 - a);
- A2[q] = (float)(App*s2 + Aqq*c2 + a);
- A1[q] = A2[p] = 0.0f;
- } /*q*/
- } /*p*/
- } while (ind);
- Amax /= n;
- } /* while ( Amax > ax ) */
-
- for(i=0, k=0; i<n; i++, k+=n+1) E[i] = A[k];
- /*printf(" M = %d\n", M);*/
-
- /* -------- ordering --------*/
- for(i=0; i<n; i++)
- {
- int m = i;
- float Em = (float)fabs(E[i]);
- for(j=i+1; j<n; j++)
- {
- float Ej = (float)fabs(E[j]);
- m = ( Em < Ej ) ? j : m;
- Em = ( Em < Ej ) ? Ej : Em;
- }
- if( m != i )
- {
- int l;
- float b = E[i];
- E[i] = E[m];
- E[m] = b;
- for(j=0, k=i*n, l=m*n; j<n; j++, k++, l++)
- {
- b = V[k];
- V[k] = V[l];
- V[l] = b;
- }
- }
- }
-
- return CV_NO_ERR;
-}
-
-
-
-/*______________________________________________________________________________________*/
-
-int _cvCalcEigenObjects_8u32fR_q( int nObjects,
- uchar** objects,
- int objStep,
- float** eigObjs,
- int eigStep,
- CvSize size,
- float* eigVals,
- float* avg,
- int avgStep,
- int* nEigObjs,
- double* eps )
-{
- int i, j, k, l;
- uchar *bu;
- float *c=0, *ev=0, *bf, *bf1, *bf2, m;
- int r;
-
-
- if ( nObjects < 2 ) return CV_BADFACTOR_ERR;
- if ( size.width > objStep || 4*size.width > eigStep ||
- 4*size.width > avgStep || size.height < 1) return CV_BADSIZE_ERR;
- if ( objects == NULL || eigObjs == NULL || eigVals == NULL ||
- avg == NULL || nEigObjs == NULL || eps == NULL ) return CV_NULLPTR_ERR;
- for( i=0; i<nObjects; i++ ) if( objects[i] == NULL ) return CV_NULLPTR_ERR;
- for( i=0; i<*nEigObjs; i++ ) if( eigObjs[i] == NULL ) return CV_NULLPTR_ERR;
-
- eigStep /= 4;
- avgStep /= 4;
-
-/* Calculation of averaged object */
- bf = avg;
- for(i = 0; i < size.height; i++, bf += avgStep)
- for(j = 0; j < size.width; j++)
- bf[j] = 0.f;
- for(k = 0; k < nObjects; k++)
- {
- bu = objects[k];
- bf = avg;
- for(i = 0; i < size.height; i++, bu +=objStep, bf += avgStep)
- for(j = 0; j < size.width; j++)
- bf[j] += bu[j];
- }
- m = 1.0f/(float)nObjects;
- bf = avg;
- for(i = 0; i < size.height; i++, bf += avgStep)
- for(j = 0; j < size.width; j++)
- bf[j] *= m;
-
-/* Calculation of covariance matrix */
- c = (float*)cvAlloc ( sizeof(float)*nObjects*nObjects );
- if(c==NULL) return CV_OUTOFMEM_ERR;
-
- r = _cvCalcCovarMatrix_8u32fR_q ( nObjects, objects, objStep,
- avg, 4*avgStep, size, c );
- if(r) { cvFree( &c ); return r; }
-
-/* Calculation of eigenvalues & eigenvectors */
- ev = (float*)cvAlloc ( sizeof(float)*nObjects*nObjects );
- if(ev==NULL) { cvFree( &c ); return CV_OUTOFMEM_ERR; }
-
- _cvJacobiEigens_32f( c, ev, eigVals, nObjects, 0.0f );
- cvFree( &c );
-
- for(i=0; i<*nEigObjs; i++) if( fabs(eigVals[i]/eigVals[0]) < *eps ) break;
- *nEigObjs = i;
- *eps = fabs(eigVals[*nEigObjs-1]/eigVals[0]);
-
-/* Calculation of eigenobjects */
- bf2 = ev;
- for(i=0; i<*nEigObjs; i++, bf2+=nObjects)
- {
- float e = (float)(1.0/sqrt(eigVals[i]));
- float* u = eigObjs[i];
-
- bf = u;
- for(l=0; l<size.height; l++, bf+=eigStep)
- for(j=0; j<size.width; j++) bf[j] = 0.0f;
-
- for(k=0; k<nObjects; k++)
- {
- float v = e*bf2[k];
- bf = u;
- bu = objects[k];
- bf1 = avg;
- for(l=0; l<size.height; l++, bf+=eigStep, bf1+=avgStep, bu+=objStep)
- for(j=0; j<size.width; j++) bf[j] += v * ((float)bu[j] - bf1[j]);
- }
- }
-
- cvFree( &ev );
- return CV_NO_ERR;
-} /* --- End of _cvCalcEigenObjects_8u32fR --- */
-/*______________________________________________________________________________________*/
-
-float _cvCalcDecompCoeff_8u32fR_q( uchar* obj,
- int objStep,
- float* eigObj,
- int eigStep,
- float* avg,
- int avgStep,
- CvSize size )
-{
- int i, k;
- float w = 0.0f;
-
- if ( size.width > objStep || 4*size.width > eigStep
- || 4*size.width > avgStep || size.height < 1) return -1.0e30f;
- if ( obj == NULL || eigObj == NULL || avg == NULL ) return -1.0e30f;
-
- eigStep /= 4;
- avgStep /= 4;
-
- for(i = 0; i < size.height; i++, obj += objStep, eigObj += eigStep, avg += avgStep)
- for(k = 0; k < size.width; k++)
- w += eigObj[k]*( (float)obj[k] - avg[k] );
-
- return w;
-}
-/*______________________________________________________________________________________*/
-
-int _cvEigenDecomposite_8u32fR_q( uchar* obj,
- int objStep,
- int nEigObjs,
- float** eigObjs,
- int eigStep,
- float* avg,
- int avgStep,
- CvSize size,
- float* coeffs )
-{
- int i;
-
- if ( nEigObjs < 2 ) return CV_BADFACTOR_ERR;
- if ( size.width > objStep || 4*size.width > eigStep ||
- 4*size.width > avgStep || size.height < 1) return CV_BADSIZE_ERR;
- if ( obj == NULL || eigObjs == NULL || coeffs == NULL || avg == NULL)
- return CV_NULLPTR_ERR;
-
- for(i=0; i<nEigObjs; i++)
- {
- float w = _cvCalcDecompCoeff_8u32fR_q( obj, objStep, eigObjs[i], eigStep,
- avg, avgStep, size );
- if( w < -1.0e29f ) return CV_NOTDEFINED_ERR;
- coeffs[i] = w;
- }
- return CV_NO_ERR;
-}
-/*______________________________________________________________________________________*/
-
-int _cvEigenProjection_8u32fR_q( int nEigObjs,
- float** eigens,
- int eigStep,
- float* coeffs,
- float* avg,
- int avgStep,
- uchar* rest,
- int restStep,
- CvSize size )
-{
- int i, j, k;
-
- if ( size.width > avgStep || 4*size.width > eigStep || size.height < 1)
- return CV_BADSIZE_ERR;
- if ( rest == NULL || eigens == NULL || avg == NULL || coeffs == NULL )
- return CV_NULLPTR_ERR;
- eigStep /= 4;
- avgStep /= 4;
-
- for(i = 0; i < size.height; i++, rest+=restStep, avg+=avgStep)
- {
- int ij = i*eigStep;
- for(j = 0; j < size.width; j++, ij++)
- {
- float w = avg[j];
- for(k=0; k<nEigObjs-3; k+=4)
- {
- float* b = eigens[k];
- w += coeffs[k ] * b[ij];
- b = eigens [k+1];
- w += coeffs[k+1] * b[ij];
- b = eigens [k+2];
- w += coeffs[k+2] * b[ij];
- b = eigens [k+3];
- w += coeffs[k+3] * b[ij];
- }
- for(; k<nEigObjs; k++)
- {
- float* b = eigens[k];
- w += coeffs[k] * b[ij];
- }
- w = w<-0.499999f ? -0.499999f : w>255.499f ? 255.499f : w;
- rest[j] = (uchar)cvRound( w );
- }
- }
- return CV_NO_ERR;
-}
-/*______________________________________________________________________________________*/
-
-/* << End of file >> */
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-/*////////////////////// emd_test /////////////////////////*/
-
-typedef struct matr_info
-{
- float* x_origin;
- float* y_origin;
- float* matr;
- int rows;
- int cols;
-}
-matr_info;
-
-static float matr_dist( const float* x, const float* y, void* param )
-{
- matr_info* mi = (matr_info*)param;
- int i = (int)(x - mi->x_origin) - 1;
- int j = (int)(y - mi->y_origin) - 1;
- assert( 0 <= i && i < mi->rows &&
- 0 <= j && j < mi->cols );
- return mi->matr[i*mi->cols + j];
-}
-
-class CV_EMDTest : public CvTest
-{
-public:
- CV_EMDTest();
-protected:
- void run(int);
-};
-
-
-CV_EMDTest::CV_EMDTest():
- CvTest( "emd", "cvCalcEMD" )
-{
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;
-}
-
-void CV_EMDTest::run( int )
-{
- int code = CvTS::OK;
- const double success_error_level = 1e-6;
- #define M 10000
- double emd0 = 2460./210;
- static float cost[] =
- {
- 16, 16, 13, 22, 17,
- 14, 14, 13, 19, 15,
- 19, 19, 20, 23, M,
- M , 0, M, 0, 0
- };
- static float w1[] = { 50, 60, 50, 50 },
- w2[] = { 30, 20, 70, 30, 60 };
- matr_info mi;
- float emd;
-
- mi.x_origin = w1;
- mi.y_origin = w2;
-
- mi.rows = sizeof(w1)/sizeof(w1[0]);
- mi.cols = sizeof(w2)/sizeof(w2[0]);
- mi.matr = cost;
-
- emd = cvCalcEMD( w1, mi.rows, w2, mi.cols, 0, (CvDisType)-1,
- matr_dist, 0, &mi );
-
- if( fabs( emd - emd0 ) > success_error_level*emd0 )
- {
- ts->printf( CvTS::LOG,
- "The computed distance is %.2f, while it should be %.2f\n", emd, emd0 );
- code = CvTS::FAIL_BAD_ACCURACY;
- }
-
- if( code < 0 )
- ts->set_failed_test_info( code );
-}
-
-CV_EMDTest emd_test;
-
-/* End of file. */
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
-// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of the copyright holders may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-#include <string>
-#include <iostream>
-#include <fstream>
-#include <iterator>
-#include <limits>
-#include <numeric>
-#include "cvaux.h"
-
-using namespace cv;
-using namespace std;
-
-class CV_RigidTransform_Test : public CvTest
-{
-public:
- CV_RigidTransform_Test();
- ~CV_RigidTransform_Test();
-protected:
- void run(int);
-
- bool testNPoints(int);
- bool testImage();
-};
-
-CV_RigidTransform_Test::CV_RigidTransform_Test(): CvTest( "optflow-estimate-rigid", "?" )
-{
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;
-}
-CV_RigidTransform_Test::~CV_RigidTransform_Test() {}
-
-struct WrapAff2D
-{
- const double *F;
- WrapAff2D(const Mat& aff) : F(aff.ptr<double>()) {}
- Point2f operator()(const Point2f& p)
- {
- return Point2d( p.x * F[0] + p.y * F[1] + F[2],
- p.x * F[3] + p.y * F[4] + F[5]);
- }
-};
-
-bool CV_RigidTransform_Test::testNPoints(int from)
-{
- cv::RNG rng(*ts->get_rng());
-
- int progress = 0;
- int k, ntests = 10000;
-
- for( k = from; k < ntests; k++ )
- {
- ts->update_context( this, k, true );
- progress = update_progress(progress, k, ntests, 0);
-
- Mat aff(2, 3, CV_64F);
- rng.fill(aff, CV_RAND_UNI, Scalar(-2), Scalar(2));
-
- int n = (unsigned)rng % 100 + 10;
-
- Mat fpts(1, n, CV_32FC2);
- Mat tpts(1, n, CV_32FC2);
-
- rng.fill(fpts, CV_RAND_UNI, Scalar(0,0), Scalar(10,10));
- transform(fpts.ptr<Point2f>(), fpts.ptr<Point2f>() + n, tpts.ptr<Point2f>(), WrapAff2D(aff));
-
- Mat noise(1, n, CV_32FC2);
- rng.fill(noise, CV_RAND_NORMAL, Scalar::all(0), Scalar::all(0.001*(n<=7 ? 0 : n <= 30 ? 1 : 10)));
- tpts += noise;
-
- Mat aff_est = estimateRigidTransform(fpts, tpts, true);
-
- double thres = 0.1*norm(aff);
- double d = norm(aff_est, aff, NORM_L2);
- if (d > thres)
- {
- double dB=0, nB=0;
- if (n <= 4)
- {
- Mat A = fpts.reshape(1, 3);
- Mat B = A - repeat(A.row(0), 3, 1), Bt = B.t();
- B = Bt*B;
- dB = cv::determinant(B);
- nB = norm(B);
- if( fabs(dB) < 0.01*nB )
- continue;
- }
- ts->set_failed_test_info(CvTS::FAIL_BAD_ACCURACY);
- ts->printf( CvTS::LOG, "Threshold = %f, norm of difference = %f", thres, d );
- return false;
- }
- }
- return true;
-}
-
-bool CV_RigidTransform_Test::testImage()
-{
- Mat img;
- pyrDown(imread( string(ts->get_data_path()) + "shared/graffiti.png", 1), img);
-
- Mat aff = cv::getRotationMatrix2D(Point(img.cols/2, img.rows/2), 1, 0.99);
- aff.ptr<double>()[2]+=3;
- aff.ptr<double>()[5]+=3;
-
- Mat rotated;
- warpAffine(img, rotated, aff, img.size());
-
- Mat aff_est = estimateRigidTransform(img, rotated, true);
-
- const double thres = 0.03;
- if (norm(aff_est, aff, NORM_INF) > thres)
- {
- ts->set_failed_test_info(CvTS::FAIL_BAD_ACCURACY);
- ts->printf( CvTS::LOG, "Threshold = %f, norm of difference = %f", thres,
- norm(aff_est, aff, NORM_INF) );
- return false;
- }
-
- return true;
-}
-
-void CV_RigidTransform_Test::run( int start_from )
-{
- DefaultRngAuto dra; (void)dra;
-
- if (!testNPoints(start_from))
- return;
-
- if (!testImage())
- return;
-
- ts->set_failed_test_info(CvTS::OK);
-}
-
-CV_RigidTransform_Test CV_RigidTransform_test;
-
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-#include "cvtest.h"
-#include "opencv2/core/core.hpp"
-
-using namespace std;
-using namespace cv;
-
-const string FEATURES2D_DIR = "features2d";
-const string DETECTOR_DIR = FEATURES2D_DIR + "/feature_detectors";
-const string DESCRIPTOR_DIR = FEATURES2D_DIR + "/descriptor_extractors";
-const string IMAGE_FILENAME = "tsukuba.png";
-
-/****************************************************************************************\
-* Regression tests for feature detectors comparing keypoints. *
-\****************************************************************************************/
-
-class CV_FeatureDetectorTest : public CvTest
-{
-public:
- CV_FeatureDetectorTest( const char* testName, const Ptr<FeatureDetector>& _fdetector ) :
- CvTest( testName, "cv::FeatureDetector::detect"), fdetector(_fdetector) {}
-
-protected:
- bool isSimilarKeypoints( const KeyPoint& p1, const KeyPoint& p2 );
- void compareKeypointSets( const vector<KeyPoint>& validKeypoints, const vector<KeyPoint>& calcKeypoints );
-
- void emptyDataTest();
- void regressionTest(); // TODO test of detect() with mask
-
- virtual void run( int );
-
- Ptr<FeatureDetector> fdetector;
-};
-
-void CV_FeatureDetectorTest::emptyDataTest()
-{
- assert( !fdetector.empty() && !fdetector->empty() );
-
- // One image.
- Mat image;
- vector<KeyPoint> keypoints;
- try
- {
- fdetector->detect( image, keypoints );
- }
- catch(...)
- {
- ts->printf( CvTS::LOG, "detect() on empty image must not generate exception (1).\n" );
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- }
-
- if( !keypoints.empty() )
- {
- ts->printf( CvTS::LOG, "detect() on empty image must return empty keypoints vector (1).\n" );
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- return;
- }
-
- // Several images.
- vector<Mat> images;
- vector<vector<KeyPoint> > keypointCollection;
- try
- {
- fdetector->detect( images, keypointCollection );
- }
- catch(...)
- {
- ts->printf( CvTS::LOG, "detect() on empty image vector must not generate exception (2).\n" );
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- }
-}
-
-bool CV_FeatureDetectorTest::isSimilarKeypoints( const KeyPoint& p1, const KeyPoint& p2 )
-{
- const float maxPtDif = 1.f;
- const float maxSizeDif = 1.f;
- const float maxAngleDif = 2.f;
- const float maxResponseDif = 0.1f;
-
- float dist = (float)norm( p1.pt - p2.pt );
- return (dist < maxPtDif &&
- fabs(p1.size - p2.size) < maxSizeDif &&
- abs(p1.angle - p2.angle) < maxAngleDif &&
- abs(p1.response - p2.response) < maxResponseDif &&
- p1.octave == p2.octave &&
- p1.class_id == p2.class_id );
-}
-
-void CV_FeatureDetectorTest::compareKeypointSets( const vector<KeyPoint>& validKeypoints, const vector<KeyPoint>& calcKeypoints )
-{
- const float maxCountRatioDif = 0.01f;
-
- // Compare counts of validation and calculated keypoints.
- float countRatio = (float)validKeypoints.size() / (float)calcKeypoints.size();
- if( countRatio < 1 - maxCountRatioDif || countRatio > 1.f + maxCountRatioDif )
- {
- ts->printf( CvTS::LOG, "Bad keypoints count ratio (validCount = %d, calcCount = %d).\n",
- validKeypoints.size(), calcKeypoints.size() );
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- return;
- }
-
- int progress = 0, progressCount = validKeypoints.size() * calcKeypoints.size();
- int badPointCount = 0, commonPointCount = max(validKeypoints.size(), calcKeypoints.size());
- for( size_t v = 0; v < validKeypoints.size(); v++ )
- {
- int nearestIdx = -1;
- float minDist = std::numeric_limits<float>::max();
-
- for( size_t c = 0; c < calcKeypoints.size(); c++ )
- {
- progress = update_progress( progress, v*calcKeypoints.size() + c, progressCount, 0 );
- float curDist = (float)norm( calcKeypoints[c].pt - validKeypoints[v].pt );
- if( curDist < minDist )
- {
- minDist = curDist;
- nearestIdx = c;
- }
- }
-
- assert( minDist >= 0 );
- if( !isSimilarKeypoints( validKeypoints[v], calcKeypoints[nearestIdx] ) )
- badPointCount++;
- }
- ts->printf( CvTS::LOG, "badPointCount = %d; validPointCount = %d; calcPointCount = %d\n",
- badPointCount, validKeypoints.size(), calcKeypoints.size() );
- if( badPointCount > 0.9 * commonPointCount )
- {
- ts->printf( CvTS::LOG, " - Bad accuracy!\n" );
- ts->set_failed_test_info( CvTS::FAIL_BAD_ACCURACY );
- return;
- }
- ts->printf( CvTS::LOG, " - OK\n" );
-}
-
-void CV_FeatureDetectorTest::regressionTest()
-{
- assert( !fdetector.empty() && !fdetector->empty() );
- string imgFilename = string(ts->get_data_path()) + FEATURES2D_DIR + "/" + IMAGE_FILENAME;
- string resFilename = string(ts->get_data_path()) + DETECTOR_DIR + "/" + string(name) + ".xml.gz";
-
- // Read the test image.
- Mat image = imread( imgFilename );
- if( image.empty() )
- {
- ts->printf( CvTS::LOG, "Image %s can not be read.\n", imgFilename.c_str() );
- ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA );
- return;
- }
-
- FileStorage fs( resFilename, FileStorage::READ );
-
- // Compute keypoints.
- vector<KeyPoint> calcKeypoints;
- fdetector->detect( image, calcKeypoints );
-
- if( fs.isOpened() ) // Compare computed and valid keypoints.
- {
- // TODO compare saved feature detector params with current ones
-
- // Read validation keypoints set.
- vector<KeyPoint> validKeypoints;
- read( fs["keypoints"], validKeypoints );
- if( validKeypoints.empty() )
- {
- ts->printf( CvTS::LOG, "Keypoints can not be read.\n" );
- ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA );
- return;
- }
-
- compareKeypointSets( validKeypoints, calcKeypoints );
- }
- else // Write detector parameters and computed keypoints as validation data.
- {
- fs.open( resFilename, FileStorage::WRITE );
- if( !fs.isOpened() )
- {
- ts->printf( CvTS::LOG, "File %s can not be opened to write.\n", resFilename.c_str() );
- ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA );
- return;
- }
- else
- {
- fs << "detector_params" << "{";
- fdetector->write( fs );
- fs << "}";
-
- write( fs, "keypoints", calcKeypoints );
- }
- }
-}
-
-void CV_FeatureDetectorTest::run( int /*start_from*/ )
-{
- if( fdetector.empty() || fdetector->empty() )
- {
- ts->printf( CvTS::LOG, "Feature detector is empty.\n" );
- ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA );
- return;
- }
-
- emptyDataTest();
- regressionTest();
-
- ts->set_failed_test_info( CvTS::OK );
-}
-
-/****************************************************************************************\
-* Regression tests for descriptor extractors. *
-\****************************************************************************************/
-static void writeMatInBin( const Mat& mat, const string& filename )
-{
- FILE* f = fopen( filename.c_str(), "wb");
- if( f )
- {
- int type = mat.type();
- fwrite( (void*)&mat.rows, sizeof(int), 1, f );
- fwrite( (void*)&mat.cols, sizeof(int), 1, f );
- fwrite( (void*)&type, sizeof(int), 1, f );
- int dataSize = mat.step * mat.rows * mat.channels();
- fwrite( (void*)&dataSize, sizeof(int), 1, f );
- fwrite( (void*)mat.data, 1, dataSize, f );
- fclose(f);
- }
-}
-
-static Mat readMatFromBin( const string& filename )
-{
- FILE* f = fopen( filename.c_str(), "rb" );
- if( f )
- {
- int rows, cols, type, dataSize;
- fread( (void*)&rows, sizeof(int), 1, f );
- fread( (void*)&cols, sizeof(int), 1, f );
- fread( (void*)&type, sizeof(int), 1, f );
- fread( (void*)&dataSize, sizeof(int), 1, f );
-
- uchar* data = (uchar*)cvAlloc(dataSize);
- fread( (void*)data, 1, dataSize, f );
- fclose(f);
-
- return Mat( rows, cols, type, data );
- }
- return Mat();
-}
-
-template<class Distance>
-class CV_DescriptorExtractorTest : public CvTest
-{
-public:
- typedef typename Distance::ValueType ValueType;
- typedef typename Distance::ResultType DistanceType;
-
- CV_DescriptorExtractorTest( const char* testName, DistanceType _maxDist, const Ptr<DescriptorExtractor>& _dextractor, float _prevTime,
- Distance d = Distance() ):
- CvTest( testName, "cv::DescriptorExtractor::compute" ),
- maxDist(_maxDist), prevTime(_prevTime), dextractor(_dextractor), distance(d) {}
-protected:
- virtual void createDescriptorExtractor(){}
-
- void compareDescriptors( const Mat& validDescriptors, const Mat& calcDescriptors )
- {
- if( validDescriptors.size != calcDescriptors.size || validDescriptors.type() != calcDescriptors.type() )
- {
- ts->printf(CvTS::LOG, "Valid and computed descriptors matrices must have the same size and type.\n");
- ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA );
- return;
- }
-
- CV_Assert( DataType<ValueType>::type == validDescriptors.type() );
-
- int dimension = validDescriptors.cols;
- DistanceType curMaxDist = -std::numeric_limits<DistanceType>::max();
- for( int y = 0; y < validDescriptors.rows; y++ )
- {
- DistanceType dist = distance( validDescriptors.ptr<ValueType>(y), calcDescriptors.ptr<ValueType>(y), dimension );
- if( dist > curMaxDist )
- curMaxDist = dist;
- }
-
- stringstream ss;
- ss << "Max distance between valid and computed descriptors " << curMaxDist;
- if( curMaxDist < maxDist )
- ss << "." << endl;
- else
- {
- ss << ">" << maxDist << " - bad accuracy!"<< endl;
- ts->set_failed_test_info( CvTS::FAIL_BAD_ACCURACY );
- }
- ts->printf(CvTS::LOG, ss.str().c_str() );
- }
-
- void emptyDataTest()
- {
- assert( !dextractor.empty() && !dextractor->empty() );
-
- // One image.
- Mat image;
- vector<KeyPoint> keypoints;
- Mat descriptors;
-
- try
- {
- dextractor->compute( image, keypoints, descriptors );
- }
- catch(...)
- {
- ts->printf( CvTS::LOG, "compute() on empty image and empty keypoints must not generate exception (1).\n");
- ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA );
- }
-
- image.create( 50, 50, CV_8UC3 );
- try
- {
- dextractor->compute( image, keypoints, descriptors );
- }
- catch(...)
- {
- ts->printf( CvTS::LOG, "compute() on nonempty image and empty keypoints must not generate exception (1).\n");
- ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA );
- }
-
- // Several images.
- vector<Mat> images;
- vector<vector<KeyPoint> > keypointsCollection;
- vector<Mat> descriptorsCollection;
- try
- {
- dextractor->compute( images, keypointsCollection, descriptorsCollection );
- }
- catch(...)
- {
- ts->printf( CvTS::LOG, "compute() on empty images and empty keypoints collection must not generate exception (2).\n");
- ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA );
- }
- }
-
- void regressionTest()
- {
- assert( !dextractor.empty() && !dextractor->empty() );
-
- // Read the test image.
- string imgFilename = string(ts->get_data_path()) + FEATURES2D_DIR + "/" + IMAGE_FILENAME;
-
- Mat img = imread( imgFilename );
- if( img.empty() )
- {
- ts->printf( CvTS::LOG, "Image %s can not be read.\n", imgFilename.c_str() );
- ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA );
- return;
- }
-
- vector<KeyPoint> keypoints;
- FileStorage fs( string(ts->get_data_path()) + FEATURES2D_DIR + "/keypoints.xml.gz", FileStorage::READ );
- if( fs.isOpened() )
- {
- read( fs.getFirstTopLevelNode(), keypoints );
-
- Mat calcDescriptors;
- double t = (double)getTickCount();
- dextractor->compute( img, keypoints, calcDescriptors );
- t = getTickCount() - t;
- ts->printf(CvTS::LOG, "\nAverage time of computiting one descriptor = %g ms (previous time = %g ms).\n", t/((double)cvGetTickFrequency()*1000.)/calcDescriptors.rows, prevTime );
-
- if( calcDescriptors.rows != (int)keypoints.size() )
- {
- ts->printf( CvTS::LOG, "Count of computed descriptors and keypoints count must be equal.\n" );
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- return;
- }
-
- if( calcDescriptors.cols != dextractor->descriptorSize() || calcDescriptors.type() != dextractor->descriptorType() )
- {
- ts->printf( CvTS::LOG, "Incorrect descriptor size or descriptor type.\n" );
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- return;
- }
-
- // TODO read and write descriptor extractor parameters and check them
- Mat validDescriptors = readDescriptors();
- if( !validDescriptors.empty() )
- compareDescriptors( validDescriptors, calcDescriptors );
- else
- {
- if( !writeDescriptors( calcDescriptors ) )
- {
- ts->printf( CvTS::LOG, "Descriptors can not be written.\n" );
- ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA );
- return;
- }
- }
- }
- else
- {
- ts->printf( CvTS::LOG, "Compute and write keypoints.\n" );
- fs.open( string(ts->get_data_path()) + FEATURES2D_DIR + "/keypoints.xml.gz", FileStorage::WRITE );
- if( fs.isOpened() )
- {
- SurfFeatureDetector fd;
- fd.detect(img, keypoints);
- write( fs, "keypoints", keypoints );
- }
- else
- {
- ts->printf(CvTS::LOG, "File for writting keypoints can not be opened.\n");
- ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA );
- return;
- }
- }
- }
-
- void run(int)
- {
- createDescriptorExtractor();
- if( dextractor.empty() || dextractor->empty() )
- {
- ts->printf(CvTS::LOG, "Descriptor extractor is empty.\n");
- ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA );
- return;
- }
-
- emptyDataTest();
- regressionTest();
-
- ts->set_failed_test_info( CvTS::OK );
- }
-
- virtual Mat readDescriptors()
- {
- Mat res = readMatFromBin( string(ts->get_data_path()) + DESCRIPTOR_DIR + "/" + string(name) );
- return res;
- }
-
- virtual bool writeDescriptors( Mat& descs )
- {
- writeMatInBin( descs, string(ts->get_data_path()) + DESCRIPTOR_DIR + "/" + string(name) );
- return true;
- }
-
- const DistanceType maxDist;
- const float prevTime;
-
- Ptr<DescriptorExtractor> dextractor;
- Distance distance;
-
-private:
- CV_DescriptorExtractorTest& operator=(const CV_DescriptorExtractorTest&) { return *this; }
-};
-
-template<typename T, typename Distance>
-class CV_CalonderDescriptorExtractorTest : public CV_DescriptorExtractorTest<Distance>
-{
-public:
- CV_CalonderDescriptorExtractorTest( const char* testName, float _normDif, float _prevTime ) :
- CV_DescriptorExtractorTest<Distance>( testName, _normDif, Ptr<DescriptorExtractor>(), _prevTime )
- {}
-
-protected:
- virtual void createDescriptorExtractor()
- {
- string filename = string(CV_DescriptorExtractorTest<Distance>::ts->get_data_path()) +
- FEATURES2D_DIR + "/calonder_classifier.rtc";
- CV_DescriptorExtractorTest<Distance>::dextractor =
- new CalonderDescriptorExtractor<T>( filename );
- if( CV_DescriptorExtractorTest<Distance>::dextractor->empty() )
- {
- stringstream ss; ss << "Calonder descriptor extractor can not be loaded from file" << filename<< endl;
- CV_DescriptorExtractorTest<Distance>::ts->printf( CvTS::LOG, ss.str().c_str() );
- CV_DescriptorExtractorTest<Distance>::ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA );
- }
- }
-};
-
-/****************************************************************************************\
-* Algorithmic tests for descriptor matchers *
-\****************************************************************************************/
-class CV_DescriptorMatcherTest : public CvTest
-{
-public:
- CV_DescriptorMatcherTest( const char* testName, const Ptr<DescriptorMatcher>& _dmatcher, float _badPart ) :
- CvTest( testName, "cv::DescritorMatcher::[,knn,radius]match()"), badPart(_badPart), dmatcher(_dmatcher)
- {}
-protected:
- static const int dim = 500;
- static const int queryDescCount = 300; // must be even number because we split train data in some cases in two
- static const int countFactor = 4; // do not change it
- const float badPart;
-
- virtual void run( int );
- void generateData( Mat& query, Mat& train );
-
- void emptyDataTest();
- void matchTest( const Mat& query, const Mat& train );
- void knnMatchTest( const Mat& query, const Mat& train );
- void radiusMatchTest( const Mat& query, const Mat& train );
-
- Ptr<DescriptorMatcher> dmatcher;
-private:
- CV_DescriptorMatcherTest& operator=(const CV_DescriptorMatcherTest&) { return *this; }
-};
-
-void CV_DescriptorMatcherTest::emptyDataTest()
-{
- assert( !dmatcher.empty() && !dmatcher->empty() );
-
- Mat queryDescriptors, trainDescriptors, mask;
- vector<Mat> trainDescriptorCollection, masks;
- vector<DMatch> matches;
- vector<vector<DMatch> > vmatches;
-
- try
- {
- dmatcher->match( queryDescriptors, trainDescriptors, matches, mask );
- }
- catch(...)
- {
- ts->printf( CvTS::LOG, "match() on empty descriptors must not generate exception (1).\n" );
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- }
-
- try
- {
- dmatcher->knnMatch( queryDescriptors, trainDescriptors, vmatches, 2, mask );
- }
- catch(...)
- {
- ts->printf( CvTS::LOG, "knnMatch() on empty descriptors must not generate exception (1).\n" );
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- }
-
- try
- {
- dmatcher->radiusMatch( queryDescriptors, trainDescriptors, vmatches, 10.f, mask );
- }
- catch(...)
- {
- ts->printf( CvTS::LOG, "radiusMatch() on empty descriptors must not generate exception (1).\n" );
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- }
-
- try
- {
- dmatcher->add( trainDescriptorCollection );
- }
- catch(...)
- {
- ts->printf( CvTS::LOG, "add() on empty descriptors must not generate exception.\n" );
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- }
-
- try
- {
- dmatcher->match( queryDescriptors, matches, masks );
- }
- catch(...)
- {
- ts->printf( CvTS::LOG, "match() on empty descriptors must not generate exception (2).\n" );
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- }
-
- try
- {
- dmatcher->knnMatch( queryDescriptors, vmatches, 2, masks );
- }
- catch(...)
- {
- ts->printf( CvTS::LOG, "knnMatch() on empty descriptors must not generate exception (2).\n" );
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- }
-
- try
- {
- dmatcher->radiusMatch( queryDescriptors, vmatches, 10.f, masks );
- }
- catch(...)
- {
- ts->printf( CvTS::LOG, "radiusMatch() on empty descriptors must not generate exception (2).\n" );
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- }
-
-}
-
-void CV_DescriptorMatcherTest::generateData( Mat& query, Mat& train )
-{
- RNG& rng = theRNG();
-
- // Generate query descriptors randomly.
- // Descriptor vector elements are integer values.
- Mat buf( queryDescCount, dim, CV_32SC1 );
- rng.fill( buf, RNG::UNIFORM, Scalar::all(0), Scalar(3) );
- buf.convertTo( query, CV_32FC1 );
-
- // Generate train decriptors as follows:
- // copy each query descriptor to train set countFactor times
- // and perturb some one element of the copied descriptors in
- // in ascending order. General boundaries of the perturbation
- // are (0.f, 1.f).
- train.create( query.rows*countFactor, query.cols, CV_32FC1 );
- float step = 1.f / countFactor;
- for( int qIdx = 0; qIdx < query.rows; qIdx++ )
- {
- Mat queryDescriptor = query.row(qIdx);
- for( int c = 0; c < countFactor; c++ )
- {
- int tIdx = qIdx * countFactor + c;
- Mat trainDescriptor = train.row(tIdx);
- queryDescriptor.copyTo( trainDescriptor );
- int elem = rng(dim);
- float diff = rng.uniform( step*c, step*(c+1) );
- trainDescriptor.at<float>(0, elem) += diff;
- }
- }
-}
-
-void CV_DescriptorMatcherTest::matchTest( const Mat& query, const Mat& train )
-{
- dmatcher->clear();
-
- // test const version of match()
- {
- vector<DMatch> matches;
- dmatcher->match( query, train, matches );
-
- if( (int)matches.size() != queryDescCount )
- {
- ts->printf(CvTS::LOG, "Incorrect matches count while test match() function (1).\n");
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- }
- else
- {
- int badCount = 0;
- for( size_t i = 0; i < matches.size(); i++ )
- {
- DMatch match = matches[i];
- if( (match.queryIdx != (int)i) || (match.trainIdx != (int)i*countFactor) || (match.imgIdx != 0) )
- badCount++;
- }
- if( (float)badCount > (float)queryDescCount*badPart )
- {
- ts->printf( CvTS::LOG, "%f - too large bad matches part while test match() function (1).\n",
- (float)badCount/(float)queryDescCount );
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- }
- }
- }
-
- // test version of match() with add()
- {
- vector<DMatch> matches;
- // make add() twice to test such case
- dmatcher->add( vector<Mat>(1,train.rowRange(0, train.rows/2)) );
- dmatcher->add( vector<Mat>(1,train.rowRange(train.rows/2, train.rows)) );
- // prepare masks (make first nearest match illegal)
- vector<Mat> masks(2);
- for(int mi = 0; mi < 2; mi++ )
- {
- masks[mi] = Mat(query.rows, train.rows/2, CV_8UC1, Scalar::all(1));
- for( int di = 0; di < queryDescCount/2; di++ )
- masks[mi].col(di*countFactor).setTo(Scalar::all(0));
- }
-
- dmatcher->match( query, matches, masks );
-
- if( (int)matches.size() != queryDescCount )
- {
- ts->printf(CvTS::LOG, "Incorrect matches count while test match() function (2).\n");
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- }
- else
- {
- int badCount = 0;
- for( size_t i = 0; i < matches.size(); i++ )
- {
- DMatch match = matches[i];
- int shift = dmatcher->isMaskSupported() ? 1 : 0;
- {
- if( i < queryDescCount/2 )
- {
- if( (match.queryIdx != (int)i) || (match.trainIdx != (int)i*countFactor + shift) || (match.imgIdx != 0) )
- badCount++;
- }
- else
- {
- if( (match.queryIdx != (int)i) || (match.trainIdx != ((int)i-queryDescCount/2)*countFactor + shift) || (match.imgIdx != 1) )
- badCount++;
- }
- }
- }
- if( (float)badCount > (float)queryDescCount*badPart )
- {
- ts->printf( CvTS::LOG, "%f - too large bad matches part while test match() function (2).\n",
- (float)badCount/(float)queryDescCount );
- ts->set_failed_test_info( CvTS::FAIL_BAD_ACCURACY );
- }
- }
- }
-}
-
-void CV_DescriptorMatcherTest::knnMatchTest( const Mat& query, const Mat& train )
-{
- dmatcher->clear();
-
- // test const version of knnMatch()
- {
- const int knn = 3;
-
- vector<vector<DMatch> > matches;
- dmatcher->knnMatch( query, train, matches, knn );
-
- if( (int)matches.size() != queryDescCount )
- {
- ts->printf(CvTS::LOG, "Incorrect matches count while test knnMatch() function (1).\n");
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- }
- else
- {
- int badCount = 0;
- for( size_t i = 0; i < matches.size(); i++ )
- {
- if( (int)matches[i].size() != knn )
- badCount++;
- else
- {
- int localBadCount = 0;
- for( int k = 0; k < knn; k++ )
- {
- DMatch match = matches[i][k];
- if( (match.queryIdx != (int)i) || (match.trainIdx != (int)i*countFactor+k) || (match.imgIdx != 0) )
- localBadCount++;
- }
- badCount += localBadCount > 0 ? 1 : 0;
- }
- }
- if( (float)badCount > (float)queryDescCount*badPart )
- {
- ts->printf( CvTS::LOG, "%f - too large bad matches part while test knnMatch() function (1).\n",
- (float)badCount/(float)queryDescCount );
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- }
- }
- }
-
- // test version of knnMatch() with add()
- {
- const int knn = 2;
- vector<vector<DMatch> > matches;
- // make add() twice to test such case
- dmatcher->add( vector<Mat>(1,train.rowRange(0, train.rows/2)) );
- dmatcher->add( vector<Mat>(1,train.rowRange(train.rows/2, train.rows)) );
- // prepare masks (make first nearest match illegal)
- vector<Mat> masks(2);
- for(int mi = 0; mi < 2; mi++ )
- {
- masks[mi] = Mat(query.rows, train.rows/2, CV_8UC1, Scalar::all(1));
- for( int di = 0; di < queryDescCount/2; di++ )
- masks[mi].col(di*countFactor).setTo(Scalar::all(0));
- }
-
- dmatcher->knnMatch( query, matches, knn, masks );
-
- if( (int)matches.size() != queryDescCount )
- {
- ts->printf(CvTS::LOG, "Incorrect matches count while test knnMatch() function (2).\n");
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- }
- else
- {
- int badCount = 0;
- int shift = dmatcher->isMaskSupported() ? 1 : 0;
- for( size_t i = 0; i < matches.size(); i++ )
- {
- if( (int)matches[i].size() != knn )
- badCount++;
- else
- {
- int localBadCount = 0;
- for( int k = 0; k < knn; k++ )
- {
- DMatch match = matches[i][k];
- {
- if( i < queryDescCount/2 )
- {
- if( (match.queryIdx != (int)i) || (match.trainIdx != (int)i*countFactor + k + shift) ||
- (match.imgIdx != 0) )
- localBadCount++;
- }
- else
- {
- if( (match.queryIdx != (int)i) || (match.trainIdx != ((int)i-queryDescCount/2)*countFactor + k + shift) ||
- (match.imgIdx != 1) )
- localBadCount++;
- }
- }
- }
- badCount += localBadCount > 0 ? 1 : 0;
- }
- }
- if( (float)badCount > (float)queryDescCount*badPart )
- {
- ts->printf( CvTS::LOG, "%f - too large bad matches part while test knnMatch() function (2).\n",
- (float)badCount/(float)queryDescCount );
- ts->set_failed_test_info( CvTS::FAIL_BAD_ACCURACY );
- }
- }
- }
-}
-
-void CV_DescriptorMatcherTest::radiusMatchTest( const Mat& query, const Mat& train )
-{
- dmatcher->clear();
- // test const version of match()
- {
- const float radius = 1.f/countFactor;
- vector<vector<DMatch> > matches;
- dmatcher->radiusMatch( query, train, matches, radius );
-
- if( (int)matches.size() != queryDescCount )
- {
- ts->printf(CvTS::LOG, "Incorrect matches count while test radiusMatch() function (1).\n");
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- }
- else
- {
- int badCount = 0;
- for( size_t i = 0; i < matches.size(); i++ )
- {
- if( (int)matches[i].size() != 1 )
- badCount++;
- else
- {
- DMatch match = matches[i][0];
- if( (match.queryIdx != (int)i) || (match.trainIdx != (int)i*countFactor) || (match.imgIdx != 0) )
- badCount++;
- }
- }
- if( (float)badCount > (float)queryDescCount*badPart )
- {
- ts->printf( CvTS::LOG, "%f - too large bad matches part while test radiusMatch() function (1).\n",
- (float)badCount/(float)queryDescCount );
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- }
- }
- }
-
- // test version of match() with add()
- {
- int n = 3;
- const float radius = 1.f/countFactor * n;
- vector<vector<DMatch> > matches;
- // make add() twice to test such case
- dmatcher->add( vector<Mat>(1,train.rowRange(0, train.rows/2)) );
- dmatcher->add( vector<Mat>(1,train.rowRange(train.rows/2, train.rows)) );
- // prepare masks (make first nearest match illegal)
- vector<Mat> masks(2);
- for(int mi = 0; mi < 2; mi++ )
- {
- masks[mi] = Mat(query.rows, train.rows/2, CV_8UC1, Scalar::all(1));
- for( int di = 0; di < queryDescCount/2; di++ )
- masks[mi].col(di*countFactor).setTo(Scalar::all(0));
- }
-
- dmatcher->radiusMatch( query, matches, radius, masks );
-
- int curRes = CvTS::OK;
- if( (int)matches.size() != queryDescCount )
- {
- ts->printf(CvTS::LOG, "Incorrect matches count while test radiusMatch() function (1).\n");
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- }
-
- int badCount = 0;
- int shift = dmatcher->isMaskSupported() ? 1 : 0;
- int needMatchCount = dmatcher->isMaskSupported() ? n-1 : n;
- for( size_t i = 0; i < matches.size(); i++ )
- {
- if( (int)matches[i].size() != needMatchCount )
- badCount++;
- else
- {
- int localBadCount = 0;
- for( int k = 0; k < needMatchCount; k++ )
- {
- DMatch match = matches[i][k];
- {
- if( i < queryDescCount/2 )
- {
- if( (match.queryIdx != (int)i) || (match.trainIdx != (int)i*countFactor + k + shift) ||
- (match.imgIdx != 0) )
- localBadCount++;
- }
- else
- {
- if( (match.queryIdx != (int)i) || (match.trainIdx != ((int)i-queryDescCount/2)*countFactor + k + shift) ||
- (match.imgIdx != 1) )
- localBadCount++;
- }
- }
- }
- badCount += localBadCount > 0 ? 1 : 0;
- }
- }
- if( (float)badCount > (float)queryDescCount*badPart )
- {
- curRes = CvTS::FAIL_INVALID_OUTPUT;
- ts->printf( CvTS::LOG, "%f - too large bad matches part while test radiusMatch() function (2).\n",
- (float)badCount/(float)queryDescCount );
- ts->set_failed_test_info( CvTS::FAIL_BAD_ACCURACY );
- }
- }
-}
-
-void CV_DescriptorMatcherTest::run( int )
-{
- Mat query, train;
- generateData( query, train );
-
- matchTest( query, train );
-
- knnMatchTest( query, train );
-
- radiusMatchTest( query, train );
-}
-
-/****************************************************************************************\
-* Tests registrations *
-\****************************************************************************************/
-
-/*
- * Detectors
- * "detector-fast, detector-gftt, detector-harris, detector-mser, detector-sift, detector-star, detector-surf, detector-grid-fast, detector-pyramid-fast"
- */
-CV_FeatureDetectorTest fastTest( "detector-fast", FeatureDetector::create("FAST") );
-CV_FeatureDetectorTest gfttTest( "detector-gftt", FeatureDetector::create("GFTT") );
-CV_FeatureDetectorTest harrisTest( "detector-harris", FeatureDetector::create("HARRIS") );
-CV_FeatureDetectorTest mserTest( "detector-mser", FeatureDetector::create("MSER") );
-CV_FeatureDetectorTest siftTest( "detector-sift", FeatureDetector::create("SIFT") );
-CV_FeatureDetectorTest starTest( "detector-star", FeatureDetector::create("STAR") );
-CV_FeatureDetectorTest surfTest( "detector-surf", FeatureDetector::create("SURF") );
-CV_FeatureDetectorTest gridFastfTest( "detector-grid-fast", FeatureDetector::create("GridFAST") );
-CV_FeatureDetectorTest pyramidFastTest( "detector-pyramid-fast", FeatureDetector::create("PyramidFAST") );
-
-/*
- * Descriptors
- * "descriptor-sift, descriptor-surf, descriptor-calonder-uchar, descriptor-calonder-float, descriptor-brief, descriptor-opponent-sift, descriptor-opponent-surf"
- */
-CV_DescriptorExtractorTest<L2<float> > siftDescriptorTest( "descriptor-sift", 0.03f,
- DescriptorExtractor::create("SIFT"), 8.06652f );
-CV_DescriptorExtractorTest<L2<float> > surfDescriptorTest( "descriptor-surf", 0.035f,
- DescriptorExtractor::create("SURF"), 0.147372f );
-CV_DescriptorExtractorTest<Hamming> briefDescriptorTest( "descriptor-brief", 1,
- DescriptorExtractor::create("BRIEF"), 0.00527548f );
-
-CV_DescriptorExtractorTest<L2<float> > oppSiftDescriptorTest( "descriptor-opponent-sift", 0.18f,
- DescriptorExtractor::create("OpponentSIFT"), 8.06652f );
-CV_DescriptorExtractorTest<L2<float> > oppurfDescriptorTest( "descriptor-opponent-surf", 0.18f,
- DescriptorExtractor::create("OpponentSURF"), 0.147372f );
-
-#if CV_SSE2
-CV_CalonderDescriptorExtractorTest<uchar, L2<uchar> > ucharCalonderTest( "descriptor-calonder-uchar",
- std::numeric_limits<float>::epsilon() + 1,
- 0.0132175f );
-CV_CalonderDescriptorExtractorTest<float, L2<float> > floatCalonderTest( "descriptor-calonder-float",
- std::numeric_limits<float>::epsilon(),
- 0.0221308f );
-#endif // CV_SSE2
-
-/*
- * Matchers
- * "descriptor-matcher-brute-force, descriptor-matcher-flann-based"
- */
-CV_DescriptorMatcherTest bruteForceMatcherTest( "descriptor-matcher-brute-force",
- new BruteForceMatcher<L2<float> >, 0.01f );
-CV_DescriptorMatcherTest flannBasedMatcherTest( "descriptor-matcher-flann-based",
- new FlannBasedMatcher, 0.04f );
-
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////\r
-//\r
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.\r
-//\r
-// By downloading, copying, installing or using the software you agree to this license.\r
-// If you do not agree to this license, do not download, install,\r
-// copy or use the software.\r
-//\r
-//\r
-// License Agreement\r
-// For Open Source Computer Vision Library\r
-//\r
-// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.\r
-// Copyright (C) 2009, Willow Garage Inc., all rights reserved.\r
-// Third party copyrights are property of their respective owners.\r
-//\r
-// Redistribution and use in source and binary forms, with or without modification,\r
-// are permitted provided that the following conditions are met:\r
-//\r
-// * Redistribution's of source code must retain the above copyright notice,\r
-// this list of conditions and the following disclaimer.\r
-//\r
-// * Redistribution's in binary form must reproduce the above copyright notice,\r
-// this list of conditions and the following disclaimer in the documentation\r
-// and/or other materials provided with the distribution.\r
-//\r
-// * The name of the copyright holders may not be used to endorse or promote products\r
-// derived from this software without specific prior written permission.\r
-//\r
-// This software is provided by the copyright holders and contributors "as is" and\r
-// any express or implied warranties, including, but not limited to, the implied\r
-// warranties of merchantability and fitness for a particular purpose are disclaimed.\r
-// In no event shall the Intel Corporation or contributors be liable for any direct,\r
-// indirect, incidental, special, exemplary, or consequential damages\r
-// (including, but not limited to, procurement of substitute goods or services;\r
-// loss of use, data, or profits; or business interruption) however caused\r
-// and on any theory of liability, whether in contract, strict liability,\r
-// or tort (including negligence or otherwise) arising in any way out of\r
-// the use of this software, even if advised of the possibility of such damage.\r
-//\r
-//M*/\r
-\r
-#include "cvtest.h"\r
-#include <string>\r
-#include <iostream>\r
-#include <fstream>\r
-#include <iterator>\r
-#include <limits>\r
-#include <numeric>\r
-#include "cvaux.h"\r
-\r
-using namespace cv;\r
-using namespace std;\r
-\r
-class CV_Affine3D_EstTest : public CvTest\r
-{\r
-public:\r
- CV_Affine3D_EstTest();\r
- ~CV_Affine3D_EstTest(); \r
-protected:\r
- void run(int); \r
-\r
- bool test4Points();\r
- bool testNPoints();\r
-};\r
-\r
-CV_Affine3D_EstTest::CV_Affine3D_EstTest(): CvTest( "algorithm-estimateAffine3D", "cv::estimateAffine3D" )\r
-{\r
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;\r
-}\r
-CV_Affine3D_EstTest::~CV_Affine3D_EstTest() {}\r
-\r
-\r
-float rngIn(float from, float to) { return from + (to-from) * (float)theRNG(); }\r
-\r
-\r
-struct WrapAff\r
-{\r
- const double *F;\r
- WrapAff(const Mat& aff) : F(aff.ptr<double>()) {}\r
- Point3f operator()(const Point3f& p)\r
- {\r
- return Point3d( p.x * F[0] + p.y * F[1] + p.z * F[2] + F[3],\r
- p.x * F[4] + p.y * F[5] + p.z * F[6] + F[7],\r
- p.x * F[8] + p.y * F[9] + p.z * F[10] + F[11] ); \r
- }\r
-};\r
-\r
-bool CV_Affine3D_EstTest::test4Points()\r
-{ \r
- Mat aff(3, 4, CV_64F);\r
- cv::randu(aff, Scalar(1), Scalar(3));\r
- \r
- // setting points that are no in the same line\r
-\r
- Mat fpts(1, 4, CV_32FC3);\r
- Mat tpts(1, 4, CV_32FC3);\r
- \r
- fpts.ptr<Point3f>()[0] = Point3f( rngIn(1,2), rngIn(1,2), rngIn(5, 6) );\r
- fpts.ptr<Point3f>()[1] = Point3f( rngIn(3,4), rngIn(3,4), rngIn(5, 6) );\r
- fpts.ptr<Point3f>()[2] = Point3f( rngIn(1,2), rngIn(3,4), rngIn(5, 6) );\r
- fpts.ptr<Point3f>()[3] = Point3f( rngIn(3,4), rngIn(1,2), rngIn(5, 6) );\r
- \r
- transform(fpts.ptr<Point3f>(), fpts.ptr<Point3f>() + 4, tpts.ptr<Point3f>(), WrapAff(aff));\r
-\r
- Mat aff_est;\r
- vector<uchar> outliers;\r
- estimateAffine3D(fpts, tpts, aff_est, outliers);\r
-\r
- const double thres = 1e-3;\r
- if (norm(aff_est, aff, NORM_INF) > thres)\r
- {\r
- //cout << norm(aff_est, aff, NORM_INF) << endl;\r
- ts->set_failed_test_info(CvTS::FAIL_MISMATCH);\r
- return false;\r
- } \r
- return true;\r
-}\r
-\r
-struct Noise\r
-{\r
- float l;\r
- Noise(float level) : l(level) {}\r
- Point3f operator()(const Point3f& p)\r
- {\r
- RNG& rng = theRNG(); \r
- return Point3f( p.x + l * (float)rng, p.y + l * (float)rng, p.z + l * (float)rng); \r
- }\r
-};\r
-\r
-bool CV_Affine3D_EstTest::testNPoints()\r
-{ \r
- Mat aff(3, 4, CV_64F);\r
- cv::randu(aff, Scalar(-2), Scalar(2));\r
- \r
- // setting points that are no in the same line\r
- \r
- const int n = 100;\r
- const int m = 3*n/5;\r
- const Point3f shift_outl = Point3f(15, 15, 15);\r
- const float noise_level = 20.f;\r
- \r
- Mat fpts(1, n, CV_32FC3);\r
- Mat tpts(1, n, CV_32FC3);\r
- \r
- randu(fpts, Scalar::all(0), Scalar::all(100)); \r
- transform(fpts.ptr<Point3f>(), fpts.ptr<Point3f>() + n, tpts.ptr<Point3f>(), WrapAff(aff));\r
-\r
- /* adding noise*/\r
- transform(tpts.ptr<Point3f>() + m, tpts.ptr<Point3f>() + n, tpts.ptr<Point3f>() + m, bind2nd(plus<Point3f>(), shift_outl));\r
- transform(tpts.ptr<Point3f>() + m, tpts.ptr<Point3f>() + n, tpts.ptr<Point3f>() + m, Noise(noise_level));\r
- \r
- Mat aff_est;\r
- vector<uchar> outl;\r
- int res = estimateAffine3D(fpts, tpts, aff_est, outl);\r
-\r
- if (!res)\r
- { \r
- ts->set_failed_test_info(CvTS::FAIL_MISMATCH);\r
- return false;\r
- }\r
-\r
- const double thres = 1e-4;\r
- if (norm(aff_est, aff, NORM_INF) > thres)\r
- { \r
- ts->set_failed_test_info(CvTS::FAIL_MISMATCH);\r
- return false;\r
- } \r
-\r
- bool outl_good = count(outl.begin(), outl.end(), 1) == m && \r
- m == accumulate(outl.begin(), outl.begin() + m, 0);\r
-\r
- if (!outl_good)\r
- {\r
- ts->set_failed_test_info(CvTS::FAIL_MISMATCH);\r
- return false;\r
- }\r
- return true;\r
-}\r
-\r
-\r
-void CV_Affine3D_EstTest::run( int /* start_from */)\r
-{ \r
- DefaultRngAuto dra; (void)dra;\r
-\r
- if (!test4Points())\r
- return;\r
-\r
- if (!testNPoints())\r
- return;\r
-\r
- ts->set_failed_test_info(CvTS::OK);\r
-}\r
-\r
-CV_Affine3D_EstTest CV_Affine3D_Est_test;\r
-\r
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-static const CvSize filter_sizes[] = {{30,30}, {320, 240}, {720,480}, {-1,-1}};
-static const CvSize filter_whole_sizes[] = {{320,240}, {320, 240}, {720,480}, {-1,-1}};
-static const int filter_depths[] = { CV_8U, CV_16U, CV_32F, -1 };
-static const int filter_channels[] = { 1, 3, 4, -1 };
-
-class CV_FilterBaseTestImpl : public CvArrTest
-{
-public:
- CV_FilterBaseTestImpl( const char* test_name, const char* test_funcs, bool _fp_kernel );
-
-protected:
- int prepare_test_case( int test_case_idx );
- void prepare_to_validation( int /*test_case_idx*/ );
- int read_params( CvFileStorage* fs );
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void get_minmax_bounds( int i, int j, int type, CvScalar* low, CvScalar* high );
- int write_default_params(CvFileStorage* fs);
- CvSize aperture_size;
- CvPoint anchor;
- int max_aperture_size;
- bool fp_kernel;
- bool inplace;
-};
-
-
-CV_FilterBaseTestImpl::CV_FilterBaseTestImpl( const char* test_name, const char* test_funcs, bool _fp_kernel )
- : CvArrTest( test_name, test_funcs, "" ), fp_kernel(_fp_kernel)
-{
- test_array[INPUT].push(NULL);
- test_array[INPUT].push(NULL);
- test_array[TEMP].push(NULL);
- test_array[OUTPUT].push(NULL);
- test_array[REF_OUTPUT].push(NULL);
- max_aperture_size = 13;
- inplace = false;
- aperture_size = cvSize(0,0);
- anchor = cvPoint(0,0);
- element_wise_relative_error = false;
-
- size_list = filter_sizes;
- whole_size_list = filter_whole_sizes;
- depth_list = filter_depths;
- cn_list = filter_channels;
-}
-
-
-int CV_FilterBaseTestImpl::read_params( CvFileStorage* fs )
-{
- int code = CvArrTest::read_params( fs );
- if( code < 0 )
- return code;
-
- if( ts->get_testing_mode() == CvTS::CORRECTNESS_CHECK_MODE )
- {
- max_aperture_size = cvReadInt( find_param( fs, "max_aperture_size" ), max_aperture_size );
- max_aperture_size = cvTsClipInt( max_aperture_size, 1, 100 );
- }
-
- return code;
-}
-
-
-int CV_FilterBaseTestImpl::write_default_params( CvFileStorage* fs )
-{
- int code = CvArrTest::write_default_params( fs );
- if( code < 0 )
- return code;
-
- if( ts->get_testing_mode() == CvTS::CORRECTNESS_CHECK_MODE )
- {
- write_param( fs, "max_aperture_size", max_aperture_size );
- }
-
- return code;
-}
-
-
-void CV_FilterBaseTestImpl::get_minmax_bounds( int i, int j, int type, CvScalar* low, CvScalar* high )
-{
- CvArrTest::get_minmax_bounds( i, j, type, low, high );
- if( i == INPUT )
- {
- if( j == 1 )
- {
- if( fp_kernel )
- {
- if( ts->get_testing_mode() == CvTS::TIMING_MODE )
- {
- *low = cvScalarAll(-1);
- *high = cvScalarAll(1);
- }
- else
- {
- CvRNG* rng = ts->get_rng();
- double val = exp( cvTsRandReal(rng)*10 - 4 );
- *low = cvScalarAll(-val);
- *high = cvScalarAll(val);
- }
- }
- else
- {
- *low = cvScalarAll(0);
- *high = cvScalarAll(2);
- }
- }
- else if( CV_MAT_DEPTH(type) == CV_32F )
- {
- *low = cvScalarAll(-10.);
- *high = cvScalarAll(10.);
- }
- }
-}
-
-
-void CV_FilterBaseTestImpl::get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- int depth = cvTsRandInt(rng) % CV_32F;
- int cn = cvTsRandInt(rng) % 3 + 1;
- CvArrTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- depth += depth == CV_8S;
- cn += cn == 2;
-
- types[INPUT][0] = types[OUTPUT][0] = types[REF_OUTPUT][0] = types[TEMP][0] = CV_MAKETYPE(depth, cn);
-
- aperture_size.width = cvTsRandInt(rng) % max_aperture_size + 1;
- aperture_size.height = cvTsRandInt(rng) % max_aperture_size + 1;
- anchor.x = cvTsRandInt(rng) % aperture_size.width;
- anchor.y = cvTsRandInt(rng) % aperture_size.height;
-
- types[INPUT][1] = fp_kernel ? CV_32FC1 : CV_8UC1;
- sizes[INPUT][1] = aperture_size;
- sizes[TEMP][0].width += aperture_size.width - 1;
- sizes[TEMP][0].height += aperture_size.height - 1;
-
- inplace = cvTsRandInt(rng) % 2 != 0;
-}
-
-
-int CV_FilterBaseTestImpl::prepare_test_case( int test_case_idx )
-{
- int code = CvArrTest::prepare_test_case( test_case_idx );
- if( code > 0 )
- {
- if( inplace && CV_ARE_TYPES_EQ(&test_mat[INPUT][0],&test_mat[OUTPUT][0]))
- cvTsCopy( &test_mat[INPUT][0], &test_mat[OUTPUT][0] );
- else
- inplace = false;
- }
- return code;
-}
-
-
-void CV_FilterBaseTestImpl::prepare_to_validation( int /*test_case_idx*/ )
-{
- CvMat* src = &test_mat[INPUT][0];
-
- if( !CV_ARE_TYPES_EQ( src, &test_mat[TEMP][0] ))
- {
- cvTsConvert( src, &test_mat[REF_OUTPUT][0] );
- src = &test_mat[REF_OUTPUT][0];
- }
- cvTsPrepareToFilter( src, &test_mat[TEMP][0],
- anchor, CV_TS_BORDER_REPLICATE );
-}
-
-
-CV_FilterBaseTestImpl filter_base( "filter", "", false );
-
-
-class CV_FilterBaseTest : public CV_FilterBaseTestImpl
-{
-public:
- CV_FilterBaseTest( const char* test_name, const char* test_funcs, bool _fp_kernel );
-};
-
-
-CV_FilterBaseTest::CV_FilterBaseTest( const char* test_name, const char* test_funcs, bool _fp_kernel )
- : CV_FilterBaseTestImpl( test_name, test_funcs, _fp_kernel )
-{
- size_list = 0;
- whole_size_list = 0;
- depth_list = 0;
- cn_list = 0;
-}
-
-
-/////////////////////////
-
-static const char* morph_param_names[] = { "mask_size", "shape", "size", "channels", "depth", 0 };
-static const int morph_depths[] = { CV_8U, CV_32F, -1 };
-static const int morph_mask_size[] = { 3, 5, 11 };
-static const char* morph_mask_shape[] = { "rect", "ellipse", 0 };
-
-class CV_MorphologyBaseTestImpl : public CV_FilterBaseTest
-{
-public:
- CV_MorphologyBaseTestImpl( const char* test_name, const char* test_funcs );
-
-protected:
- void prepare_to_validation( int test_case_idx );
- int prepare_test_case( int test_case_idx );
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void get_timing_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types,
- CvSize** whole_sizes, bool *are_images );
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
- double get_success_error_level( int test_case_idx, int i, int j );
- int write_default_params(CvFileStorage* fs);
- int optype, optype_min, optype_max;
- int shape;
- IplConvKernel* element;
-};
-
-
-CV_MorphologyBaseTestImpl::CV_MorphologyBaseTestImpl( const char* test_name, const char* test_funcs )
- : CV_FilterBaseTest( test_name, test_funcs, false )
-{
- shape = -1;
- element = 0;
- size_list = filter_sizes;
- whole_size_list = filter_whole_sizes;
- depth_list = morph_depths;
- cn_list = filter_channels;
- optype = optype_min = optype_max = -1;
-
- element = 0;
-}
-
-
-int CV_MorphologyBaseTestImpl::write_default_params( CvFileStorage* fs )
-{
- int code = CV_FilterBaseTest::write_default_params( fs );
- if( code >= 0 && ts->get_testing_mode() == CvTS::TIMING_MODE && strcmp(tested_functions,"") == 0 )
- {
- start_write_param( fs );
- write_int_list( fs, "mask_size", morph_mask_size, CV_DIM(morph_mask_size) );
- write_string_list( fs, "shape", morph_mask_shape );
- }
- return code;
-}
-
-
-void CV_MorphologyBaseTestImpl::get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- CV_FilterBaseTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- int depth = cvTsRandInt(rng) % 4;
- depth = depth == 0 ? CV_8U : depth == 1 ? CV_16U : depth == 2 ? CV_16S : CV_32F;
- int cn = CV_MAT_CN(types[INPUT][0]);
-
- types[INPUT][0] = types[OUTPUT][0] = types[REF_OUTPUT][0] = types[TEMP][0] = CV_MAKETYPE(depth, cn);
- shape = cvTsRandInt(rng) % 4;
- if( shape >= 3 )
- shape = CV_SHAPE_CUSTOM;
- else
- sizes[INPUT][1] = cvSize(0,0);
- optype = cvTsRandInt(rng) % (optype_max - optype_min + 1) + optype_min;
-}
-
-
-void CV_MorphologyBaseTestImpl::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images )
-{
- CV_FilterBaseTest::get_timing_test_array_types_and_sizes( test_case_idx, sizes, types,
- whole_sizes, are_images );
- const char* shape_str = cvReadString( find_timing_param( "shape" ), "rect" );
- shape = strcmp( shape_str, "rect" ) == 0 ? CV_SHAPE_RECT : CV_SHAPE_ELLIPSE;
- aperture_size.width = cvReadInt( find_timing_param( "mask_size" ), 3 );
- aperture_size.height = aperture_size.width;
- anchor.x = anchor.y = aperture_size.width / 2;
-}
-
-
-void CV_MorphologyBaseTestImpl::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- sprintf( ptr, "%dx%d,", aperture_size.width, aperture_size.height );
- ptr += strlen(ptr);
- sprintf( ptr, "%s,", shape == CV_SHAPE_RECT ? "rect" : "ellipse" );
- ptr += strlen(ptr);
- params_left -= 2;
-
- CV_FilterBaseTest::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-
-double CV_MorphologyBaseTestImpl::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- return CV_MAT_DEPTH(test_mat[INPUT][0].type) < CV_32F ||
- (optype == CV_MOP_ERODE || optype == CV_MOP_DILATE ||
- optype == CV_MOP_OPEN || optype == CV_MOP_CLOSE) ? 0 : 1e-5;
-}
-
-
-int CV_MorphologyBaseTestImpl::prepare_test_case( int test_case_idx )
-{
- int code = CV_FilterBaseTest::prepare_test_case( test_case_idx );
- int* eldata = 0;
-
- if( code <= 0 )
- return code;
-
- if( shape == CV_SHAPE_CUSTOM )
- {
- eldata = (int*)alloca( aperture_size.width*aperture_size.height*sizeof(eldata[0]) );
- uchar* src = test_mat[INPUT][1].data.ptr;
- int srcstep = test_mat[INPUT][1].step;
- int i, j, nonzero = 0;
-
- for( i = 0; i < aperture_size.height; i++ )
- {
- for( j = 0; j < aperture_size.width; j++ )
- {
- eldata[i*aperture_size.width + j] = src[i*srcstep + j];
- nonzero += src[i*srcstep + j] != 0;
- }
- }
-
- if( nonzero == 0 )
- eldata[anchor.y*aperture_size.width + anchor.x] = 1;
- }
-
- cvReleaseStructuringElement( &element );
- element = cvCreateStructuringElementEx( aperture_size.width, aperture_size.height,
- anchor.x, anchor.y, shape, eldata );
- return code;
-}
-
-
-void CV_MorphologyBaseTestImpl::prepare_to_validation( int test_case_idx )
-{
- CV_FilterBaseTest::prepare_to_validation( test_case_idx );
- CvMat *src = &test_mat[TEMP][0], *dst = &test_mat[REF_OUTPUT][0];
-
- if( optype == CV_MOP_ERODE || optype == CV_MOP_DILATE )
- {
- cvTsMinMaxFilter( src, dst, element, optype );
- }
- else
- {
- cv::Ptr<CvMat> dst0 = cvCloneMat(dst), src1 = cvCloneMat(src);
- if( optype == CV_MOP_OPEN )
- {
- cvTsMinMaxFilter( src, dst0, element, CV_MOP_ERODE );
- cvTsPrepareToFilter( dst0, src1, anchor, CV_TS_BORDER_REPLICATE );
- cvTsMinMaxFilter( src1, dst, element, CV_MOP_DILATE );
- }
- else if( optype == CV_MOP_CLOSE )
- {
- cvTsMinMaxFilter( src, dst0, element, CV_MOP_DILATE );
- cvTsPrepareToFilter( dst0, src1, anchor, CV_TS_BORDER_REPLICATE );
- cvTsMinMaxFilter( src1, dst, element, CV_MOP_ERODE );
- }
- else if( optype == CV_MOP_GRADIENT )
- {
- cvTsMinMaxFilter( src, dst0, element, CV_MOP_ERODE );
- cvTsMinMaxFilter( src, dst, element, CV_MOP_DILATE );
- cvTsAdd( dst, cvScalarAll(1), dst0, cvScalarAll(-1), cvScalarAll(0), dst, 0 );
- }
- else if( optype == CV_MOP_TOPHAT )
- {
- cvTsMinMaxFilter( src, dst0, element, CV_MOP_ERODE );
- cvTsPrepareToFilter( dst0, src1, anchor, CV_TS_BORDER_REPLICATE );
- cvTsMinMaxFilter( src1, dst, element, CV_MOP_DILATE );
- cvTsAdd( dst, cvScalarAll(-1), &test_mat[INPUT][0], cvScalarAll(1), cvScalarAll(0), dst, 0 );
- }
- else
- {
- cvTsMinMaxFilter( src, dst0, element, CV_MOP_DILATE );
- cvTsPrepareToFilter( dst0, src1, anchor, CV_TS_BORDER_REPLICATE );
- cvTsMinMaxFilter( src1, dst, element, CV_MOP_ERODE );
- cvTsAdd( dst, cvScalarAll(1), &test_mat[INPUT][0], cvScalarAll(-1), cvScalarAll(0), dst, 0 );
- }
- }
-
- cvReleaseStructuringElement( &element );
-}
-
-
-CV_MorphologyBaseTestImpl morph( "morph", "" );
-
-
-class CV_MorphologyBaseTest : public CV_MorphologyBaseTestImpl
-{
-public:
- CV_MorphologyBaseTest( const char* test_name, const char* test_funcs );
-};
-
-
-CV_MorphologyBaseTest::CV_MorphologyBaseTest( const char* test_name, const char* test_funcs )
- : CV_MorphologyBaseTestImpl( test_name, test_funcs )
-{
- default_timing_param_names = morph_param_names;
- depth_list = 0;
- size_list = 0;
- cn_list = 0;
-}
-
-
-/////////////// erode ///////////////
-
-class CV_ErodeTest : public CV_MorphologyBaseTest
-{
-public:
- CV_ErodeTest();
-protected:
- void run_func();
-};
-
-
-CV_ErodeTest::CV_ErodeTest()
- : CV_MorphologyBaseTest( "morph-erode", "cvErode" )
-{
- optype_min = optype_max = CV_MOP_ERODE;
-}
-
-
-void CV_ErodeTest::run_func()
-{
- cvErode( inplace ? test_array[OUTPUT][0] : test_array[INPUT][0],
- test_array[OUTPUT][0], element, 1 );
-}
-
-CV_ErodeTest erode_test;
-
-
-/////////////// dilate ///////////////
-
-class CV_DilateTest : public CV_MorphologyBaseTest
-{
-public:
- CV_DilateTest();
-protected:
- void run_func();
-};
-
-
-CV_DilateTest::CV_DilateTest()
- : CV_MorphologyBaseTest( "morph-dilate", "cvDilate" )
-{
- optype_min = optype_max = CV_MOP_DILATE;
-}
-
-
-void CV_DilateTest::run_func()
-{
- cvDilate( inplace ? test_array[OUTPUT][0] : test_array[INPUT][0],
- test_array[OUTPUT][0], element, 1 );
-}
-
-CV_DilateTest dilate_test;
-
-/////////////// morphEx ///////////////
-
-class CV_MorphExTest : public CV_MorphologyBaseTest
-{
-public:
- CV_MorphExTest();
-protected:
- void run_func();
-};
-
-
-CV_MorphExTest::CV_MorphExTest()
- : CV_MorphologyBaseTest( "morph-ex", "cvMorphologyEx" )
-{
- optype_min = CV_MOP_ERODE;
- optype_max = CV_MOP_BLACKHAT;
-}
-
-
-void CV_MorphExTest::run_func()
-{
- cvMorphologyEx( inplace ? test_array[OUTPUT][0] : test_array[INPUT][0],
- test_array[OUTPUT][0], 0, element, optype, 1 );
-}
-
-CV_MorphExTest morphex_test;
-
-/////////////// generic filter ///////////////
-
-static const char* filter_generic_param_names[] = { "mask_size", "size", "channels", "depth", 0 };
-
-class CV_FilterTest : public CV_FilterBaseTest
-{
-public:
- CV_FilterTest();
-
-protected:
- void prepare_to_validation( int test_case_idx );
- void run_func();
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- double get_success_error_level( int test_case_idx, int i, int j );
-
- void get_timing_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types,
- CvSize** whole_sizes, bool *are_images );
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
- int write_default_params(CvFileStorage* fs);
-};
-
-
-CV_FilterTest::CV_FilterTest()
- : CV_FilterBaseTest( "filter-generic", "cvFilter2D", true )
-{
- default_timing_param_names = filter_generic_param_names;
-}
-
-
-int CV_FilterTest::write_default_params( CvFileStorage* fs )
-{
- int code = CV_FilterBaseTest::write_default_params( fs );
- if( code >= 0 && ts->get_testing_mode() == CvTS::TIMING_MODE )
- {
- start_write_param( fs );
- write_int_list( fs, "mask_size", morph_mask_size, CV_DIM(morph_mask_size) );
- }
- return code;
-}
-
-
-void CV_FilterTest::get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types )
-{
- CV_FilterBaseTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- CvRNG* rng = ts->get_rng();
- int depth = cvTsRandInt(rng)%3;
- int cn = CV_MAT_CN(types[INPUT][0]);
- depth = depth == 0 ? CV_8U : depth == 1 ? CV_16U : CV_32F;
- types[INPUT][0] = types[OUTPUT][0] = types[REF_OUTPUT][0] = types[TEMP][0] = CV_MAKETYPE(depth, cn);
-}
-
-
-void CV_FilterTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images )
-{
- CV_FilterBaseTest::get_timing_test_array_types_and_sizes( test_case_idx, sizes, types,
- whole_sizes, are_images );
- aperture_size.width = cvReadInt( find_timing_param( "mask_size" ), 3 );
- aperture_size.height = aperture_size.width;
- anchor.x = anchor.y = aperture_size.width / 2;
- sizes[INPUT][1] = aperture_size;
- types[INPUT][1] = CV_32FC1;
-}
-
-
-void CV_FilterTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- sprintf( ptr, "%dx%d,", aperture_size.width, aperture_size.height );
- ptr += strlen(ptr);
- params_left--;
-
- CV_FilterBaseTest::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-
-double CV_FilterTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- int depth = CV_MAT_DEPTH(test_mat[INPUT][0].type);
- return depth <= CV_8S ? 2 : depth <= CV_32S ? 32 :
- depth == CV_32F ? 1e-4 : 1e-10;
-}
-
-
-void CV_FilterTest::run_func()
-{
- cvFilter2D( inplace ? test_array[OUTPUT][0] : test_array[INPUT][0],
- test_array[OUTPUT][0], &test_mat[INPUT][1], anchor );
-}
-
-
-void CV_FilterTest::prepare_to_validation( int test_case_idx )
-{
- CV_FilterBaseTest::prepare_to_validation( test_case_idx );
- cvTsConvolve2D( &test_mat[TEMP][0], &test_mat[REF_OUTPUT][0], &test_mat[INPUT][1], anchor );
-}
-
-CV_FilterTest filter;
-
-
-////////////////////////
-
-static const int laplace_aperture[] = { 3, 5, 7 };
-static const int sobel_aperture[] = { -1, 3, 5, 7 };
-static const char* laplace_param_names[] = { "aperture", "size", "depth", 0 };
-static const char* sobel_param_names[] = { "deriv_type", "aperture", "size", "depth", 0 };
-static const char* sobel_deriv_type[] = { "dx", "dy", "d2x", "d2y", "dxdy", 0 };
-
-class CV_DerivBaseTest : public CV_FilterBaseTest
-{
-public:
- CV_DerivBaseTest( const char* test_name, const char* test_funcs );
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- double get_success_error_level( int test_case_idx, int i, int j );
- void get_timing_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types,
- CvSize** whole_sizes, bool *are_images );
- int _aperture_size;
-};
-
-
-CV_DerivBaseTest::CV_DerivBaseTest( const char* test_name, const char* test_funcs )
- : CV_FilterBaseTest( test_name, test_funcs, true )
-{
- max_aperture_size = 7;
- depth_list = morph_depths;
- cn_list = 0;
-}
-
-
-void CV_DerivBaseTest::get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- CV_FilterBaseTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- int depth = cvTsRandInt(rng) % 2;
- depth = depth == 0 ? CV_8U : CV_32F;
- types[INPUT][0] = CV_MAKETYPE(depth,1);
- types[TEMP][0] = types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_MAKETYPE(depth==CV_8U?CV_16S:CV_32F,1);
- _aperture_size = (cvTsRandInt(rng)%5)*2 - 1;
- sizes[INPUT][1] = aperture_size = cvSize(_aperture_size, _aperture_size);
-}
-
-
-double CV_DerivBaseTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- int depth = CV_MAT_DEPTH(test_mat[INPUT][0].type);
- return depth <= CV_8S ? 2 : 5e-4;
-}
-
-
-void CV_DerivBaseTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images )
-{
- CV_FilterBaseTest::get_timing_test_array_types_and_sizes( test_case_idx, sizes, types,
- whole_sizes, are_images );
- _aperture_size = cvReadInt( find_timing_param( "aperture" ), 3 );
- aperture_size.width = aperture_size.height = _aperture_size < 0 ? 3 : _aperture_size;
- anchor.x = anchor.y = aperture_size.width / 2;
- sizes[INPUT][1] = aperture_size;
- types[INPUT][1] = CV_32FC1;
- types[OUTPUT][0] = types[INPUT][0] == CV_8UC1 ? CV_16SC1 : types[INPUT][0];
-}
-
-
-/////////////// sobel ///////////////
-
-class CV_SobelTest : public CV_DerivBaseTest
-{
-public:
- CV_SobelTest();
-
-protected:
- int prepare_test_case( int test_case_idx );
- void prepare_to_validation( int test_case_idx );
- void run_func();
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void get_timing_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types,
- CvSize** whole_sizes, bool *are_images );
- int write_default_params( CvFileStorage* fs );
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
- int dx, dy, origin;
- IplImage img;
- void* src;
-};
-
-
-CV_SobelTest::CV_SobelTest() : CV_DerivBaseTest( "filter-sobel", "cvSobel" )
-{
- src = 0;
- default_timing_param_names = sobel_param_names;
-}
-
-
-int CV_SobelTest::write_default_params( CvFileStorage* fs )
-{
- int code = CV_DerivBaseTest::write_default_params( fs );
- if( code >= 0 && ts->get_testing_mode() == CvTS::TIMING_MODE )
- {
- start_write_param( fs );
- write_int_list( fs, "aperture", sobel_aperture, CV_DIM(sobel_aperture) );
- write_string_list( fs, "deriv_type", sobel_deriv_type );
- }
- return code;
-}
-
-
-void CV_SobelTest::get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- CV_DerivBaseTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- int max_d = _aperture_size > 0 ? 2 : 1;
- origin = cvTsRandInt(rng) % 2;
- dx = cvTsRandInt(rng) % (max_d + 1);
- dy = cvTsRandInt(rng) % (max_d + 1 - dx);
- if( dx == 0 && dy == 0 )
- dx = 1;
- if( cvTsRandInt(rng) % 2 )
- {
- int t;
- CV_SWAP( dx, dy, t );
- }
-
- if( _aperture_size < 0 )
- aperture_size = cvSize(3, 3);
- else if( _aperture_size == 1 )
- {
- if( dx == 0 )
- aperture_size = cvSize(1, 3);
- else if( dy == 0 )
- aperture_size = cvSize(3, 1);
- else
- {
- _aperture_size = 3;
- aperture_size = cvSize(3, 3);
- }
- }
- else
- aperture_size = cvSize(_aperture_size, _aperture_size);
-
- sizes[INPUT][1] = aperture_size;
- sizes[TEMP][0].width = sizes[INPUT][0].width + aperture_size.width - 1;
- sizes[TEMP][0].height = sizes[INPUT][0].height + aperture_size.height - 1;
- anchor.x = aperture_size.width / 2;
- anchor.y = aperture_size.height / 2;
-}
-
-
-void CV_SobelTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images )
-{
- CV_DerivBaseTest::get_timing_test_array_types_and_sizes( test_case_idx, sizes, types,
- whole_sizes, are_images );
- //_aperture_size = cvReadInt( find_timing_param( "mask_size" ), 3 );
- const char* mask_type = cvReadString( find_timing_param( "deriv_type" ), "dx" );
- if( strcmp( mask_type, "dx" ) == 0 )
- dx = 1, dy = 0;
- else if( strcmp( mask_type, "dy" ) == 0 )
- dx = 0, dy = 1;
- else if( strcmp( mask_type, "d2x" ) == 0 )
- dx = 2, dy = 0;
- else if( strcmp( mask_type, "d2y" ) == 0 )
- dx = 0, dy = 2;
- else
- dx = 1, dy = 1;
- origin = 0;
-
- aperture_size.width = aperture_size.height = _aperture_size < 0 ? 3 : _aperture_size;
- anchor.x = anchor.y = aperture_size.width / 2;
- sizes[INPUT][1] = aperture_size;
- types[INPUT][1] = CV_32FC1;
- types[OUTPUT][0] = types[INPUT][0] == CV_8UC1 ? CV_16SC1 : types[INPUT][0];
-}
-
-
-int CV_SobelTest::prepare_test_case( int test_case_idx )
-{
- int code = CV_DerivBaseTest::prepare_test_case( test_case_idx );
-
- if( code > 0 )
- {
- if( _aperture_size < 0 && ((dx != 1 || dy != 0) && (dx != 0 || dy != 1)) )
- return 0;
-
- if( origin )
- {
- src = inplace ? &test_mat[OUTPUT][0] : &test_mat[INPUT][0];
- cvGetImage( src, &img );
- img.origin = origin;
- src = &img;
- }
- else
- src = inplace ? test_array[OUTPUT][0] : test_array[INPUT][0];
- }
- return code;
-}
-
-
-void CV_SobelTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- const char* mask_type = cvReadString( find_timing_param( "deriv_type" ), "dx" );
- sprintf( ptr, "%dx%d,%s_%s,", aperture_size.width, aperture_size.height,
- _aperture_size > 0 ? "Sobel" : "Scharr", mask_type );
- ptr += strlen(ptr);
- params_left -= 2;
-
- CV_DerivBaseTest::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-
-void CV_SobelTest::run_func()
-{
- cvSobel( src, test_array[OUTPUT][0], dx, dy, _aperture_size );
-}
-
-
-static void cvTsCalcSobelKernel1D( int order, int _aperture_size, int size, int* kernel )
-{
- int i, j, oldval, newval;
-
- if( _aperture_size < 0 )
- {
- static const int scharr[] = { 3, 10, 3, -1, 0, 1 };
- assert( size == 3 );
- memcpy( kernel, scharr + order*3, 3*sizeof(scharr[0]));
- return;
- }
-
- memset( kernel + 1, 0, size * sizeof(kernel[0]));
- kernel[0] = 1;
-
- for( i = 0; i < size - order - 1; i++ )
- {
- oldval = kernel[0];
- for( j = 1; j <= size; j++ )
- {
- newval = kernel[j] + kernel[j-1];
- kernel[j-1] = oldval;
- oldval = newval;
- }
- }
-
- for( i = 0; i < order; i++ )
- {
- oldval = -kernel[0];
- for( j = 1; j <= size; j++ )
- {
- newval = kernel[j-1] - kernel[j];
- kernel[j-1] = oldval;
- oldval = newval;
- }
- }
-}
-
-
-void cvTsCalcSobelKernel2D( int dx, int dy, int _aperture_size, int origin, CvMat* kernel )
-{
- int i, j;
- int* kx = (int*)alloca( (kernel->cols+1)*sizeof(kx[0]) );
- int* ky = (int*)alloca( (kernel->rows+1)*sizeof(ky[0]) );
-
- assert( CV_MAT_TYPE(kernel->type) == CV_32F );
-
- cvTsCalcSobelKernel1D( dx, _aperture_size, kernel->cols, kx );
- cvTsCalcSobelKernel1D( dy, _aperture_size, kernel->rows, ky );
-
- for( i = 0; i < kernel->rows; i++ )
- {
- float* kdata = (float*)(kernel->data.ptr + i*kernel->step);
- float ay = (float)ky[i]*(origin && (dy & 1) ? -1 : 1);
- for( j = 0; j < kernel->cols; j++ )
- {
- kdata[j] = kx[j]*ay;
- }
- }
-}
-
-
-void CV_SobelTest::prepare_to_validation( int test_case_idx )
-{
- CV_DerivBaseTest::prepare_to_validation( test_case_idx );
- cvTsCalcSobelKernel2D( dx, dy, _aperture_size, origin, &test_mat[INPUT][1] );
- cvTsConvolve2D( &test_mat[TEMP][0], &test_mat[REF_OUTPUT][0], &test_mat[INPUT][1], anchor );
-}
-
-CV_SobelTest sobel_test;
-
-
-/////////////// laplace ///////////////
-
-class CV_LaplaceTest : public CV_DerivBaseTest
-{
-public:
- CV_LaplaceTest();
-
-protected:
- int prepare_test_case( int test_case_idx );
- void prepare_to_validation( int test_case_idx );
- void run_func();
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- int write_default_params( CvFileStorage* fs );
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
-};
-
-
-CV_LaplaceTest::CV_LaplaceTest() : CV_DerivBaseTest( "filter-laplace", "cvLaplace" )
-{
- default_timing_param_names = laplace_param_names;
-}
-
-
-int CV_LaplaceTest::write_default_params( CvFileStorage* fs )
-{
- int code = CV_DerivBaseTest::write_default_params( fs );
- if( code >= 0 && ts->get_testing_mode() == CvTS::TIMING_MODE )
- {
- start_write_param( fs );
- write_int_list( fs, "aperture", laplace_aperture, CV_DIM(laplace_aperture) );
- }
- return code;
-}
-
-
-void CV_LaplaceTest::get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types )
-{
- CV_DerivBaseTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- if( _aperture_size <= 1 )
- {
- if( _aperture_size < 0 )
- _aperture_size = 1;
- aperture_size = cvSize(3, 3);
- }
- else
- aperture_size = cvSize(_aperture_size, _aperture_size);
-
- sizes[INPUT][1] = aperture_size;
- sizes[TEMP][0].width = sizes[INPUT][0].width + aperture_size.width - 1;
- sizes[TEMP][0].height = sizes[INPUT][0].height + aperture_size.height - 1;
- anchor.x = aperture_size.width / 2;
- anchor.y = aperture_size.height / 2;
-}
-
-
-void CV_LaplaceTest::run_func()
-{
- cvLaplace( inplace ? test_array[OUTPUT][0] : test_array[INPUT][0],
- test_array[OUTPUT][0], _aperture_size );
-}
-
-
-static void cvTsCalcLaplaceKernel2D( int _aperture_size, CvMat* kernel )
-{
- int i, j;
- int* kx = (int*)alloca( (kernel->cols+1)*sizeof(kx[0]) );
- int* ky = (int*)alloca( (kernel->rows+1)*sizeof(ky[0]) );
-
- cvTsCalcSobelKernel1D( 2, _aperture_size, kernel->cols, kx );
- if( _aperture_size > 1 )
- cvTsCalcSobelKernel1D( 0, _aperture_size, kernel->rows, ky );
- else
- ky[0] = ky[2] = 0, ky[1] = 1;
-
- for( i = 0; i < kernel->rows; i++ )
- {
- float* kdata = (float*)(kernel->data.ptr + i*kernel->step);
- for( j = 0; j < kernel->cols; j++ )
- {
- kdata[j] = (float)(kx[j]*ky[i] + kx[i]*ky[j]);
- }
- }
-}
-
-
-int CV_LaplaceTest::prepare_test_case( int test_case_idx )
-{
- int code = CV_DerivBaseTest::prepare_test_case( test_case_idx );
- return _aperture_size < 0 ? 0 : code;
-}
-
-
-void CV_LaplaceTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- sprintf( ptr, "%dx%d,", aperture_size.width, aperture_size.height );
- ptr += strlen(ptr);
- params_left--;
-
- CV_DerivBaseTest::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-
-void CV_LaplaceTest::prepare_to_validation( int test_case_idx )
-{
- CV_DerivBaseTest::prepare_to_validation( test_case_idx );
- cvTsCalcLaplaceKernel2D( _aperture_size, &test_mat[INPUT][1] );
- cvTsConvolve2D( &test_mat[TEMP][0], &test_mat[REF_OUTPUT][0], &test_mat[INPUT][1], anchor );
-}
-
-
-CV_LaplaceTest laplace_test;
-
-
-////////////////////////////////////////////////////////////
-
-static const char* smooth_param_names[] = { "mask_size", "size", "channels", "depth", 0 };
-static const int smooth_depths[] = { CV_8U, CV_32F, -1 };
-
-class CV_SmoothBaseTest : public CV_FilterBaseTest
-{
-public:
- CV_SmoothBaseTest( const char* test_name, const char* test_funcs );
-
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- double get_success_error_level( int test_case_idx, int i, int j );
- void get_timing_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types,
- CvSize** whole_sizes, bool *are_images );
- int write_default_params( CvFileStorage* fs );
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
- const char* smooth_type;
-};
-
-
-CV_SmoothBaseTest::CV_SmoothBaseTest( const char* test_name, const char* test_funcs )
- : CV_FilterBaseTest( test_name, test_funcs, true )
-{
- default_timing_param_names = smooth_param_names;
- depth_list = smooth_depths;
- smooth_type = "";
-}
-
-
-int CV_SmoothBaseTest::write_default_params( CvFileStorage* fs )
-{
- int code = CV_FilterBaseTest::write_default_params( fs );
- if( code >= 0 && ts->get_testing_mode() == CvTS::TIMING_MODE )
- {
- start_write_param( fs );
- write_int_list( fs, "mask_size", morph_mask_size, CV_DIM(morph_mask_size) );
- }
- return code;
-}
-
-void CV_SmoothBaseTest::get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- CV_FilterBaseTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- int depth = cvTsRandInt(rng) % 2;
- int cn = CV_MAT_CN(types[INPUT][0]);
- depth = depth == 0 ? CV_8U : CV_32F;
- types[INPUT][0] = types[TEMP][0] =
- types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_MAKETYPE(depth,cn);
- anchor.x = cvTsRandInt(rng)%(max_aperture_size/2+1);
- anchor.y = cvTsRandInt(rng)%(max_aperture_size/2+1);
- aperture_size.width = anchor.x*2 + 1;
- aperture_size.height = anchor.y*2 + 1;
- sizes[INPUT][1] = aperture_size;
- sizes[TEMP][0].width = sizes[INPUT][0].width + aperture_size.width - 1;
- sizes[TEMP][0].height = sizes[INPUT][0].height + aperture_size.height - 1;
-}
-
-
-double CV_SmoothBaseTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- int depth = CV_MAT_DEPTH(test_mat[INPUT][0].type);
- return depth <= CV_8S ? 1 : 1e-5;
-}
-
-
-void CV_SmoothBaseTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images )
-{
- CV_FilterBaseTest::get_timing_test_array_types_and_sizes( test_case_idx,
- sizes, types, whole_sizes, are_images );
-
- aperture_size.width = aperture_size.height = cvReadInt( find_timing_param( "mask_size" ), 3 );
- anchor.x = anchor.y = aperture_size.width / 2;
- sizes[INPUT][1] = aperture_size;
- types[INPUT][1] = CV_32FC1;
-}
-
-
-void CV_SmoothBaseTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- sprintf( ptr, "%dx%d,%s,", aperture_size.width, aperture_size.height, smooth_type );
- ptr += strlen(ptr);
- params_left -= 2;
-
- CV_FilterBaseTest::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-
-/////////////// blur ///////////////
-
-static const char* blur_param_names[] = { "normalize", "mask_size", "size", "channels", "depth", 0 };
-static const int blur_normalize[] = { 0, 1 };
-
-class CV_BlurTest : public CV_SmoothBaseTest
-{
-public:
- CV_BlurTest();
-
-protected:
- int prepare_test_case( int test_case_idx );
- void prepare_to_validation( int test_case_idx );
- void run_func();
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void get_timing_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types,
- CvSize** whole_sizes, bool *are_images );
- int write_default_params( CvFileStorage* fs );
- bool normalize;
-};
-
-
-CV_BlurTest::CV_BlurTest() : CV_SmoothBaseTest( "filter-blur", "cvSmooth" )
-{
- default_timing_param_names = blur_param_names;
-}
-
-
-void CV_BlurTest::get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- CV_SmoothBaseTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- normalize = cvTsRandInt(rng) % 2 != 0;
- if( !normalize )
- {
- int depth = CV_MAT_DEPTH(types[INPUT][0]);
- types[INPUT][0] = CV_MAKETYPE(depth, 1);
- types[TEMP][0] = types[OUTPUT][0] =
- types[REF_OUTPUT][0] = CV_MAKETYPE(depth==CV_8U?CV_16S:CV_32F,1);
- }
-}
-
-
-int CV_BlurTest::write_default_params( CvFileStorage* fs )
-{
- int code = CV_SmoothBaseTest::write_default_params( fs );
- if( code >= 0 && ts->get_testing_mode() == CvTS::TIMING_MODE )
- {
- write_int_list( fs, "normalize", blur_normalize, CV_DIM(blur_normalize) );
- }
- return code;
-}
-
-
-void CV_BlurTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images )
-{
- CV_SmoothBaseTest::get_timing_test_array_types_and_sizes( test_case_idx,
- sizes, types, whole_sizes, are_images );
- normalize = cvReadInt( find_timing_param( "normalize" ), 1 ) != 0;
- smooth_type = normalize ? "Blur" : "Blur_NoScale";
- sizes[INPUT][1] = aperture_size;
- types[INPUT][1] = CV_32FC1;
- if( !normalize && types[INPUT][0] == CV_8UC1 )
- types[OUTPUT][0] = CV_16SC1;
-}
-
-
-void CV_BlurTest::run_func()
-{
- cvSmooth( inplace ? test_array[OUTPUT][0] : test_array[INPUT][0],
- test_array[OUTPUT][0], normalize ? CV_BLUR : CV_BLUR_NO_SCALE,
- aperture_size.width, aperture_size.height );
-}
-
-
-int CV_BlurTest::prepare_test_case( int test_case_idx )
-{
- int code = CV_SmoothBaseTest::prepare_test_case( test_case_idx );
- return code > 0 && !normalize && CV_MAT_CN(test_mat[INPUT][0].type) > 1 ? 0 : code;
-}
-
-
-void CV_BlurTest::prepare_to_validation( int test_case_idx )
-{
- CvMat* kernel = &test_mat[INPUT][1];
- CV_SmoothBaseTest::prepare_to_validation( test_case_idx );
- cvTsAdd( 0, cvScalarAll(0.), 0, cvScalarAll(0.),
- cvScalarAll(normalize ? 1./(kernel->rows*kernel->cols) : 1.), kernel, 0 );
- cvTsConvolve2D( &test_mat[TEMP][0], &test_mat[REF_OUTPUT][0], kernel, anchor );
-}
-
-
-CV_BlurTest blur_test;
-
-
-/////////////// gaussian ///////////////
-
-class CV_GaussianBlurTest : public CV_SmoothBaseTest
-{
-public:
- CV_GaussianBlurTest();
-
-protected:
- void prepare_to_validation( int test_case_idx );
- void run_func();
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- double get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ );
- void get_timing_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types,
- CvSize** whole_sizes, bool *are_images );
- double sigma;
- int param1, param2;
-};
-
-
-CV_GaussianBlurTest::CV_GaussianBlurTest() : CV_SmoothBaseTest( "filter-gaussian", "cvSmooth" )
-{
- sigma = 0.;
- smooth_type = "Gaussian";
-}
-
-
-double CV_GaussianBlurTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- int depth = CV_MAT_DEPTH(test_mat[INPUT][0].type);
- return depth <= CV_8S ? 8 : 1e-5;
-}
-
-
-void CV_GaussianBlurTest::get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- int kernel_case = cvTsRandInt(rng) % 2;
- CV_SmoothBaseTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- anchor = cvPoint(aperture_size.width/2,aperture_size.height/2);
- sizes[TEMP][0].width = sizes[INPUT][0].width + aperture_size.width - 1;
- sizes[TEMP][0].height = sizes[INPUT][0].height + aperture_size.height - 1;
-
- sigma = exp(cvTsRandReal(rng)*5-2);
- param1 = aperture_size.width;
- param2 = aperture_size.height;
-
- if( kernel_case == 0 )
- sigma = 0.;
- /*else if( kernel_case == 2 )
- {
- int depth = CV_MAT_DEPTH(types[INPUT][0]);
- // !!! Copied from cvSmooth, if this formula is changed in cvSmooth,
- // make sure to update this one too.
- aperture_size.width = cvRound(sigma*(depth == CV_8U ? 3 : 4)*2 + 1)|1;
- aperture_size.width = MIN( aperture_size.width, 31 );
- aperture_size.height = aperture_size.width;
- anchor.x = aperture_size.width / 2;
- anchor.y = aperture_size.height / 2;
- sizes[INPUT][1] = aperture_size;
- sizes[TEMP][0].width = sizes[INPUT][0].width + aperture_size.width - 1;
- sizes[TEMP][0].height = sizes[INPUT][0].height + aperture_size.height - 1;
- param1 = aperture_size.width; param2 = aperture_size.height;
- }*/
-}
-
-
-void CV_GaussianBlurTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images )
-{
- CV_SmoothBaseTest::get_timing_test_array_types_and_sizes( test_case_idx,
- sizes, types, whole_sizes, are_images );
- param1 = aperture_size.width;
- param2 = aperture_size.height;
- sigma = sqrt(2.);
-}
-
-void CV_GaussianBlurTest::run_func()
-{
- cvSmooth( inplace ? test_array[OUTPUT][0] : test_array[INPUT][0],
- test_array[OUTPUT][0], CV_GAUSSIAN, param1, param2, sigma );
-}
-
-
-// !!! Copied from cvSmooth, if the code is changed in cvSmooth,
-// make sure to update this one too.
-#define SMALL_GAUSSIAN_SIZE 7
-static void
-icvCalcGaussianKernel( int n, double sigma, float* kernel )
-{
- static const float small_gaussian_tab[][SMALL_GAUSSIAN_SIZE] =
- {
- {1.f},
- {0.25f, 0.5f, 0.25f},
- {0.0625f, 0.25f, 0.375f, 0.25f, 0.0625f},
- {0.03125, 0.109375, 0.21875, 0.28125, 0.21875, 0.109375, 0.03125}
- };
-
- if( n <= SMALL_GAUSSIAN_SIZE && sigma <= 0 )
- {
- assert( n%2 == 1 );
- memcpy( kernel, small_gaussian_tab[n>>1], n*sizeof(kernel[0]));
- }
- else
- {
- double sigmaX = sigma > 0 ? sigma : (n/2 - 1)*0.3 + 0.8;
- double scale2X = -0.5/(sigmaX*sigmaX);
- double sum = 1.;
- int i;
- sum = kernel[n/2] = 1.f;
-
- for( i = 1; i <= n/2; i++ )
- {
- kernel[n/2+i] = kernel[n/2-i] = (float)exp(scale2X*i*i);
- sum += kernel[n/2+i]*2;
- }
-
- sum = 1./sum;
- for( i = 0; i <= n/2; i++ )
- kernel[n/2+i] = kernel[n/2-i] = (float)(kernel[n/2+i]*sum);
- }
-}
-
-
-static void cvTsCalcGaussianKernel2D( double sigma, CvMat* kernel )
-{
- int i, j;
- float* kx = (float*)alloca( kernel->cols*sizeof(kx[0]) );
- float* ky = (float*)alloca( kernel->rows*sizeof(ky[0]) );
-
- icvCalcGaussianKernel( kernel->cols, sigma, kx );
- icvCalcGaussianKernel( kernel->rows, sigma, ky );
-
- for( i = 0; i < kernel->rows; i++ )
- {
- float* kdata = (float*)(kernel->data.ptr + i*kernel->step);
- for( j = 0; j < kernel->cols; j++ )
- kdata[j] = kx[j]*ky[i];
- }
-}
-
-
-void CV_GaussianBlurTest::prepare_to_validation( int test_case_idx )
-{
- CvMat* kernel = &test_mat[INPUT][1];
- CV_SmoothBaseTest::prepare_to_validation( test_case_idx );
- cvTsCalcGaussianKernel2D( sigma, &test_mat[INPUT][1] );
- cvTsConvolve2D( &test_mat[TEMP][0], &test_mat[REF_OUTPUT][0], kernel, anchor );
-}
-
-
-CV_GaussianBlurTest gaussianblur_test;
-
-
-/////////////// median ///////////////
-
-static const int smooth_median_depths[] = { CV_8U, -1 };
-
-class CV_MedianBlurTest : public CV_SmoothBaseTest
-{
-public:
- CV_MedianBlurTest();
-
-protected:
- void prepare_to_validation( int test_case_idx );
- double get_success_error_level( int test_case_idx, int i, int j );
- void run_func();
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
-};
-
-
-CV_MedianBlurTest::CV_MedianBlurTest() : CV_SmoothBaseTest( "filter-median", "cvSmooth" )
-{
- test_array[TEMP].push(NULL);
- smooth_type = "Median";
- depth_list = smooth_median_depths;
-}
-
-
-void CV_MedianBlurTest::get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types )
-{
- CV_SmoothBaseTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- int depth = CV_8U;
- int cn = CV_MAT_CN(types[INPUT][0]);
- types[INPUT][0] = types[TEMP][0] = types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_MAKETYPE(depth,cn);
- types[INPUT][1] = types[TEMP][0] = types[TEMP][1] = CV_MAKETYPE(depth,1);
-
- aperture_size.height = aperture_size.width;
- anchor.x = anchor.y = aperture_size.width / 2;
- sizes[INPUT][1] = cvSize(aperture_size.width,aperture_size.height);
-
- sizes[OUTPUT][0] = sizes[INPUT][0];
- sizes[REF_OUTPUT][0] = sizes[INPUT][0];
-
- sizes[TEMP][0].width = sizes[INPUT][0].width + aperture_size.width - 1;
- sizes[TEMP][0].height = sizes[INPUT][0].height + aperture_size.height - 1;
-
- sizes[TEMP][1] = cn > 1 ? sizes[INPUT][0] : cvSize(0,0);
- inplace = false;
-}
-
-
-double CV_MedianBlurTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- return 0;
-}
-
-
-void CV_MedianBlurTest::run_func()
-{
- cvSmooth( test_array[INPUT][0], test_array[OUTPUT][0],
- CV_MEDIAN, aperture_size.width );
-}
-
-
-struct median_pair
-{
- int col;
- int val;
- median_pair() {};
- median_pair( int _col, int _val ) : col(_col), val(_val) {};
-};
-
-
-static void cvTsMedianFilter( const CvMat* src, CvMat* dst, int m )
-{
- int i, j, k, l, m2 = m*m, n;
- int* col_buf = (int*)cvAlloc( (m+1)*sizeof(col_buf[0]));
- median_pair* buf0 = (median_pair*)cvAlloc( (m*m+1)*sizeof(buf0[0]));
- median_pair* buf1 = (median_pair*)cvAlloc( (m*m+1)*sizeof(buf1[0]));
- median_pair* tbuf;
- int step = src->step/CV_ELEM_SIZE(src->type);
-
- assert( src->rows == dst->rows + m - 1 && src->cols == dst->cols + m - 1 &&
- CV_ARE_TYPES_EQ(src,dst) && CV_MAT_TYPE(src->type) == CV_8UC1 );
-
- for( i = 0; i < dst->rows; i++ )
- {
- uchar* dst1 = (uchar*)(dst->data.ptr + dst->step*i);
- for( k = 0; k < m; k++ )
- {
- const uchar* src1 = (const uchar*)(src->data.ptr + (i+k)*src->step);
- for( j = 0; j < m-1; j++ )
- *buf0++ = median_pair(j, src1[j]);
- }
-
- n = m2 - m;
- buf0 -= n;
- for( k = n-1; k > 0; k-- )
- {
- int f = 0;
- for( j = 0; j < k; j++ )
- {
- if( buf0[j].val > buf0[j+1].val )
- {
- median_pair t;
- CV_SWAP( buf0[j], buf0[j+1], t );
- f = 1;
- }
- }
- if( !f )
- break;
- }
-
- for( j = 0; j < dst->cols; j++ )
- {
- int ins_col = j + m - 1;
- int del_col = j - 1;
- const uchar* src1 = (const uchar*)(src->data.ptr + src->step*i) + ins_col;
- for( k = 0; k < m; k++, src1 += step )
- {
- col_buf[k] = src1[0];
- for( l = k-1; l >= 0; l-- )
- {
- int t;
- if( col_buf[l] < col_buf[l+1] )
- break;
- CV_SWAP( col_buf[l], col_buf[l+1], t );
- }
- }
-
- col_buf[m] = INT_MAX;
-
- for( k = 0, l = 0; k < n; )
- {
- if( buf0[k].col == del_col )
- k++;
- else if( buf0[k].val < col_buf[l] )
- *buf1++ = buf0[k++];
- else
- {
- assert( col_buf[l] < INT_MAX );
- *buf1++ = median_pair(ins_col,col_buf[l++]);
- }
- }
-
- for( ; l < m; l++ )
- *buf1++ = median_pair(ins_col,col_buf[l]);
-
- if( del_col < 0 )
- n += m;
- buf1 -= n;
- assert( n == m2 );
- dst1[j] = (uchar)buf1[n/2].val;
- CV_SWAP( buf0, buf1, tbuf );
- }
- }
-
- cvFree(&col_buf);
- cvFree(&buf0);
- cvFree(&buf1);
-}
-
-
-void CV_MedianBlurTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- // CV_SmoothBaseTest::prepare_to_validation( test_case_idx );
- CvMat* src0 = &test_mat[INPUT][0];
- CvMat* dst0 = &test_mat[REF_OUTPUT][0];
- int i, cn = CV_MAT_CN(src0->type);
- CvMat* src = &test_mat[TEMP][0], *dst = dst0;
- if( cn > 1 )
- dst = &test_mat[TEMP][1];
-
- for( i = 0; i < cn; i++ )
- {
- CvMat* ptr = src0;
- if( cn > 1 )
- {
- cvTsExtract( src0, dst, i );
- ptr = dst;
- }
- cvTsPrepareToFilter( ptr, src, anchor, CV_TS_BORDER_REPLICATE );
- cvTsMedianFilter( src, dst, aperture_size.width );
- if( cn > 1 )
- cvTsInsert( dst, dst0, i );
- }
-}
-
-
-CV_MedianBlurTest medianblur_test;
-
-
-/////////////// pyramid tests ///////////////
-
-static const char* pyramid_param_names[] = { "size", "channels", "depth", 0 };
-static int pyramid_channels[] = { 1, 3, -1 };
-
-class CV_PyramidBaseTest : public CV_FilterBaseTest
-{
-public:
- CV_PyramidBaseTest( const char* test_name, const char* test_funcs, bool downsample );
-
-protected:
- int prepare_test_case( int test_case_idx );
- double get_success_error_level( int test_case_idx, int i, int j );
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void get_timing_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types,
- CvSize** whole_sizes, bool *are_images );
- bool downsample;
-};
-
-
-CV_PyramidBaseTest::CV_PyramidBaseTest( const char* test_name, const char* test_funcs, bool _downsample )
- : CV_FilterBaseTest( test_name, test_funcs, true ), downsample(_downsample)
-{
- test_array[TEMP].push(NULL);
- size_list = filter_sizes;
- depth_list = smooth_depths;
- cn_list = pyramid_channels;
- default_timing_param_names = 0;
- if( strcmp( test_funcs, "" ) != 0 )
- {
- default_timing_param_names = pyramid_param_names;
- size_list = 0;
- cn_list = 0;
- depth_list = 0;
- }
-}
-
-
-double CV_PyramidBaseTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- int depth = CV_MAT_DEPTH(test_mat[INPUT][0].type);
- return depth <= CV_8S ? 1 : 1e-5;
-}
-
-
-void CV_PyramidBaseTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- CvSize sz;
- CV_FilterBaseTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
-
- int depth = cvTsRandInt(rng) % 2 ? CV_32F : CV_8U;
- int cn = cvTsRandInt(rng) & 1 ? 3 : 1;
-
- aperture_size = cvSize(5,5);
- anchor = cvPoint(aperture_size.width/2, aperture_size.height/2);
-
- types[INPUT][0] = types[OUTPUT][0] = types[REF_OUTPUT][0] =
- types[TEMP][0] = types[TEMP][1] = CV_MAKETYPE(depth, cn);
-
- sz.width = MAX( sizes[INPUT][0].width/2, 1 );
- sz.height = MAX( sizes[INPUT][0].height/2, 1 );
-
- if( downsample )
- {
- sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = sz;
- sz.width *= 2;
- sz.height *= 2;
- sizes[INPUT][0] = sizes[TEMP][1] = sz;
- }
- else
- {
- sizes[INPUT][0] = sz;
- sz.width *= 2;
- sz.height *= 2;
- sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = sz;
- sizes[TEMP][1] = cvSize(0,0);
- }
-
- sizes[INPUT][1] = aperture_size;
- sizes[TEMP][0].width = sz.width + aperture_size.width - 1;
- sizes[TEMP][0].height = sz.height + aperture_size.height - 1;
- inplace = false;
-}
-
-
-void CV_PyramidBaseTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images )
-{
- CV_FilterBaseTest::get_timing_test_array_types_and_sizes( test_case_idx,
- sizes, types, whole_sizes, are_images );
- CvSize sz = sizes[INPUT][0];
- sz.width /= 2;
- sz.height /= 2;
- if( downsample )
- sizes[OUTPUT][0] = sz;
- else
- sizes[INPUT][0] = sz;
- aperture_size.width = aperture_size.height = 5;
- anchor.x = anchor.y = aperture_size.width / 2;
- sizes[INPUT][1] = aperture_size;
- types[INPUT][1] = CV_32FC1;
-}
-
-
-int CV_PyramidBaseTest::prepare_test_case( int test_case_idx )
-{
- static const float kdata[] = { 1.f, 4.f, 6.f, 4.f, 1.f };
- int i, j;
- double scale = 1./256;
- CvMat* kernel;
- int code = CV_FilterBaseTest::prepare_test_case( test_case_idx );
-
- if( code <= 0 )
- return code;
-
- if( !downsample )
- scale *= 4;
-
- kernel = &test_mat[INPUT][1];
-
- for( i = 0; i < aperture_size.height; i++ )
- {
- float* krow = (float*)(kernel->data.ptr + i*kernel->step);
- for( j = 0; j < aperture_size.width; j++ )
- krow[j] = (float)(scale*kdata[i]*kdata[j]);
- }
- return code;
-}
-
-
-CV_PyramidBaseTest pyr_base( "pyramid", "", false );
-
-
-/////// pyrdown ////////
-
-static void cvTsDownsample( const CvMat* src, CvMat* dst )
-{
- int i, j, k;
- int elem_size = CV_ELEM_SIZE(src->type);
- int ncols = dst->cols*elem_size;
- int is_dword = elem_size % sizeof(int) == 0;
-
- if( is_dword )
- {
- elem_size /= sizeof(int);
- ncols /= sizeof(int);
- }
-
- for( i = 0; i < dst->rows; i++ )
- {
- const uchar* src_row = src->data.ptr + i*2*src->step;
- uchar* dst_row = dst->data.ptr + i*dst->step;
-
- if( !is_dword )
- {
- for( j = 0; j < ncols; j += elem_size )
- {
- for( k = 0; k < elem_size; k++ )
- dst_row[j+k] = src_row[j*2+k];
- }
- }
- else
- {
- for( j = 0; j < ncols; j += elem_size )
- {
- for( k = 0; k < elem_size; k++ )
- ((int*)dst_row)[j+k] = ((const int*)src_row)[j*2+k];
- }
- }
- }
-}
-
-
-class CV_PyramidDownTest : public CV_PyramidBaseTest
-{
-public:
- CV_PyramidDownTest();
-
-protected:
- void run_func();
- void prepare_to_validation( int );
-};
-
-
-CV_PyramidDownTest::CV_PyramidDownTest()
- : CV_PyramidBaseTest( "pyramid-down", "cvPyrDown", true )
-{
-}
-
-
-void CV_PyramidDownTest::run_func()
-{
- cvPyrDown( test_array[INPUT][0], test_array[OUTPUT][0], CV_GAUSSIAN_5x5 );
-}
-
-
-void CV_PyramidDownTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- cvTsPrepareToFilter( &test_mat[INPUT][0], &test_mat[TEMP][0],
- anchor, CV_TS_BORDER_REFLECT );
- cvTsConvolve2D( &test_mat[TEMP][0], &test_mat[TEMP][1],
- &test_mat[INPUT][1], anchor );
- cvTsDownsample( &test_mat[TEMP][1], &test_mat[REF_OUTPUT][0] );
-}
-
-
-CV_PyramidDownTest pyrdown;
-
-
-/////// pyrup ////////
-
-static void cvTsUpsample( const CvMat* src, CvMat* dst )
-{
- int i, j, k;
- int elem_size = CV_ELEM_SIZE(src->type);
- int ncols = src->cols*elem_size;
- int is_dword = elem_size % sizeof(int) == 0;
-
- if( is_dword )
- {
- elem_size /= sizeof(int);
- ncols /= sizeof(int);
- }
-
- for( i = 0; i < src->rows; i++ )
- {
- const uchar* src_row = src->data.ptr + i*src->step;
- uchar* dst_row = dst->data.ptr + i*2*dst->step;
-
- if( !is_dword )
- {
- memset( dst_row + dst->step, 0, dst->cols*elem_size );
- for( j = 0; j < ncols; j += elem_size )
- {
- for( k = 0; k < elem_size; k++ )
- {
- dst_row[j*2+k] = src_row[j+k];
- dst_row[j*2+k+elem_size] = 0;
- }
- }
- }
- else
- {
- memset( dst_row + dst->step, 0, dst->cols*elem_size*sizeof(int) );
- for( j = 0; j < ncols; j += elem_size )
- {
- for( k = 0; k < elem_size; k++ )
- {
- ((int*)dst_row)[j*2+k] = ((const int*)src_row)[j+k];
- ((int*)dst_row)[j*2+k+elem_size] = 0;
- }
- }
- }
- }
-}
-
-
-class CV_PyramidUpTest : public CV_PyramidBaseTest
-{
-public:
- CV_PyramidUpTest();
-
-protected:
- void run_func();
- void prepare_to_validation( int );
-};
-
-
-CV_PyramidUpTest::CV_PyramidUpTest()
- : CV_PyramidBaseTest( "pyramid-up", "cvPyrUp", false )
-{
-}
-
-
-void CV_PyramidUpTest::run_func()
-{
- cvPyrUp( test_array[INPUT][0], test_array[OUTPUT][0], CV_GAUSSIAN_5x5 );
-}
-
-
-void CV_PyramidUpTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- CvMat src2, dst2;
- CvSize sz;
- cvTsUpsample( &test_mat[INPUT][0], &test_mat[REF_OUTPUT][0] );
- cvTsPrepareToFilter( &test_mat[REF_OUTPUT][0], &test_mat[TEMP][0],
- anchor, CV_TS_BORDER_REFLECT );
- cvTsConvolve2D( &test_mat[TEMP][0], &test_mat[REF_OUTPUT][0],
- &test_mat[INPUT][1], anchor );
- // currently IPP and OpenCV process right/bottom part of the image differently, so
- // we just patch the last two rows/columns to have consistent test results.
- sz = cvGetMatSize( &test_mat[REF_OUTPUT][0]);
- cvTsSelect( &test_mat[REF_OUTPUT][0], &src2, cvRect(sz.width-2,0,2,sz.height) );
- cvTsSelect( &test_mat[OUTPUT][0], &dst2, cvRect(sz.width-2,0,2,sz.height) );
- cvTsCopy( &src2, &dst2, 0 );
- cvTsSelect( &test_mat[REF_OUTPUT][0], &src2, cvRect(0,sz.height-2,sz.width,2) );
- cvTsSelect( &test_mat[OUTPUT][0], &dst2, cvRect(0,sz.height-2,sz.width,2) );
- cvTsCopy( &src2, &dst2, 0 );
-}
-
-
-CV_PyramidUpTest pyrup;
-
-
-
-//////////////////////// feature selection //////////////////////////
-
-static const char* featuresel_param_names[] = { "block_size", "aperture", "size", "depth", 0 };
-static const int featuresel_block_size[] = { 3, 5, 11 };
-
-class CV_FeatureSelBaseTestImpl : public CvArrTest
-{
-public:
- CV_FeatureSelBaseTestImpl( const char* test_name, const char* test_funcs, int width_factor );
-
-protected:
- int read_params( CvFileStorage* fs );
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void get_minmax_bounds( int i, int j, int type, CvScalar* low, CvScalar* high );
- double get_success_error_level( int test_case_idx, int i, int j );
- int write_default_params(CvFileStorage* fs);
- void get_timing_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types,
- CvSize** whole_sizes, bool *are_images );
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
- int aperture_size, block_size;
- int max_aperture_size;
- int max_block_size;
- int width_factor;
-};
-
-
-CV_FeatureSelBaseTestImpl::CV_FeatureSelBaseTestImpl( const char* test_name, const char* test_funcs, int _width_factor )
- : CvArrTest( test_name, test_funcs, "" )
-{
- max_aperture_size = 7;
- max_block_size = 21;
- // 1 input, 1 output, temp arrays are allocated in the reference functions
- test_array[INPUT].push(NULL);
- test_array[OUTPUT].push(NULL);
- test_array[REF_OUTPUT].push(NULL);
- element_wise_relative_error = false;
- width_factor = _width_factor;
-
- size_list = filter_sizes;
- whole_size_list = filter_whole_sizes;
- depth_list = morph_depths;
- cn_list = 0;
-}
-
-
-int CV_FeatureSelBaseTestImpl::read_params( CvFileStorage* fs )
-{
- int code = CvTest::read_params( fs );
- if( code < 0 )
- return code;
-
- if( ts->get_testing_mode() == CvTS::CORRECTNESS_CHECK_MODE )
- {
- max_aperture_size = cvReadInt( find_param( fs, "max_aperture_size" ), max_aperture_size );
- max_aperture_size = cvTsClipInt( max_aperture_size, 1, 9 );
- max_block_size = cvReadInt( find_param( fs, "max_block_size" ), max_block_size );
- max_block_size = cvTsClipInt( max_aperture_size, 1, 100 );
- }
-
- return code;
-}
-
-
-int CV_FeatureSelBaseTestImpl::write_default_params( CvFileStorage* fs )
-{
- int code = CvArrTest::write_default_params( fs );
- if( code < 0 )
- return code;
-
- if( ts->get_testing_mode() == CvTS::CORRECTNESS_CHECK_MODE )
- {
- write_param( fs, "max_aperture_size", max_aperture_size );
- write_param( fs, "max_block_size", max_block_size );
- }
- else if( ts->get_testing_mode() == CvTS::TIMING_MODE && strcmp( tested_functions, "" ) == 0 )
- {
- start_write_param( fs );
- write_int_list( fs, "aperture", sobel_aperture, CV_DIM(sobel_aperture) );
- write_int_list( fs, "block_size", featuresel_block_size, CV_DIM(featuresel_block_size) );
- }
-
- return code;
-}
-
-
-double CV_FeatureSelBaseTestImpl::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- int depth = CV_MAT_DEPTH(test_mat[INPUT][0].type);
- return depth <= CV_8S ? 3e-2 : depth == CV_32F ? 1e-3 : 1e-10;
-}
-
-
-void CV_FeatureSelBaseTestImpl::get_minmax_bounds( int i, int j, int type, CvScalar* low, CvScalar* high )
-{
- CvArrTest::get_minmax_bounds( i, j, type, low, high );
- if( i == INPUT && CV_MAT_DEPTH(type) == CV_32F )
- {
- *low = cvScalarAll(-10.);
- *high = cvScalarAll(10.);
- }
-}
-
-
-void CV_FeatureSelBaseTestImpl::get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- CvArrTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- int depth = cvTsRandInt(rng) % 2, asz;
-
- depth = depth == 0 ? CV_8U : CV_32F;
- types[INPUT][0] = depth;
- types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_32FC1;
-
- aperture_size = (cvTsRandInt(rng) % (max_aperture_size+2) - 1) | 1;
- if( aperture_size == 1 )
- aperture_size = 3;
- if( depth == CV_8U )
- aperture_size = MIN( aperture_size, 5 );
- block_size = (cvTsRandInt(rng) % max_block_size + 1) | 1;
- if( block_size <= 3 )
- block_size = 3;
- asz = aperture_size > 0 ? aperture_size : 3;
-
- sizes[INPUT][0].width = MAX( sizes[INPUT][0].width, asz + block_size );
- sizes[INPUT][0].height = MAX( sizes[INPUT][0].height, asz + block_size );
- sizes[OUTPUT][0].height = sizes[REF_OUTPUT][0].height = sizes[INPUT][0].height;
- sizes[OUTPUT][0].width = sizes[REF_OUTPUT][0].width = sizes[INPUT][0].width*width_factor;
-}
-
-
-void CV_FeatureSelBaseTestImpl::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images )
-{
- CvArrTest::get_timing_test_array_types_and_sizes( test_case_idx, sizes, types,
- whole_sizes, are_images );
- aperture_size = cvReadInt( find_timing_param( "aperture" ), 3 );
- block_size = cvReadInt( find_timing_param( "block_size" ), 0 );
- int asz = aperture_size < 0 ? 3 : aperture_size;
-
- sizes[INPUT][0].width = MAX( sizes[INPUT][0].width, asz + block_size );
- sizes[INPUT][0].height = MAX( sizes[INPUT][0].height, asz + block_size );
- whole_sizes[INPUT][0].width = MAX( whole_sizes[INPUT][0].width, asz + block_size );
- whole_sizes[INPUT][0].height = MAX( whole_sizes[INPUT][0].height, asz + block_size );
- sizes[OUTPUT][0].height = sizes[INPUT][0].height;
- sizes[OUTPUT][0].width = sizes[INPUT][0].width*width_factor;
- whole_sizes[OUTPUT][0].height = whole_sizes[INPUT][0].height;
- whole_sizes[OUTPUT][0].width = MAX(whole_sizes[OUTPUT][0].width,sizes[OUTPUT][0].width);
- types[OUTPUT][0] = CV_32FC1;
-}
-
-
-void CV_FeatureSelBaseTestImpl::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- int asz = aperture_size < 0 ? 3 : aperture_size;
- sprintf( ptr, "%s(%dx%d),", aperture_size < 0 ? "Scharr" : "Sobel", asz, asz );
- ptr += strlen(ptr);
- params_left--;
- if( block_size > 0 )
- {
- sprintf( ptr, "block_size=%dx%d,", block_size, block_size );
- ptr += strlen(ptr);
- params_left--;
- }
-
- CvArrTest::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-
-CV_FeatureSelBaseTestImpl featuresel_base( "features", "", 0 );
-
-
-
-class CV_FeatureSelBaseTest : public CV_FeatureSelBaseTestImpl
-{
-public:
- CV_FeatureSelBaseTest( const char* test_name, const char* test_funcs, int width_factor );
-};
-
-
-CV_FeatureSelBaseTest::CV_FeatureSelBaseTest( const char* test_name, const char* test_funcs, int _width_factor )
- : CV_FeatureSelBaseTestImpl( test_name, test_funcs, _width_factor )
-{
- depth_list = 0;
- size_list = whole_size_list = 0;
- default_timing_param_names = featuresel_param_names;
-}
-
-
-static void
-cvTsCornerEigenValsVecs( const CvMat* _src, CvMat* eigenv, CvMat* ocv_eigenv,
- int block_size, int _aperture_size, int mode )
-{
- CvMat *dx2 = 0, *dxdy = 0, *dy2 = 0;
- CvMat* kernel = 0, *src2 = 0;
- const CvMat* src = _src;
-
- int type, ftype;
- double denom;
-
- CV_FUNCNAME( "cvTsCornerEigenValsVecs" );
-
- __BEGIN__;
-
- int i, j;
- int aperture_size = _aperture_size < 0 ? 3 : _aperture_size;
- CvPoint anchor = { aperture_size/2, aperture_size/2 };
-
- assert( (CV_MAT_TYPE(src->type) == CV_8UC1 ||
- CV_MAT_TYPE(src->type) == CV_32FC1) &&
- CV_MAT_TYPE(eigenv->type) == CV_32FC1 );
-
- assert( src->rows == eigenv->rows &&
- ((mode > 0 && src->cols == eigenv->cols) ||
- (mode == 0 && src->cols*6 == eigenv->cols)) );
-
- type = CV_MAT_TYPE(src->type);
- ftype = CV_32FC1;
-
- CV_CALL( dx2 = cvCreateMat( src->rows, src->cols, ftype ));
- CV_CALL( dy2 = cvCreateMat( src->rows, src->cols, ftype ));
- CV_CALL( dxdy = cvCreateMat( src->rows, src->cols, ftype ));
-
- CV_CALL( kernel = cvCreateMat( aperture_size, aperture_size, CV_32FC1 ));
- CV_CALL( src2 = cvCreateMat( src->rows + aperture_size - 1,
- src->cols + aperture_size - 1, ftype ));
-
- if( type != ftype )
- {
- cvTsAdd( src, cvScalarAll(1./255), 0, cvScalarAll(0.), cvScalarAll(0.), dx2, 0 );
- src = dx2;
- }
-
- cvTsPrepareToFilter( src, src2, anchor, CV_TS_BORDER_REPLICATE );
- cvTsCalcSobelKernel2D( 1, 0, _aperture_size, 0, kernel );
- cvTsConvolve2D( src2, dx2, kernel, anchor );
- cvTsCalcSobelKernel2D( 0, 1, _aperture_size, 0, kernel );
- cvTsConvolve2D( src2, dy2, kernel, anchor );
- cvReleaseMat( &src2 );
- cvReleaseMat( &kernel );
-
- denom = (1 << (aperture_size-1))*block_size;
- denom = denom * denom;
- if( _aperture_size < 0 )
- denom *= 4;
- denom = 1./denom;
-
- for( i = 0; i < src->rows; i++ )
- {
- float* dxdyp = (float*)(dxdy->data.ptr + i*dxdy->step);
- float* dx2p = (float*)(dx2->data.ptr + i*dx2->step);
- float* dy2p = (float*)(dy2->data.ptr + i*dy2->step);
-
- for( j = 0; j < src->cols; j++ )
- {
- double xval = dx2p[j], yval = dy2p[j];
- dxdyp[j] = (float)(xval*yval*denom);
- dx2p[j] = (float)(xval*xval*denom);
- dy2p[j] = (float)(yval*yval*denom);
- }
- }
-
- CV_CALL( src2 = cvCreateMat( src->rows + block_size - 1, src->cols + block_size - 1, CV_32F ));
- CV_CALL( kernel = cvCreateMat( block_size, block_size, CV_32F ));
- cvTsAdd( 0, cvScalarAll(0), 0, cvScalarAll(0), cvScalarAll(1./*(block_size*block_size)*/), kernel, 0 );
- anchor = cvPoint( block_size/2, block_size/2 );
-
- cvTsPrepareToFilter( dx2, src2, anchor, CV_TS_BORDER_REPLICATE );
- cvTsConvolve2D( src2, dx2, kernel, anchor );
- cvTsPrepareToFilter( dy2, src2, anchor, CV_TS_BORDER_REPLICATE );
- cvTsConvolve2D( src2, dy2, kernel, anchor );
- cvTsPrepareToFilter( dxdy, src2, anchor, CV_TS_BORDER_REPLICATE );
- cvTsConvolve2D( src2, dxdy, kernel, anchor );
-
- if( mode == 0 )
- {
- for( i = 0; i < src->rows; i++ )
- {
- float* eigenvp = (float*)(eigenv->data.ptr + i*eigenv->step);
- float* ocv_eigenvp = (float*)(ocv_eigenv->data.ptr + i*ocv_eigenv->step);
- const float* dxdyp = (float*)(dxdy->data.ptr + i*dxdy->step);
- const float* dx2p = (float*)(dx2->data.ptr + i*dx2->step);
- const float* dy2p = (float*)(dy2->data.ptr + i*dy2->step);
-
- for( j = 0; j < src->cols; j++ )
- {
- double a = dx2p[j], b = dxdyp[j], c = dy2p[j];
- double d = sqrt((a-c)*(a-c) + 4*b*b);
- double l1 = 0.5*(a + c + d);
- double l2 = 0.5*(a + c - d);
- double x1, y1, x2, y2, s;
-
- if( fabs(a - l1) + fabs(b) >= 1e-3 )
- x1 = b, y1 = l1 - a;
- else
- x1 = l1 - c, y1 = b;
- s = 1./(sqrt(x1*x1+y1*y1)+DBL_EPSILON);
- x1 *= s; y1 *= s;
-
- if( fabs(a - l2) + fabs(b) >= 1e-3 )
- x2 = b, y2 = l2 - a;
- else
- x2 = l2 - c, y2 = b;
- s = 1./(sqrt(x2*x2+y2*y2)+DBL_EPSILON);
- x2 *= s; y2 *= s;
-
- /* the orientation of eigen vectors might be inversed relative to OpenCV function,
- which is normal */
- if( (fabs(x1) >= fabs(y1) && ocv_eigenvp[j*6+2]*x1 < 0) ||
- (fabs(x1) < fabs(y1) && ocv_eigenvp[j*6+3]*y1 < 0) )
- x1 = -x1, y1 = -y1;
-
- if( (fabs(x2) >= fabs(y2) && ocv_eigenvp[j*6+4]*x2 < 0) ||
- (fabs(x2) < fabs(y2) && ocv_eigenvp[j*6+5]*y2 < 0) )
- x2 = -x2, y2 = -y2;
-
- eigenvp[j*6] = (float)l1;
- eigenvp[j*6+1] = (float)l2;
- eigenvp[j*6+2] = (float)x1;
- eigenvp[j*6+3] = (float)y1;
- eigenvp[j*6+4] = (float)x2;
- eigenvp[j*6+5] = (float)y2;
- }
- }
- }
- else if( mode == 1 )
- {
- for( i = 0; i < src->rows; i++ )
- {
- float* eigenvp = (float*)(eigenv->data.ptr + i*eigenv->step);
- const float* dxdyp = (float*)(dxdy->data.ptr + i*dxdy->step);
- const float* dx2p = (float*)(dx2->data.ptr + i*dx2->step);
- const float* dy2p = (float*)(dy2->data.ptr + i*dy2->step);
-
- for( j = 0; j < src->cols; j++ )
- {
- double a = dx2p[j], b = dxdyp[j], c = dy2p[j];
- double d = sqrt((a-c)*(a-c) + 4*b*b);
- eigenvp[j] = (float)(0.5*(a + c - d));
- }
- }
- }
-
- __END__;
-
- cvReleaseMat( &dx2 );
- cvReleaseMat( &dy2 );
- cvReleaseMat( &dxdy );
- cvReleaseMat( &src2 );
- cvReleaseMat( &kernel );
-}
-
-
-// min eigenval
-class CV_MinEigenValTest : public CV_FeatureSelBaseTest
-{
-public:
- CV_MinEigenValTest();
-
-protected:
- void run_func();
- void prepare_to_validation( int );
-};
-
-
-CV_MinEigenValTest::CV_MinEigenValTest()
- : CV_FeatureSelBaseTest( "features-mineval", "cvCornerMinEigenVal", 1 )
-{
-}
-
-
-void CV_MinEigenValTest::run_func()
-{
- cvCornerMinEigenVal( test_array[INPUT][0], test_array[OUTPUT][0],
- block_size, aperture_size );
-}
-
-
-void CV_MinEigenValTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- cvTsCornerEigenValsVecs( &test_mat[INPUT][0], &test_mat[REF_OUTPUT][0],
- &test_mat[OUTPUT][0], block_size, aperture_size, 1 );
-}
-
-
-CV_MinEigenValTest features_mineval;
-
-
-// eigenval's & vec's
-class CV_EigenValVecTest : public CV_FeatureSelBaseTest
-{
-public:
- CV_EigenValVecTest();
-
-protected:
- void run_func();
- void prepare_to_validation( int );
-};
-
-
-CV_EigenValVecTest::CV_EigenValVecTest()
- : CV_FeatureSelBaseTest( "features-evalvec", "cvCornerEigenValsAndVecs", 6 )
-{
-}
-
-
-void CV_EigenValVecTest::run_func()
-{
- cvCornerEigenValsAndVecs( test_array[INPUT][0], test_array[OUTPUT][0],
- block_size, aperture_size );
-}
-
-
-void CV_EigenValVecTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- cvTsCornerEigenValsVecs( &test_mat[INPUT][0], &test_mat[REF_OUTPUT][0],
- &test_mat[OUTPUT][0], block_size, aperture_size, 0 );
-}
-
-
-CV_EigenValVecTest features_evalvec;
-
-
-
-static const char* precorner_param_names[] = { "aperture", "size", "depth", 0 };
-static const int precorner_aperture[] = { 3, 5, 7 };
-
-// precornerdetect
-class CV_PreCornerDetectTest : public CV_FeatureSelBaseTest
-{
-public:
- CV_PreCornerDetectTest();
-
-protected:
- void run_func();
- void prepare_to_validation( int );
- int prepare_test_case( int );
- int write_default_params(CvFileStorage* fs);
-};
-
-
-CV_PreCornerDetectTest::CV_PreCornerDetectTest()
- : CV_FeatureSelBaseTest( "features-precorner", "cvPreCornerDetect", 1 )
-{
- default_timing_param_names = precorner_param_names;
-}
-
-
-int CV_PreCornerDetectTest::write_default_params( CvFileStorage* fs )
-{
- int code = CV_FeatureSelBaseTest::write_default_params( fs );
- if( code < 0 )
- return code;
-
- if( ts->get_testing_mode() == CvTS::TIMING_MODE )
- {
- start_write_param( fs );
- write_int_list( fs, "aperture", precorner_aperture, CV_DIM(precorner_aperture) );
- }
-
- return code;
-}
-
-
-void CV_PreCornerDetectTest::run_func()
-{
- cvPreCornerDetect( test_array[INPUT][0], test_array[OUTPUT][0], aperture_size );
-}
-
-
-int CV_PreCornerDetectTest::prepare_test_case( int test_case_idx )
-{
- int code = CV_FeatureSelBaseTest::prepare_test_case( test_case_idx );
- if( aperture_size < 0 )
- aperture_size = 3;
- return code;
-}
-
-
-void CV_PreCornerDetectTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- /*cvTsCornerEigenValsVecs( &test_mat[INPUT][0], &test_mat[REF_OUTPUT][0],
- block_size, aperture_size, 0 );*/
- const CvMat* src = &test_mat[INPUT][0];
- CvMat* dst = &test_mat[REF_OUTPUT][0];
-
- int type = CV_MAT_TYPE(src->type), ftype = CV_32FC1;
- CvPoint anchor = { aperture_size/2, aperture_size/2 };
- double denom;
- int i, j;
-
- CvMat* dx = cvCreateMat( src->rows, src->cols, ftype );
- CvMat* dy = cvCreateMat( src->rows, src->cols, ftype );
- CvMat* d2x = cvCreateMat( src->rows, src->cols, ftype );
- CvMat* d2y = cvCreateMat( src->rows, src->cols, ftype );
- CvMat* dxy = cvCreateMat( src->rows, src->cols, ftype );
- CvMat* tmp = cvCreateMat( src->rows + aperture_size - 1,
- src->cols + aperture_size - 1, ftype );
- CvMat* kernel = cvCreateMat( aperture_size, aperture_size, ftype );
-
- if( type != ftype )
- {
- cvTsAdd( src, cvScalarAll(1./255), 0, cvScalarAll(0.), cvScalarAll(0.), dx, 0 );
- src = dx;
- }
-
- cvTsPrepareToFilter( src, tmp, anchor, CV_TS_BORDER_REPLICATE );
-
- cvTsCalcSobelKernel2D( 1, 0, aperture_size, 0, kernel );
- cvTsConvolve2D( tmp, dx, kernel, anchor );
- cvTsCalcSobelKernel2D( 0, 1, aperture_size, 0, kernel );
- cvTsConvolve2D( tmp, dy, kernel, anchor );
- cvTsCalcSobelKernel2D( 2, 0, aperture_size, 0, kernel );
- cvTsConvolve2D( tmp, d2x, kernel, anchor );
- cvTsCalcSobelKernel2D( 0, 2, aperture_size, 0, kernel );
- cvTsConvolve2D( tmp, d2y, kernel, anchor );
- cvTsCalcSobelKernel2D( 1, 1, aperture_size, 0, kernel );
- cvTsConvolve2D( tmp, dxy, kernel, anchor );
-
- denom = 1 << (aperture_size-1);
- denom = denom * denom * denom;
- denom = 1./denom;
-
- for( i = 0; i < src->rows; i++ )
- {
- const float* _dx = (const float*)(dx->data.ptr + i*dx->step);
- const float* _dy = (const float*)(dy->data.ptr + i*dy->step);
- const float* _d2x = (const float*)(d2x->data.ptr + i*d2x->step);
- const float* _d2y = (const float*)(d2y->data.ptr + i*d2y->step);
- const float* _dxy = (const float*)(dxy->data.ptr + i*dxy->step);
- float* corner = (float*)(dst->data.ptr + i*dst->step);
-
- for( j = 0; j < src->cols; j++ )
- {
- double x = _dx[j];
- double y = _dy[j];
-
- corner[j] = (float)(denom*(x*x*_d2y[j] + y*y*_d2x[j] - 2*x*y*_dxy[j]));
- }
- }
-
- cvReleaseMat( &dx );
- cvReleaseMat( &dy );
- cvReleaseMat( &d2x );
- cvReleaseMat( &d2y );
- cvReleaseMat( &dxy );
- cvReleaseMat( &tmp );
- cvReleaseMat( &kernel );
-}
-
-
-CV_PreCornerDetectTest precorner;
-
-
-///////// integral /////////
-
-static const char* integral_param_names[] = { "output", "size", "channels", "sum_depth", "depth", 0 };
-static const int integral_sum_depth[] = { CV_32S, CV_64F, -1 };
-static const int integral_block_size[] = { 3, 5, 11 };
-static const char* integral_output[] = { "sum", "sum+sqsum", "all", 0 };
-
-class CV_IntegralTest : public CvArrTest
-{
-public:
- CV_IntegralTest();
-
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void get_minmax_bounds( int i, int j, int type, CvScalar* low, CvScalar* high );
- double get_success_error_level( int test_case_idx, int i, int j );
- void run_func();
- void prepare_to_validation( int );
-
- int prepare_test_case( int test_case_idx );
- int write_default_params(CvFileStorage* fs);
- void get_timing_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types,
- CvSize** whole_sizes, bool *are_images );
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
-};
-
-
-CV_IntegralTest::CV_IntegralTest()
- : CvArrTest( "integral", "cvIntegral", "" )
-{
- test_array[INPUT].push(NULL);
- test_array[OUTPUT].push(NULL);
- test_array[OUTPUT].push(NULL);
- test_array[OUTPUT].push(NULL);
- test_array[REF_OUTPUT].push(NULL);
- test_array[REF_OUTPUT].push(NULL);
- test_array[REF_OUTPUT].push(NULL);
- test_array[TEMP].push(NULL);
- test_array[TEMP].push(NULL);
- test_array[TEMP].push(NULL);
- test_array[TEMP].push(NULL);
- test_array[TEMP].push(NULL);
- element_wise_relative_error = false;
-
- size_list = filter_sizes;
- whole_size_list = filter_whole_sizes;
- default_timing_param_names = integral_param_names;
- depth_list = morph_depths;
- cn_list = filter_channels;
-}
-
-
-void CV_IntegralTest::get_minmax_bounds( int i, int j, int type, CvScalar* low, CvScalar* high )
-{
- CvArrTest::get_minmax_bounds( i, j, type, low, high );
- int depth = CV_MAT_DEPTH(type);
- if( depth == CV_32F )
- {
- *low = cvScalarAll(-10.);
- *high = cvScalarAll(10.);
- }
-}
-
-
-int CV_IntegralTest::write_default_params( CvFileStorage* fs )
-{
- int code = CvArrTest::write_default_params( fs );
- if( code < 0 )
- return code;
-
- if( ts->get_testing_mode() == CvTS::TIMING_MODE )
- {
- int i;
- start_write_param( fs );
-
- cvStartWriteStruct( fs, "sum_depth", CV_NODE_SEQ+CV_NODE_FLOW );
- for( i = 0; integral_sum_depth[i] >= 0; i++ )
- cvWriteString( fs, 0, cvTsGetTypeName(integral_sum_depth[i]) );
- cvEndWriteStruct(fs);
-
- write_string_list( fs, "output", integral_output );
- }
-
- return code;
-}
-
-
-void CV_IntegralTest::get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- int depth = cvTsRandInt(rng) % 2, sum_depth;
- int cn = cvTsRandInt(rng) % 3 + 1;
- CvArrTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- CvSize sum_size;
-
- depth = depth == 0 ? CV_8U : CV_32F;
- cn += cn == 2;
- sum_depth = depth == CV_8U && (cvTsRandInt(rng) & 1) == 1 ? CV_32S : CV_64F;
-
- //sizes[INPUT][0].width = 1;
-
- types[INPUT][0] = CV_MAKETYPE(depth,cn);
- types[OUTPUT][0] = types[REF_OUTPUT][0] =
- types[OUTPUT][2] = types[REF_OUTPUT][2] = CV_MAKETYPE(sum_depth, cn);
- types[OUTPUT][1] = types[REF_OUTPUT][1] = CV_MAKETYPE(CV_64F, cn);
-
- sum_size.width = sizes[INPUT][0].width + 1;
- sum_size.height = sizes[INPUT][0].height + 1;
-
- sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = sum_size;
- sizes[OUTPUT][1] = sizes[REF_OUTPUT][1] =
- sizes[OUTPUT][2] = sizes[REF_OUTPUT][2] = cvSize(0,0);
-
- if( cvTsRandInt(rng) % 3 > 0 )
- {
- sizes[OUTPUT][1] = sizes[REF_OUTPUT][1] = sum_size;
- if( cvTsRandInt(rng) % 2 > 0 )
- sizes[REF_OUTPUT][2] = sizes[OUTPUT][2] = sum_size;
- }
-
- types[TEMP][0] = CV_MAKETYPE(depth,1);
- types[TEMP][1] = CV_MAKETYPE(CV_32F,1);
- types[TEMP][2] = types[TEMP][3] = types[TEMP][4] = CV_MAKETYPE(CV_64F,1);
-
- sizes[TEMP][0] = cn > 1 ? sizes[INPUT][0] : cvSize(0,0);
- sizes[TEMP][1] = depth == CV_8U ? sum_size : cvSize(0,0);
-
- sizes[TEMP][2] = cn > 1 || sum_depth == CV_32S ? sizes[OUTPUT][0] : cvSize(0,0);
- sizes[TEMP][3] = cn > 1 ? sizes[OUTPUT][1] : cvSize(0,0);
- sizes[TEMP][4] = cn > 1 || sum_depth == CV_32S ? sizes[OUTPUT][2] : cvSize(0,0);
-}
-
-
-double CV_IntegralTest::get_success_error_level( int /*test_case_idx*/, int i, int j )
-{
- int depth = CV_MAT_DEPTH(test_mat[i][j].type);
- return depth == CV_32S ? 0 : FLT_EPSILON;
-}
-
-
-void CV_IntegralTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images )
-{
- CvArrTest::get_timing_test_array_types_and_sizes( test_case_idx, sizes, types,
- whole_sizes, are_images );
- const char* output = cvReadString( find_timing_param( "output" ), "sum" );
- CvSize sum_size = { sizes[INPUT][0].width + 1, sizes[INPUT][0].height + 1 };
- const char* _sum_depth = cvReadString( find_timing_param( "sum_depth" ), "64f" );
- int cn = CV_MAT_CN(types[INPUT][0]);
- int sum_depth = strcmp( _sum_depth, "32s" ) == 0 ? CV_32S : CV_64F;
-
- sizes[OUTPUT][0] = sizes[OUTPUT][1] = sizes[OUTPUT][2] = cvSize(0,0);
- whole_sizes[OUTPUT][0] = whole_sizes[OUTPUT][1] = whole_sizes[OUTPUT][2] = cvSize(0,0);
-
- if( strcmp( output, "sum" ) == 0 )
- sizes[OUTPUT][0] = whole_sizes[OUTPUT][0] = sum_size;
- else if( strcmp( output, "all" ) == 0 )
- sizes[OUTPUT][0] = sizes[OUTPUT][1] = sizes[OUTPUT][2] =
- whole_sizes[OUTPUT][0] = whole_sizes[OUTPUT][1] = whole_sizes[OUTPUT][2] = sum_size;
- else
- sizes[OUTPUT][0] = sizes[OUTPUT][1] =
- whole_sizes[OUTPUT][0] = whole_sizes[OUTPUT][1] = sum_size;
-
- sizes[TEMP][0] = sizes[TEMP][1] = sizes[TEMP][2] = sizes[TEMP][3] = sizes[TEMP][4] = cvSize(0,0);
-
- types[OUTPUT][0] = types[OUTPUT][2] = CV_MAKETYPE( sum_depth, cn );
- types[OUTPUT][1] = CV_MAKETYPE( CV_64F, cn );
-}
-
-
-void CV_IntegralTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- sprintf( ptr, "%s,", cvReadString( find_timing_param( "output" ), "sum" ) );
- ptr += strlen(ptr);
- params_left--;
-
- CvArrTest::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-
-int CV_IntegralTest::prepare_test_case( int test_case_idx )
-{
- int code = CvArrTest::prepare_test_case( test_case_idx );
- return code > 0 && ((test_array[OUTPUT][2] && CV_MAT_CN(test_mat[OUTPUT][2].type) > 1) ||
- CV_MAT_DEPTH(test_mat[OUTPUT][0].type) < CV_MAT_DEPTH(test_mat[INPUT][0].type)) ? 0 : code;
-}
-
-
-void CV_IntegralTest::run_func()
-{
- cvIntegral( test_array[INPUT][0], test_array[OUTPUT][0],
- test_array[OUTPUT][1], test_array[OUTPUT][2] );
-}
-
-
-static void
-cvTsIntegral( const CvMat* img, const CvMat* sum, const CvMat* sqsum, const CvMat* tilted )
-{
- const float* data = img->data.fl;
- double* sdata = sum->data.db;
- double* sqdata = sqsum ? sqsum->data.db : 0;
- double* tdata = tilted ? tilted->data.db : 0;
- int step = img->step/sizeof(data[0]);
- int sstep = sum->step/sizeof(sdata[0]);
- int sqstep = sqsum ? sqsum->step/sizeof(sqdata[0]) : 0;
- int tstep = tilted ? tilted->step/sizeof(tdata[0]) : 0;
- CvSize size = cvGetMatSize( img );
-
- memset( sdata, 0, (size.width+1)*sizeof(sdata[0]) );
- if( sqsum )
- memset( sqdata, 0, (size.width+1)*sizeof(sqdata[0]) );
- if( tilted )
- memset( tdata, 0, (size.width+1)*sizeof(tdata[0]) );
-
- for( ; size.height--; data += step )
- {
- double s = 0, sq = 0;
- int x;
- sdata += sstep;
- sqdata += sqstep;
- tdata += tstep;
-
- for( x = 0; x <= size.width; x++ )
- {
- double t = x > 0 ? data[x-1] : 0, ts = t;
- s += t;
- sq += t*t;
-
- sdata[x] = s + sdata[x - sstep];
- if( sqdata )
- sqdata[x] = sq + sqdata[x - sqstep];
-
- if( !tdata )
- continue;
-
- if( x == 0 )
- ts += tdata[-tstep+1];
- else
- {
- ts += tdata[x-tstep-1];
- if( data > img->data.fl )
- {
- ts += data[x-step-1];
- if( x < size.width )
- ts += tdata[x-tstep+1] - tdata[x-tstep*2];
- }
- }
-
- tdata[x] = ts;
- }
- }
-}
-
-
-void CV_IntegralTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- CvMat* src0 = &test_mat[INPUT][0];
- int i, cn = CV_MAT_CN(src0->type), depth = CV_MAT_DEPTH(src0->type);
- CvMat* plane = cn > 1 ? &test_mat[TEMP][0] : 0;
- CvMat ibuf, *plane32f = 0;
-
- CvMat* sum0 = &test_mat[REF_OUTPUT][0];
- CvMat* sqsum0 = test_array[REF_OUTPUT][1] ? &test_mat[REF_OUTPUT][1] : 0;
- CvMat* tsum0 = test_array[REF_OUTPUT][2] ? &test_mat[REF_OUTPUT][2] : 0;
-
- CvMat* sum1 = test_array[TEMP][2] ? &test_mat[TEMP][2] : sum0;
- CvMat* sqsum1 = test_array[TEMP][3] ? &test_mat[TEMP][3] : sqsum0;
- CvMat* tsum1 = test_array[TEMP][4] ? &test_mat[TEMP][4] : tsum0;
- CvMat buf, *ptr = 0;
-
- if( depth == CV_8U )
- {
- ibuf = test_mat[TEMP][1];
- plane32f = &ibuf;
- plane32f->cols--;
- plane32f->rows--;
- plane32f->type &= ~CV_MAT_CONT_FLAG;
-
- if( CV_MAT_DEPTH(sum0->type) == CV_32S && cn > 1 )
- {
- // in case of 8u->32s integral transform aliase the temporary output buffer with temporary input buffer
- buf = test_mat[TEMP][1];
- ptr = &buf;
- ptr->type = (ptr->type & ~CV_MAT_DEPTH_MASK) | CV_32S;
- }
- }
-
- for( i = 0; i < cn; i++ )
- {
- CvMat* sptr = src0;
- CvMat* dptr;
- if( cn > 1 )
- {
- cvTsExtract( sptr, plane, i );
- sptr = plane;
- }
-
- if( CV_MAT_DEPTH(sptr->type) != CV_32F )
- {
- cvTsConvert( sptr, plane32f );
- sptr = plane32f;
- }
-
- cvTsIntegral( sptr, sum1, sqsum1, tsum1 );
- if( sum1 != sum0 )
- {
- dptr = sum1;
- if( ptr )
- {
- cvTsConvert( dptr, ptr );
- dptr = ptr;
- }
- if( cn == 1 )
- cvTsConvert( dptr, sum0 );
- else
- cvTsInsert( dptr, sum0, i );
- }
-
- if( tsum1 != tsum0 )
- {
- dptr = tsum1;
- if( ptr )
- {
- cvTsConvert( dptr, ptr );
- dptr = ptr;
- }
- if( cn == 1 )
- cvTsConvert( dptr, tsum0 );
- else
- cvTsInsert( dptr, tsum0, i );
- }
-
- if( sqsum1 != sqsum0 )
- cvTsInsert( sqsum1, sqsum0, i );
- }
-}
-
-
-CV_IntegralTest integral_test;
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-static const char* floodfill_param_names[] = { "size", "channels", "depth", "dist_type", "labels", 0 };
-static const CvSize floodfill_sizes[] = {{320, 240}, {720,480}, {-1,-1}};
-static const CvSize floodfill_whole_sizes[] = {{320, 240}, {720,480}, {-1,-1}};
-//static const char* floodfill_types[] = { "fixed_level", "fixed_range", "floating_range", 0 };
-static const int floodfill_depths[] = { CV_8U, CV_32F, -1 };
-static const int floodfill_channels[] = { 1, 3, -1 };
-
-class CV_FloodFillTest : public CvArrTest
-{
-public:
- CV_FloodFillTest();
-
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- double get_success_error_level( int test_case_idx, int i, int j );
- void run_func();
- void prepare_to_validation( int );
-
- void fill_array( int test_case_idx, int i, int j, CvMat* arr );
-
- /*int write_default_params(CvFileStorage* fs);
- void get_timing_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types,
- CvSize** whole_sizes, bool *are_images );
- void print_timing_params( int test_case_idx, char* ptr, int params_left );*/
- CvPoint seed_pt;
- CvScalar new_val;
- CvScalar l_diff, u_diff;
- int connectivity;
- bool use_mask, mask_only;
- int range_type;
- int new_mask_val;
- bool test_cpp;
-};
-
-
-CV_FloodFillTest::CV_FloodFillTest()
- : CvArrTest( "floodfill", "cvFloodFill", "" )
-{
- test_array[INPUT_OUTPUT].push(NULL);
- test_array[INPUT_OUTPUT].push(NULL);
- test_array[REF_INPUT_OUTPUT].push(NULL);
- test_array[REF_INPUT_OUTPUT].push(NULL);
- test_array[OUTPUT].push(NULL);
- test_array[REF_OUTPUT].push(NULL);
- optional_mask = false;
- element_wise_relative_error = true;
-
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;
-
- default_timing_param_names = floodfill_param_names;
- depth_list = floodfill_depths;
- size_list = floodfill_sizes;
- whole_size_list = floodfill_whole_sizes;
- cn_list = floodfill_channels;
- test_cpp = false;
-}
-
-
-void CV_FloodFillTest::get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- int depth, cn;
- int i;
- double buf[8];
- CvArrTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
-
- depth = cvTsRandInt(rng) % 2;
- depth = depth == 0 ? CV_8U : CV_32F;
- cn = cvTsRandInt(rng) & 1 ? 3 : 1;
-
- use_mask = (cvTsRandInt(rng) & 1) != 0;
- connectivity = (cvTsRandInt(rng) & 1) ? 4 : 8;
- mask_only = use_mask && (cvTsRandInt(rng) & 1) != 0;
- new_mask_val = cvTsRandInt(rng) & 255;
- range_type = cvTsRandInt(rng) % 3;
-
- types[INPUT_OUTPUT][0] = types[REF_INPUT_OUTPUT][0] = CV_MAKETYPE(depth, cn);
- types[INPUT_OUTPUT][1] = types[REF_INPUT_OUTPUT][1] = CV_8UC1;
- types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_64FC1;
- sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = cvSize(9,1);
-
- if( !use_mask )
- sizes[INPUT_OUTPUT][1] = sizes[REF_INPUT_OUTPUT][1] = cvSize(0,0);
- else
- {
- CvSize sz = sizes[INPUT_OUTPUT][0];
- sizes[INPUT_OUTPUT][1] = sizes[REF_INPUT_OUTPUT][1] = cvSize(sz.width+2,sz.height+2);
- }
-
- seed_pt.x = cvTsRandInt(rng) % sizes[INPUT_OUTPUT][0].width;
- seed_pt.y = cvTsRandInt(rng) % sizes[INPUT_OUTPUT][0].height;
-
- if( range_type == 0 )
- l_diff = u_diff = cvScalarAll(0.);
- else
- {
- CvMat m = cvMat( 1, 8, CV_16S, buf );
- cvRandArr( rng, &m, CV_RAND_NORMAL, cvScalarAll(0), cvScalarAll(32) );
- for( i = 0; i < 4; i++ )
- {
- l_diff.val[i] = fabs(m.data.s[i]/16.);
- u_diff.val[i] = fabs(m.data.s[i+4]/16.);
- }
- }
-
- new_val = cvScalarAll(0.);
- for( i = 0; i < cn; i++ )
- new_val.val[i] = cvTsRandReal(rng)*255;
-
- test_cpp = (cvTsRandInt(rng) & 256) == 0;
-}
-
-
-double CV_FloodFillTest::get_success_error_level( int /*test_case_idx*/, int i, int j )
-{
- return i == OUTPUT ? FLT_EPSILON : j == 0 ? FLT_EPSILON : 0;
-}
-
-
-void CV_FloodFillTest::fill_array( int test_case_idx, int i, int j, CvMat* arr )
-{
- CvRNG* rng = ts->get_rng();
-
- if( i != INPUT && i != INPUT_OUTPUT )
- {
- CvArrTest::fill_array( test_case_idx, i, j, arr );
- return;
- }
-
- if( j == 0 )
- {
- CvMat* tmp = arr;
- CvScalar m = cvScalarAll(128);
- CvScalar s = cvScalarAll(10);
-
- if( CV_MAT_DEPTH(arr->type) == CV_32FC1 )
- tmp = cvCreateMat( arr->rows, arr->cols, arr->type & CV_MAT_CN_MASK );
-
- if( range_type == 0 )
- s = cvScalarAll(2);
-
- cvRandArr( rng, tmp, CV_RAND_NORMAL, m, s );
- if( arr != tmp )
- {
- cvTsConvert( tmp, arr );
- cvReleaseMat( &tmp );
- }
- }
- else
- {
- CvScalar l = cvScalarAll(-2);
- CvScalar u = cvScalarAll(2);
- cvRandArr( rng, arr, CV_RAND_UNI, l, u );
- cvRectangle( arr, cvPoint(0,0), cvPoint(arr->cols-1,arr->rows-1), cvScalarAll(1), 1, 8, 0 );
- }
-}
-
-
-void CV_FloodFillTest::run_func()
-{
- int flags = connectivity + (mask_only ? CV_FLOODFILL_MASK_ONLY : 0) +
- (range_type == 1 ? CV_FLOODFILL_FIXED_RANGE : 0) + (new_mask_val << 8);
- double* odata = test_mat[OUTPUT][0].data.db;
-
- if(!test_cpp)
- {
- CvConnectedComp comp;
- cvFloodFill( test_array[INPUT_OUTPUT][0], seed_pt, new_val, l_diff, u_diff, &comp,
- flags, test_array[INPUT_OUTPUT][1] );
- odata[0] = comp.area;
- odata[1] = comp.rect.x;
- odata[2] = comp.rect.y;
- odata[3] = comp.rect.width;
- odata[4] = comp.rect.height;
- odata[5] = comp.value.val[0];
- odata[6] = comp.value.val[1];
- odata[7] = comp.value.val[2];
- odata[8] = comp.value.val[3];
- }
- else
- {
- cv::Mat img = cv::cvarrToMat(test_array[INPUT_OUTPUT][0]),
- mask = test_array[INPUT_OUTPUT][1] ? cv::cvarrToMat(test_array[INPUT_OUTPUT][1]) : cv::Mat();
- cv::Rect rect;
- int area;
- if( !mask.data )
- area = cv::floodFill( img, seed_pt, new_val, &rect, l_diff, u_diff, flags );
- else
- area = cv::floodFill( img, mask, seed_pt, new_val, &rect, l_diff, u_diff, flags );
- odata[0] = area;
- odata[1] = rect.x;
- odata[2] = rect.y;
- odata[3] = rect.width;
- odata[4] = rect.height;
- odata[5] = odata[6] = odata[7] = odata[8] = 0;
- }
-}
-
-
-typedef struct ff_offset_pair_t
-{
- int mofs, iofs;
-}
-ff_offset_pair_t;
-
-static void
-cvTsFloodFill( CvMat* _img, CvPoint seed_pt, CvScalar new_val,
- CvScalar l_diff, CvScalar u_diff, CvMat* _mask,
- double* comp, int connectivity, int range_type,
- int new_mask_val, bool mask_only )
-{
- CvMemStorage* st = cvCreateMemStorage();
- ff_offset_pair_t p0, p;
- CvSeq* seq = cvCreateSeq( 0, sizeof(CvSeq), sizeof(p0), st );
- CvMat* tmp = _img;
- CvMat* mask;
- CvRect r = cvRect( 0, 0, -1, -1 );
- int area = 0;
- int i, j;
- ushort* m;
- float* img;
- int mstep, step;
- int cn = CV_MAT_CN(_img->type);
- int mdelta[8], idelta[8], ncount;
- int cols = _img->cols, rows = _img->rows;
- int u0 = 0, u1 = 0, u2 = 0;
- double s0 = 0, s1 = 0, s2 = 0;
-
- if( CV_MAT_DEPTH(_img->type) == CV_8U )
- {
- tmp = cvCreateMat( rows, cols, CV_MAKETYPE(CV_32F,CV_MAT_CN(_img->type)) );
- cvTsConvert(_img, tmp);
- }
-
- mask = cvCreateMat( rows + 2, cols + 2, CV_16UC1 );
-
- if( _mask )
- cvTsConvert( _mask, mask );
- else
- {
- cvTsZero( mask );
- cvRectangle( mask, cvPoint(0,0), cvPoint(mask->cols-1,mask->rows-1), cvScalarAll(1.), 1, 8, 0 );
- }
-
- new_mask_val = (new_mask_val != 0 ? new_mask_val : 1) << 8;
-
- m = (ushort*)(mask->data.ptr + mask->step) + 1;
- mstep = mask->step / sizeof(m[0]);
- img = tmp->data.fl;
- step = tmp->step / sizeof(img[0]);
-
- p0.mofs = seed_pt.y*mstep + seed_pt.x;
- p0.iofs = seed_pt.y*step + seed_pt.x*cn;
-
- if( m[p0.mofs] )
- goto _exit_;
-
- cvSeqPush( seq, &p0 );
- m[p0.mofs] = (ushort)new_mask_val;
-
- if( connectivity == 4 )
- {
- ncount = 4;
- mdelta[0] = -mstep; idelta[0] = -step;
- mdelta[1] = -1; idelta[1] = -cn;
- mdelta[2] = 1; idelta[2] = cn;
- mdelta[3] = mstep; idelta[3] = step;
- }
- else
- {
- ncount = 8;
- mdelta[0] = -mstep-1; mdelta[1] = -mstep; mdelta[2] = -mstep+1;
- idelta[0] = -step-cn; idelta[1] = -step; idelta[2] = -step+cn;
-
- mdelta[3] = -1; mdelta[4] = 1;
- idelta[3] = -cn; idelta[4] = cn;
-
- mdelta[5] = mstep-1; mdelta[6] = mstep; mdelta[7] = mstep+1;
- idelta[5] = step-cn; idelta[6] = step; idelta[7] = step+cn;
- }
-
- if( cn == 1 )
- {
- float a0 = (float)-l_diff.val[0];
- float b0 = (float)u_diff.val[0];
-
- s0 = img[p0.iofs];
-
- if( range_type < 2 )
- {
- a0 += (float)s0; b0 += (float)s0;
- }
-
- while( seq->total )
- {
- cvSeqPop( seq, &p0 );
- float a = a0, b = b0;
- float* ptr = img + p0.iofs;
- ushort* mptr = m + p0.mofs;
-
- if( range_type == 2 )
- a += ptr[0], b += ptr[0];
-
- for( i = 0; i < ncount; i++ )
- {
- int md = mdelta[i], id = idelta[i];
- float v;
- if( !mptr[md] && a <= (v = ptr[id]) && v <= b )
- {
- mptr[md] = (ushort)new_mask_val;
- p.mofs = p0.mofs + md;
- p.iofs = p0.iofs + id;
- cvSeqPush( seq, &p );
- }
- }
- }
- }
- else
- {
- float a0 = (float)-l_diff.val[0];
- float a1 = (float)-l_diff.val[1];
- float a2 = (float)-l_diff.val[2];
- float b0 = (float)u_diff.val[0];
- float b1 = (float)u_diff.val[1];
- float b2 = (float)u_diff.val[2];
-
- s0 = img[p0.iofs];
- s1 = img[p0.iofs + 1];
- s2 = img[p0.iofs + 2];
-
- if( range_type < 2 )
- {
- a0 += (float)s0; b0 += (float)s0;
- a1 += (float)s1; b1 += (float)s1;
- a2 += (float)s2; b2 += (float)s2;
- }
-
- while( seq->total )
- {
- cvSeqPop( seq, &p0 );
- float _a0 = a0, _a1 = a1, _a2 = a2;
- float _b0 = b0, _b1 = b1, _b2 = b2;
- float* ptr = img + p0.iofs;
- ushort* mptr = m + p0.mofs;
-
- if( range_type == 2 )
- {
- _a0 += ptr[0]; _b0 += ptr[0];
- _a1 += ptr[1]; _b1 += ptr[1];
- _a2 += ptr[2]; _b2 += ptr[2];
- }
-
- for( i = 0; i < ncount; i++ )
- {
- int md = mdelta[i], id = idelta[i];
- float v;
- if( !mptr[md] &&
- _a0 <= (v = ptr[id]) && v <= _b0 &&
- _a1 <= (v = ptr[id+1]) && v <= _b1 &&
- _a2 <= (v = ptr[id+2]) && v <= _b2 )
- {
- mptr[md] = (ushort)new_mask_val;
- p.mofs = p0.mofs + md;
- p.iofs = p0.iofs + id;
- cvSeqPush( seq, &p );
- }
- }
- }
- }
-
- r.x = r.width = seed_pt.x;
- r.y = r.height = seed_pt.y;
-
- if( !mask_only )
- {
- s0 = new_val.val[0];
- s1 = new_val.val[1];
- s2 = new_val.val[2];
-
- if( tmp != _img )
- {
- u0 = cvRound(s0);
- u0 = CV_CAST_8U(u0);
- u1 = cvRound(s1);
- u1 = CV_CAST_8U(u1);
- u2 = cvRound(s2);
- u2 = CV_CAST_8U(u2);
-
- s0 = u0;
- s1 = u1;
- s2 = u2;
- }
- }
- else
- s0 = s1 = s2 = 0;
-
- new_mask_val >>= 8;
-
- for( i = 0; i < rows; i++ )
- {
- float* ptr = img + i*step;
- ushort* mptr = m + i*mstep;
- uchar* dmptr = _mask ? _mask->data.ptr + (i+1)*_mask->step + 1 : 0;
- uchar* dptr = tmp != _img ? _img->data.ptr + i*_img->step : 0;
- double area0 = area;
-
- for( j = 0; j < cols; j++ )
- {
- if( mptr[j] > 255 )
- {
- if( dmptr )
- dmptr[j] = (uchar)new_mask_val;
- if( !mask_only )
- {
- if( cn == 1 )
- {
- if( dptr )
- dptr[j] = (uchar)u0;
- else
- ptr[j] = (float)s0;
- }
- else
- {
- if( dptr )
- {
- dptr[j*3] = (uchar)u0;
- dptr[j*3+1] = (uchar)u1;
- dptr[j*3+2] = (uchar)u2;
- }
- else
- {
- ptr[j*3] = (float)s0;
- ptr[j*3+1] = (float)s1;
- ptr[j*3+2] = (float)s2;
- }
- }
- }
- else
- {
- if( cn == 1 )
- s0 += ptr[j];
- else
- {
- s0 += ptr[j*3];
- s1 += ptr[j*3+1];
- s2 += ptr[j*3+2];
- }
- }
-
- area++;
- if( r.x > j )
- r.x = j;
- if( r.width < j )
- r.width = j;
- }
- }
-
- if( area != area0 )
- {
- if( r.y > i )
- r.y = i;
- if( r.height < i )
- r.height = i;
- }
- }
-
-_exit_:
- cvReleaseMat( &mask );
- if( tmp != _img )
- cvReleaseMat( &tmp );
-
- comp[0] = area;
- comp[1] = r.x;
- comp[2] = r.y;
- comp[3] = r.width - r.x + 1;
- comp[4] = r.height - r.y + 1;
- if( mask_only )
- {
- double t = area ? 1./area : 0;
- s0 *= t;
- s1 *= t;
- s2 *= t;
- }
- comp[5] = s0;
- comp[6] = s1;
- comp[7] = s2;
- comp[8] = 0;
-}
-
-
-void CV_FloodFillTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- double* comp = test_mat[REF_OUTPUT][0].data.db;
- cvTsFloodFill( &test_mat[REF_INPUT_OUTPUT][0], seed_pt, new_val, l_diff, u_diff,
- test_array[REF_INPUT_OUTPUT][1] ? &test_mat[REF_INPUT_OUTPUT][1] : 0,
- comp, connectivity, range_type, new_mask_val, mask_only );
- if(test_cpp)
- comp[5] = comp[6] = comp[7] = comp[8] = 0;
-}
-
-
-/*int CV_FloodFillTest::write_default_params( CvFileStorage* fs )
-{
- int code = CvArrTest::write_default_params( fs );
- if( code < 0 )
- return code;
-
- if( ts->get_testing_mode() == CvTS::TIMING_MODE )
- {
- start_write_param( fs );
- write_string_list( fs, "dist_type", floodfill_types );
- write_int_list( fs, "labels", floodfill_labels, -1, -1 );
- }
-
- return code;
-}
-
-
-void CV_FloodFillTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images )
-{
- CvArrTest::get_timing_test_array_types_and_sizes( test_case_idx, sizes, types,
- whole_sizes, are_images );
- const char* distype_str = cvReadString( find_timing_param( "dist_type" ), "l2_5x5" );
- mask_size = strstr( distype_str, "3x3" ) ? 3 : 5;
- dist_type = distype_str[0] == 'c' ? CV_DIST_C : distype_str[1] == '1' ? CV_DIST_L1 : CV_DIST_L2;
- fill_labels = cvReadInt( find_timing_param( "labels" ), 0 );
-
- types[INPUT][0] = CV_8UC1;
- types[OUTPUT][0] = CV_32FC1;
- types[OUTPUT][1] = CV_32SC1;
-
- if( !fill_labels )
- sizes[OUTPUT][0] = whole_sizes[OUTPUT][0] = cvSize(0,0);
-}
-
-
-void CV_FloodFillTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- sprintf( ptr, "%s,", cvReadString( find_timing_param( "dist_type" ), "l2_5x5" ) );
- ptr += strlen(ptr);
- sprintf( ptr, "%s,", fill_labels ? "labels" : "no_labels" );
- ptr += strlen(ptr);
- params_left -= 2;
-
- CvArrTest::print_timing_params( test_case_idx, ptr, params_left );
-}*/
-
-
-CV_FloodFillTest floodfill_test;
-
-/* End of file. */
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-int cvTsRodrigues( const CvMat* src, CvMat* dst, CvMat* jacobian )
-{
- int depth;
- int i;
- float Jf[27];
- double J[27];
- CvMat _Jf, matJ = cvMat( 3, 9, CV_64F, J );
-
- depth = CV_MAT_DEPTH(src->type);
-
- if( jacobian )
- {
- assert( (jacobian->rows == 9 && jacobian->cols == 3) ||
- (jacobian->rows == 3 && jacobian->cols == 9) );
- }
-
- if( src->cols == 1 || src->rows == 1 )
- {
- double r[3], theta;
- CvMat _r = cvMat( src->rows, src->cols, CV_MAKETYPE(CV_64F,CV_MAT_CN(src->type)), r);
-
- assert( dst->rows == 3 && dst->cols == 3 );
-
- cvConvert( src, &_r );
-
- theta = sqrt(r[0]*r[0] + r[1]*r[1] + r[2]*r[2]);
- if( theta < DBL_EPSILON )
- {
- cvSetIdentity( dst );
-
- if( jacobian )
- {
- memset( J, 0, sizeof(J) );
- J[5] = J[15] = J[19] = 1;
- J[7] = J[11] = J[21] = -1;
- }
- }
- else
- {
- // omega = r/theta (~[w1, w2, w3])
- double itheta = 1./theta;
- double w1 = r[0]*itheta, w2 = r[1]*itheta, w3 = r[2]*itheta;
- double alpha = cos(theta);
- double beta = sin(theta);
- double gamma = 1 - alpha;
- double omegav[] =
- {
- 0, -w3, w2,
- w3, 0, -w1,
- -w2, w1, 0
- };
- double A[] =
- {
- w1*w1, w1*w2, w1*w3,
- w2*w1, w2*w2, w2*w3,
- w3*w1, w3*w2, w3*w3
- };
- double R[9];
- CvMat _omegav = cvMat(3, 3, CV_64F, omegav);
- CvMat matA = cvMat(3, 3, CV_64F, A);
- CvMat matR = cvMat(3, 3, CV_64F, R);
-
- cvSetIdentity( &matR, cvRealScalar(alpha) );
- cvScaleAdd( &_omegav, cvRealScalar(beta), &matR, &matR );
- cvScaleAdd( &matA, cvRealScalar(gamma), &matR, &matR );
- cvConvert( &matR, dst );
-
- if( jacobian )
- {
- // m3 = [r, theta]
- double dm3din[] =
- {
- 1, 0, 0,
- 0, 1, 0,
- 0, 0, 1,
- w1, w2, w3
- };
- // m2 = [omega, theta]
- double dm2dm3[] =
- {
- itheta, 0, 0, -w1*itheta,
- 0, itheta, 0, -w2*itheta,
- 0, 0, itheta, -w3*itheta,
- 0, 0, 0, 1
- };
- double t0[9*4];
- double dm1dm2[21*4];
- double dRdm1[9*21];
- CvMat _dm3din = cvMat( 4, 3, CV_64FC1, dm3din );
- CvMat _dm2dm3 = cvMat( 4, 4, CV_64FC1, dm2dm3 );
- CvMat _dm1dm2 = cvMat( 21, 4, CV_64FC1, dm1dm2 );
- CvMat _dRdm1 = cvMat( 9, 21, CV_64FC1, dRdm1 );
- CvMat _dRdm1_part;
- CvMat _t0 = cvMat( 9, 4, CV_64FC1, t0 );
- CvMat _t1 = cvMat( 9, 4, CV_64FC1, dRdm1 );
-
- // m1 = [alpha, beta, gamma, omegav; A]
- memset( dm1dm2, 0, sizeof(dm1dm2) );
- dm1dm2[3] = -beta;
- dm1dm2[7] = alpha;
- dm1dm2[11] = beta;
-
- // dm1dm2(4:12,1:3) = [0 0 0 0 0 1 0 -1 0;
- // 0 0 -1 0 0 0 1 0 0;
- // 0 1 0 -1 0 0 0 0 0]'
- // -------------------
- // 0 0 0 0 0 0 0 0 0
- dm1dm2[12 + 6] = dm1dm2[12 + 20] = dm1dm2[12 + 25] = 1;
- dm1dm2[12 + 9] = dm1dm2[12 + 14] = dm1dm2[12 + 28] = -1;
-
- double dm1dw[] =
- {
- 2*w1, w2, w3, w2, 0, 0, w3, 0, 0,
- 0, w1, 0, w1, 2*w2, w3, 0, w3, 0,
- 0, 0, w1, 0, 0, w2, w1, w2, 2*w3
- };
-
- CvMat _dm1dw = cvMat( 3, 9, CV_64FC1, dm1dw );
- CvMat _dm1dm2_part;
-
- cvGetSubRect( &_dm1dm2, &_dm1dm2_part, cvRect(0,12,3,9) );
- cvTranspose( &_dm1dw, &_dm1dm2_part );
-
- memset( dRdm1, 0, sizeof(dRdm1) );
- dRdm1[0*21] = dRdm1[4*21] = dRdm1[8*21] = 1;
-
- cvGetCol( &_dRdm1, &_dRdm1_part, 1 );
- cvTranspose( &_omegav, &_omegav );
- cvReshape( &_omegav, &_omegav, 1, 1 );
- cvTranspose( &_omegav, &_dRdm1_part );
-
- cvGetCol( &_dRdm1, &_dRdm1_part, 2 );
- cvReshape( &matA, &matA, 1, 1 );
- cvTranspose( &matA, &_dRdm1_part );
-
- cvGetSubRect( &_dRdm1, &_dRdm1_part, cvRect(3,0,9,9) );
- cvSetIdentity( &_dRdm1_part, cvScalarAll(beta) );
-
- cvGetSubRect( &_dRdm1, &_dRdm1_part, cvRect(12,0,9,9) );
- cvSetIdentity( &_dRdm1_part, cvScalarAll(gamma) );
-
- matJ = cvMat( 9, 3, CV_64FC1, J );
-
- cvMatMul( &_dRdm1, &_dm1dm2, &_t0 );
- cvMatMul( &_t0, &_dm2dm3, &_t1 );
- cvMatMul( &_t1, &_dm3din, &matJ );
-
- _t0 = cvMat( 3, 9, CV_64FC1, t0 );
- cvTranspose( &matJ, &_t0 );
-
- for( i = 0; i < 3; i++ )
- {
- _t1 = cvMat( 3, 3, CV_64FC1, t0 + i*9 );
- cvTranspose( &_t1, &_t1 );
- }
-
- cvTranspose( &_t0, &matJ );
- }
- }
- }
- else if( src->cols == 3 && src->rows == 3 )
- {
- double R[9], A[9], I[9], r[3], W[3], U[9], V[9];
- double tr, alpha, beta, theta;
- CvMat matR = cvMat( 3, 3, CV_64F, R );
- CvMat matA = cvMat( 3, 3, CV_64F, A );
- CvMat matI = cvMat( 3, 3, CV_64F, I );
- CvMat _r = cvMat( dst->rows, dst->cols, CV_MAKETYPE(CV_64F, CV_MAT_CN(dst->type)), r );
- CvMat matW = cvMat( 1, 3, CV_64F, W );
- CvMat matU = cvMat( 3, 3, CV_64F, U );
- CvMat matV = cvMat( 3, 3, CV_64F, V );
-
- cvConvert( src, &matR );
- cvSVD( &matR, &matW, &matU, &matV, CV_SVD_MODIFY_A + CV_SVD_U_T + CV_SVD_V_T );
- cvGEMM( &matU, &matV, 1, 0, 0, &matR, CV_GEMM_A_T );
-
- cvMulTransposed( &matR, &matA, 0 );
- cvSetIdentity( &matI );
-
- if( cvNorm( &matA, &matI, CV_C ) > 1e-3 ||
- fabs( cvDet(&matR) - 1 ) > 1e-3 )
- return 0;
-
- tr = (cvTrace(&matR).val[0] - 1.)*0.5;
- tr = tr > 1. ? 1. : tr < -1. ? -1. : tr;
- theta = acos(tr);
- alpha = cos(theta);
- beta = sin(theta);
-
- if( beta >= 1e-5 )
- {
- double dtheta_dtr = -1./sqrt(1 - tr*tr);
- double vth = 1/(2*beta);
-
- // om1 = [R(3,2) - R(2,3), R(1,3) - R(3,1), R(2,1) - R(1,2)]'
- double om1[] = { R[7] - R[5], R[2] - R[6], R[3] - R[1] };
- // om = om1*vth
- // r = om*theta
- double d3 = vth*theta;
-
- r[0] = om1[0]*d3; r[1] = om1[1]*d3; r[2] = om1[2]*d3;
- cvConvert( &_r, dst );
-
- if( jacobian )
- {
- // var1 = [vth;theta]
- // var = [om1;var1] = [om1;vth;theta]
- double dvth_dtheta = -vth*alpha/beta;
- double d1 = 0.5*dvth_dtheta*dtheta_dtr;
- double d2 = 0.5*dtheta_dtr;
- // dvar1/dR = dvar1/dtheta*dtheta/dR = [dvth/dtheta; 1] * dtheta/dtr * dtr/dR
- double dvardR[5*9] =
- {
- 0, 0, 0, 0, 0, 1, 0, -1, 0,
- 0, 0, -1, 0, 0, 0, 1, 0, 0,
- 0, 1, 0, -1, 0, 0, 0, 0, 0,
- d1, 0, 0, 0, d1, 0, 0, 0, d1,
- d2, 0, 0, 0, d2, 0, 0, 0, d2
- };
- // var2 = [om;theta]
- double dvar2dvar[] =
- {
- vth, 0, 0, om1[0], 0,
- 0, vth, 0, om1[1], 0,
- 0, 0, vth, om1[2], 0,
- 0, 0, 0, 0, 1
- };
- double domegadvar2[] =
- {
- theta, 0, 0, om1[0]*vth,
- 0, theta, 0, om1[1]*vth,
- 0, 0, theta, om1[2]*vth
- };
-
- CvMat _dvardR = cvMat( 5, 9, CV_64FC1, dvardR );
- CvMat _dvar2dvar = cvMat( 4, 5, CV_64FC1, dvar2dvar );
- CvMat _domegadvar2 = cvMat( 3, 4, CV_64FC1, domegadvar2 );
- double t0[3*5];
- CvMat _t0 = cvMat( 3, 5, CV_64FC1, t0 );
-
- cvMatMul( &_domegadvar2, &_dvar2dvar, &_t0 );
- cvMatMul( &_t0, &_dvardR, &matJ );
- }
- }
- else if( tr > 0 )
- {
- cvZero( dst );
- if( jacobian )
- {
- memset( J, 0, sizeof(J) );
- J[5] = J[15] = J[19] = 0.5;
- J[7] = J[11] = J[21] = -0.5;
- }
- }
- else
- {
- r[0] = theta*sqrt((R[0] + 1)*0.5);
- r[1] = theta*sqrt((R[4] + 1)*0.5)*(R[1] >= 0 ? 1 : -1);
- r[2] = theta*sqrt((R[8] + 1)*0.5)*(R[2] >= 0 ? 1 : -1);
- cvConvert( &_r, dst );
-
- if( jacobian )
- memset( J, 0, sizeof(J) );
- }
-
- if( jacobian )
- {
- for( i = 0; i < 3; i++ )
- {
- CvMat t = cvMat( 3, 3, CV_64F, J + i*9 );
- cvTranspose( &t, &t );
- }
- }
- }
- else
- {
- assert(0);
- return 0;
- }
-
- if( jacobian )
- {
- if( depth == CV_32F )
- {
- if( jacobian->rows == matJ.rows )
- cvConvert( &matJ, jacobian );
- else
- {
- _Jf = cvMat( matJ.rows, matJ.cols, CV_32FC1, Jf );
- cvConvert( &matJ, &_Jf );
- cvTranspose( &_Jf, jacobian );
- }
- }
- else if( jacobian->rows == matJ.rows )
- cvCopy( &matJ, jacobian );
- else
- cvTranspose( &matJ, jacobian );
- }
-
- return 1;
-}
-
-
-void
-cvTsConvertHomogeneous( const CvMat* src, CvMat* dst )
-{
- CvMat* src_buf = 0;
- CvMat* dst_buf = 0;
- CvMat* dst0 = dst;
- int i, count, sdims, ddims;
- int sstep1, sstep2, dstep1, dstep2;
- double *s, *d;
-
- if( CV_MAT_DEPTH(src->type) != CV_64F )
- {
- src_buf = cvCreateMat( src->rows, src->cols, CV_MAKETYPE(CV_64F, CV_MAT_CN(src->type)) );
- cvTsConvert( src, src_buf );
- src = src_buf;
- }
-
- if( CV_MAT_DEPTH(dst->type) != CV_64F )
- {
- dst_buf = cvCreateMat( dst->rows, dst->cols, CV_MAKETYPE(CV_64F, CV_MAT_CN(dst->type)) );
- dst = dst_buf;
- }
-
- if( src->rows > src->cols )
- {
- count = src->rows;
- sdims = CV_MAT_CN(src->type)*src->cols;
- sstep1 = src->step/sizeof(double);
- sstep2 = 1;
- }
- else
- {
- count = src->cols;
- sdims = CV_MAT_CN(src->type)*src->rows;
- if( src->rows == 1 )
- {
- sstep1 = sdims;
- sstep2 = 1;
- }
- else
- {
- sstep1 = 1;
- sstep2 = src->step/sizeof(double);
- }
- }
-
- if( dst->rows > dst->cols )
- {
- assert( count == dst->rows );
- ddims = CV_MAT_CN(dst->type)*dst->cols;
- dstep1 = dst->step/sizeof(double);
- dstep2 = 1;
- }
- else
- {
- assert( count == dst->cols );
- ddims = CV_MAT_CN(dst->type)*dst->rows;
- if( dst->rows == 1 )
- {
- dstep1 = ddims;
- dstep2 = 1;
- }
- else
- {
- dstep1 = 1;
- dstep2 = dst->step/sizeof(double);
- }
- }
-
- s = src->data.db;
- d = dst->data.db;
-
- if( sdims <= ddims )
- {
- int wstep = dstep2*(ddims - 1);
-
- for( i = 0; i < count; i++, s += sstep1, d += dstep1 )
- {
- double x = s[0];
- double y = s[sstep2];
-
- d[wstep] = 1;
- d[0] = x;
- d[dstep2] = y;
-
- if( sdims >= 3 )
- {
- d[dstep2*2] = s[sstep2*2];
- if( sdims == 4 )
- d[dstep2*3] = s[sstep2*3];
- }
- }
- }
- else
- {
- int wstep = sstep2*(sdims - 1);
-
- for( i = 0; i < count; i++, s += sstep1, d += dstep1 )
- {
- double w = s[wstep];
- double x = s[0];
- double y = s[sstep2];
-
- w = w ? 1./w : 1;
-
- d[0] = x*w;
- d[dstep2] = y*w;
-
- if( ddims == 3 )
- d[dstep2*2] = s[sstep2*2]*w;
- }
- }
-
- if( dst != dst0 )
- cvTsConvert( dst, dst0 );
-
- cvReleaseMat( &src_buf );
- cvReleaseMat( &dst_buf );
-}
-
-
-void
-cvTsProjectPoints( const CvMat* _3d, const CvMat* Rt, const CvMat* A,
- CvMat* _2d, CvRNG* rng, double sigma )
-{
- double p[12];
- CvMat P = cvMat( 3, 4, CV_64F, p );
-
- int i, count = _3d->cols;
-
- CvMat* temp;
- CvMat* noise = 0;
-
- cvMatMul( A, Rt, &P );
-
- if( rng )
- {
- if( sigma == 0 )
- rng = 0;
- else
- {
- noise = cvCreateMat( 1, _3d->cols, CV_64FC2 );
- cvRandArr( rng, noise, CV_RAND_NORMAL, cvScalarAll(0), cvScalarAll(sigma) );
- }
- }
-
- temp = cvCreateMat( 1, count, CV_64FC3 );
-
- for( i = 0; i < count; i++ )
- {
- const double* M = _3d->data.db + i*3;
- double* m = temp->data.db + i*3;
- double X = M[0], Y = M[1], Z = M[2];
- double u = p[0]*X + p[1]*Y + p[2]*Z + p[3];
- double v = p[4]*X + p[5]*Y + p[6]*Z + p[7];
- double s = p[8]*X + p[9]*Y + p[10]*Z + p[11];
-
- if( noise )
- {
- u += noise->data.db[i*2]*s;
- v += noise->data.db[i*2+1]*s;
- }
-
- m[0] = u;
- m[1] = v;
- m[2] = s;
- }
-
- cvTsConvertHomogeneous( temp, _2d );
- cvReleaseMat( &noise );
- cvReleaseMat( &temp );
-}
-
-
-/********************************** Rodrigues transform ********************************/
-
-class CV_RodriguesTest : public CvArrTest
-{
-public:
- CV_RodriguesTest();
-
-protected:
- int read_params( CvFileStorage* fs );
- void fill_array( int test_case_idx, int i, int j, CvMat* arr );
- int prepare_test_case( int test_case_idx );
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- double get_success_error_level( int test_case_idx, int i, int j );
- void run_func();
- void prepare_to_validation( int );
-
- bool calc_jacobians;
- bool test_cpp;
-};
-
-
-CV_RodriguesTest::CV_RodriguesTest()
- : CvArrTest( "_3d-rodrigues", "cvRodrigues2", "" )
-{
- test_array[INPUT].push(NULL); // rotation vector
- test_array[OUTPUT].push(NULL); // rotation matrix
- test_array[OUTPUT].push(NULL); // jacobian (J)
- test_array[OUTPUT].push(NULL); // rotation vector (backward transform result)
- test_array[OUTPUT].push(NULL); // inverse transform jacobian (J1)
- test_array[OUTPUT].push(NULL); // J*J1 (or J1*J) == I(3x3)
- test_array[REF_OUTPUT].push(NULL);
- test_array[REF_OUTPUT].push(NULL);
- test_array[REF_OUTPUT].push(NULL);
- test_array[REF_OUTPUT].push(NULL);
- test_array[REF_OUTPUT].push(NULL);
-
- element_wise_relative_error = false;
- calc_jacobians = false;
-
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;
- default_timing_param_names = 0;
- test_cpp = false;
-}
-
-
-int CV_RodriguesTest::read_params( CvFileStorage* fs )
-{
- int code = CvArrTest::read_params( fs );
- return code;
-}
-
-
-void CV_RodriguesTest::get_test_array_types_and_sizes(
- int /*test_case_idx*/, CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- int depth = cvTsRandInt(rng) % 2 == 0 ? CV_32F : CV_64F;
- int i, code;
-
- code = cvTsRandInt(rng) % 3;
- types[INPUT][0] = CV_MAKETYPE(depth, 1);
-
- if( code == 0 )
- {
- sizes[INPUT][0] = cvSize(1,1);
- types[INPUT][0] = CV_MAKETYPE(depth, 3);
- }
- else if( code == 1 )
- sizes[INPUT][0] = cvSize(3,1);
- else
- sizes[INPUT][0] = cvSize(1,3);
-
- sizes[OUTPUT][0] = cvSize(3, 3);
- types[OUTPUT][0] = CV_MAKETYPE(depth, 1);
-
- types[OUTPUT][1] = CV_MAKETYPE(depth, 1);
-
- if( cvTsRandInt(rng) % 2 )
- sizes[OUTPUT][1] = cvSize(3,9);
- else
- sizes[OUTPUT][1] = cvSize(9,3);
-
- types[OUTPUT][2] = types[INPUT][0];
- sizes[OUTPUT][2] = sizes[INPUT][0];
-
- types[OUTPUT][3] = types[OUTPUT][1];
- sizes[OUTPUT][3] = cvSize(sizes[OUTPUT][1].height, sizes[OUTPUT][1].width);
-
- types[OUTPUT][4] = types[OUTPUT][1];
- sizes[OUTPUT][4] = cvSize(3,3);
-
- calc_jacobians = cvTsRandInt(rng) % 3 != 0;
- if( !calc_jacobians )
- sizes[OUTPUT][1] = sizes[OUTPUT][3] = sizes[OUTPUT][4] = cvSize(0,0);
-
- for( i = 0; i < 5; i++ )
- {
- types[REF_OUTPUT][i] = types[OUTPUT][i];
- sizes[REF_OUTPUT][i] = sizes[OUTPUT][i];
- }
- test_cpp = (cvTsRandInt(rng) & 256) == 0;
-}
-
-
-double CV_RodriguesTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int j )
-{
- return j == 4 ? 1e-2 : 1e-2;
-}
-
-
-void CV_RodriguesTest::fill_array( int test_case_idx, int i, int j, CvMat* arr )
-{
- if( i == INPUT && j == 0 )
- {
- double r[3], theta0, theta1, f;
- CvMat _r = cvMat( arr->rows, arr->cols, CV_MAKETYPE(CV_64F,CV_MAT_CN(arr->type)), r );
- CvRNG* rng = ts->get_rng();
-
- r[0] = cvTsRandReal(rng)*CV_PI*2;
- r[1] = cvTsRandReal(rng)*CV_PI*2;
- r[2] = cvTsRandReal(rng)*CV_PI*2;
-
- theta0 = sqrt(r[0]*r[0] + r[1]*r[1] + r[2]*r[2]);
- theta1 = fmod(theta0, CV_PI*2);
-
- if( theta1 > CV_PI )
- theta1 = -(CV_PI*2 - theta1);
-
- f = theta1/(theta0 ? theta0 : 1);
- r[0] *= f;
- r[1] *= f;
- r[2] *= f;
-
- cvTsConvert( &_r, arr );
- }
- else
- CvArrTest::fill_array( test_case_idx, i, j, arr );
-}
-
-
-int CV_RodriguesTest::prepare_test_case( int test_case_idx )
-{
- int code = CvArrTest::prepare_test_case( test_case_idx );
- return code;
-}
-
-
-void CV_RodriguesTest::run_func()
-{
- CvMat *v2m_jac = 0, *m2v_jac = 0;
-
- if( calc_jacobians )
- {
- v2m_jac = &test_mat[OUTPUT][1];
- m2v_jac = &test_mat[OUTPUT][3];
- }
-
- if( !test_cpp )
- {
- cvRodrigues2( &test_mat[INPUT][0], &test_mat[OUTPUT][0], v2m_jac );
- cvRodrigues2( &test_mat[OUTPUT][0], &test_mat[OUTPUT][2], m2v_jac );
- }
- else
- {
- cv::Mat v(&test_mat[INPUT][0]), M(&test_mat[OUTPUT][0]), v2(&test_mat[OUTPUT][2]);
- cv::Mat M0 = M, v2_0 = v2;
- if( !calc_jacobians )
- {
- cv::Rodrigues(v, M);
- cv::Rodrigues(M, v2);
- }
- else
- {
- cv::Mat J1(&test_mat[OUTPUT][1]), J2(&test_mat[OUTPUT][3]);
- cv::Mat J1_0 = J1, J2_0 = J2;
- cv::Rodrigues(v, M, J1);
- cv::Rodrigues(M, v2, J2);
- if( J1.data != J1_0.data )
- {
- if( J1.size() != J1_0.size() )
- J1 = J1.t();
- J1.convertTo(J1_0, J1_0.type());
- }
- if( J2.data != J2_0.data )
- {
- if( J2.size() != J2_0.size() )
- J2 = J2.t();
- J2.convertTo(J2_0, J2_0.type());
- }
- }
- if( M.data != M0.data )
- M.reshape(M0.channels(), M0.rows).convertTo(M0, M0.type());
- if( v2.data != v2_0.data )
- v2.reshape(v2_0.channels(), v2_0.rows).convertTo(v2_0, v2_0.type());
- }
-}
-
-
-void CV_RodriguesTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- const CvMat* vec = &test_mat[INPUT][0];
- CvMat* m = &test_mat[REF_OUTPUT][0];
- CvMat* vec2 = &test_mat[REF_OUTPUT][2];
- CvMat* v2m_jac = 0, *m2v_jac = 0;
- double theta0, theta1;
-
- if( calc_jacobians )
- {
- v2m_jac = &test_mat[REF_OUTPUT][1];
- m2v_jac = &test_mat[REF_OUTPUT][3];
- }
-
-
- cvTsRodrigues( vec, m, v2m_jac );
- cvTsRodrigues( m, vec2, m2v_jac );
- cvTsCopy( vec, vec2 );
-
- theta0 = cvNorm( vec2, 0, CV_L2 );
- theta1 = fmod( theta0, CV_PI*2 );
-
- if( theta1 > CV_PI )
- theta1 = -(CV_PI*2 - theta1);
- cvScale( vec2, vec2, theta1/(theta0 ? theta0 : 1) );
-
- if( calc_jacobians )
- {
- //cvInvert( v2m_jac, m2v_jac, CV_SVD );
- double nrm = cvNorm(&test_mat[REF_OUTPUT][3],0,CV_C);
- if( FLT_EPSILON < nrm && nrm < 1000 )
- {
- cvTsGEMM( &test_mat[OUTPUT][1], &test_mat[OUTPUT][3],
- 1, 0, 0, &test_mat[OUTPUT][4],
- v2m_jac->rows == 3 ? 0 : CV_GEMM_A_T + CV_GEMM_B_T );
- }
- else
- {
- cvTsSetIdentity( &test_mat[OUTPUT][4], cvScalarAll(1.) );
- cvTsCopy( &test_mat[REF_OUTPUT][2], &test_mat[OUTPUT][2] );
- }
- cvTsSetIdentity( &test_mat[REF_OUTPUT][4], cvScalarAll(1.) );
- }
-}
-
-
-CV_RodriguesTest rodrigues_test;
-
-
-/********************************** fundamental matrix *********************************/
-
-class CV_FundamentalMatTest : public CvArrTest
-{
-public:
- CV_FundamentalMatTest();
-
-protected:
- int read_params( CvFileStorage* fs );
- void fill_array( int test_case_idx, int i, int j, CvMat* arr );
- int prepare_test_case( int test_case_idx );
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- double get_success_error_level( int test_case_idx, int i, int j );
- void run_func();
- void prepare_to_validation( int );
-
- int method;
- int img_size;
- int cube_size;
- int dims;
- int f_result;
- double min_f, max_f;
- double sigma;
- bool test_cpp;
-};
-
-
-CV_FundamentalMatTest::CV_FundamentalMatTest()
- : CvArrTest( "_3d-fundam", "cvFindFundamentalMatrix", "" )
-{
- // input arrays:
- // 0, 1 - arrays of 2d points that are passed to %func%.
- // Can have different data type, layout, be stored in homogeneous coordinates or not.
- // 2 - array of 3d points that are projected to both view planes
- // 3 - [R|t] matrix for the second view plane (for the first one it is [I|0]
- // 4, 5 - intrinsic matrices
- test_array[INPUT].push(NULL);
- test_array[INPUT].push(NULL);
- test_array[INPUT].push(NULL);
- test_array[INPUT].push(NULL);
- test_array[INPUT].push(NULL);
- test_array[INPUT].push(NULL);
- test_array[TEMP].push(NULL);
- test_array[TEMP].push(NULL);
- test_array[OUTPUT].push(NULL);
- test_array[OUTPUT].push(NULL);
- test_array[REF_OUTPUT].push(NULL);
- test_array[REF_OUTPUT].push(NULL);
-
- element_wise_relative_error = false;
-
- method = 0;
- img_size = 10;
- cube_size = 10;
- min_f = 1;
- max_f = 3;
- sigma = 0;//0.1;
- f_result = 0;
-
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;
- default_timing_param_names = 0;
- test_cpp = false;
-}
-
-
-int CV_FundamentalMatTest::read_params( CvFileStorage* fs )
-{
- int code = CvArrTest::read_params( fs );
- return code;
-}
-
-
-void CV_FundamentalMatTest::get_test_array_types_and_sizes( int /*test_case_idx*/,
- CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- int pt_depth = cvTsRandInt(rng) % 2 == 0 ? CV_32F : CV_64F;
- double pt_count_exp = cvTsRandReal(rng)*6 + 1;
- int pt_count = cvRound(exp(pt_count_exp));
-
- dims = cvTsRandInt(rng) % 2 + 2;
- method = 1 << (cvTsRandInt(rng) % 4);
-
- if( method == CV_FM_7POINT )
- pt_count = 7;
- else
- {
- pt_count = MAX( pt_count, 8 + (method == CV_FM_8POINT) );
- if( pt_count >= 8 && cvTsRandInt(rng) % 2 )
- method |= CV_FM_8POINT;
- }
-
- types[INPUT][0] = CV_MAKETYPE(pt_depth, 1);
-
- if( cvTsRandInt(rng) % 2 )
- sizes[INPUT][0] = cvSize(pt_count, dims);
- else
- {
- sizes[INPUT][0] = cvSize(dims, pt_count);
- if( cvTsRandInt(rng) % 2 )
- {
- types[INPUT][0] = CV_MAKETYPE(pt_depth, dims);
- if( cvTsRandInt(rng) % 2 )
- sizes[INPUT][0] = cvSize(pt_count, 1);
- else
- sizes[INPUT][0] = cvSize(1, pt_count);
- }
- }
-
- sizes[INPUT][1] = sizes[INPUT][0];
- types[INPUT][1] = types[INPUT][0];
-
- sizes[INPUT][2] = cvSize(pt_count, 1 );
- types[INPUT][2] = CV_64FC3;
-
- sizes[INPUT][3] = cvSize(4,3);
- types[INPUT][3] = CV_64FC1;
-
- sizes[INPUT][4] = sizes[INPUT][5] = cvSize(3,3);
- types[INPUT][4] = types[INPUT][5] = CV_MAKETYPE(CV_64F, 1);
-
- sizes[TEMP][0] = cvSize(3,3);
- types[TEMP][0] = CV_64FC1;
- sizes[TEMP][1] = cvSize(pt_count,1);
- types[TEMP][1] = CV_8UC1;
-
- sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = cvSize(3,1);
- types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_64FC1;
- sizes[OUTPUT][1] = sizes[REF_OUTPUT][1] = cvSize(pt_count,1);
- types[OUTPUT][1] = types[REF_OUTPUT][1] = CV_8UC1;
-
- test_cpp = (cvTsRandInt(rng) & 256) == 0;
-}
-
-
-double CV_FundamentalMatTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- return 1e-2;
-}
-
-
-void CV_FundamentalMatTest::fill_array( int test_case_idx, int i, int j, CvMat* arr )
-{
- double t[12];
- CvMat T;
- double* p = arr->data.db;
- CvRNG* rng = ts->get_rng();
-
- if( i != INPUT )
- {
- CvArrTest::fill_array( test_case_idx, i, j, arr );
- return;
- }
-
- switch( j )
- {
- case 0:
- case 1:
- return; // fill them later in prepare_test_case
- case 2:
- for( i = 0; i < arr->cols*3; i += 3 )
- {
- p[i] = cvTsRandReal(rng)*cube_size;
- p[i+1] = cvTsRandReal(rng)*cube_size;
- p[i+2] = cvTsRandReal(rng)*cube_size + cube_size;
- }
- break;
- case 3:
- {
- double r[3];
- CvMat rot_vec = cvMat( 3, 1, CV_64F, r );
- CvMat rot_mat = cvMat( 3, 3, CV_64F );
- r[0] = cvTsRandReal(rng)*CV_PI*2;
- r[1] = cvTsRandReal(rng)*CV_PI*2;
- r[2] = cvTsRandReal(rng)*CV_PI*2;
-
- cvSetData( &rot_mat, t, 4*sizeof(t[0]) );
- cvTsRodrigues( &rot_vec, &rot_mat );
- t[3] = cvTsRandReal(rng)*cube_size;
- t[7] = cvTsRandReal(rng)*cube_size;
- t[11] = cvTsRandReal(rng)*cube_size;
- T = cvMat( 3, 4, CV_64F, t );
- cvTsConvert( &T, arr );
- }
- break;
- case 4:
- case 5:
- memset( t, 0, sizeof(t) );
- t[0] = t[4] = cvTsRandReal(rng)*(max_f - min_f) + min_f;
- t[2] = (img_size*0.5 + cvTsRandReal(rng)*4. - 2.)*t[0];
- t[5] = (img_size*0.5 + cvTsRandReal(rng)*4. - 2.)*t[4];
- t[8] = 1.;
- T = cvMat( 3, 3, CV_64F, t );
- cvTsConvert( &T, arr );
- break;
- }
-}
-
-
-int CV_FundamentalMatTest::prepare_test_case( int test_case_idx )
-{
- int code = CvArrTest::prepare_test_case( test_case_idx );
- if( code > 0 )
- {
- const CvMat* _3d = &test_mat[INPUT][2];
- CvRNG* rng = ts->get_rng();
- double Idata[] = { 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0 };
- CvMat I = cvMat( 3, 4, CV_64F, Idata );
- int k;
-
- for( k = 0; k < 2; k++ )
- {
- const CvMat* Rt = k == 0 ? &I : &test_mat[INPUT][3];
- const CvMat* A = &test_mat[INPUT][k == 0 ? 4 : 5];
- CvMat* _2d = &test_mat[INPUT][k];
-
- cvTsProjectPoints( _3d, Rt, A, _2d, rng, sigma );
- }
- }
-
- return code;
-}
-
-
-void CV_FundamentalMatTest::run_func()
-{
- //if(!test_cpp)
- {
- f_result = cvFindFundamentalMat( &test_mat[INPUT][0], &test_mat[INPUT][1],
- &test_mat[TEMP][0], method, MAX(sigma*3, 0.01), 0, &test_mat[TEMP][1] );
- }
- /*else
- {
- cv::findFundamentalMat(const Mat& points1, const Mat& points2,
- vector<uchar>& mask, int method=FM_RANSAC,
- double param1=3., double param2=0.99 );
-
- CV_EXPORTS Mat findFundamentalMat( const Mat& points1, const Mat& points2,
- int method=FM_RANSAC,
- double param1=3., double param2=0.99 );
- }*/
-
-}
-
-
-void CV_FundamentalMatTest::prepare_to_validation( int test_case_idx )
-{
- const CvMat* Rt = &test_mat[INPUT][3];
- const CvMat* A1 = &test_mat[INPUT][4];
- const CvMat* A2 = &test_mat[INPUT][5];
- double f0[9];
- CvMat F0 = cvMat( 3, 3, CV_64FC1, f0 );
-
- double _invA1[9], _invA2[9], temp[9];
- CvMat invA1 = cvMat( 3, 3, CV_64F, _invA1 );
- CvMat invA2 = cvMat( 3, 3, CV_64F, _invA2 );
- CvMat R = cvMat( 3, 3, CV_64F );
- CvMat T = cvMat( 3, 3, CV_64F, temp );
-
- cvSetData( &R, Rt->data.db, Rt->step ); // R = Rt(:,1:3)
-
- // F = (A2^-T)*[t]_x*R*(A1^-1)
- cvInvert( A1, &invA1, CV_SVD );
- cvInvert( A2, &invA2, CV_SVD );
-
- {
- double tx = ((double*)(Rt->data.ptr))[3];
- double ty = ((double*)(Rt->data.ptr + Rt->step))[3];
- double tz = ((double*)(Rt->data.ptr + Rt->step*2))[3];
-
- double _t_x[] = { 0, -tz, ty, tz, 0, -tx, -ty, tx, 0 };
- CvMat t_x = cvMat( 3, 3, CV_64F, _t_x );
-
- cvGEMM( &invA2, &t_x, 1, 0, 0, &T, CV_GEMM_A_T );
- cvMatMul( &R, &invA1, &invA2 );
- cvMatMul( &T, &invA2, &F0 );
- cvScale( &F0, &F0, f0[8] );
- }
-
- double f[9];
- CvMat F = cvMat(3, 3, CV_64F, f);
- uchar* status = test_mat[TEMP][1].data.ptr;
- double err_level = get_success_error_level( test_case_idx, OUTPUT, 1 );
- uchar* mtfm1 = test_mat[REF_OUTPUT][1].data.ptr;
- uchar* mtfm2 = test_mat[OUTPUT][1].data.ptr;
- double* f_prop1 = test_mat[REF_OUTPUT][0].data.db;
- double* f_prop2 = test_mat[OUTPUT][0].data.db;
-
- int i, pt_count = test_mat[INPUT][2].cols;
- CvMat* p1 = cvCreateMat( 1, pt_count, CV_64FC2 );
- CvMat* p2 = cvCreateMat( 1, pt_count, CV_64FC2 );
-
- cvTsConvertHomogeneous( &test_mat[INPUT][0], p1 );
- cvTsConvertHomogeneous( &test_mat[INPUT][1], p2 );
-
- cvTsConvert( &test_mat[TEMP][0], &F );
-
- if( method <= CV_FM_8POINT )
- memset( status, 1, pt_count );
-
- for( i = 0; i < pt_count; i++ )
- {
- double x1 = p1->data.db[i*2];
- double y1 = p1->data.db[i*2+1];
- double x2 = p2->data.db[i*2];
- double y2 = p2->data.db[i*2+1];
- double n1 = 1./sqrt(x1*x1 + y1*y1 + 1);
- double n2 = 1./sqrt(x2*x2 + y2*y2 + 1);
- double t0 = fabs(f0[0]*x2*x1 + f0[1]*x2*y1 + f0[2]*x2 +
- f0[3]*y2*x1 + f0[4]*y2*y1 + f0[5]*y2 +
- f0[6]*x1 + f0[7]*y1 + f0[8])*n1*n2;
- double t = fabs(f[0]*x2*x1 + f[1]*x2*y1 + f[2]*x2 +
- f[3]*y2*x1 + f[4]*y2*y1 + f[5]*y2 +
- f[6]*x1 + f[7]*y1 + f[8])*n1*n2;
- mtfm1[i] = 1;
- mtfm2[i] = !status[i] || t0 > err_level || t < err_level;
- }
-
- f_prop1[0] = 1;
- f_prop1[1] = 1;
- f_prop1[2] = 0;
-
- f_prop2[0] = f_result != 0;
- f_prop2[1] = f[8];
- f_prop2[2] = cvDet( &F );
-
- cvReleaseMat( &p1 );
- cvReleaseMat( &p2 );
-}
-
-
-CV_FundamentalMatTest fmatrix_test;
-
-
-/********************************** convert homogeneous *********************************/
-
-class CV_ConvertHomogeneousTest : public CvArrTest
-{
-public:
- CV_ConvertHomogeneousTest();
-
-protected:
- int read_params( CvFileStorage* fs );
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void fill_array( int test_case_idx, int i, int j, CvMat* arr );
- double get_success_error_level( int test_case_idx, int i, int j );
- void run_func();
- void prepare_to_validation( int );
-
- int dims1, dims2;
- int pt_count;
-};
-
-
-CV_ConvertHomogeneousTest::CV_ConvertHomogeneousTest()
- : CvArrTest( "_3d-cvt-homogen", "cvConvertPointsHomogeniuos", "" )
-{
- test_array[INPUT].push(NULL);
- test_array[OUTPUT].push(NULL);
- test_array[REF_OUTPUT].push(NULL);
- element_wise_relative_error = false;
-
- pt_count = dims1 = dims2 = 0;
-
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;
- default_timing_param_names = 0;
-}
-
-
-int CV_ConvertHomogeneousTest::read_params( CvFileStorage* fs )
-{
- int code = CvArrTest::read_params( fs );
- return code;
-}
-
-
-void CV_ConvertHomogeneousTest::get_test_array_types_and_sizes( int /*test_case_idx*/,
- CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- int pt_depth1 = cvTsRandInt(rng) % 2 == 0 ? CV_32F : CV_64F;
- int pt_depth2 = cvTsRandInt(rng) % 2 == 0 ? CV_32F : CV_64F;
- double pt_count_exp = cvTsRandReal(rng)*6 + 1;
- int t;
-
- pt_count = cvRound(exp(pt_count_exp));
- pt_count = MAX( pt_count, 5 );
-
- dims1 = 2 + (cvTsRandInt(rng) % 3);
- dims2 = 2 + (cvTsRandInt(rng) % 3);
-
- if( dims1 == dims2 + 2 )
- dims1--;
- else if( dims1 == dims2 - 2 )
- dims1++;
-
- if( cvTsRandInt(rng) % 2 )
- CV_SWAP( dims1, dims2, t );
-
- types[INPUT][0] = CV_MAKETYPE(pt_depth1, 1);
-
- if( cvTsRandInt(rng) % 2 )
- sizes[INPUT][0] = cvSize(pt_count, dims1);
- else
- {
- sizes[INPUT][0] = cvSize(dims1, pt_count);
- if( cvTsRandInt(rng) % 2 )
- {
- types[INPUT][0] = CV_MAKETYPE(pt_depth1, dims1);
- if( cvTsRandInt(rng) % 2 )
- sizes[INPUT][0] = cvSize(pt_count, 1);
- else
- sizes[INPUT][0] = cvSize(1, pt_count);
- }
- }
-
- types[OUTPUT][0] = CV_MAKETYPE(pt_depth2, 1);
-
- if( cvTsRandInt(rng) % 2 )
- sizes[OUTPUT][0] = cvSize(pt_count, dims2);
- else
- {
- sizes[OUTPUT][0] = cvSize(dims2, pt_count);
- if( cvTsRandInt(rng) % 2 )
- {
- types[OUTPUT][0] = CV_MAKETYPE(pt_depth2, dims2);
- if( cvTsRandInt(rng) % 2 )
- sizes[OUTPUT][0] = cvSize(pt_count, 1);
- else
- sizes[OUTPUT][0] = cvSize(1, pt_count);
- }
- }
-
- types[REF_OUTPUT][0] = types[OUTPUT][0];
- sizes[REF_OUTPUT][0] = sizes[OUTPUT][0];
-}
-
-
-double CV_ConvertHomogeneousTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- return 1e-5;
-}
-
-
-void CV_ConvertHomogeneousTest::fill_array( int /*test_case_idx*/, int /*i*/, int /*j*/, CvMat* arr )
-{
- CvMat* temp = cvCreateMat( 1, pt_count, CV_MAKETYPE(CV_64FC1,dims1) );
- CvRNG* rng = ts->get_rng();
- CvScalar low = cvScalarAll(0), high = cvScalarAll(10);
-
- if( dims1 > dims2 )
- low.val[dims1-1] = 1.;
-
- cvRandArr( rng, temp, CV_RAND_UNI, low, high );
- cvTsConvertHomogeneous( temp, arr );
- cvReleaseMat( &temp );
-}
-
-
-void CV_ConvertHomogeneousTest::run_func()
-{
- cvConvertPointsHomogeneous( &test_mat[INPUT][0], &test_mat[OUTPUT][0] );
-}
-
-
-void CV_ConvertHomogeneousTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- cvTsConvertHomogeneous( &test_mat[INPUT][0], &test_mat[REF_OUTPUT][0] );
-}
-
-
-CV_ConvertHomogeneousTest cvt_homogen_test;
-
-
-/************************** compute corresponding epipolar lines ************************/
-
-class CV_ComputeEpilinesTest : public CvArrTest
-{
-public:
- CV_ComputeEpilinesTest();
-
-protected:
- int read_params( CvFileStorage* fs );
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void fill_array( int test_case_idx, int i, int j, CvMat* arr );
- double get_success_error_level( int test_case_idx, int i, int j );
- void run_func();
- void prepare_to_validation( int );
-
- int which_image;
- int dims;
- int pt_count;
-};
-
-
-CV_ComputeEpilinesTest::CV_ComputeEpilinesTest()
- : CvArrTest( "_3d-epilines", "cvComputeCorrespondingEpilines", "" )
-{
- test_array[INPUT].push(NULL);
- test_array[INPUT].push(NULL);
- test_array[OUTPUT].push(NULL);
- test_array[REF_OUTPUT].push(NULL);
- element_wise_relative_error = false;
-
- pt_count = dims = which_image = 0;
-
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;
- default_timing_param_names = 0;
-}
-
-
-int CV_ComputeEpilinesTest::read_params( CvFileStorage* fs )
-{
- int code = CvArrTest::read_params( fs );
- return code;
-}
-
-
-void CV_ComputeEpilinesTest::get_test_array_types_and_sizes( int /*test_case_idx*/,
- CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- int fm_depth = cvTsRandInt(rng) % 2 == 0 ? CV_32F : CV_64F;
- int pt_depth = cvTsRandInt(rng) % 2 == 0 ? CV_32F : CV_64F;
- int ln_depth = cvTsRandInt(rng) % 2 == 0 ? CV_32F : CV_64F;
- double pt_count_exp = cvTsRandReal(rng)*6 + 1;
-
- which_image = 1 + (cvTsRandInt(rng) % 2);
-
- pt_count = cvRound(exp(pt_count_exp));
- pt_count = MAX( pt_count, 5 );
-
- dims = 2 + (cvTsRandInt(rng) % 2);
-
- types[INPUT][0] = CV_MAKETYPE(pt_depth, 1);
-
- if( cvTsRandInt(rng) % 2 )
- sizes[INPUT][0] = cvSize(pt_count, dims);
- else
- {
- sizes[INPUT][0] = cvSize(dims, pt_count);
- if( cvTsRandInt(rng) % 2 )
- {
- types[INPUT][0] = CV_MAKETYPE(pt_depth, dims);
- if( cvTsRandInt(rng) % 2 )
- sizes[INPUT][0] = cvSize(pt_count, 1);
- else
- sizes[INPUT][0] = cvSize(1, pt_count);
- }
- }
-
- types[INPUT][1] = CV_MAKETYPE(fm_depth, 1);
- sizes[INPUT][1] = cvSize(3, 3);
-
- types[OUTPUT][0] = CV_MAKETYPE(ln_depth, 1);
-
- if( cvTsRandInt(rng) % 2 )
- sizes[OUTPUT][0] = cvSize(pt_count, 3);
- else
- {
- sizes[OUTPUT][0] = cvSize(3, pt_count);
- if( cvTsRandInt(rng) % 2 )
- {
- types[OUTPUT][0] = CV_MAKETYPE(ln_depth, 3);
- if( cvTsRandInt(rng) % 2 )
- sizes[OUTPUT][0] = cvSize(pt_count, 1);
- else
- sizes[OUTPUT][0] = cvSize(1, pt_count);
- }
- }
-
- types[REF_OUTPUT][0] = types[OUTPUT][0];
- sizes[REF_OUTPUT][0] = sizes[OUTPUT][0];
-}
-
-
-double CV_ComputeEpilinesTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- return 1e-5;
-}
-
-
-void CV_ComputeEpilinesTest::fill_array( int test_case_idx, int i, int j, CvMat* arr )
-{
- CvRNG* rng = ts->get_rng();
-
- if( i == INPUT && j == 0 )
- {
- CvMat* temp = cvCreateMat( 1, pt_count, CV_MAKETYPE(CV_64FC1,dims) );
- cvRandArr( rng, temp, CV_RAND_UNI, cvScalar(0,0,1), cvScalarAll(10) );
- cvTsConvertHomogeneous( temp, arr );
- cvReleaseMat( &temp );
- }
- else if( i == INPUT && j == 1 )
- cvRandArr( rng, arr, CV_RAND_UNI, cvScalarAll(0), cvScalarAll(10) );
- else
- CvArrTest::fill_array( test_case_idx, i, j, arr );
-}
-
-
-void CV_ComputeEpilinesTest::run_func()
-{
- cvComputeCorrespondEpilines( &test_mat[INPUT][0], which_image,
- &test_mat[INPUT][1], &test_mat[OUTPUT][0] );
-}
-
-
-void CV_ComputeEpilinesTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- CvMat* pt = cvCreateMat( 1, pt_count, CV_MAKETYPE(CV_64F, 3) );
- CvMat* lines = cvCreateMat( 1, pt_count, CV_MAKETYPE(CV_64F, 3) );
- double f[9];
- CvMat F = cvMat( 3, 3, CV_64F, f );
- int i;
-
- cvTsConvertHomogeneous( &test_mat[INPUT][0], pt );
- cvTsConvert( &test_mat[INPUT][1], &F );
- if( which_image == 2 )
- cvTranspose( &F, &F );
-
- for( i = 0; i < pt_count; i++ )
- {
- double* p = pt->data.db + i*3;
- double* l = lines->data.db + i*3;
- double t0 = f[0]*p[0] + f[1]*p[1] + f[2]*p[2];
- double t1 = f[3]*p[0] + f[4]*p[1] + f[5]*p[2];
- double t2 = f[6]*p[0] + f[7]*p[1] + f[8]*p[2];
- double d = sqrt(t0*t0 + t1*t1);
- d = d ? 1./d : 1.;
- l[0] = t0*d; l[1] = t1*d; l[2] = t2*d;
- }
-
- cvTsConvertHomogeneous( lines, &test_mat[REF_OUTPUT][0] );
- cvReleaseMat( &pt );
- cvReleaseMat( &lines );
-}
-
-
-CV_ComputeEpilinesTest epilines_test;
-
-
-/* End of file. */
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-class CV_BaseHistTest : public CvTest
-{
-public:
- enum { MAX_HIST = 12 };
-
- CV_BaseHistTest( const char* test_name, const char* test_funcs );
- ~CV_BaseHistTest();
- void clear();
- int write_default_params(CvFileStorage* fs);
-
-protected:
- int read_params( CvFileStorage* fs );
- void run_func(void);
- int prepare_test_case( int test_case_idx );
- int validate_test_results( int test_case_idx );
- virtual void init_hist( int test_case_idx, int i );
-
- virtual void get_hist_params( int test_case_idx );
- virtual float** get_hist_ranges( int test_case_idx );
-
- int max_log_size;
- int max_cdims;
- int cdims;
- int dims[CV_MAX_DIM];
- int dims_sum[CV_MAX_DIM+1];
- int total_size;
- int hist_type;
- int hist_count;
- int uniform;
- int gen_random_hist;
- double gen_hist_max_val, gen_hist_sparse_nz_ratio;
-
- int init_ranges;
- int img_type;
- int img_max_log_size;
- double low, high, range_delta;
- CvSize img_size;
-
- CvHistogram* hist[MAX_HIST];
- float* _ranges;
- float* ranges[CV_MAX_DIM];
- bool test_cpp;
-};
-
-
-CV_BaseHistTest::CV_BaseHistTest( const char* test_name, const char* test_funcs ):
- CvTest( test_name, test_funcs )
-{
- int i;
-
- test_case_count = 100;
- max_log_size = 20;
- img_max_log_size = 8;
- max_cdims = 6;
- _ranges = 0;
- hist_count = 1;
- init_ranges = 0;
- gen_random_hist = 0;
- gen_hist_max_val = 100;
-
- for( i = 0; i < MAX_HIST; i++ )
- hist[i] = 0;
-
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;
- test_cpp = false;
-}
-
-
-CV_BaseHistTest::~CV_BaseHistTest()
-{
- clear();
-}
-
-
-void CV_BaseHistTest::clear()
-{
- int i;
- CvTest::clear();
- for( i = 0; i < MAX_HIST; i++ )
- cvReleaseHist( &hist[i] );
- delete[] _ranges;
- _ranges = 0;
-}
-
-
-int CV_BaseHistTest::write_default_params( CvFileStorage* fs )
-{
- CvTest::write_default_params( fs );
- if( ts->get_testing_mode() != CvTS::TIMING_MODE )
- {
- write_param( fs, "test_case_count", test_case_count );
- write_param( fs, "max_log_size", max_log_size );
- write_param( fs, "max_log_array_size", img_max_log_size );
- write_param( fs, "max_dims", max_cdims );
- }
- return 0;
-}
-
-
-int CV_BaseHistTest::read_params( CvFileStorage* fs )
-{
- int code = CvTest::read_params( fs );
- if( code < 0 )
- return code;
-
- test_case_count = cvReadInt( find_param( fs, "struct_count" ), test_case_count );
- max_log_size = cvReadInt( find_param( fs, "max_log_size" ), max_log_size );
- max_log_size = cvTsClipInt( max_log_size, 1, 20 );
- img_max_log_size = cvReadInt( find_param( fs, "max_log_array_size" ), img_max_log_size );
- img_max_log_size = cvTsClipInt( img_max_log_size, 1, 9 );
-
- max_cdims = cvReadInt( find_param( fs, "max_cdims" ), max_cdims );
- max_cdims = cvTsClipInt( max_cdims, 1, 6 );
-
- return 0;
-}
-
-
-void CV_BaseHistTest::get_hist_params( int /*test_case_idx*/ )
-{
- CvRNG* rng = ts->get_rng();
- int i, max_dim_size, max_ni_dim_size = 31;
- double hist_size;
-
- cdims = cvTsRandInt(rng) % max_cdims + 1;
- hist_size = exp(cvTsRandReal(rng)*max_log_size*CV_LOG2);
- max_dim_size = cvRound(pow(hist_size,1./cdims));
- total_size = 1;
- uniform = cvTsRandInt(rng) % 2;
- hist_type = cvTsRandInt(rng) % 2 ? CV_HIST_SPARSE : CV_HIST_ARRAY;
-
- for( i = 0; i < cdims; i++ )
- {
- dims[i] = cvTsRandInt(rng) % (max_dim_size + 2) + 2;
- if( !uniform )
- dims[i] = MIN(dims[i], max_ni_dim_size);
- total_size *= dims[i];
- }
-
- img_type = cvTsRandInt(rng) % 2 ? CV_32F : CV_8U;
- img_size.width = cvRound( exp(cvRandReal(rng) * img_max_log_size*CV_LOG2) );
- img_size.height = cvRound( exp(cvRandReal(rng) * img_max_log_size*CV_LOG2) );
-
- low = cvTsMinVal(img_type);
- high = cvTsMaxVal(img_type);
-
- range_delta = (cvTsRandInt(rng) % 2)*(high-low)*0.05;
-}
-
-
-float** CV_BaseHistTest::get_hist_ranges( int /*test_case_idx*/ )
-{
- double _low = low + range_delta, _high = high - range_delta;
-
- if( init_ranges )
- {
- int i;
- dims_sum[0] = 0;
- for( i = 0; i < cdims; i++ )
- dims_sum[i+1] = dims_sum[i] + dims[i] + 1;
-
- if( uniform )
- {
- _ranges = new float[cdims*2];
- for( i = cdims-1; i >= 0; i-- )
- {
- _ranges[i*2] = (float)_low;
- _ranges[i*2+1] = (float)_high;
- ranges[i] = _ranges + i*2;
- }
- }
- else
- {
- _ranges = new float[dims_sum[cdims]];
-
- for( i = 0; i < cdims; i++ )
- {
- int j, n = dims[i], ofs = dims_sum[i];
- // generate logarithmic scale
- double delta, q, val;
- for( j = 0; j < 10; j++ )
- {
- q = 1. + (j+1)*0.1;
- if( (pow(q,(double)n)-1)/(q-1.) >= _high-_low )
- break;
- }
-
- if( j == 0 )
- {
- delta = (_high-_low)/n;
- q = 1.;
- }
- else
- {
- q = 1 + j*0.1;
- delta = cvFloor((_high-_low)*(q-1)/(pow(q,(double)n) - 1));
- delta = MAX(delta, 1.);
- }
- val = _low;
-
- for( j = 0; j <= n; j++ )
- {
- _ranges[j+ofs] = (float)MIN(val,_high);
- val += delta;
- delta *= q;
- }
- ranges[i] = _ranges + ofs;
- }
- }
- return ranges;
- }
-
- return 0;
-}
-
-
-void CV_BaseHistTest::init_hist( int /*test_case_idx*/, int hist_i )
-{
- if( gen_random_hist )
- {
- CvRNG* rng = ts->get_rng();
- CvArr* h = hist[hist_i]->bins;
-
- if( hist_type == CV_HIST_ARRAY )
- {
- cvRandArr( rng, h, CV_RAND_UNI,
- cvScalarAll(0), cvScalarAll(gen_hist_max_val) );
- }
- else
- {
- int i, j, total_size = 1, nz_count;
- int idx[CV_MAX_DIM];
- for( i = 0; i < cdims; i++ )
- total_size *= dims[i];
-
- nz_count = cvTsRandInt(rng) % MAX( total_size/4, 100 );
- nz_count = MIN( nz_count, total_size );
-
- // a zero number of non-zero elements should be allowed
- for( i = 0; i < nz_count; i++ )
- {
- for( j = 0; j < cdims; j++ )
- idx[j] = cvTsRandInt(rng) % dims[j];
- cvSetRealND( h, idx, cvTsRandReal(rng)*gen_hist_max_val );
- }
- }
- }
-}
-
-
-int CV_BaseHistTest::prepare_test_case( int test_case_idx )
-{
- int i;
- float** r;
-
- clear();
-
- CvTest::prepare_test_case( test_case_idx );
- get_hist_params( test_case_idx );
- r = get_hist_ranges( test_case_idx );
-
- for( i = 0; i < hist_count; i++ )
- {
- hist[i] = cvCreateHist( cdims, dims, hist_type, r, uniform );
- init_hist( test_case_idx, i );
- }
- test_cpp = (cvTsRandInt(ts->get_rng()) % 2) != 0;
-
- return 1;
-}
-
-
-void CV_BaseHistTest::run_func(void)
-{
-}
-
-
-int CV_BaseHistTest::validate_test_results( int /*test_case_idx*/ )
-{
- return 0;
-}
-
-
-CV_BaseHistTest hist_basetest( "hist", "" );
-
-
-
-////////////// testing operation for reading/writing individual histogram bins //////////////
-
-class CV_QueryHistTest : public CV_BaseHistTest
-{
-public:
- CV_QueryHistTest();
- ~CV_QueryHistTest();
- void clear();
-
-protected:
- void run_func(void);
- int prepare_test_case( int test_case_idx );
- int validate_test_results( int test_case_idx );
- void init_hist( int test_case_idx, int i );
-
- CvMat* indices;
- CvMat* values;
- CvMat* values0;
-};
-
-
-
-CV_QueryHistTest::CV_QueryHistTest() : CV_BaseHistTest( "hist-query",
- "cvGetReal1D, cvGetReal2D, cvGetReal3D, cvGetRealND, "
- "cvPtr1D, cvPtr2D, cvPtr3D, cvPtrND, "
- "cvSetReal1D, cvSetReal2D, cvSetReal3D, cvSetRealND" )
-{
- hist_count = 1;
- indices = 0;
- values = 0;
- values0 = 0;
-}
-
-
-CV_QueryHistTest::~CV_QueryHistTest()
-{
- clear();
-}
-
-
-void CV_QueryHistTest::clear()
-{
- cvReleaseMat( &indices );
- cvReleaseMat( &values );
- cvReleaseMat( &values0 );
- CV_BaseHistTest::clear();
-}
-
-
-void CV_QueryHistTest::init_hist( int /*test_case_idx*/, int i )
-{
- if( hist_type == CV_HIST_ARRAY )
- cvZero( hist[i]->bins );
-}
-
-
-int CV_QueryHistTest::prepare_test_case( int test_case_idx )
-{
- int code = CV_BaseHistTest::prepare_test_case( test_case_idx );
-
- if( code > 0 )
- {
- int i, j, iters;
- float default_value = 0.f;
- CvRNG* rng = ts->get_rng();
- CvMat* bit_mask = 0;
- int* idx;
-
- iters = (cvTsRandInt(rng) % MAX(total_size/10,100)) + 1;
- iters = MIN( iters, total_size*9/10 + 1 );
-
- indices = cvCreateMat( 1, iters*cdims, CV_32S );
- values = cvCreateMat( 1, iters, CV_32F );
- values0 = cvCreateMat( 1, iters, CV_32F );
- idx = indices->data.i;
-
- //printf( "total_size = %d, cdims = %d, iters = %d\n", total_size, cdims, iters );
-
- bit_mask = cvCreateMat( 1, (total_size + 7)/8, CV_8U );
- cvZero( bit_mask );
-
- #define GET_BIT(n) (bit_mask->data.ptr[(n)/8] & (1 << ((n)&7)))
- #define SET_BIT(n) bit_mask->data.ptr[(n)/8] |= (1 << ((n)&7))
-
- // set random histogram bins' values to the linear indices of the bins
- for( i = 0; i < iters; i++ )
- {
- int lin_idx = 0;
- for( j = 0; j < cdims; j++ )
- {
- int t = cvTsRandInt(rng) % dims[j];
- idx[i*cdims + j] = t;
- lin_idx = lin_idx*dims[j] + t;
- }
-
- if( cvTsRandInt(rng) % 8 || GET_BIT(lin_idx) )
- {
- values0->data.fl[i] = (float)(lin_idx+1);
- SET_BIT(lin_idx);
- }
- else
- // some histogram bins will not be initialized intentionally,
- // they should be equal to the default value
- values0->data.fl[i] = default_value;
- }
-
- // do the second pass to make values0 consistent with bit_mask
- for( i = 0; i < iters; i++ )
- {
- int lin_idx = 0;
- for( j = 0; j < cdims; j++ )
- lin_idx = lin_idx*dims[j] + idx[i*cdims + j];
-
- if( GET_BIT(lin_idx) )
- values0->data.fl[i] = (float)(lin_idx+1);
- }
-
- cvReleaseMat( &bit_mask );
- }
-
- return code;
-}
-
-
-void CV_QueryHistTest::run_func(void)
-{
- int i, iters = values->cols;
- CvArr* h = hist[0]->bins;
- const int* idx = indices->data.i;
- float* val = values->data.fl;
- float default_value = 0.f;
-
- // stage 1: write bins
- if( cdims == 1 )
- for( i = 0; i < iters; i++ )
- {
- float v0 = values0->data.fl[i];
- if( fabs(v0 - default_value) < FLT_EPSILON )
- continue;
- if( !(i % 2) )
- {
- if( !(i % 4) )
- cvSetReal1D( h, idx[i], v0 );
- else
- *(float*)cvPtr1D( h, idx[i] ) = v0;
- }
- else
- cvSetRealND( h, idx+i, v0 );
- }
- else if( cdims == 2 )
- for( i = 0; i < iters; i++ )
- {
- float v0 = values0->data.fl[i];
- if( fabs(v0 - default_value) < FLT_EPSILON )
- continue;
- if( !(i % 2) )
- {
- if( !(i % 4) )
- cvSetReal2D( h, idx[i*2], idx[i*2+1], v0 );
- else
- *(float*)cvPtr2D( h, idx[i*2], idx[i*2+1] ) = v0;
- }
- else
- cvSetRealND( h, idx+i*2, v0 );
- }
- else if( cdims == 3 )
- for( i = 0; i < iters; i++ )
- {
- float v0 = values0->data.fl[i];
- if( fabs(v0 - default_value) < FLT_EPSILON )
- continue;
- if( !(i % 2) )
- {
- if( !(i % 4) )
- cvSetReal3D( h, idx[i*3], idx[i*3+1], idx[i*3+2], v0 );
- else
- *(float*)cvPtr3D( h, idx[i*3], idx[i*3+1], idx[i*3+2] ) = v0;
- }
- else
- cvSetRealND( h, idx+i*3, v0 );
- }
- else
- for( i = 0; i < iters; i++ )
- {
- float v0 = values0->data.fl[i];
- if( fabs(v0 - default_value) < FLT_EPSILON )
- continue;
- if( !(i % 2) )
- cvSetRealND( h, idx+i*cdims, v0 );
- else
- *(float*)cvPtrND( h, idx+i*cdims ) = v0;
- }
-
- // stage 2: read bins
- if( cdims == 1 )
- for( i = 0; i < iters; i++ )
- {
- if( !(i % 2) )
- val[i] = *(float*)cvPtr1D( h, idx[i] );
- else
- val[i] = (float)cvGetReal1D( h, idx[i] );
- }
- else if( cdims == 2 )
- for( i = 0; i < iters; i++ )
- {
- if( !(i % 2) )
- val[i] = *(float*)cvPtr2D( h, idx[i*2], idx[i*2+1] );
- else
- val[i] = (float)cvGetReal2D( h, idx[i*2], idx[i*2+1] );
- }
- else if( cdims == 3 )
- for( i = 0; i < iters; i++ )
- {
- if( !(i % 2) )
- val[i] = *(float*)cvPtr3D( h, idx[i*3], idx[i*3+1], idx[i*3+2] );
- else
- val[i] = (float)cvGetReal3D( h, idx[i*3], idx[i*3+1], idx[i*3+2] );
- }
- else
- for( i = 0; i < iters; i++ )
- {
- if( !(i % 2) )
- val[i] = *(float*)cvPtrND( h, idx+i*cdims );
- else
- val[i] = (float)cvGetRealND( h, idx+i*cdims );
- }
-}
-
-
-int CV_QueryHistTest::validate_test_results( int /*test_case_idx*/ )
-{
- int code = CvTS::OK;
- int i, j, iters = values->cols;
-
- for( i = 0; i < iters; i++ )
- {
- float v = values->data.fl[i], v0 = values0->data.fl[i];
-
- if( cvIsNaN(v) || cvIsInf(v) )
- {
- ts->printf( CvTS::LOG, "The bin #%d has invalid value\n", i );
- code = CvTS::FAIL_INVALID_OUTPUT;
- }
- else if( fabs(v - v0) > FLT_EPSILON )
- {
- ts->printf( CvTS::LOG, "The bin #%d = %g, while it should be %g\n", i, v, v0 );
- code = CvTS::FAIL_BAD_ACCURACY;
- }
-
- if( code < 0 )
- {
- ts->printf( CvTS::LOG, "The bin index = (" );
- for( j = 0; j < cdims; j++ )
- ts->printf( CvTS::LOG, "%d%s", indices->data.i[i*cdims + j],
- j < cdims-1 ? ", " : ")\n" );
- break;
- }
- }
-
- if( code < 0 )
- ts->set_failed_test_info( code );
- return code;
-}
-
-
-CV_QueryHistTest hist_query_test;
-
-
-////////////// cvGetMinMaxHistValue //////////////
-
-class CV_MinMaxHistTest : public CV_BaseHistTest
-{
-public:
- CV_MinMaxHistTest();
-
-protected:
- void run_func(void);
- void init_hist(int, int);
- int validate_test_results( int test_case_idx );
- int min_idx[CV_MAX_DIM], max_idx[CV_MAX_DIM];
- float min_val, max_val;
- int min_idx0[CV_MAX_DIM], max_idx0[CV_MAX_DIM];
- float min_val0, max_val0;
-};
-
-
-
-CV_MinMaxHistTest::CV_MinMaxHistTest() :
- CV_BaseHistTest( "hist-minmax", "cvGetMinMaxHistValue" )
-{
- hist_count = 1;
- gen_random_hist = 1;
-}
-
-
-void CV_MinMaxHistTest::init_hist(int test_case_idx, int hist_i)
-{
- int i, eq = 1;
- CvRNG* rng = ts->get_rng();
- CV_BaseHistTest::init_hist( test_case_idx, hist_i );
-
- for(;;)
- {
- for( i = 0; i < cdims; i++ )
- {
- min_idx0[i] = cvTsRandInt(rng) % dims[i];
- max_idx0[i] = cvTsRandInt(rng) % dims[i];
- eq &= min_idx0[i] == max_idx0[i];
- }
- if( !eq || total_size == 1 )
- break;
- }
-
- min_val0 = (float)(-cvTsRandReal(rng)*10 - FLT_EPSILON);
- max_val0 = (float)(cvTsRandReal(rng)*10 + FLT_EPSILON + gen_hist_max_val);
-
- if( total_size == 1 )
- min_val0 = max_val0;
-
- cvSetRealND( hist[0]->bins, min_idx0, min_val0 );
- cvSetRealND( hist[0]->bins, max_idx0, max_val0 );
-}
-
-
-void CV_MinMaxHistTest::run_func(void)
-{
- if( hist_type != CV_HIST_ARRAY && test_cpp )
- {
- cv::SparseMat h((CvSparseMat*)hist[0]->bins);
- double _min_val = 0, _max_val = 0;
- cv::minMaxLoc(h, &_min_val, &_max_val, min_idx, max_idx );
- min_val = (float)_min_val;
- max_val = (float)_max_val;
- }
- else
- cvGetMinMaxHistValue( hist[0], &min_val, &max_val, min_idx, max_idx );
-}
-
-
-int CV_MinMaxHistTest::validate_test_results( int /*test_case_idx*/ )
-{
- int code = CvTS::OK;
-
- if( cvIsNaN(min_val) || cvIsInf(min_val) ||
- cvIsNaN(max_val) || cvIsInf(max_val) )
- {
- ts->printf( CvTS::LOG,
- "The extrema histogram bin values are invalid (min = %g, max = %g)\n", min_val, max_val );
- code = CvTS::FAIL_INVALID_OUTPUT;
- }
- else if( fabs(min_val - min_val0) > FLT_EPSILON ||
- fabs(max_val - max_val0) > FLT_EPSILON )
- {
- ts->printf( CvTS::LOG,
- "The extrema histogram bin values are incorrect: (min = %g, should be = %g), (max = %g, should be = %g)\n",
- min_val, min_val0, max_val, max_val0 );
- code = CvTS::FAIL_BAD_ACCURACY;
- }
- else
- {
- int i;
- for( i = 0; i < cdims; i++ )
- {
- if( min_idx[i] != min_idx0[i] || max_idx[i] != max_idx0[i] )
- {
- ts->printf( CvTS::LOG,
- "The %d-th coordinates of extrema histogram bin values are incorrect: "
- "(min = %d, should be = %d), (max = %d, should be = %d)\n",
- i, min_idx[i], min_idx0[i], max_idx[i], max_idx0[i] );
- code = CvTS::FAIL_BAD_ACCURACY;
- }
- }
- }
-
- if( code < 0 )
- ts->set_failed_test_info( code );
- return code;
-}
-
-
-CV_MinMaxHistTest hist_minmax_test;
-
-
-
-////////////// cvNormalizeHist //////////////
-
-class CV_NormHistTest : public CV_BaseHistTest
-{
-public:
- CV_NormHistTest();
-
-protected:
- int prepare_test_case( int test_case_idx );
- void run_func(void);
- int validate_test_results( int test_case_idx );
- double factor;
-};
-
-
-
-CV_NormHistTest::CV_NormHistTest() :
- CV_BaseHistTest( "hist-normalize", "cvNormalizeHist" )
-{
- hist_count = 1;
- gen_random_hist = 1;
- factor = 0;
-}
-
-
-int CV_NormHistTest::prepare_test_case( int test_case_idx )
-{
- int code = CV_BaseHistTest::prepare_test_case( test_case_idx );
-
- if( code > 0 )
- {
- CvRNG* rng = ts->get_rng();
- factor = cvTsRandReal(rng)*10 + 0.1;
- if( hist_type == CV_HIST_SPARSE &&
- ((CvSparseMat*)hist[0]->bins)->heap->active_count == 0 )
- factor = 0;
- }
-
- return code;
-}
-
-
-void CV_NormHistTest::run_func(void)
-{
- if( hist_type != CV_HIST_ARRAY && test_cpp )
- {
- cv::SparseMat h((CvSparseMat*)hist[0]->bins);
- cv::normalize(h, h, factor, CV_L1);
- cvReleaseSparseMat((CvSparseMat**)&hist[0]->bins);
- hist[0]->bins = (CvSparseMat*)h;
- }
- else
- cvNormalizeHist( hist[0], factor );
-}
-
-
-int CV_NormHistTest::validate_test_results( int /*test_case_idx*/ )
-{
- int code = CvTS::OK;
- double sum = 0;
-
- if( hist_type == CV_HIST_ARRAY )
- {
- int i;
- const float* ptr = (float*)cvPtr1D( hist[0]->bins, 0 );
-
- for( i = 0; i < total_size; i++ )
- sum += ptr[i];
- }
- else
- {
- CvSparseMat* sparse = (CvSparseMat*)hist[0]->bins;
- CvSparseMatIterator iterator;
- CvSparseNode *node;
-
- for( node = cvInitSparseMatIterator( sparse, &iterator );
- node != 0; node = cvGetNextSparseNode( &iterator ))
- {
- sum += *(float*)CV_NODE_VAL(sparse,node);
- }
- }
-
- if( cvIsNaN(sum) || cvIsInf(sum) )
- {
- ts->printf( CvTS::LOG,
- "The normalized histogram has invalid sum =%g\n", sum );
- code = CvTS::FAIL_INVALID_OUTPUT;
- }
- else if( fabs(sum - factor) > FLT_EPSILON*10*fabs(factor) )
- {
- ts->printf( CvTS::LOG,
- "The normalized histogram has incorrect sum =%g, while it should be =%g\n", sum, factor );
- code = CvTS::FAIL_BAD_ACCURACY;
- }
-
- if( code < 0 )
- ts->set_failed_test_info( code );
- return code;
-}
-
-
-CV_NormHistTest hist_norm_test;
-
-
-
-////////////// cvThreshHist //////////////
-
-class CV_ThreshHistTest : public CV_BaseHistTest
-{
-public:
- CV_ThreshHistTest();
- ~CV_ThreshHistTest();
- void clear();
-
-protected:
- int prepare_test_case( int test_case_idx );
- void run_func(void);
- int validate_test_results( int test_case_idx );
- CvMat* indices;
- CvMat* values;
- int orig_nz_count;
-
- double threshold;
-};
-
-
-
-CV_ThreshHistTest::CV_ThreshHistTest() :
- CV_BaseHistTest( "hist-threshold", "cvThreshHist" )
-{
- hist_count = 1;
- gen_random_hist = 1;
- threshold = 0;
- indices = values = 0;
-}
-
-
-CV_ThreshHistTest::~CV_ThreshHistTest()
-{
- clear();
-}
-
-
-void CV_ThreshHistTest::clear()
-{
- cvReleaseMat( &indices );
- cvReleaseMat( &values );
- CV_BaseHistTest::clear();
-}
-
-
-int CV_ThreshHistTest::prepare_test_case( int test_case_idx )
-{
- int code = CV_BaseHistTest::prepare_test_case( test_case_idx );
-
- if( code > 0 )
- {
- CvRNG* rng = ts->get_rng();
- threshold = cvTsRandReal(rng)*gen_hist_max_val;
-
- if( hist_type == CV_HIST_ARRAY )
- {
- orig_nz_count = total_size;
-
- values = cvCreateMat( 1, total_size, CV_32F );
- memcpy( values->data.fl, cvPtr1D( hist[0]->bins, 0 ), total_size*sizeof(float) );
- }
- else
- {
- CvSparseMat* sparse = (CvSparseMat*)hist[0]->bins;
- CvSparseMatIterator iterator;
- CvSparseNode* node;
- int i, k;
-
- orig_nz_count = sparse->heap->active_count;
-
- values = cvCreateMat( 1, orig_nz_count+1, CV_32F );
- indices = cvCreateMat( 1, (orig_nz_count+1)*cdims, CV_32S );
-
- for( node = cvInitSparseMatIterator( sparse, &iterator ), i = 0;
- node != 0; node = cvGetNextSparseNode( &iterator ), i++ )
- {
- const int* idx = CV_NODE_IDX(sparse,node);
-
- OPENCV_ASSERT( i < orig_nz_count, "CV_ThreshHistTest::prepare_test_case", "Buffer overflow" );
-
- values->data.fl[i] = *(float*)CV_NODE_VAL(sparse,node);
- for( k = 0; k < cdims; k++ )
- indices->data.i[i*cdims + k] = idx[k];
- }
-
- OPENCV_ASSERT( i == orig_nz_count, "Unmatched buffer size",
- "CV_ThreshHistTest::prepare_test_case" );
- }
- }
-
- return code;
-}
-
-
-void CV_ThreshHistTest::run_func(void)
-{
- cvThreshHist( hist[0], threshold );
-}
-
-
-int CV_ThreshHistTest::validate_test_results( int /*test_case_idx*/ )
-{
- int code = CvTS::OK;
- int i;
- float* ptr0 = values->data.fl;
- float* ptr = 0;
- CvSparseMat* sparse = 0;
-
- if( hist_type == CV_HIST_ARRAY )
- ptr = (float*)cvPtr1D( hist[0]->bins, 0 );
- else
- sparse = (CvSparseMat*)hist[0]->bins;
-
- if( code > 0 )
- {
- for( i = 0; i < orig_nz_count; i++ )
- {
- float v0 = ptr0[i], v;
-
- if( hist_type == CV_HIST_ARRAY )
- v = ptr[i];
- else
- {
- v = (float)cvGetRealND( sparse, indices->data.i + i*cdims );
- cvClearND( sparse, indices->data.i + i*cdims );
- }
-
- if( v0 <= threshold ) v0 = 0.f;
- if( cvIsNaN(v) || cvIsInf(v) )
- {
- ts->printf( CvTS::LOG, "The %d-th bin is invalid (=%g)\n", i, v );
- code = CvTS::FAIL_INVALID_OUTPUT;
- break;
- }
- else if( fabs(v0 - v) > FLT_EPSILON*10*fabs(v0) )
- {
- ts->printf( CvTS::LOG, "The %d-th bin is incorrect (=%g, should be =%g)\n", i, v, v0 );
- code = CvTS::FAIL_BAD_ACCURACY;
- break;
- }
- }
- }
-
- if( code > 0 && hist_type == CV_HIST_SPARSE )
- {
- if( sparse->heap->active_count > 0 )
- {
- ts->printf( CvTS::LOG,
- "There some extra histogram bins in the sparse histogram after the thresholding\n" );
- code = CvTS::FAIL_INVALID_OUTPUT;
- }
- }
-
- if( code < 0 )
- ts->set_failed_test_info( code );
- return code;
-}
-
-
-CV_ThreshHistTest hist_thresh_test;
-
-
-////////////// cvCompareHist //////////////
-
-class CV_CompareHistTest : public CV_BaseHistTest
-{
-public:
- enum { MAX_METHOD = 4 };
-
- CV_CompareHistTest();
-protected:
- int prepare_test_case( int test_case_idx );
- void run_func(void);
- int validate_test_results( int test_case_idx );
- double result[MAX_METHOD+1];
-};
-
-
-
-CV_CompareHistTest::CV_CompareHistTest() :
- CV_BaseHistTest( "hist-compare", "cvCompareHist" )
-{
- hist_count = 2;
- gen_random_hist = 1;
-}
-
-
-int CV_CompareHistTest::prepare_test_case( int test_case_idx )
-{
- int code = CV_BaseHistTest::prepare_test_case( test_case_idx );
-
- return code;
-}
-
-
-void CV_CompareHistTest::run_func(void)
-{
- int k;
- if( hist_type != CV_HIST_ARRAY && test_cpp )
- {
- cv::SparseMat h0((CvSparseMat*)hist[0]->bins);
- cv::SparseMat h1((CvSparseMat*)hist[1]->bins);
- for( k = 0; k < MAX_METHOD; k++ )
- result[k] = cv::compareHist(h0, h1, k);
- }
- else
- for( k = 0; k < MAX_METHOD; k++ )
- result[k] = cvCompareHist( hist[0], hist[1], k );
-}
-
-
-int CV_CompareHistTest::validate_test_results( int /*test_case_idx*/ )
-{
- int code = CvTS::OK;
- int i;
- double result0[MAX_METHOD+1];
- double s0 = 0, s1 = 0, sq0 = 0, sq1 = 0, t;
-
- for( i = 0; i < MAX_METHOD; i++ )
- result0[i] = 0;
-
- if( hist_type == CV_HIST_ARRAY )
- {
- float* ptr0 = (float*)cvPtr1D( hist[0]->bins, 0 );
- float* ptr1 = (float*)cvPtr1D( hist[1]->bins, 0 );
-
- for( i = 0; i < total_size; i++ )
- {
- double v0 = ptr0[i], v1 = ptr1[i];
- result0[CV_COMP_CORREL] += v0*v1;
- result0[CV_COMP_INTERSECT] += MIN(v0,v1);
- if( fabs(v0 + v1) > DBL_EPSILON )
- result0[CV_COMP_CHISQR] += (v0 - v1)*(v0 - v1)/(v0 + v1);
- s0 += v0;
- s1 += v1;
- sq0 += v0*v0;
- sq1 += v1*v1;
- result0[CV_COMP_BHATTACHARYYA] += sqrt(v0*v1);
- }
- }
- else
- {
- CvSparseMat* sparse0 = (CvSparseMat*)hist[0]->bins;
- CvSparseMat* sparse1 = (CvSparseMat*)hist[1]->bins;
- CvSparseMatIterator iterator;
- CvSparseNode* node;
-
- for( node = cvInitSparseMatIterator( sparse0, &iterator );
- node != 0; node = cvGetNextSparseNode( &iterator ) )
- {
- const int* idx = CV_NODE_IDX(sparse0, node);
- double v0 = *(float*)CV_NODE_VAL(sparse0, node);
- double v1 = (float)cvGetRealND(sparse1, idx);
-
- result0[CV_COMP_CORREL] += v0*v1;
- result0[CV_COMP_INTERSECT] += MIN(v0,v1);
- if( fabs(v0 + v1) > DBL_EPSILON )
- result0[CV_COMP_CHISQR] += (v0 - v1)*(v0 - v1)/(v0 + v1);
- s0 += v0;
- sq0 += v0*v0;
- result0[CV_COMP_BHATTACHARYYA] += sqrt(v0*v1);
- }
-
- for( node = cvInitSparseMatIterator( sparse1, &iterator );
- node != 0; node = cvGetNextSparseNode( &iterator ) )
- {
- const int* idx = CV_NODE_IDX(sparse1, node);
- double v1 = *(float*)CV_NODE_VAL(sparse1, node);
- double v0 = (float)cvGetRealND(sparse0, idx);
-
- if( fabs(v0) < DBL_EPSILON )
- result0[CV_COMP_CHISQR] += v1;
- s1 += v1;
- sq1 += v1*v1;
- }
- }
-
- t = (sq0 - s0*s0/total_size)*(sq1 - s1*s1/total_size);
- result0[CV_COMP_CORREL] = fabs(t) > DBL_EPSILON ?
- (result0[CV_COMP_CORREL] - s0*s1/total_size)/sqrt(t) : 1;
-
- s1 *= s0;
- s0 = result0[CV_COMP_BHATTACHARYYA];
- s0 = 1. - s0*(s1 > FLT_EPSILON ? 1./sqrt(s1) : 1.);
- result0[CV_COMP_BHATTACHARYYA] = sqrt(MAX(s0,0.));
-
- for( i = 0; i < MAX_METHOD; i++ )
- {
- double v = result[i], v0 = result0[i];
- const char* method_name =
- i == CV_COMP_CHISQR ? "Chi-Square" :
- i == CV_COMP_CORREL ? "Correlation" :
- i == CV_COMP_INTERSECT ? "Intersection" :
- i == CV_COMP_BHATTACHARYYA ? "Bhattacharyya" : "Unknown";
-
- if( cvIsNaN(v) || cvIsInf(v) )
- {
- ts->printf( CvTS::LOG, "The comparison result using the method #%d (%s) is invalid (=%g)\n",
- i, method_name, v );
- code = CvTS::FAIL_INVALID_OUTPUT;
- break;
- }
- else if( fabs(v0 - v) > FLT_EPSILON*10*MAX(fabs(v0),0.1) )
- {
- ts->printf( CvTS::LOG, "The comparison result using the method #%d (%s)\n\tis inaccurate (=%g, should be =%g)\n",
- i, method_name, v, v0 );
- code = CvTS::FAIL_BAD_ACCURACY;
- break;
- }
- }
-
- if( code < 0 )
- ts->set_failed_test_info( code );
- return code;
-}
-
-
-CV_CompareHistTest hist_compare_test;
-
-
-
-////////////// cvCalcHist //////////////
-
-class CV_CalcHistTest : public CV_BaseHistTest
-{
-public:
- CV_CalcHistTest();
- ~CV_CalcHistTest();
- void clear();
-
-protected:
- int prepare_test_case( int test_case_idx );
- void run_func(void);
- int validate_test_results( int test_case_idx );
- IplImage* images[CV_MAX_DIM+1];
- int channels[CV_MAX_DIM+1];
-};
-
-
-
-CV_CalcHistTest::CV_CalcHistTest() :
- CV_BaseHistTest( "hist-calc", "cvCalcHist" )
-{
- int i;
-
- hist_count = 2;
- gen_random_hist = 0;
- init_ranges = 1;
-
- for( i = 0; i <= CV_MAX_DIM; i++ )
- {
- images[i] = 0;
- channels[i] = 0;
- }
-}
-
-
-CV_CalcHistTest::~CV_CalcHistTest()
-{
- clear();
-}
-
-
-void CV_CalcHistTest::clear()
-{
- int i;
-
- for( i = 0; i <= CV_MAX_DIM; i++ )
- cvReleaseImage( &images[i] );
-
- CV_BaseHistTest::clear();
-}
-
-
-int CV_CalcHistTest::prepare_test_case( int test_case_idx )
-{
- int code = CV_BaseHistTest::prepare_test_case( test_case_idx );
-
- if( code > 0 )
- {
- CvRNG* rng = ts->get_rng();
- int i;
-
- for( i = 0; i <= CV_MAX_DIM; i++ )
- {
- if( i < cdims )
- {
- int nch = 1; //cvTsRandInt(rng) % 3 + 1;
- images[i] = cvCreateImage( img_size,
- img_type == CV_8U ? IPL_DEPTH_8U : IPL_DEPTH_32F, nch );
- channels[i] = cvTsRandInt(rng) % nch;
-
- cvRandArr( rng, images[i], CV_RAND_UNI,
- cvScalarAll(low), cvScalarAll(high) );
- }
- else if( i == CV_MAX_DIM && cvTsRandInt(rng) % 2 )
- {
- // create mask
- images[i] = cvCreateImage( img_size, IPL_DEPTH_8U, 1 );
- // make ~25% pixels in the mask non-zero
- cvRandArr( rng, images[i], CV_RAND_UNI,
- cvScalarAll(-2), cvScalarAll(2) );
- }
- }
- }
-
- return code;
-}
-
-
-void CV_CalcHistTest::run_func(void)
-{
- cvCalcHist( images, hist[0], 0, images[CV_MAX_DIM] );
-}
-
-
-static void
-cvTsCalcHist( IplImage** _images, CvHistogram* hist, IplImage* _mask, int* channels )
-{
- int x, y, k, cdims;
- union
- {
- float* fl;
- uchar* ptr;
- }
- plane[CV_MAX_DIM];
- int nch[CV_MAX_DIM];
- int dims[CV_MAX_DIM];
- int uniform = CV_IS_UNIFORM_HIST(hist);
- CvSize img_size = cvGetSize(_images[0]);
- CvMat images[CV_MAX_DIM], mask = cvMat(1,1,CV_8U);
- int img_depth = _images[0]->depth;
-
- cdims = cvGetDims( hist->bins, dims );
-
- cvZero( hist->bins );
-
- for( k = 0; k < cdims; k++ )
- {
- cvGetMat( _images[k], &images[k] );
- nch[k] = _images[k]->nChannels;
- }
-
- if( _mask )
- cvGetMat( _mask, &mask );
-
- for( y = 0; y < img_size.height; y++ )
- {
- const uchar* mptr = _mask ? &CV_MAT_ELEM(mask, uchar, y, 0 ) : 0;
-
- if( img_depth == IPL_DEPTH_8U )
- for( k = 0; k < cdims; k++ )
- plane[k].ptr = &CV_MAT_ELEM(images[k], uchar, y, 0 ) + channels[k];
- else
- for( k = 0; k < cdims; k++ )
- plane[k].fl = &CV_MAT_ELEM(images[k], float, y, 0 ) + channels[k];
-
- for( x = 0; x < img_size.width; x++ )
- {
- float val[CV_MAX_DIM];
- int idx[CV_MAX_DIM];
-
- if( mptr && !mptr[x] )
- continue;
- if( img_depth == IPL_DEPTH_8U )
- for( k = 0; k < cdims; k++ )
- val[k] = plane[k].ptr[x*nch[k]];
- else
- for( k = 0; k < cdims; k++ )
- val[k] = plane[k].fl[x*nch[k]];
-
- idx[cdims-1] = -1;
-
- if( uniform )
- {
- for( k = 0; k < cdims; k++ )
- {
- double v = val[k], lo = hist->thresh[k][0], hi = hist->thresh[k][1];
- idx[k] = cvFloor((v - lo)*dims[k]/(hi - lo));
- if( idx[k] < 0 || idx[k] >= dims[k] )
- break;
- }
- }
- else
- {
- for( k = 0; k < cdims; k++ )
- {
- float v = val[k];
- float* t = hist->thresh2[k];
- int j, n = dims[k];
-
- for( j = 0; j <= n; j++ )
- if( v < t[j] )
- break;
- if( j <= 0 || j > n )
- break;
- idx[k] = j-1;
- }
- }
-
- if( k < cdims )
- continue;
-
- (*(float*)cvPtrND( hist->bins, idx ))++;
- }
- }
-}
-
-
-int CV_CalcHistTest::validate_test_results( int /*test_case_idx*/ )
-{
- int code = CvTS::OK;
- double diff;
- cvTsCalcHist( images, hist[1], images[CV_MAX_DIM], channels );
- diff = cvCompareHist( hist[0], hist[1], CV_COMP_CHISQR );
- if( diff > DBL_EPSILON )
- {
- ts->printf( CvTS::LOG, "The histogram does not match to the reference one\n" );
- code = CvTS::FAIL_BAD_ACCURACY;
-
- }
-
- if( code < 0 )
- ts->set_failed_test_info( code );
- return code;
-}
-
-
-CV_CalcHistTest hist_calc_test;
-
-
-
-////////////// cvCalcBackProject //////////////
-
-class CV_CalcBackProjectTest : public CV_BaseHistTest
-{
-public:
- CV_CalcBackProjectTest();
- ~CV_CalcBackProjectTest();
- void clear();
-
-protected:
- int prepare_test_case( int test_case_idx );
- void run_func(void);
- int validate_test_results( int test_case_idx );
- IplImage* images[CV_MAX_DIM+3];
- int channels[CV_MAX_DIM+3];
-};
-
-
-
-CV_CalcBackProjectTest::CV_CalcBackProjectTest() :
- CV_BaseHistTest( "hist-backproj", "cvCalcBackProject" )
-{
- int i;
-
- hist_count = 1;
- gen_random_hist = 0;
- init_ranges = 1;
-
- for( i = 0; i < CV_MAX_DIM+3; i++ )
- {
- images[i] = 0;
- channels[i] = 0;
- }
-}
-
-
-CV_CalcBackProjectTest::~CV_CalcBackProjectTest()
-{
- clear();
-}
-
-
-void CV_CalcBackProjectTest::clear()
-{
- int i;
-
- for( i = 0; i < CV_MAX_DIM+3; i++ )
- cvReleaseImage( &images[i] );
-
- CV_BaseHistTest::clear();
-}
-
-
-int CV_CalcBackProjectTest::prepare_test_case( int test_case_idx )
-{
- int code = CV_BaseHistTest::prepare_test_case( test_case_idx );
-
- if( code > 0 )
- {
- CvRNG* rng = ts->get_rng();
- int i, j, n, img_len = img_size.width*img_size.height;
-
- for( i = 0; i < CV_MAX_DIM + 3; i++ )
- {
- if( i < cdims )
- {
- int nch = 1; //cvTsRandInt(rng) % 3 + 1;
- images[i] = cvCreateImage( img_size,
- img_type == CV_8U ? IPL_DEPTH_8U : IPL_DEPTH_32F, nch );
- channels[i] = cvTsRandInt(rng) % nch;
-
- cvRandArr( rng, images[i], CV_RAND_UNI,
- cvScalarAll(low), cvScalarAll(high) );
- }
- else if( i == CV_MAX_DIM && cvTsRandInt(rng) % 2 )
- {
- // create mask
- images[i] = cvCreateImage( img_size, IPL_DEPTH_8U, 1 );
- // make ~25% pixels in the mask non-zero
- cvRandArr( rng, images[i], CV_RAND_UNI,
- cvScalarAll(-2), cvScalarAll(2) );
- }
- else if( i > CV_MAX_DIM )
- {
- images[i] = cvCreateImage( img_size, images[0]->depth, 1 );
- }
- }
-
- cvTsCalcHist( images, hist[0], images[CV_MAX_DIM], channels );
-
- // now modify the images a bit to add some zeros go to the backprojection
- n = cvTsRandInt(rng) % (img_len/20+1);
- for( i = 0; i < cdims; i++ )
- {
- char* data = images[i]->imageData;
- for( j = 0; j < n; j++ )
- {
- int idx = cvTsRandInt(rng) % img_len;
- double val = cvTsRandReal(rng)*(high - low) + low;
-
- if( img_type == CV_8U )
- ((uchar*)data)[idx] = (uchar)cvRound(val);
- else
- ((float*)data)[idx] = (float)val;
- }
- }
- }
-
- return code;
-}
-
-
-void CV_CalcBackProjectTest::run_func(void)
-{
- cvCalcBackProject( images, images[CV_MAX_DIM+1], hist[0] );
-}
-
-
-static void
-cvTsCalcBackProject( IplImage** images, IplImage* dst, CvHistogram* hist, int* channels )
-{
- int x, y, k, cdims;
- union
- {
- float* fl;
- uchar* ptr;
- }
- plane[CV_MAX_DIM];
- int nch[CV_MAX_DIM];
- int dims[CV_MAX_DIM];
- int uniform = CV_IS_UNIFORM_HIST(hist);
- CvSize img_size = cvGetSize(images[0]);
- int img_depth = images[0]->depth;
-
- cdims = cvGetDims( hist->bins, dims );
-
- for( k = 0; k < cdims; k++ )
- nch[k] = images[k]->nChannels;
-
- for( y = 0; y < img_size.height; y++ )
- {
- if( img_depth == IPL_DEPTH_8U )
- for( k = 0; k < cdims; k++ )
- plane[k].ptr = &CV_IMAGE_ELEM(images[k], uchar, y, 0 ) + channels[k];
- else
- for( k = 0; k < cdims; k++ )
- plane[k].fl = &CV_IMAGE_ELEM(images[k], float, y, 0 ) + channels[k];
-
- for( x = 0; x < img_size.width; x++ )
- {
- float val[CV_MAX_DIM];
- float bin_val = 0;
- int idx[CV_MAX_DIM];
-
- if( img_depth == IPL_DEPTH_8U )
- for( k = 0; k < cdims; k++ )
- val[k] = plane[k].ptr[x*nch[k]];
- else
- for( k = 0; k < cdims; k++ )
- val[k] = plane[k].fl[x*nch[k]];
- idx[cdims-1] = -1;
-
- if( uniform )
- {
- for( k = 0; k < cdims; k++ )
- {
- double v = val[k], lo = hist->thresh[k][0], hi = hist->thresh[k][1];
- idx[k] = cvFloor((v - lo)*dims[k]/(hi - lo));
- if( idx[k] < 0 || idx[k] >= dims[k] )
- break;
- }
- }
- else
- {
- for( k = 0; k < cdims; k++ )
- {
- float v = val[k];
- float* t = hist->thresh2[k];
- int j, n = dims[k];
-
- for( j = 0; j <= n; j++ )
- if( v < t[j] )
- break;
- if( j <= 0 || j > n )
- break;
- idx[k] = j-1;
- }
- }
-
- if( k == cdims )
- bin_val = (float)cvGetRealND( hist->bins, idx );
-
- if( img_depth == IPL_DEPTH_8U )
- {
- int t = cvRound(bin_val);
- CV_IMAGE_ELEM( dst, uchar, y, x ) = CV_CAST_8U(t);
- }
- else
- CV_IMAGE_ELEM( dst, float, y, x ) = bin_val;
- }
- }
-}
-
-
-int CV_CalcBackProjectTest::validate_test_results( int /*test_case_idx*/ )
-{
- int code = CvTS::OK;
-
- cvTsCalcBackProject( images, images[CV_MAX_DIM+2], hist[0], channels );
- code = cvTsCmpEps2( ts, images[CV_MAX_DIM+1], images[CV_MAX_DIM+2], 0, true,
- "Back project image" );
-
- if( code < 0 )
- ts->set_failed_test_info( code );
-
- return code;
-}
-
-
-CV_CalcBackProjectTest hist_backproj_test;
-
-
-////////////// cvCalcBackProjectPatch //////////////
-
-class CV_CalcBackProjectPatchTest : public CV_BaseHistTest
-{
-public:
- CV_CalcBackProjectPatchTest();
- ~CV_CalcBackProjectPatchTest();
- void clear();
-
-protected:
- int prepare_test_case( int test_case_idx );
- void run_func(void);
- int validate_test_results( int test_case_idx );
- IplImage* images[CV_MAX_DIM+2];
- int channels[CV_MAX_DIM+2];
-
- CvSize patch_size;
- double factor;
- int method;
-};
-
-
-
-CV_CalcBackProjectPatchTest::CV_CalcBackProjectPatchTest() :
- CV_BaseHistTest( "hist-backprojpatch", "cvCalcBackProjectPatch" )
-{
- int i;
-
- hist_count = 1;
- gen_random_hist = 0;
- init_ranges = 1;
- img_max_log_size = 6;
-
- for( i = 0; i < CV_MAX_DIM+2; i++ )
- {
- images[i] = 0;
- channels[i] = 0;
- }
-}
-
-
-CV_CalcBackProjectPatchTest::~CV_CalcBackProjectPatchTest()
-{
- clear();
-}
-
-
-void CV_CalcBackProjectPatchTest::clear()
-{
- int i;
-
- for( i = 0; i < CV_MAX_DIM+2; i++ )
- cvReleaseImage( &images[i] );
-
- CV_BaseHistTest::clear();
-}
-
-
-int CV_CalcBackProjectPatchTest::prepare_test_case( int test_case_idx )
-{
- int code = CV_BaseHistTest::prepare_test_case( test_case_idx );
-
- if( code > 0 )
- {
- CvRNG* rng = ts->get_rng();
- int i, j, n, img_len = img_size.width*img_size.height;
-
- patch_size.width = cvTsRandInt(rng) % img_size.width + 1;
- patch_size.height = cvTsRandInt(rng) % img_size.height + 1;
- patch_size.width = MIN( patch_size.width, 30 );
- patch_size.height = MIN( patch_size.height, 30 );
-
- factor = 1.;
- method = cvTsRandInt(rng) % CV_CompareHistTest::MAX_METHOD;
-
- for( i = 0; i < CV_MAX_DIM + 2; i++ )
- {
- if( i < cdims )
- {
- int nch = 1; //cvTsRandInt(rng) % 3 + 1;
- images[i] = cvCreateImage( img_size,
- img_type == CV_8U ? IPL_DEPTH_8U : IPL_DEPTH_32F, nch );
- channels[i] = cvTsRandInt(rng) % nch;
-
- cvRandArr( rng, images[i], CV_RAND_UNI,
- cvScalarAll(low), cvScalarAll(high) );
- }
- else if( i >= CV_MAX_DIM )
- {
- images[i] = cvCreateImage(
- cvSize(img_size.width - patch_size.width + 1,
- img_size.height - patch_size.height + 1),
- IPL_DEPTH_32F, 1 );
- }
- }
-
- cvTsCalcHist( images, hist[0], 0, channels );
- cvNormalizeHist( hist[0], factor );
-
- // now modify the images a bit
- n = cvTsRandInt(rng) % (img_len/10+1);
- for( i = 0; i < cdims; i++ )
- {
- char* data = images[i]->imageData;
- for( j = 0; j < n; j++ )
- {
- int idx = cvTsRandInt(rng) % img_len;
- double val = cvTsRandReal(rng)*(high - low) + low;
-
- if( img_type == CV_8U )
- ((uchar*)data)[idx] = (uchar)cvRound(val);
- else
- ((float*)data)[idx] = (float)val;
- }
- }
- }
-
- return code;
-}
-
-
-void CV_CalcBackProjectPatchTest::run_func(void)
-{
- cvCalcBackProjectPatch( images, images[CV_MAX_DIM], patch_size, hist[0], method, factor );
-}
-
-
-static void
-cvTsCalcBackProjectPatch( IplImage** images, IplImage* dst, CvSize patch_size,
- CvHistogram* hist, int method,
- double factor, int* channels )
-{
- CvHistogram* model = 0;
-
- IplImage imgstub[CV_MAX_DIM], *img[CV_MAX_DIM];
- IplROI roi;
- int i, dims;
- int x, y;
- CvSize size = cvGetSize(dst);
-
- dims = cvGetDims( hist->bins );
- cvCopyHist( hist, &model );
- cvNormalizeHist( hist, factor );
- cvZero( dst );
-
- for( i = 0; i < dims; i++ )
- {
- CvMat stub, *mat;
- mat = cvGetMat( images[i], &stub, 0, 0 );
- img[i] = cvGetImage( mat, &imgstub[i] );
- img[i]->roi = &roi;
- }
-
- roi.coi = 0;
-
- for( y = 0; y < size.height; y++ )
- {
- for( x = 0; x < size.width; x++ )
- {
- double result;
-
- roi.xOffset = x;
- roi.yOffset = y;
- roi.width = patch_size.width;
- roi.height = patch_size.height;
-
- cvTsCalcHist( img, model, 0, channels );
- cvNormalizeHist( model, factor );
- result = cvCompareHist( model, hist, method );
- CV_IMAGE_ELEM( dst, float, y, x ) = (float)result;
- }
- }
-
- cvReleaseHist( &model );
-}
-
-
-int CV_CalcBackProjectPatchTest::validate_test_results( int /*test_case_idx*/ )
-{
- int code = CvTS::OK;
- double err_level = 5e-3;
-
- cvTsCalcBackProjectPatch( images, images[CV_MAX_DIM+1],
- patch_size, hist[0], method, factor, channels );
-
- code = cvTsCmpEps2( ts, images[CV_MAX_DIM], images[CV_MAX_DIM+1], err_level, true,
- "BackProjectPatch result" );
-
- if( code < 0 )
- ts->set_failed_test_info( code );
-
- return code;
-}
-
-
-CV_CalcBackProjectPatchTest hist_backprojpatch_test;
-
-
-////////////// cvCalcBayesianProb //////////////
-
-class CV_BayesianProbTest : public CV_BaseHistTest
-{
-public:
- enum { MAX_METHOD = 4 };
-
- CV_BayesianProbTest();
-protected:
- int prepare_test_case( int test_case_idx );
- void run_func(void);
- int validate_test_results( int test_case_idx );
- void init_hist( int test_case_idx, int i );
- void get_hist_params( int test_case_idx );
-};
-
-
-
-CV_BayesianProbTest::CV_BayesianProbTest() :
- CV_BaseHistTest( "hist-bayesianprob", "cvBayesianProb" )
-{
- hist_count = CV_MAX_DIM;
- gen_random_hist = 1;
-}
-
-
-void CV_BayesianProbTest::get_hist_params( int test_case_idx )
-{
- CV_BaseHistTest::get_hist_params( test_case_idx );
- hist_type = CV_HIST_ARRAY;
-}
-
-
-void CV_BayesianProbTest::init_hist( int test_case_idx, int hist_i )
-{
- if( hist_i < hist_count/2 )
- CV_BaseHistTest::init_hist( test_case_idx, hist_i );
-}
-
-
-int CV_BayesianProbTest::prepare_test_case( int test_case_idx )
-{
- CvRNG* rng = ts->get_rng();
-
- hist_count = (cvTsRandInt(rng) % (MAX_HIST/2-1) + 2)*2;
- hist_count = MIN( hist_count, MAX_HIST );
- int code = CV_BaseHistTest::prepare_test_case( test_case_idx );
-
- return code;
-}
-
-
-void CV_BayesianProbTest::run_func(void)
-{
- cvCalcBayesianProb( hist, hist_count/2, hist + hist_count/2 );
-}
-
-
-int CV_BayesianProbTest::validate_test_results( int /*test_case_idx*/ )
-{
- int code = CvTS::OK;
- int i, j, n = hist_count/2;
- double s[CV_MAX_DIM];
- const double err_level = 1e-5;
-
- for( i = 0; i < total_size; i++ )
- {
- double sum = 0;
- for( j = 0; j < n; j++ )
- {
- double v = hist[j]->mat.data.fl[i];
- sum += v;
- s[j] = v;
- }
- sum = sum > DBL_EPSILON ? 1./sum : 0;
-
- for( j = 0; j < n; j++ )
- {
- double v0 = s[j]*sum;
- double v = hist[j+n]->mat.data.fl[i];
-
- if( cvIsNaN(v) || cvIsInf(v) )
- {
- ts->printf( CvTS::LOG,
- "The element #%d in the destination histogram #%d is invalid (=%g)\n",
- i, j, v );
- code = CvTS::FAIL_INVALID_OUTPUT;
- break;
- }
- else if( fabs(v0 - v) > err_level*fabs(v0) )
- {
- ts->printf( CvTS::LOG,
- "The element #%d in the destination histogram #%d is inaccurate (=%g, should be =%g)\n",
- i, j, v, v0 );
- code = CvTS::FAIL_BAD_ACCURACY;
- break;
- }
- }
- if( j < n )
- break;
- }
-
- if( code < 0 )
- ts->set_failed_test_info( code );
- return code;
-}
-
-
-CV_BayesianProbTest hist_bayesianprob_test;
-
-/* End Of File */
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-#if 0 /* avoid this while a substitution for IPL DCT is not ready */
-
-#include <stdlib.h>
-#include <assert.h>
-#include <limits.h>
-#include <float.h>
-
-static char* funcs[] =
-{
- "cvImgToObs_DCT"
-};
-
-static char *test_desc[] =
-{
- "Comparing against IPL DCT"
-};
-
-/* actual parameters */
-static int min_img_size, max_img_size;
-static int max_dct_size;
-static int base_iters;
-
-static int init_hmm_obs_params = 0;
-
-static const int img8u_range = 256;
-
-static void read_hmm_obs_params( void )
-{
- if( !init_hmm_obs_params )
- {
- /* read tests params */
- trsiRead( &min_img_size, "10", "Minimal width or height of image" );
- trsiRead( &max_img_size, "300", "Maximal width or height of image" );
- trsiRead( &max_dct_size, "24", "Maximum DCT size" );
- trsiRead( &base_iters, "100", "Base number of iterations" );
-
- init_hmm_obs_params = 1;
- }
-}
-
-
-static CvSize hmm_obs_dct_get_size( IplImage* img, CvSize dctSize, CvSize delta )
-{
- CvSize result;
- CvRect roi = cvGetImageROI( img );
-
- result.width = (roi.width - dctSize.width + delta.width) / delta.width;
- result.height = (roi.height - dctSize.height + delta.height) / delta.height;
-
- return result;
-}
-
-
-static void hmm_obs_dct_etalon( IplImage* img, char* obs, CvSize dctSize,
- CvSize obsSize, CvSize delta )
-{
- IplImage *src = cvCreateImage( dctSize, IPL_DEPTH_8U, 1 );
- IplImage *dst = cvCreateImage( dctSize, IPL_DEPTH_32F, 1 );
-
- CvSize result = hmm_obs_dct_get_size( img, dctSize, delta );
-
- int x, y, j;
- int obs_step = obsSize.width*sizeof(float);
-
- result.width *= delta.width;
- result.height *= delta.height;
-
- for( y = 0; y < result.height; y += delta.height )
- for( x = 0; x < result.width; x += delta.width )
- {
- cvSetImageROI( img, cvRect( x, y, dctSize.width, dctSize.height ));
- cvCopy( img, src );
- iplDCT2D( src, dst, IPL_DCT_Forward );
- for( j = 0; j < obsSize.height; j++ )
- {
- memcpy( obs, dst->imageData + dst->widthStep*j, obs_step );
- obs += obs_step;
- }
- }
-
- cvReleaseImage( &src );
- cvReleaseImage( &dst );
-}
-
-
-
-/* ///////////////////// moments_test ///////////////////////// */
-static int hmm_dct_test( void )
-{
- const double success_error_level = 1.1;
-
- int seed = atsGetSeed();
- int code = TRS_OK;
- const int max_obs_size = 8;
-
- /* position where the maximum error occured */
- int i, merr_iter = 0;
-
- /* test parameters */
- double max_err = 0.;
-
- IplImage *img = 0;
- IplImage *obs = 0;
- IplImage *obs2 = 0;
- AtsRandState rng_state;
- CvSize obs_size;
-
- atsRandInit( &rng_state, 0, img8u_range, seed );
-
- read_hmm_obs_params();
-
- img = cvCreateImage( cvSize( max_img_size, max_img_size ), IPL_DEPTH_8U, 1 );
- obs_size.height = max_img_size;
- obs_size.width = obs_size.height*64;
- obs = cvCreateImage( obs_size, IPL_DEPTH_32F, 1 );
- obs2 = cvCreateImage( obs_size, IPL_DEPTH_32F, 1 );
-
- for( i = 0; i < base_iters; i++ )
- {
- CvSize size;
- CvSize dctSize, obsSize, delta, result;
- double err = 0;
-
- size.width = atsRandPlain32s( &rng_state ) %
- (max_img_size - min_img_size + 1) + min_img_size;
- size.height = atsRandPlain32s( &rng_state ) %
- (max_img_size - min_img_size + 1) + min_img_size;
-
- dctSize.width = atsRandPlain32s( &rng_state ) % (max_dct_size - 1) + 2;
- if( dctSize.width > size.width )
- dctSize.width = size.width;
- dctSize.height = atsRandPlain32s( &rng_state ) % (max_dct_size - 1) + 2;
- if( dctSize.height > size.height )
- dctSize.height = size.height;
-
- obsSize.width = atsRandPlain32s( &rng_state ) % max_obs_size + 1;
- if( obsSize.width > dctSize.width )
- obsSize.width = dctSize.width;
- obsSize.height = atsRandPlain32s( &rng_state ) % max_obs_size + 1;
- if( obsSize.height > dctSize.height )
- obsSize.height = dctSize.height;
-
- delta.width = atsRandPlain32s( &rng_state ) % dctSize.width + 1;
- delta.height = atsRandPlain32s( &rng_state ) % dctSize.height + 1;
-
- cvSetImageROI( img, cvRect( 0, 0, size.width, size.height ));
-
- result = hmm_obs_dct_get_size( img, dctSize, delta );
-
- atsFillRandomImageEx( img, &rng_state );
-
- OPENCV_CALL( cvImgToObs_DCT( img, (float*)(obs->imageData), dctSize, obsSize, delta ));
-
- hmm_obs_dct_etalon( img, obs2->imageData, dctSize, obsSize, delta );
-
- obs->width = obs2->width = result.width*obsSize.width*obsSize.height;
- obs->height = obs2->height = result.height;
- obs->widthStep = obs2->widthStep = obs->width*sizeof(float);
-
- assert( obs->roi == 0 && obs2->roi == 0 );
-
- err = cvNorm( obs, obs2, CV_C );
-
- obs->width = obs2->width = max_img_size;
- obs->height = obs2->height = max_img_size;
- obs->widthStep = obs2->widthStep = obs->width*sizeof(float);
-
- if( err > max_err )
- {
- merr_iter = i;
- max_err = err;
- if( max_err > success_error_level )
- goto test_exit;
- }
- }
-
-test_exit:
-
- cvReleaseImage( &img );
- cvReleaseImage( &obs );
- cvReleaseImage( &obs2 );
-
- if( code == TRS_OK )
- {
- trsWrite( ATS_LST, "Max err is %g at iter = %d, seed = %08x",
- max_err, merr_iter, seed );
-
- return max_err <= success_error_level ?
- trsResult( TRS_OK, "No errors" ) :
- trsResult( TRS_FAIL, "Bad accuracy" );
- }
- /*else
- {
- trsWrite( ATS_LST, "Fatal error at iter = %d, seed = %08x", i, seed );
- return trsResult( TRS_FAIL, "Function returns error code" );
- }*/
-}
-
-
-void InitAImageToHMMObs( void )
-{
- /* Register test functions */
-
- trsReg( funcs[0], test_desc[0], atsAlgoClass, hmm_dct_test );
-
-} /* InitAMoments */
-
-#endif
-
-/* End of file. */
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-#if 0
-
-#include <stdlib.h>
-#include <math.h>
-#include <float.h>
-
-#define HT_STANDARD (size_t)1
-#define HT_PP (size_t)2
-#define HT_MD (size_t)3
-
-static char* func_names[] = {"cvHoughTransform", "cvHoughTransformP", "cvHoughTransformSDiv"};
-static char* test_desc[] = { "Run the hough transform function"};
-
-int test_dt(void* arg);
-int read_image_dims(void);
-int read_gen_type(void);
-
-int test_ht(void* arg)
-{
- int nlines = 10;
- int* lines = new int[4*nlines];
- float* flines = new float[2*nlines];
- float rho = 10.0f, theta = 0.1f;
- int srn = 10, stn = 10;
- int threshold = 10;
- int lineLength = 10, lineGap = 2;
- int w = 100; /* width and height of the rect */
- int h = 100;
- int type = (int)(size_t)arg;
- IplImage* image; /* Source and destination images */
- image = cvCreateImage( cvSize(w, h), 8, 1 );
- cvZero(image);
-
- if( image == NULL )
- {
- delete lines;
- delete flines;
- return trsResult(TRS_FAIL, "Not enough memory to perform the test");
- }
-
- switch(type)
- {
- case HT_STANDARD:
- /* Run the distance transformation function */
- cvHoughLines(image, rho, theta, threshold, flines, nlines);
- break;
-
- case HT_PP:
- cvHoughLinesP(image, rho, theta, threshold, lineLength, lineGap, lines, nlines);
- break;
-
- case HT_MD:
- cvHoughLinesSDiv(image, rho, srn, theta, stn, threshold, flines, nlines);
- break;
-
- default:
- cvReleaseImage(& image);
- delete lines;
- delete flines;
- trsResult(TRS_FAIL, "No such function");
- }
- cvReleaseImage( &image );
- delete lines;
- delete flines;
- if(cvGetErrStatus() < 0)
- {
- return trsResult(TRS_FAIL, "Function returned 'bad argument'");
- }
- else
- {
- return trsResult(TRS_OK, "No errors");
- }
-}
-
-void InitAHoughLines(void)
-{
- /* Registering test functions */
- trsRegArg(func_names[0], test_desc[0], atsAlgoClass, test_ht, HT_STANDARD);
- trsRegArg(func_names[1], test_desc[0], atsAlgoClass, test_ht, HT_PP);
- trsRegArg(func_names[2], test_desc[0], atsAlgoClass, test_ht, HT_MD);
-
-} /* InitADistanceTransform*/
-
-#endif
-
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-#if 0
-
-#define DEPTH_8U 0
-
-/* Testing parameters */
-static char test_desc[] = "Image Creation & access";
-static char func_name[] = "cvCreateImage cvCreateImageHeader cvSetImageROI cvGetImageROI "
- "cvSetImageCOI cvCreateImageData cvReleaseImageData "
- "cvSetImageData cvCloneImage cvCopyImage cvInitImageHeader";
-
-static int depths[] = { IPL_DEPTH_8U, IPL_DEPTH_8S, IPL_DEPTH_16S,
- IPL_DEPTH_32S, IPL_DEPTH_32F, IPL_DEPTH_64F, 0};
-static int channels[] = {1, 2, 3, 4, 0};
-
-static char* imageData = (char*)cvAlloc(10000);
-
-const int align = 4;
-
-static int foaImage( void )
-{
- CvSize size = cvSize(320, 200);
- int i, j;
- int Errors = 0;
- //Creating new image with different channels & depths
- for( i = 0; depths[i] != 0; i++ ) // cycle for depths
- for(j = 0; channels[j] != 0; j++) // cycle for channels
- {
- if( depths[i] == IPL_DEPTH_1U && channels[j] != 1 ) // skip for IPL_DEPTH_1U
- continue; // all non 1 channels
- IplImage* image = cvCreateImage( size, depths[i], channels[j] );
- if( image->width != size.width || image->height != size.height )
- {
- trsWrite( ATS_CON | ATS_LST,
- "cvCreateImage: Size mismatch: act %d x %d exp %d x %d\n",
- image->width, image->height, size.width, size.height );
- Errors++;
- }
- if( size.width * (depths[i] & IPL_DEPTH_MASK) / 8 > image->widthStep ||
- (image->widthStep & 3) )
- {
- trsWrite( ATS_CON | ATS_LST, "cvCreateImage: Wrong widthStep: act %d\n",
- image->widthStep );
- Errors++;
- }
-
- cvReleaseImage( &image );
- }
- trsWrite( ATS_CON, "cvCreateImage: ... done\n" );
-
- //Creating new image header with different channels & depths
- for( i = 0; depths[i] != 0; i++ ) // cycle for depths
- for(j = 0; channels[j] != 0; j++) // cycle for channels
- {
- if( depths[i] == IPL_DEPTH_1U && channels[j] != 1 ) // skip for IPL_DEPTH_1U
- continue; // all non 1 channels
- if( depths[i] == (int)IPL_DEPTH_8S )
- continue;
- IplImage* image = cvCreateImageHeader( size, depths[i], channels[j] );
- if( image->width != size.width || image->height != size.height )
- {
- trsWrite( ATS_CON | ATS_LST,
- "cvCreateImageHeader: Size mismatch: act %d x %d exp %d x %d\n",
- image->width, image->height, size.width, size.height );
- Errors++;
- }
- if( size.width * (depths[i] & IPL_DEPTH_MASK) / 8 > image->widthStep ||
- (image->widthStep & 3) )
- {
- trsWrite( ATS_CON | ATS_LST, "cvCreateImageHeader: Wrong widthStep: act %d\n",
- image->widthStep );
- Errors++;
- }
- if( image->imageData )
- {
- trsWrite( ATS_CON | ATS_LST, "cvCreateImageHeader: imageData created :(\n" );
- Errors++;
- }
-
- cvSetImageROI( image, cvRect(1, 1, size.width - 1, size.height - 1) );
- if( image->roi->coi )
- {
- trsWrite( ATS_CON | ATS_LST, "cvSetImageROI: coi non zero\n" );
- Errors++;
- }
-
- CvRect rect = cvGetImageROI( image );
- if( rect.x != 1 || rect.y != 1 ||
- rect.width != size.width - 1 || rect.height != size.height - 1 )
- {
- trsWrite( ATS_CON | ATS_LST,
- "cvGetImageROI: wrong rect: act %d x %d x %d x %d "
- "exp %d x %d x %d x %d\n",
- rect.x, rect.y, rect.width, rect.height,
- 1, 1, size.width - 1, size.height - 1 );
- Errors++;
- }
-
- cvSetImageCOI( image, 1 );
- if( image->roi->coi != 1 )
- {
- trsWrite( ATS_CON | ATS_LST, "cvSetImageCOI: soi non 1\n" );
- Errors++;
- }
- if( image->roi->xOffset != 1 || image->roi->yOffset != 1 ||
- image->roi->width != size.width - 1 ||
- image->roi->height != size.height - 1)
- {
- trsWrite( ATS_CON | ATS_LST,
- "cvCreateImageHeader: Size mismatch: act %d x %d x %d x %d"
- "exp %d x %d x %d x %d\n",
- image->roi->xOffset, image->roi->yOffset,
- image->roi->width, image->roi->height,
- 1, 1, size.width - 1, size.height - 1 );
- Errors++;
- }
-
- cvCreateImageData( image );
- if( !image->imageData )
- {
- trsWrite( ATS_CON | ATS_LST,
- "cvCreateImageData: Wow :)... where is imageData ?....\n" );
- Errors++;
- }
-
- cvReleaseImageData( image );
- if( image->imageData )
- {
- trsWrite( ATS_CON | ATS_LST, "cvReleaseImageData: imageData non zero :(\n" );
- Errors++;
- }
-
- cvSetImageData( image, imageData, size.width * channels[j] * 8 ); // magic width step :)
- if( image->imageData != imageData )
- {
- trsWrite( ATS_CON | ATS_LST,
- "cvSetImageData: wrong pointer to imageData: act %x, exp %x\n",
- image->imageData, imageData );
- Errors++;
- }
- if( image->widthStep != size.width * channels[j] * 8 )
- {
- trsWrite( ATS_CON | ATS_LST, "cvSetImageData: wrong imageStep: act %d, exp %d\n",
- image->widthStep, size.width * channels[j] * 8 );
- Errors++;
- }
-
- cvReleaseImageHeader( &image );
- }
- trsWrite( ATS_CON, "cvCreateImageHeader: ... done\n" );
- trsWrite( ATS_CON, "cvSetImageROI: ... done\n" );
- trsWrite( ATS_CON, "cvGetImageROI: ... done\n" );
- trsWrite( ATS_CON, "cvSetImageCOI: ... done\n" );
- trsWrite( ATS_CON, "cvCreateImageData: ... done\n" );
- trsWrite( ATS_CON, "cvReleaseImageData: ... done\n" );
- trsWrite( ATS_CON, "cvSetImageData: ... done\n" );
-
- for( i = 0; depths[i] != 0; i++ ) // cycle for depths
- for(j = 0; channels[j] != 0; j++) // cycle for channels
- {
- if( depths[i] == IPL_DEPTH_1U && channels[j] != 1 ) // skip for IPL_DEPTH_1U
- continue; // all non 1 channels
- if( depths[i] == (int)IPL_DEPTH_8S )
- continue;
- IplImage* src = cvCreateImage( size, depths[i], channels[j] );
- //IplImage* dst = cvCreateImage( size, depths[i], channels[j] );
- IplImage* dst = 0;
- IplImage* clone = 0;
-
- cvSetImageROI( src, cvRect(1, 1, size.width - 1, size.height - 1) );
-
- for( int k = 0; k < src->widthStep * src->height; k++ )
- src->imageData[k] = (char)k;
-
- //cvCopy/*Image*/( src, dst );
- dst = cvCloneImage( src );
- clone = dst;
-
- if( clone->width != dst->width || clone->height != dst->height )
- {
- trsWrite( ATS_CON | ATS_LST,
- "cvCopyImage/cvCloneImage: wrong destination size:"
- "%d x %d <> %d %d\n",
- clone->width, clone->height, dst->width, dst->height );
- Errors++;
- }
- if( clone->widthStep != src->widthStep )
- {
- trsWrite( ATS_CON | ATS_LST,
- "cvCloneImage: wrong width step: act %d exp %d\n",
- clone->widthStep, src->widthStep );
- Errors++;
- }
- if( !clone->roi )
- {
- trsWrite( ATS_CON | ATS_LST, "cvCloneImage: roi was lost\n" );
- Errors++;
- }
- else
- {
- if( clone->roi->xOffset != 1 || clone->roi->yOffset != 1 ||
- clone->roi->width != size.width - 1 ||
- clone->roi->height != size.height - 1 )
- {
- trsWrite( ATS_CON | ATS_LST,
- "cvCloneImage: Size mismatch: act %d x %d x %d x %d"
- "exp %d x %d x %d x %d\n",
- clone->roi->xOffset, clone->roi->yOffset,
- clone->roi->width, clone->roi->height,
- 1, 1, size.width - 1, size.height - 1 );
- Errors++;
- }
-
- }
- if( depths[i] == IPL_DEPTH_32F )
- {
- src->depth = IPL_DEPTH_32S;
- dst->depth = IPL_DEPTH_32S;
- }
- else if( depths[i] == IPL_DEPTH_64F )
- {
- src->depth = IPL_DEPTH_32S;
- dst->depth = IPL_DEPTH_32S;
-
- src->width *= 2;
- dst->width *= 2;
- }
-
- if( cvNorm( src, dst, CV_L1 ) )
- {
- trsWrite( ATS_CON | ATS_LST, "cvCopyImage: wrong destination image\n" );
- Errors++;
- }
- /*if( cvNorm( src, clone, CV_L1 ) )
- {
- trsWrite( ATS_CON | ATS_LST, "cvCloneImage: wrong destination image\n" );
- Errors++;
- }*/
-
- cvReleaseImage( &src );
- cvReleaseImage( &clone );
- }
- trsWrite( ATS_CON, "cvCloneImage: ... done\n" );
- //trsWrite( ATS_CON, "cvCopyImage: ... done\n" );
-
- //Init new image header with different channels & depths
- for( i = 0; depths[i] != 0; i++ ) // cycle for depths
- for(j = 0; channels[j] != 0; j++) // cycle for channels
- {
- if( depths[i] == IPL_DEPTH_1U && channels[j] != 1 ) // skip for IPL_DEPTH_1U
- continue; // all non 1 channels
- IplImage image;
- cvInitImageHeader( &image, size, depths[i], channels[j], IPL_ORIGIN_TL, align );
- if( image.width != size.width || image.height != size.height )
- {
- trsWrite( ATS_CON | ATS_LST,
- "cvInitImageHeader: Size mismatch: act %d x %d exp %d x %d\n",
- image.width, image.height, size.width, size.height );
- Errors++;
- }
- if( ((size.width * channels[j] * (depths[i] & IPL_DEPTH_MASK) / 8 + align - 1) &
- ~(align - 1)) != image.widthStep )
- {
- trsWrite( ATS_CON | ATS_LST,
- "cvCreateImageHeader: Wrong widthStep: act %d exp: %d\n",
- image.widthStep,
- (size.width * (depths[i] & IPL_DEPTH_MASK) / 8 + align - 1) &
- ~(align - 1) );
- Errors++;
- }
- if( image.imageData )
- {
- trsWrite( ATS_CON | ATS_LST, "cvCreateImageHeader: imageData created :(\n" );
- Errors++;
- }
- }
- trsWrite( ATS_CON, "cvInitImageHeader: ... done\n" );
-
- if( !Errors )
- return trsResult( TRS_OK, "Ok" );
- else
- return trsResult( TRS_FAIL, "%d errors" );
-}
-
-
-
-void InitAImage()
-{
- /* Register test function */
- trsReg( func_name, test_desc, atsAlgoClass, foaImage );
-} /* InitACanny */
-
-#endif
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-static const int imgwarp_depths[] = { CV_8U, CV_16U, CV_32F, -1 };
-static const int imgwarp_channels[] = { 1, 3, 4, -1 };
-static const CvSize imgwarp_sizes[] = {{320, 240}, {1024,768}, {-1,-1}};
-
-static const double imgwarp_resize_coeffs[] = { 0.5, 0.333, 2, 2.9 };
-static const char* imgwarp_resize_methods[] = { "nearest", "linear", "cubic", "area", 0 };
-static const char* imgwarp_resize_param_names[] = { "method", "coeff", "size", "channels", "depth", 0 };
-
-static const double imgwarp_affine_rotate_scale[][4] = { {0.5,0.5,30.,1.4}, {0.5,0.5,-130,0.4}, {-1,-1,-1,-1} };
-static const char* imgwarp_affine_param_names[] = { "rotate_scale", "size", "channels", "depth", 0 };
-
-static const double imgwarp_perspective_shift_vtx[][8] = { {0.03,0.01,0.04,0.02,0.01,0.01,0.01,0.02}, {-1} };
-static const char* imgwarp_perspective_param_names[] = { "shift_vtx", "size", "channels", "depth", 0 };
-
-class CV_ImgWarpBaseTestImpl : public CvArrTest
-{
-public:
- CV_ImgWarpBaseTestImpl( const char* test_name, const char* test_funcs, bool warp_matrix );
-
-protected:
- int read_params( CvFileStorage* fs );
- int prepare_test_case( int test_case_idx );
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void get_minmax_bounds( int i, int j, int type, CvScalar* low, CvScalar* high );
- void fill_array( int test_case_idx, int i, int j, CvMat* arr );
-
- int interpolation;
- int max_interpolation;
- double spatial_scale_zoom, spatial_scale_decimate;
-};
-
-
-CV_ImgWarpBaseTestImpl::CV_ImgWarpBaseTestImpl( const char* test_name, const char* test_funcs, bool warp_matrix )
- : CvArrTest( test_name, test_funcs, "" )
-{
- test_array[INPUT].push(NULL);
- if( warp_matrix )
- test_array[INPUT].push(NULL);
- test_array[INPUT_OUTPUT].push(NULL);
- test_array[REF_INPUT_OUTPUT].push(NULL);
- max_interpolation = 5;
- interpolation = 0;
- element_wise_relative_error = false;
- spatial_scale_zoom = 0.01;
- spatial_scale_decimate = 0.005;
-
- size_list = whole_size_list = imgwarp_sizes;
- depth_list = imgwarp_depths;
- cn_list = imgwarp_channels;
- default_timing_param_names = 0;
-}
-
-
-int CV_ImgWarpBaseTestImpl::read_params( CvFileStorage* fs )
-{
- int code = CvArrTest::read_params( fs );
- return code;
-}
-
-
-void CV_ImgWarpBaseTestImpl::get_minmax_bounds( int i, int j, int type, CvScalar* low, CvScalar* high )
-{
- CvArrTest::get_minmax_bounds( i, j, type, low, high );
- if( CV_MAT_DEPTH(type) == CV_32F )
- {
- *low = cvScalarAll(-10.);
- *high = cvScalarAll(10);
- }
-}
-
-
-void CV_ImgWarpBaseTestImpl::get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- int depth = cvTsRandInt(rng) % 3;
- int cn = cvTsRandInt(rng) % 3 + 1;
- CvArrTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- depth = depth == 0 ? CV_8U : depth == 1 ? CV_16U : CV_32F;
- cn += cn == 2;
-
- types[INPUT][0] = types[INPUT_OUTPUT][0] = types[REF_INPUT_OUTPUT][0] = CV_MAKETYPE(depth, cn);
- if( test_array[INPUT].size() > 1 )
- types[INPUT][1] = cvTsRandInt(rng) & 1 ? CV_32FC1 : CV_64FC1;
-
- interpolation = cvTsRandInt(rng) % max_interpolation;
-}
-
-
-void CV_ImgWarpBaseTestImpl::fill_array( int test_case_idx, int i, int j, CvMat* arr )
-{
- if( i != INPUT || j != 0 )
- CvArrTest::fill_array( test_case_idx, i, j, arr );
-}
-
-int CV_ImgWarpBaseTestImpl::prepare_test_case( int test_case_idx )
-{
- int code = CvArrTest::prepare_test_case( test_case_idx );
- CvMat* img = &test_mat[INPUT][0];
- int i, j, cols = img->cols;
- int type = CV_MAT_TYPE(img->type), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
- double scale = depth == CV_16U ? 1000. : 255.*0.5;
- double space_scale = spatial_scale_decimate;
- float* buffer;
-
- if( code <= 0 )
- return code;
-
- if( test_mat[INPUT_OUTPUT][0].cols >= img->cols &&
- test_mat[INPUT_OUTPUT][0].rows >= img->rows )
- space_scale = spatial_scale_zoom;
-
- buffer = (float*)cvAlloc( img->cols*cn*sizeof(buffer[0]) );
-
- for( i = 0; i < img->rows; i++ )
- {
- uchar* ptr = img->data.ptr + i*img->step;
- switch( cn )
- {
- case 1:
- for( j = 0; j < cols; j++ )
- buffer[j] = (float)((sin((i+1)*space_scale)*sin((j+1)*space_scale)+1.)*scale);
- break;
- case 2:
- for( j = 0; j < cols; j++ )
- {
- buffer[j*2] = (float)((sin((i+1)*space_scale)+1.)*scale);
- buffer[j*2+1] = (float)((sin((i+j)*space_scale)+1.)*scale);
- }
- break;
- case 3:
- for( j = 0; j < cols; j++ )
- {
- buffer[j*3] = (float)((sin((i+1)*space_scale)+1.)*scale);
- buffer[j*3+1] = (float)((sin(j*space_scale)+1.)*scale);
- buffer[j*3+2] = (float)((sin((i+j)*space_scale)+1.)*scale);
- }
- break;
- case 4:
- for( j = 0; j < cols; j++ )
- {
- buffer[j*4] = (float)((sin((i+1)*space_scale)+1.)*scale);
- buffer[j*4+1] = (float)((sin(j*space_scale)+1.)*scale);
- buffer[j*4+2] = (float)((sin((i+j)*space_scale)+1.)*scale);
- buffer[j*4+3] = (float)((sin((i-j)*space_scale)+1.)*scale);
- }
- break;
- default:
- assert(0);
- }
-
- /*switch( depth )
- {
- case CV_8U:
- for( j = 0; j < cols*cn; j++ )
- ptr[j] = (uchar)cvRound(buffer[j]);
- break;
- case CV_16U:
- for( j = 0; j < cols*cn; j++ )
- ((ushort*)ptr)[j] = (ushort)cvRound(buffer[j]);
- break;
- case CV_32F:
- for( j = 0; j < cols*cn; j++ )
- ((float*)ptr)[j] = (float)buffer[j];
- break;
- default:
- assert(0);
- }*/
- cv::Mat src(1, cols*cn, CV_32F, buffer);
- cv::Mat dst(1, cols*cn, depth, ptr);
- src.convertTo(dst, dst.type());
- }
-
- cvFree( &buffer );
-
- return code;
-}
-
-CV_ImgWarpBaseTestImpl imgwarp_base( "warp", "", false );
-
-
-class CV_ImgWarpBaseTest : public CV_ImgWarpBaseTestImpl
-{
-public:
- CV_ImgWarpBaseTest( const char* test_name, const char* test_funcs, bool warp_matrix );
-};
-
-
-CV_ImgWarpBaseTest::CV_ImgWarpBaseTest( const char* test_name, const char* test_funcs, bool warp_matrix )
- : CV_ImgWarpBaseTestImpl( test_name, test_funcs, warp_matrix )
-{
- size_list = whole_size_list = 0;
- depth_list = 0;
- cn_list = 0;
-}
-
-
-/////////////////////////
-
-class CV_ResizeTest : public CV_ImgWarpBaseTest
-{
-public:
- CV_ResizeTest();
-
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void run_func();
- void prepare_to_validation( int /*test_case_idx*/ );
- double get_success_error_level( int test_case_idx, int i, int j );
-
- int write_default_params(CvFileStorage* fs);
- void get_timing_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types,
- CvSize** whole_sizes, bool *are_images );
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
-};
-
-
-CV_ResizeTest::CV_ResizeTest()
- : CV_ImgWarpBaseTest( "warp-resize", "cvResize", false )
-{
- default_timing_param_names = imgwarp_resize_param_names;
-}
-
-
-int CV_ResizeTest::write_default_params( CvFileStorage* fs )
-{
- int code = CV_ImgWarpBaseTest::write_default_params( fs );
- if( code < 0 )
- return code;
-
- if( ts->get_testing_mode() == CvTS::TIMING_MODE )
- {
- start_write_param( fs );
- write_real_list( fs, "coeff", imgwarp_resize_coeffs, CV_DIM(imgwarp_resize_coeffs) );
- write_string_list( fs, "method", imgwarp_resize_methods );
- }
-
- return code;
-}
-
-
-void CV_ResizeTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- CV_ImgWarpBaseTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- CvSize sz;
-
- sz.width = (cvTsRandInt(rng) % sizes[INPUT][0].width) + 1;
- sz.height = (cvTsRandInt(rng) % sizes[INPUT][0].height) + 1;
-
- if( cvTsRandInt(rng) & 1 )
- {
- int xfactor = cvTsRandInt(rng) % 10 + 1;
- int yfactor = cvTsRandInt(rng) % 10 + 1;
-
- if( cvTsRandInt(rng) & 1 )
- yfactor = xfactor;
-
- sz.width = sizes[INPUT][0].width / xfactor;
- sz.width = MAX(sz.width,1);
- sz.height = sizes[INPUT][0].height / yfactor;
- sz.height = MAX(sz.height,1);
- sizes[INPUT][0].width = sz.width * xfactor;
- sizes[INPUT][0].height = sz.height * yfactor;
- }
-
- if( cvTsRandInt(rng) & 1 )
- sizes[INPUT_OUTPUT][0] = sizes[REF_INPUT_OUTPUT][0] = sz;
- else
- {
- sizes[INPUT_OUTPUT][0] = sizes[REF_INPUT_OUTPUT][0] = sizes[INPUT][0];
- sizes[INPUT][0] = sz;
- }
- if( interpolation == 4 &&
- (MIN(sizes[INPUT][0].width,sizes[INPUT_OUTPUT][0].width) < 4 ||
- MIN(sizes[INPUT][0].height,sizes[INPUT_OUTPUT][0].height) < 4))
- interpolation = 2;
-}
-
-
-void CV_ResizeTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images )
-{
- CV_ImgWarpBaseTest::get_timing_test_array_types_and_sizes( test_case_idx, sizes, types,
- whole_sizes, are_images );
- const char* method_str = cvReadString( find_timing_param( "method" ), "linear" );
- double coeff = cvReadReal( find_timing_param( "coeff" ), 1. );
- CvSize size = sizes[INPUT][0];
-
- size.width = cvRound(size.width*coeff);
- size.height = cvRound(size.height*coeff);
- sizes[INPUT_OUTPUT][0] = whole_sizes[INPUT_OUTPUT][0] = size;
-
- interpolation = strcmp( method_str, "nearest" ) == 0 ? CV_INTER_NN :
- strcmp( method_str, "linear" ) == 0 ? CV_INTER_LINEAR :
- strcmp( method_str, "cubic" ) == 0 ? CV_INTER_CUBIC : CV_INTER_AREA;
-}
-
-
-void CV_ResizeTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- sprintf( ptr, "coeff=%.3f,", cvReadReal( find_timing_param( "coeff" ), 1. ) );
- ptr += strlen(ptr);
- sprintf( ptr, "method=%s,", cvReadString( find_timing_param( "method" ), "linear" ) );
- ptr += strlen(ptr);
- params_left -= 2;
-
- CV_ImgWarpBaseTest::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-
-void CV_ResizeTest::run_func()
-{
- cvResize( test_array[INPUT][0], test_array[INPUT_OUTPUT][0], interpolation );
-}
-
-
-double CV_ResizeTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- int depth = CV_MAT_DEPTH(test_mat[INPUT][0].type);
- return depth == CV_8U ? 16 : depth == CV_16U ? 1024 : 1e-1;
-}
-
-
-void CV_ResizeTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- CvMat* src = &test_mat[INPUT][0];
- CvMat* dst = &test_mat[REF_INPUT_OUTPUT][0];
- int i, j, k;
- CvMat* x_idx = cvCreateMat( 1, dst->cols, CV_32SC1 );
- CvMat* y_idx = cvCreateMat( 1, dst->rows, CV_32SC1 );
- int* x_tab = x_idx->data.i;
- int elem_size = CV_ELEM_SIZE(src->type);
- int drows = dst->rows, dcols = dst->cols;
-
- if( interpolation == CV_INTER_NN )
- {
- for( j = 0; j < dcols; j++ )
- {
- int t = (j*src->cols*2 + MIN(src->cols,dcols) - 1)/(dcols*2);
- t -= t >= src->cols;
- x_idx->data.i[j] = t*elem_size;
- }
-
- for( j = 0; j < drows; j++ )
- {
- int t = (j*src->rows*2 + MIN(src->rows,drows) - 1)/(drows*2);
- t -= t >= src->rows;
- y_idx->data.i[j] = t;
- }
- }
- else
- {
- double scale_x = (double)src->cols/dcols;
- double scale_y = (double)src->rows/drows;
-
- for( j = 0; j < dcols; j++ )
- {
- double f = ((j+0.5)*scale_x - 0.5);
- i = cvRound(f);
- x_idx->data.i[j] = (i < 0 ? 0 : i >= src->cols ? src->cols - 1 : i)*elem_size;
- }
-
- for( j = 0; j < drows; j++ )
- {
- double f = ((j+0.5)*scale_y - 0.5);
- i = cvRound(f);
- y_idx->data.i[j] = i < 0 ? 0 : i >= src->rows ? src->rows - 1 : i;
- }
- }
-
- for( i = 0; i < drows; i++ )
- {
- uchar* dptr = dst->data.ptr + dst->step*i;
- const uchar* sptr0 = src->data.ptr + src->step*y_idx->data.i[i];
-
- for( j = 0; j < dcols; j++, dptr += elem_size )
- {
- const uchar* sptr = sptr0 + x_tab[j];
- for( k = 0; k < elem_size; k++ )
- dptr[k] = sptr[k];
- }
- }
-
- cvReleaseMat( &x_idx );
- cvReleaseMat( &y_idx );
-}
-
-CV_ResizeTest warp_resize_test;
-
-
-/////////////////////////
-
-void cvTsRemap( const CvMat* src, CvMat* dst,
- const CvMat* mapx, const CvMat* mapy,
- CvMat* mask, int interpolation=CV_INTER_LINEAR )
-{
- int x, y, k;
- int drows = dst->rows, dcols = dst->cols;
- int srows = src->rows, scols = src->cols;
- uchar* sptr0 = src->data.ptr;
- int depth = CV_MAT_DEPTH(src->type), cn = CV_MAT_CN(src->type);
- int elem_size = CV_ELEM_SIZE(src->type);
- int step = src->step / CV_ELEM_SIZE(depth);
- int delta;
-
- if( interpolation != CV_INTER_CUBIC )
- {
- delta = 0;
- scols -= 1; srows -= 1;
- }
- else
- {
- delta = 1;
- scols = MAX(scols - 3, 0);
- srows = MAX(srows - 3, 0);
- }
-
- int scols1 = MAX(scols - 2, 0);
- int srows1 = MAX(srows - 2, 0);
-
- if( mask )
- cvTsZero(mask);
-
- for( y = 0; y < drows; y++ )
- {
- uchar* dptr = dst->data.ptr + dst->step*y;
- const float* mx = (const float*)(mapx->data.ptr + mapx->step*y);
- const float* my = (const float*)(mapy->data.ptr + mapy->step*y);
- uchar* m = mask ? mask->data.ptr + mask->step*y : 0;
-
- for( x = 0; x < dcols; x++, dptr += elem_size )
- {
- float xs = mx[x];
- float ys = my[x];
- int ixs = cvFloor(xs);
- int iys = cvFloor(ys);
-
- if( (unsigned)(ixs - delta - 1) >= (unsigned)scols1 ||
- (unsigned)(iys - delta - 1) >= (unsigned)srows1 )
- {
- if( m )
- m[x] = 1;
- if( (unsigned)(ixs - delta) >= (unsigned)scols ||
- (unsigned)(iys - delta) >= (unsigned)srows )
- continue;
- }
-
- xs -= ixs;
- ys -= iys;
-
- switch( depth )
- {
- case CV_8U:
- {
- const uchar* sptr = sptr0 + iys*step + ixs*cn;
- for( k = 0; k < cn; k++ )
- {
- float v00 = sptr[k];
- float v01 = sptr[cn + k];
- float v10 = sptr[step + k];
- float v11 = sptr[step + cn + k];
-
- v00 = v00 + xs*(v01 - v00);
- v10 = v10 + xs*(v11 - v10);
- v00 = v00 + ys*(v10 - v00);
- dptr[k] = (uchar)cvRound(v00);
- }
- }
- break;
- case CV_16U:
- {
- const ushort* sptr = (const ushort*)sptr0 + iys*step + ixs*cn;
- for( k = 0; k < cn; k++ )
- {
- float v00 = sptr[k];
- float v01 = sptr[cn + k];
- float v10 = sptr[step + k];
- float v11 = sptr[step + cn + k];
-
- v00 = v00 + xs*(v01 - v00);
- v10 = v10 + xs*(v11 - v10);
- v00 = v00 + ys*(v10 - v00);
- ((ushort*)dptr)[k] = (ushort)cvRound(v00);
- }
- }
- break;
- case CV_32F:
- {
- const float* sptr = (const float*)sptr0 + iys*step + ixs*cn;
- for( k = 0; k < cn; k++ )
- {
- float v00 = sptr[k];
- float v01 = sptr[cn + k];
- float v10 = sptr[step + k];
- float v11 = sptr[step + cn + k];
-
- v00 = v00 + xs*(v01 - v00);
- v10 = v10 + xs*(v11 - v10);
- v00 = v00 + ys*(v10 - v00);
- ((float*)dptr)[k] = (float)v00;
- }
- }
- break;
- default:
- assert(0);
- }
- }
- }
-}
-
-/////////////////////////
-
-class CV_WarpAffineTest : public CV_ImgWarpBaseTest
-{
-public:
- CV_WarpAffineTest();
-
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void run_func();
- int prepare_test_case( int test_case_idx );
- void prepare_to_validation( int /*test_case_idx*/ );
- double get_success_error_level( int test_case_idx, int i, int j );
-
- int write_default_params(CvFileStorage* fs);
- void get_timing_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types,
- CvSize** whole_sizes, bool *are_images );
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
-};
-
-
-CV_WarpAffineTest::CV_WarpAffineTest()
- : CV_ImgWarpBaseTest( "warp-affine", "cvWarpAffine", true )
-{
- //spatial_scale_zoom = spatial_scale_decimate;
- test_array[TEMP].push(NULL);
- test_array[TEMP].push(NULL);
-
- spatial_scale_decimate = spatial_scale_zoom;
-
- default_timing_param_names = imgwarp_affine_param_names;
-}
-
-
-int CV_WarpAffineTest::write_default_params( CvFileStorage* fs )
-{
- int code = CV_ImgWarpBaseTest::write_default_params( fs );
- if( code < 0 )
- return code;
-
- if( ts->get_testing_mode() == CvTS::TIMING_MODE )
- {
- int i;
- start_write_param( fs );
-
- cvStartWriteStruct( fs, "rotate_scale", CV_NODE_SEQ+CV_NODE_FLOW );
- for( i = 0; imgwarp_affine_rotate_scale[i][0] >= 0; i++ )
- {
- cvStartWriteStruct( fs, 0, CV_NODE_SEQ+CV_NODE_FLOW );
- cvWriteRawData( fs, imgwarp_affine_rotate_scale[i], 4, "d" );
- cvEndWriteStruct(fs);
- }
- cvEndWriteStruct(fs);
- }
-
- return code;
-}
-
-
-void CV_WarpAffineTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CV_ImgWarpBaseTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- CvSize sz = sizes[INPUT][0];
- // run for the second time to get output of a different size
- CV_ImgWarpBaseTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- sizes[INPUT][0] = sz;
- sizes[INPUT][1] = cvSize( 3, 2 );
- sizes[TEMP][0] = sizes[TEMP][1] = sizes[INPUT_OUTPUT][0];
- types[TEMP][0] = types[TEMP][1] = CV_32FC1;
-}
-
-
-void CV_WarpAffineTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images )
-{
- CV_ImgWarpBaseTest::get_timing_test_array_types_and_sizes( test_case_idx, sizes, types,
- whole_sizes, are_images );
-
- sizes[INPUT][1] = whole_sizes[INPUT][1] = cvSize(3,2);
- sizes[TEMP][0] = whole_sizes[TEMP][0] =
- sizes[TEMP][1] = whole_sizes[TEMP][1] = cvSize(0,0);
- types[INPUT][1] = CV_64FC1;
-
- interpolation = CV_INTER_LINEAR;
-}
-
-
-void CV_WarpAffineTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- double coeffs[4];
- const CvFileNode* node = find_timing_param( "rotate_scale" );
- assert( node && CV_NODE_IS_SEQ(node->tag) );
- cvReadRawData( ts->get_file_storage(), node, coeffs, "4d" );
-
- sprintf( ptr, "fx=%.2f,fy=%.2f,angle=%.1fdeg,scale=%.1f,", coeffs[0], coeffs[1], coeffs[2], coeffs[3] );
- ptr += strlen(ptr);
- params_left -= 4;
-
- CV_ImgWarpBaseTest::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-
-void CV_WarpAffineTest::run_func()
-{
- cvWarpAffine( test_array[INPUT][0], test_array[INPUT_OUTPUT][0],
- &test_mat[INPUT][1], interpolation );
-}
-
-
-double CV_WarpAffineTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- int depth = CV_MAT_DEPTH(test_mat[INPUT][0].type);
- return depth == CV_8U ? 16 : depth == CV_16U ? 1024 : 5e-2;
-}
-
-
-int CV_WarpAffineTest::prepare_test_case( int test_case_idx )
-{
- CvRNG* rng = ts->get_rng();
- int code = CV_ImgWarpBaseTest::prepare_test_case( test_case_idx );
- const CvMat* src = &test_mat[INPUT][0];
- const CvMat* dst = &test_mat[INPUT_OUTPUT][0];
- CvMat* mat = &test_mat[INPUT][1];
- CvPoint2D32f center;
- double scale, angle;
-
- if( code <= 0 )
- return code;
-
- if( ts->get_testing_mode() == CvTS::CORRECTNESS_CHECK_MODE )
- {
- double buf[6];
- CvMat tmp = cvMat( 2, 3, mat->type, buf );
-
- center.x = (float)((cvTsRandReal(rng)*1.2 - 0.1)*src->cols);
- center.y = (float)((cvTsRandReal(rng)*1.2 - 0.1)*src->rows);
- angle = cvTsRandReal(rng)*360;
- scale = ((double)dst->rows/src->rows + (double)dst->cols/src->cols)*0.5;
- cv2DRotationMatrix( center, angle, scale, mat );
- cvRandArr( rng, &tmp, CV_RAND_NORMAL, cvScalarAll(1.), cvScalarAll(0.01) );
- cvMaxS( &tmp, 0.9, &tmp );
- cvMinS( &tmp, 1.1, &tmp );
- cvMul( &tmp, mat, mat, 1. );
- }
- else
- {
- double coeffs[4];
- const CvFileNode* node = find_timing_param( "rotate_scale" );
-
- assert( node && CV_NODE_IS_SEQ(node->tag) );
- cvReadRawData( ts->get_file_storage(), node, coeffs, "4d" );
-
- center.x = (float)(coeffs[0]*src->cols);
- center.y = (float)(coeffs[1]*src->rows);
- angle = coeffs[2];
- scale = coeffs[3];
- cv2DRotationMatrix( center, angle, scale, mat );
- }
-
- return code;
-}
-
-
-void CV_WarpAffineTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- CvMat* src = &test_mat[INPUT][0];
- CvMat* dst = &test_mat[REF_INPUT_OUTPUT][0];
- CvMat* dst0 = &test_mat[INPUT_OUTPUT][0];
- CvMat* mapx = &test_mat[TEMP][0];
- CvMat* mapy = &test_mat[TEMP][1];
- int x, y;
- double m[6], tm[6];
- CvMat srcAb = cvMat(2, 3, CV_64FC1, tm ), A, b, invA, invAb, dstAb = cvMat( 2, 3, CV_64FC1, m );
-
- //cvInvert( &tM, &M, CV_LU );
- // [R|t] -> [R^-1 | -(R^-1)*t]
- cvTsConvert( &test_mat[INPUT][1], &srcAb );
- cvGetCols( &srcAb, &A, 0, 2 );
- cvGetCol( &srcAb, &b, 2 );
- cvGetCols( &dstAb, &invA, 0, 2 );
- cvGetCol( &dstAb, &invAb, 2 );
- cvInvert( &A, &invA, CV_SVD );
- cvGEMM( &invA, &b, -1, 0, 0, &invAb );
-
- for( y = 0; y < dst->rows; y++ )
- {
- float* mx = (float*)(mapx->data.ptr + y*mapx->step);
- float* my = (float*)(mapy->data.ptr + y*mapy->step);
-
- for( x = 0; x < dst->cols; x++ )
- {
- mx[x] = (float)(x*m[0] + y*m[1] + m[2]);
- my[x] = (float)(x*m[3] + y*m[4] + m[5]);
- }
- }
-
- CvMat* mask = cvCreateMat( dst->rows, dst->cols, CV_8U );
- cvTsRemap( src, dst, mapx, mapy, mask );
- cvTsZero( dst, mask );
- cvTsZero( dst0, mask );
- cvReleaseMat( &mask );
-}
-
-
-CV_WarpAffineTest warp_affine_test;
-
-
-
-/////////////////////////
-
-class CV_WarpPerspectiveTest : public CV_ImgWarpBaseTest
-{
-public:
- CV_WarpPerspectiveTest();
-
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void run_func();
- int prepare_test_case( int test_case_idx );
- void prepare_to_validation( int /*test_case_idx*/ );
- double get_success_error_level( int test_case_idx, int i, int j );
-
- int write_default_params(CvFileStorage* fs);
- void get_timing_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types,
- CvSize** whole_sizes, bool *are_images );
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
-};
-
-
-CV_WarpPerspectiveTest::CV_WarpPerspectiveTest()
- : CV_ImgWarpBaseTest( "warp-perspective", "cvWarpPerspective", true )
-{
- //spatial_scale_zoom = spatial_scale_decimate;
- test_array[TEMP].push(NULL);
- test_array[TEMP].push(NULL);
-
- spatial_scale_decimate = spatial_scale_zoom;
- default_timing_param_names = imgwarp_perspective_param_names;
-}
-
-
-int CV_WarpPerspectiveTest::write_default_params( CvFileStorage* fs )
-{
- int code = CV_ImgWarpBaseTest::write_default_params( fs );
- if( code < 0 )
- return code;
-
- if( ts->get_testing_mode() == CvTS::TIMING_MODE )
- {
- int i;
- start_write_param( fs );
-
- cvStartWriteStruct( fs, "shift_vtx", CV_NODE_SEQ+CV_NODE_FLOW );
- for( i = 0; imgwarp_perspective_shift_vtx[i][0] >= 0; i++ )
- {
- cvStartWriteStruct( fs, 0, CV_NODE_SEQ+CV_NODE_FLOW );
- cvWriteRawData( fs, imgwarp_perspective_shift_vtx[i], 8, "d" );
- cvEndWriteStruct(fs);
- }
- cvEndWriteStruct(fs);
- }
-
- return code;
-}
-
-
-void CV_WarpPerspectiveTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CV_ImgWarpBaseTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- CvSize sz = sizes[INPUT][0];
- // run for the second time to get output of a different size
- CV_ImgWarpBaseTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- sizes[INPUT][0] = sz;
- sizes[INPUT][1] = cvSize( 3, 3 );
-
- sizes[TEMP][0] = sizes[TEMP][1] = sizes[INPUT_OUTPUT][0];
- types[TEMP][0] = types[TEMP][1] = CV_32FC1;
-}
-
-
-void CV_WarpPerspectiveTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images )
-{
- CV_ImgWarpBaseTest::get_timing_test_array_types_and_sizes( test_case_idx, sizes, types,
- whole_sizes, are_images );
-
- sizes[INPUT][1] = whole_sizes[INPUT][1] = cvSize(3,3);
- sizes[TEMP][0] = whole_sizes[TEMP][0] =
- sizes[TEMP][1] = whole_sizes[TEMP][1] = cvSize(0,0);
- types[INPUT][1] = CV_64FC1;
-
- interpolation = CV_INTER_LINEAR;
-}
-
-
-void CV_WarpPerspectiveTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- CV_ImgWarpBaseTest::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-
-void CV_WarpPerspectiveTest::run_func()
-{
- cvWarpPerspective( test_array[INPUT][0], test_array[INPUT_OUTPUT][0],
- &test_mat[INPUT][1], interpolation );
-}
-
-
-double CV_WarpPerspectiveTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- int depth = CV_MAT_DEPTH(test_mat[INPUT][0].type);
- return depth == CV_8U ? 16 : depth == CV_16U ? 1024 : 5e-2;
-}
-
-
-int CV_WarpPerspectiveTest::prepare_test_case( int test_case_idx )
-{
- CvRNG* rng = ts->get_rng();
- int code = CV_ImgWarpBaseTest::prepare_test_case( test_case_idx );
- const CvMat* src = &test_mat[INPUT][0];
- const CvMat* dst = &test_mat[INPUT_OUTPUT][0];
- CvMat* mat = &test_mat[INPUT][1];
- CvPoint2D32f s[4], d[4];
- int i;
-
- if( code <= 0 )
- return code;
-
- s[0] = cvPoint2D32f(0,0);
- d[0] = cvPoint2D32f(0,0);
- s[1] = cvPoint2D32f(src->cols-1,0);
- d[1] = cvPoint2D32f(dst->cols-1,0);
- s[2] = cvPoint2D32f(src->cols-1,src->rows-1);
- d[2] = cvPoint2D32f(dst->cols-1,dst->rows-1);
- s[3] = cvPoint2D32f(0,src->rows-1);
- d[3] = cvPoint2D32f(0,dst->rows-1);
-
- if( ts->get_testing_mode() == CvTS::CORRECTNESS_CHECK_MODE )
- {
- float buf[16];
- CvMat tmp = cvMat( 1, 16, CV_32FC1, buf );
-
- cvRandArr( rng, &tmp, CV_RAND_NORMAL, cvScalarAll(0.), cvScalarAll(0.1) );
-
- for( i = 0; i < 4; i++ )
- {
- s[i].x += buf[i*4]*src->cols/2;
- s[i].y += buf[i*4+1]*src->rows/2;
- d[i].x += buf[i*4+2]*dst->cols/2;
- d[i].y += buf[i*4+3]*dst->rows/2;
- }
- }
- else
- {
- double coeffs[8];
- const CvFileNode* node = find_timing_param( "shift_vtx" );
-
- assert( node && CV_NODE_IS_SEQ(node->tag) );
- cvReadRawData( ts->get_file_storage(), node, coeffs, "8d" );
-
- for( i = 0; i < 4; i++ )
- {
- d[i].x += (float)(coeffs[i*2]*src->cols*(i == 0 || i == 3 ? 1 : -1));
- d[i].y += (float)(coeffs[i*2+1]*src->rows*(i == 0 || i == 1 ? 1 : -1));
- }
- }
-
- cvWarpPerspectiveQMatrix( s, d, mat );
- return code;
-}
-
-
-void CV_WarpPerspectiveTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- CvMat* src = &test_mat[INPUT][0];
- CvMat* dst = &test_mat[REF_INPUT_OUTPUT][0];
- CvMat* dst0 = &test_mat[INPUT_OUTPUT][0];
- CvMat* mapx = &test_mat[TEMP][0];
- CvMat* mapy = &test_mat[TEMP][1];
- int x, y;
- double m[9], tm[9];
- CvMat srcM = cvMat(3, 3, CV_64FC1, tm ), dstM = cvMat( 3, 3, CV_64FC1, m );
-
- //cvInvert( &tM, &M, CV_LU );
- // [R|t] -> [R^-1 | -(R^-1)*t]
- cvTsConvert( &test_mat[INPUT][1], &srcM );
- cvInvert( &srcM, &dstM, CV_SVD );
-
- for( y = 0; y < dst->rows; y++ )
- {
- float* mx = (float*)(mapx->data.ptr + y*mapx->step);
- float* my = (float*)(mapy->data.ptr + y*mapy->step);
-
- for( x = 0; x < dst->cols; x++ )
- {
- double xs = x*m[0] + y*m[1] + m[2];
- double ys = x*m[3] + y*m[4] + m[5];
- double ds = x*m[6] + y*m[7] + m[8];
-
- ds = ds ? 1./ds : 0;
- xs *= ds;
- ys *= ds;
-
- mx[x] = (float)xs;
- my[x] = (float)ys;
- }
- }
-
- CvMat* mask = cvCreateMat( dst->rows, dst->cols, CV_8U );
- cvTsRemap( src, dst, mapx, mapy, mask );
- cvTsZero( dst, mask );
- cvTsZero( dst0, mask );
- cvReleaseMat( &mask );
-}
-
-
-CV_WarpPerspectiveTest warp_perspective_test;
-
-
-
-/////////////////////////
-
-void cvTsInitUndistortMap( const CvMat* _a0, const CvMat* _k0, CvMat* _mapx, CvMat* _mapy )
-{
- CvMat* mapx = cvCreateMat(_mapx->rows,_mapx->cols,CV_32F);
- CvMat* mapy = cvCreateMat(_mapx->rows,_mapx->cols,CV_32F);
-
- int u, v;
- double a[9], k[5]={0,0,0,0,0};
- CvMat _a = cvMat(3, 3, CV_64F, a);
- CvMat _k = cvMat(_k0->rows,_k0->cols,
- CV_MAKETYPE(CV_64F,CV_MAT_CN(_k0->type)),k);
- double fx, fy, cx, cy, ifx, ify, cxn, cyn;
-
- cvTsConvert( _a0, &_a );
- cvTsConvert( _k0, &_k );
- fx = a[0]; fy = a[4]; cx = a[2]; cy = a[5];
- ifx = 1./fx; ify = 1./fy;
- cxn = cx;//(mapy->cols - 1)*0.5;
- cyn = cy;//(mapy->rows - 1)*0.5;
-
- for( v = 0; v < mapy->rows; v++ )
- {
- float* mx = (float*)(mapx->data.ptr + v*mapx->step);
- float* my = (float*)(mapy->data.ptr + v*mapy->step);
-
- for( u = 0; u < mapy->cols; u++ )
- {
- double x = (u - cxn)*ifx;
- double y = (v - cyn)*ify;
- double x2 = x*x, y2 = y*y;
- double r2 = x2 + y2;
- double cdist = 1 + (k[0] + (k[1] + k[4]*r2)*r2)*r2;
- double x1 = x*cdist + k[2]*2*x*y + k[3]*(r2 + 2*x2);
- double y1 = y*cdist + k[3]*2*x*y + k[2]*(r2 + 2*y2);
-
- my[u] = (float)(y1*fy + cy);
- mx[u] = (float)(x1*fx + cx);
- }
- }
-
- if (_mapy)
- {
- cvCopy(mapy,_mapy);
- cvCopy(mapx,_mapx);
- }
- else
- {
- for (int i=0;i<mapx->rows;i++)
- {
- float* _mx = (float*)(_mapx->data.ptr + _mapx->step*i);
- float* _my = (float*)(_mapx->data.ptr + _mapx->step*i);
- for (int j=0;j<mapx->cols;j++)
- {
- _mx[2*j] = mapx->data.fl[j+i*mapx->cols];
- _my[2*j+1] = mapy->data.fl[j+i*mapy->cols];
- }
- }
- }
- cvReleaseMat(&mapx);
- cvReleaseMat(&mapy);
-}
-
-
-static double remap_undistort_params[] = { 0.5, 0.5, 0.5, 0.5, 0.01, -0.01, 0.001, -0.001 };
-
-class CV_RemapTest : public CV_ImgWarpBaseTest
-{
-public:
- CV_RemapTest();
-
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void run_func();
- int prepare_test_case( int test_case_idx );
- void prepare_to_validation( int /*test_case_idx*/ );
- double get_success_error_level( int test_case_idx, int i, int j );
- void fill_array( int test_case_idx, int i, int j, CvMat* arr );
-
- int write_default_params(CvFileStorage* fs);
- void get_timing_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types,
- CvSize** whole_sizes, bool *are_images );
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
-};
-
-
-CV_RemapTest::CV_RemapTest()
- : CV_ImgWarpBaseTest( "warp-remap", "cvRemap", false )
-{
- //spatial_scale_zoom = spatial_scale_decimate;
- test_array[INPUT].push(NULL);
- test_array[INPUT].push(NULL);
-
- spatial_scale_decimate = spatial_scale_zoom;
- //default_timing_param_names = imgwarp_perspective_param_names;
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;
- default_timing_param_names = 0;
-}
-
-
-int CV_RemapTest::write_default_params( CvFileStorage* fs )
-{
- int code = CV_ImgWarpBaseTest::write_default_params( fs );
- if( code < 0 )
- return code;
-
- if( ts->get_testing_mode() == CvTS::TIMING_MODE )
- {
- int i;
- start_write_param( fs );
-
- cvStartWriteStruct( fs, "params", CV_NODE_SEQ+CV_NODE_FLOW );
- for( i = 0; i < 8; i++ )
- cvWriteReal( fs, 0, remap_undistort_params[i] );
- cvEndWriteStruct(fs);
- }
-
- return code;
-}
-
-
-void CV_RemapTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CV_ImgWarpBaseTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- types[INPUT][1] = types[INPUT][2] = CV_32FC1;
- interpolation = CV_INTER_LINEAR;
-}
-
-
-void CV_RemapTest::fill_array( int test_case_idx, int i, int j, CvMat* arr )
-{
- if( i != INPUT )
- CV_ImgWarpBaseTestImpl::fill_array( test_case_idx, i, j, arr );
-}
-
-void CV_RemapTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images )
-{
- CV_ImgWarpBaseTest::get_timing_test_array_types_and_sizes( test_case_idx, sizes, types,
- whole_sizes, are_images );
- types[INPUT][1] = types[INPUT][2] = CV_32FC1;
- interpolation = CV_INTER_LINEAR;
-}
-
-
-void CV_RemapTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- CV_ImgWarpBaseTest::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-
-void CV_RemapTest::run_func()
-{
- cvRemap( test_array[INPUT][0], test_array[INPUT_OUTPUT][0],
- test_array[INPUT][1], test_array[INPUT][2], interpolation );
-}
-
-
-double CV_RemapTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- int depth = CV_MAT_DEPTH(test_mat[INPUT][0].type);
- return depth == CV_8U ? 16 : depth == CV_16U ? 1024 : 5e-2;
-}
-
-
-int CV_RemapTest::prepare_test_case( int test_case_idx )
-{
- CvRNG* rng = ts->get_rng();
- int code = CV_ImgWarpBaseTest::prepare_test_case( test_case_idx );
- const CvMat* src = &test_mat[INPUT][0];
- double a[9] = {0,0,0,0,0,0,0,0,1}, k[4];
- CvMat _a = cvMat( 3, 3, CV_64F, a );
- CvMat _k = cvMat( 4, 1, CV_64F, k );
- double sz = MAX(src->rows, src->cols);
-
- if( code <= 0 )
- return code;
-
- if( ts->get_testing_mode() == CvTS::CORRECTNESS_CHECK_MODE )
- {
- double aspect_ratio = cvTsRandReal(rng)*0.6 + 0.7;
- a[2] = (src->cols - 1)*0.5 + cvTsRandReal(rng)*10 - 5;
- a[5] = (src->rows - 1)*0.5 + cvTsRandReal(rng)*10 - 5;
- a[0] = sz/(0.9 - cvTsRandReal(rng)*0.6);
- a[4] = aspect_ratio*a[0];
- k[0] = cvTsRandReal(rng)*0.06 - 0.03;
- k[1] = cvTsRandReal(rng)*0.06 - 0.03;
- if( k[0]*k[1] > 0 )
- k[1] = -k[1];
- k[2] = cvTsRandReal(rng)*0.004 - 0.002;
- k[3] = cvTsRandReal(rng)*0.004 - 0.002;
- }
- else
- {
- int i;
- a[2] = (src->cols - 1)*remap_undistort_params[0];
- a[5] = (src->rows - 1)*remap_undistort_params[1];
- a[0] = sz/remap_undistort_params[2];
- a[4] = sz/remap_undistort_params[3];
- for( i = 0; i < 4; i++ )
- k[i] = remap_undistort_params[i+4];
- }
-
- cvTsInitUndistortMap( &_a, &_k, &test_mat[INPUT][1], &test_mat[INPUT][2] );
- return code;
-}
-
-
-void CV_RemapTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- CvMat* dst = &test_mat[REF_INPUT_OUTPUT][0];
- CvMat* dst0 = &test_mat[INPUT_OUTPUT][0];
- CvMat* mask = cvCreateMat( dst->rows, dst->cols, CV_8U );
- cvTsRemap( &test_mat[INPUT][0], dst,
- &test_mat[INPUT][1], &test_mat[INPUT][2],
- mask, interpolation );
- cvTsZero( dst, mask );
- cvTsZero( dst0, mask );
- cvReleaseMat( &mask );
-}
-
-
-CV_RemapTest remap_test;
-
-
-////////////////////////////// undistort /////////////////////////////////
-
-class CV_UndistortTest : public CV_ImgWarpBaseTest
-{
-public:
- CV_UndistortTest();
-
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void run_func();
- int prepare_test_case( int test_case_idx );
- void prepare_to_validation( int /*test_case_idx*/ );
- double get_success_error_level( int test_case_idx, int i, int j );
- void fill_array( int test_case_idx, int i, int j, CvMat* arr );
-
- int write_default_params(CvFileStorage* fs);
- void get_timing_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types,
- CvSize** whole_sizes, bool *are_images );
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
-
-private:
- bool useCPlus;
- cv::Mat input0;
- cv::Mat input1;
- cv::Mat input2;
- cv::Mat input_new_cam;
- cv::Mat input_output;
-
- bool zero_new_cam;
- bool zero_distortion;
-};
-
-
-CV_UndistortTest::CV_UndistortTest()
- : CV_ImgWarpBaseTest( "warp-undistort", "cvUndistort2", false )
-{
- //spatial_scale_zoom = spatial_scale_decimate;
- test_array[INPUT].push(NULL);
- test_array[INPUT].push(NULL);
- test_array[INPUT].push(NULL);
-
- spatial_scale_decimate = spatial_scale_zoom;
- //default_timing_param_names = imgwarp_perspective_param_names;
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;
- default_timing_param_names = 0;
-}
-
-
-int CV_UndistortTest::write_default_params( CvFileStorage* fs )
-{
- int code = CV_ImgWarpBaseTest::write_default_params( fs );
- if( code < 0 )
- return code;
-
- if( ts->get_testing_mode() == CvTS::TIMING_MODE )
- {
- int i;
- start_write_param( fs );
-
- cvStartWriteStruct( fs, "params", CV_NODE_SEQ+CV_NODE_FLOW );
- for( i = 0; i < 8; i++ )
- cvWriteReal( fs, 0, remap_undistort_params[i] );
- cvEndWriteStruct(fs);
- }
-
- return code;
-}
-
-
-void CV_UndistortTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- CV_ImgWarpBaseTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- int type = types[INPUT][0];
- type = CV_MAKETYPE( CV_8U, CV_MAT_CN(type) );
- types[INPUT][0] = types[INPUT_OUTPUT][0] = types[REF_INPUT_OUTPUT][0] = type;
- types[INPUT][1] = cvTsRandInt(rng)%2 ? CV_64F : CV_32F;
- types[INPUT][2] = cvTsRandInt(rng)%2 ? CV_64F : CV_32F;
- sizes[INPUT][1] = cvSize(3,3);
- sizes[INPUT][2] = cvTsRandInt(rng)%2 ? cvSize(4,1) : cvSize(1,4);
- types[INPUT][3] = types[INPUT][1];
- sizes[INPUT][3] = sizes[INPUT][1];
- interpolation = CV_INTER_LINEAR;
-}
-
-
-void CV_UndistortTest::fill_array( int test_case_idx, int i, int j, CvMat* arr )
-{
- if( i != INPUT )
- CV_ImgWarpBaseTestImpl::fill_array( test_case_idx, i, j, arr );
-}
-
-void CV_UndistortTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images )
-{
- CV_ImgWarpBaseTest::get_timing_test_array_types_and_sizes( test_case_idx, sizes, types,
- whole_sizes, are_images );
- types[INPUT][1] = types[INPUT][2] = CV_32FC1;
- interpolation = CV_INTER_LINEAR;
-}
-
-
-void CV_UndistortTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- CV_ImgWarpBaseTest::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-
-void CV_UndistortTest::run_func()
-{
- if (!useCPlus)
- {
- cvUndistort2( test_array[INPUT][0], test_array[INPUT_OUTPUT][0],
- &test_mat[INPUT][1], &test_mat[INPUT][2] );
- }
- else
- {
- if (zero_distortion)
- {
- cv::undistort(input0,input_output,input1,cv::Mat());
- }
- else
- {
- cv::undistort(input0,input_output,input1,input2);
- }
- }
-}
-
-
-double CV_UndistortTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- int depth = CV_MAT_DEPTH(test_mat[INPUT][0].type);
- return depth == CV_8U ? 16 : depth == CV_16U ? 1024 : 5e-2;
-}
-
-
-int CV_UndistortTest::prepare_test_case( int test_case_idx )
-{
- CvRNG* rng = ts->get_rng();
- int code = CV_ImgWarpBaseTest::prepare_test_case( test_case_idx );
-
- const CvMat* src = &test_mat[INPUT][0];
- double k[4], a[9] = {0,0,0,0,0,0,0,0,1};
- double sz = MAX(src->rows, src->cols);
-
- double new_cam[9] = {0,0,0,0,0,0,0,0,1};
- CvMat _new_cam = cvMat(test_mat[INPUT][3].rows,test_mat[INPUT][3].cols,CV_64F,new_cam);
- CvMat* _new_cam0 = &test_mat[INPUT][3];
-
- CvMat* _a0 = &test_mat[INPUT][1], *_k0 = &test_mat[INPUT][2];
- CvMat _a = cvMat(3,3,CV_64F,a);
- CvMat _k = cvMat(_k0->rows,_k0->cols, CV_MAKETYPE(CV_64F,CV_MAT_CN(_k0->type)),k);
-
- if( code <= 0 )
- return code;
-
- if( ts->get_testing_mode() == CvTS::CORRECTNESS_CHECK_MODE )
- {
- double aspect_ratio = cvTsRandReal(rng)*0.6 + 0.7;
- a[2] = (src->cols - 1)*0.5 + cvTsRandReal(rng)*10 - 5;
- a[5] = (src->rows - 1)*0.5 + cvTsRandReal(rng)*10 - 5;
- a[0] = sz/(0.9 - cvTsRandReal(rng)*0.6);
- a[4] = aspect_ratio*a[0];
- k[0] = cvTsRandReal(rng)*0.06 - 0.03;
- k[1] = cvTsRandReal(rng)*0.06 - 0.03;
- if( k[0]*k[1] > 0 )
- k[1] = -k[1];
- if( cvTsRandInt(rng)%4 != 0 )
- {
- k[2] = cvTsRandReal(rng)*0.004 - 0.002;
- k[3] = cvTsRandReal(rng)*0.004 - 0.002;
- }
- else
- k[2] = k[3] = 0;
-
- new_cam[0] = a[0] + (cvTsRandReal(rng) - (double)0.5)*0.2*a[0]; //10%
- new_cam[4] = a[4] + (cvTsRandReal(rng) - (double)0.5)*0.2*a[4]; //10%
- new_cam[2] = a[2] + (cvTsRandReal(rng) - (double)0.5)*0.3*test_mat[INPUT][0].rows; //15%
- new_cam[5] = a[5] + (cvTsRandReal(rng) - (double)0.5)*0.3*test_mat[INPUT][0].cols; //15%
- }
- else
- {
- int i;
- a[2] = (src->cols - 1)*remap_undistort_params[0];
- a[5] = (src->rows - 1)*remap_undistort_params[1];
- a[0] = sz/remap_undistort_params[2];
- a[4] = sz/remap_undistort_params[3];
- for( i = 0; i < 4; i++ )
- k[i] = remap_undistort_params[i+4];
- }
-
- cvTsConvert( &_a, _a0 );
-
-
- zero_distortion = (cvRandInt(rng)%2) == 0 ? false : true;
- cvTsConvert( &_k, _k0 );
-
- zero_new_cam = (cvRandInt(rng)%2) == 0 ? false : true;
- cvTsConvert( &_new_cam, _new_cam0 );
-
-
- //Testing C++ code
- useCPlus = ((cvTsRandInt(rng) % 2)!=0);
- if (useCPlus)
- {
- input0 = &test_mat[INPUT][0];
- input1 = &test_mat[INPUT][1];
- input2 = &test_mat[INPUT][2];
- input_new_cam = &test_mat[INPUT][3];
- }
-
- return code;
-}
-
-
-void CV_UndistortTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- if (useCPlus)
- {
- CvMat result = input_output;
- CvMat* test_input_output = &test_mat[INPUT_OUTPUT][0];
- cvTsConvert(&result,test_input_output);
- }
- CvMat* src = &test_mat[INPUT][0];
- CvMat* dst = &test_mat[REF_INPUT_OUTPUT][0];
- CvMat* dst0 = &test_mat[INPUT_OUTPUT][0];
- CvMat* mapx = cvCreateMat( dst->rows, dst->cols, CV_32FC1 );
- CvMat* mapy = cvCreateMat( dst->rows, dst->cols, CV_32FC1 );
- cvTsInitUndistortMap( &test_mat[INPUT][1], &test_mat[INPUT][2],
- mapx, mapy );
- CvMat* mask = cvCreateMat( dst->rows, dst->cols, CV_8U );
- cvTsRemap( src, dst, mapx, mapy, mask, interpolation );
- cvTsZero( dst, mask );
- cvTsZero( dst0, mask );
-
- cvReleaseMat( &mapx );
- cvReleaseMat( &mapy );
- cvReleaseMat( &mask );
-}
-
-
-CV_UndistortTest undistort_test;
-
-
-
-class CV_UndistortMapTest : public CvArrTest
-{
-public:
- CV_UndistortMapTest();
-
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void run_func();
- int prepare_test_case( int test_case_idx );
- void prepare_to_validation( int /*test_case_idx*/ );
- double get_success_error_level( int test_case_idx, int i, int j );
- void fill_array( int test_case_idx, int i, int j, CvMat* arr );
-
- int write_default_params(CvFileStorage* fs);
- void get_timing_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types,
- CvSize** whole_sizes, bool *are_images );
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
-private:
- bool dualChannel;
-};
-
-
-CV_UndistortMapTest::CV_UndistortMapTest()
- : CvArrTest( "warp-undistort-map", "cvInitUndistortMap", "" )
-{
- test_array[INPUT].push(NULL);
- test_array[INPUT].push(NULL);
- test_array[OUTPUT].push(NULL);
- test_array[OUTPUT].push(NULL);
- test_array[REF_OUTPUT].push(NULL);
- test_array[REF_OUTPUT].push(NULL);
-
- element_wise_relative_error = false;
-
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;
- default_timing_param_names = 0;
-}
-
-
-int CV_UndistortMapTest::write_default_params( CvFileStorage* fs )
-{
- int code = CvArrTest::write_default_params( fs );
- if( code < 0 )
- return code;
-
- if( ts->get_testing_mode() == CvTS::TIMING_MODE )
- {
- int i;
- start_write_param( fs );
-
- cvStartWriteStruct( fs, "params", CV_NODE_SEQ+CV_NODE_FLOW );
- for( i = 0; i < 8; i++ )
- cvWriteReal( fs, 0, remap_undistort_params[i] );
- cvEndWriteStruct(fs);
- }
-
- return code;
-}
-
-
-void CV_UndistortMapTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- CvArrTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- int depth = cvTsRandInt(rng)%2 ? CV_64F : CV_32F;
-
-
-
- CvSize sz = sizes[OUTPUT][0];
- types[INPUT][0] = types[INPUT][1] = depth;
- dualChannel = cvTsRandInt(rng)%2 == 0;
- types[OUTPUT][0] = types[OUTPUT][1] =
- types[REF_OUTPUT][0] = types[REF_OUTPUT][1] = dualChannel ? CV_32FC2 : CV_32F;
- sizes[INPUT][0] = cvSize(3,3);
- sizes[INPUT][1] = cvTsRandInt(rng)%2 ? cvSize(4,1) : cvSize(1,4);
-
- sz.width = MAX(sz.width,16);
- sz.height = MAX(sz.height,16);
- sizes[OUTPUT][0] = sizes[OUTPUT][1] =
- sizes[REF_OUTPUT][0] = sizes[REF_OUTPUT][1] = sz;
-}
-
-
-void CV_UndistortMapTest::fill_array( int test_case_idx, int i, int j, CvMat* arr )
-{
- if( i != INPUT )
- CvArrTest::fill_array( test_case_idx, i, j, arr );
-}
-
-void CV_UndistortMapTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images )
-{
- CvArrTest::get_timing_test_array_types_and_sizes( test_case_idx, sizes, types,
- whole_sizes, are_images );
-}
-
-
-void CV_UndistortMapTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- CvArrTest::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-
-void CV_UndistortMapTest::run_func()
-{
- if (!dualChannel )
- cvInitUndistortMap( &test_mat[INPUT][0], &test_mat[INPUT][1],
- test_array[OUTPUT][0], test_array[OUTPUT][1] );
- else
- cvInitUndistortMap( &test_mat[INPUT][0], &test_mat[INPUT][1],
- test_array[OUTPUT][0], 0 );
-
-}
-
-
-double CV_UndistortMapTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- return 1e-3;
-}
-
-
-int CV_UndistortMapTest::prepare_test_case( int test_case_idx )
-{
- CvRNG* rng = ts->get_rng();
- int code = CvArrTest::prepare_test_case( test_case_idx );
- const CvMat* mapx = &test_mat[OUTPUT][0];
- double k[4], a[9] = {0,0,0,0,0,0,0,0,1};
- double sz = MAX(mapx->rows, mapx->cols);
- CvMat* _a0 = &test_mat[INPUT][0], *_k0 = &test_mat[INPUT][1];
- CvMat _a = cvMat(3,3,CV_64F,a);
- CvMat _k = cvMat(_k0->rows,_k0->cols, CV_MAKETYPE(CV_64F,CV_MAT_CN(_k0->type)),k);
-
- if( code <= 0 )
- return code;
-
- if( ts->get_testing_mode() == CvTS::CORRECTNESS_CHECK_MODE )
- {
- double aspect_ratio = cvTsRandReal(rng)*0.6 + 0.7;
- a[2] = (mapx->cols - 1)*0.5 + cvTsRandReal(rng)*10 - 5;
- a[5] = (mapx->rows - 1)*0.5 + cvTsRandReal(rng)*10 - 5;
- a[0] = sz/(0.9 - cvTsRandReal(rng)*0.6);
- a[4] = aspect_ratio*a[0];
- k[0] = cvTsRandReal(rng)*0.06 - 0.03;
- k[1] = cvTsRandReal(rng)*0.06 - 0.03;
- if( k[0]*k[1] > 0 )
- k[1] = -k[1];
- k[2] = cvTsRandReal(rng)*0.004 - 0.002;
- k[3] = cvTsRandReal(rng)*0.004 - 0.002;
- }
- else
- {
- int i;
- a[2] = (mapx->cols - 1)*remap_undistort_params[0];
- a[5] = (mapx->rows - 1)*remap_undistort_params[1];
- a[0] = sz/remap_undistort_params[2];
- a[4] = sz/remap_undistort_params[3];
- for( i = 0; i < 4; i++ )
- k[i] = remap_undistort_params[i+4];
- }
-
- cvTsConvert( &_a, _a0 );
- cvTsConvert( &_k, _k0 );
-
- if (dualChannel)
- {
- cvZero(&test_mat[REF_OUTPUT][1]);
- cvZero(&test_mat[OUTPUT][1]);
- }
-
- return code;
-}
-
-
-void CV_UndistortMapTest::prepare_to_validation( int )
-{
- if (!dualChannel )
- cvTsInitUndistortMap( &test_mat[INPUT][0], &test_mat[INPUT][1],
- &test_mat[REF_OUTPUT][0], &test_mat[REF_OUTPUT][1] );
- else
- cvTsInitUndistortMap( &test_mat[INPUT][0], &test_mat[INPUT][1],
- &test_mat[REF_OUTPUT][0], 0 );
-}
-
-
-CV_UndistortMapTest undistortmap_test;
-
-
-
-////////////////////////////// GetRectSubPix /////////////////////////////////
-
-static const CvSize rectsubpix_sizes[] = {{11, 11}, {21,21}, {41,41},{-1,-1}};
-
-static void
-cvTsGetQuadrangeSubPix( const CvMat* src, CvMat* dst, double* a )
-{
- int y, x, k, cn;
- int sstep = src->step / sizeof(float);
- int scols = src->cols, srows = src->rows;
-
- assert( CV_MAT_DEPTH(src->type) == CV_32F &&
- CV_ARE_TYPES_EQ(src, dst));
-
- cn = CV_MAT_CN(dst->type);
-
- for( y = 0; y < dst->rows; y++ )
- for( x = 0; x < dst->cols; x++ )
- {
- float* d = (float*)(dst->data.ptr + y*dst->step) + x*cn;
- float sx = (float)(a[0]*x + a[1]*y + a[2]);
- float sy = (float)(a[3]*x + a[4]*y + a[5]);
- int ix = cvFloor(sx), iy = cvFloor(sy);
- int dx = cn, dy = sstep;
- const float* s;
- sx -= ix; sy -= iy;
-
- if( (unsigned)ix >= (unsigned)(scols-1) )
- ix = ix < 0 ? 0 : scols - 1, sx = 0, dx = 0;
- if( (unsigned)iy >= (unsigned)(srows-1) )
- iy = iy < 0 ? 0 : srows - 1, sy = 0, dy = 0;
-
- s = src->data.fl + sstep*iy + ix*cn;
- for( k = 0; k < cn; k++, s++ )
- {
- float t0 = s[0] + sx*(s[dx] - s[0]);
- float t1 = s[dy] + sx*(s[dy + dx] - s[dy]);
- d[k] = t0 + sy*(t1 - t0);
- }
- }
-}
-
-
-class CV_GetRectSubPixTest : public CV_ImgWarpBaseTest
-{
-public:
- CV_GetRectSubPixTest();
-
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void run_func();
- int prepare_test_case( int test_case_idx );
- void prepare_to_validation( int /*test_case_idx*/ );
- double get_success_error_level( int test_case_idx, int i, int j );
- void fill_array( int test_case_idx, int i, int j, CvMat* arr );
-
- int write_default_params(CvFileStorage* fs);
- void get_timing_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types,
- CvSize** whole_sizes, bool *are_images );
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
- CvPoint2D32f center;
- bool test_cpp;
-};
-
-
-CV_GetRectSubPixTest::CV_GetRectSubPixTest()
- : CV_ImgWarpBaseTest( "warp-subpix-rect", "cvGetRectSubPix", false )
-{
- //spatial_scale_zoom = spatial_scale_decimate;
- spatial_scale_decimate = spatial_scale_zoom;
- //default_timing_param_names = imgwarp_perspective_param_names;
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;
- default_timing_param_names = 0;
- test_cpp = false;
-}
-
-
-int CV_GetRectSubPixTest::write_default_params( CvFileStorage* fs )
-{
- int code = CV_ImgWarpBaseTest::write_default_params( fs );
- if( code < 0 )
- return code;
-
- if( ts->get_testing_mode() == CvTS::TIMING_MODE )
- {
- int i;
- start_write_param( fs );
-
- cvStartWriteStruct( fs, "rect_size", CV_NODE_SEQ+CV_NODE_FLOW );
- for( i = 0; rectsubpix_sizes[i].width > 0; i++ )
- {
- cvStartWriteStruct( fs, 0, CV_NODE_SEQ+CV_NODE_FLOW );
- cvWriteInt( fs, 0, rectsubpix_sizes[i].width );
- cvWriteInt( fs, 0, rectsubpix_sizes[i].height );
- cvEndWriteStruct(fs);
- }
- cvEndWriteStruct(fs);
- }
-
- return code;
-}
-
-
-void CV_GetRectSubPixTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- CV_ImgWarpBaseTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- int src_depth = cvTsRandInt(rng) % 2, dst_depth;
- int cn = cvTsRandInt(rng) % 2 ? 3 : 1;
- CvSize src_size, dst_size;
-
- dst_depth = src_depth = src_depth == 0 ? CV_8U : CV_32F;
- if( src_depth < CV_32F && cvTsRandInt(rng) % 2 )
- dst_depth = CV_32F;
-
- types[INPUT][0] = CV_MAKETYPE(src_depth,cn);
- types[INPUT_OUTPUT][0] = types[REF_INPUT_OUTPUT][0] = CV_MAKETYPE(dst_depth,cn);
-
- src_size = sizes[INPUT][0];
- dst_size.width = cvRound(sqrt(cvTsRandReal(rng)*src_size.width) + 1);
- dst_size.height = cvRound(sqrt(cvTsRandReal(rng)*src_size.height) + 1);
- dst_size.width = MIN(dst_size.width,src_size.width);
- dst_size.height = MIN(dst_size.width,src_size.height);
- sizes[INPUT_OUTPUT][0] = sizes[REF_INPUT_OUTPUT][0] = dst_size;
-
- center.x = (float)(cvTsRandReal(rng)*src_size.width);
- center.y = (float)(cvTsRandReal(rng)*src_size.height);
- interpolation = CV_INTER_LINEAR;
-
- test_cpp = (cvTsRandInt(rng) & 256) == 0;
-}
-
-
-void CV_GetRectSubPixTest::fill_array( int test_case_idx, int i, int j, CvMat* arr )
-{
- if( i != INPUT )
- CV_ImgWarpBaseTestImpl::fill_array( test_case_idx, i, j, arr );
-}
-
-void CV_GetRectSubPixTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images )
-{
- CV_ImgWarpBaseTest::get_timing_test_array_types_and_sizes( test_case_idx, sizes, types,
- whole_sizes, are_images );
- interpolation = CV_INTER_LINEAR;
-}
-
-
-void CV_GetRectSubPixTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- CV_ImgWarpBaseTest::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-
-void CV_GetRectSubPixTest::run_func()
-{
- if(!test_cpp)
- cvGetRectSubPix( test_array[INPUT][0], test_array[INPUT_OUTPUT][0], center );
- else
- {
- cv::Mat _out = cv::cvarrToMat(test_array[INPUT_OUTPUT][0]);
- cv::getRectSubPix( cv::cvarrToMat(test_array[INPUT][0]), _out.size(), center, _out, _out.type());
- }
-}
-
-
-double CV_GetRectSubPixTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- int in_depth = CV_MAT_DEPTH(test_mat[INPUT][0].type);
- int out_depth = CV_MAT_DEPTH(test_mat[INPUT_OUTPUT][0].type);
-
- return in_depth >= CV_32F ? 1e-3 : out_depth >= CV_32F ? 1e-2 : 1;
-}
-
-
-int CV_GetRectSubPixTest::prepare_test_case( int test_case_idx )
-{
- return CV_ImgWarpBaseTest::prepare_test_case( test_case_idx );
-}
-
-
-void CV_GetRectSubPixTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- CvMat* src0 = &test_mat[INPUT][0];
- CvMat* dst0 = &test_mat[REF_INPUT_OUTPUT][0];
- CvMat* src = src0, *dst = dst0;
- int ftype = CV_MAKETYPE(CV_32F,CV_MAT_CN(src0->type));
- double a[] = { 1, 0, center.x - dst->cols*0.5 + 0.5,
- 0, 1, center.y - dst->rows*0.5 + 0.5 };
- if( CV_MAT_DEPTH(src->type) != CV_32F )
- {
- src = cvCreateMat( src0->rows, src0->cols, ftype );
- cvTsConvert( src0, src );
- }
-
- if( CV_MAT_DEPTH(dst->type) != CV_32F )
- dst = cvCreateMat( dst0->rows, dst0->cols, ftype );
-
- cvTsGetQuadrangeSubPix( src, dst, a );
-
- if( dst != dst0 )
- {
- cvTsConvert( dst, dst0 );
- cvReleaseMat( &dst );
- }
- if( src != src0 )
- cvReleaseMat( &src );
-}
-
-
-CV_GetRectSubPixTest subpix_rect_test;
-
-
-class CV_GetQuadSubPixTest : public CV_ImgWarpBaseTest
-{
-public:
- CV_GetQuadSubPixTest();
-
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void run_func();
- int prepare_test_case( int test_case_idx );
- void prepare_to_validation( int /*test_case_idx*/ );
- double get_success_error_level( int test_case_idx, int i, int j );
-
- int write_default_params(CvFileStorage* fs);
- void get_timing_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types,
- CvSize** whole_sizes, bool *are_images );
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
-};
-
-
-CV_GetQuadSubPixTest::CV_GetQuadSubPixTest()
- : CV_ImgWarpBaseTest( "warp-subpix-quad", "cvGetQuadSubPix", true )
-{
- //spatial_scale_zoom = spatial_scale_decimate;
- spatial_scale_decimate = spatial_scale_zoom;
- //default_timing_param_names = imgwarp_affine_param_names;
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;
- default_timing_param_names = 0;
-}
-
-
-int CV_GetQuadSubPixTest::write_default_params( CvFileStorage* fs )
-{
- int code = CV_ImgWarpBaseTest::write_default_params( fs );
- if( code < 0 )
- return code;
-
- if( ts->get_testing_mode() == CvTS::TIMING_MODE )
- {
- int i;
- start_write_param( fs );
-
- cvStartWriteStruct( fs, "rotate_scale", CV_NODE_SEQ+CV_NODE_FLOW );
- for( i = 0; imgwarp_affine_rotate_scale[i][0] >= 0; i++ )
- {
- cvStartWriteStruct( fs, 0, CV_NODE_SEQ+CV_NODE_FLOW );
- cvWriteRawData( fs, imgwarp_affine_rotate_scale[i], 4, "d" );
- cvEndWriteStruct(fs);
- }
- cvEndWriteStruct(fs);
- }
-
- return code;
-}
-
-
-void CV_GetQuadSubPixTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- int min_size = 4;
- CV_ImgWarpBaseTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- CvSize sz = sizes[INPUT][0], dsz;
- CvRNG* rng = ts->get_rng();
- int msz, src_depth = cvTsRandInt(rng) % 2, dst_depth;
- int cn = cvTsRandInt(rng) % 2 ? 3 : 1;
-
- dst_depth = src_depth = src_depth == 0 ? CV_8U : CV_32F;
- if( src_depth < CV_32F && cvTsRandInt(rng) % 2 )
- dst_depth = CV_32F;
-
- types[INPUT][0] = CV_MAKETYPE(src_depth,cn);
- types[INPUT_OUTPUT][0] = types[REF_INPUT_OUTPUT][0] = CV_MAKETYPE(dst_depth,cn);
-
- sz.width = MAX(sz.width,min_size);
- sz.height = MAX(sz.height,min_size);
- sizes[INPUT][0] = sz;
- msz = MIN( sz.width, sz.height );
-
- dsz.width = cvRound(sqrt(cvTsRandReal(rng)*msz) + 1);
- dsz.height = cvRound(sqrt(cvTsRandReal(rng)*msz) + 1);
- dsz.width = MIN(dsz.width,msz);
- dsz.height = MIN(dsz.width,msz);
- dsz.width = MAX(dsz.width,min_size);
- dsz.height = MAX(dsz.height,min_size);
- sizes[INPUT_OUTPUT][0] = sizes[REF_INPUT_OUTPUT][0] = dsz;
- sizes[INPUT][1] = cvSize( 3, 2 );
-}
-
-
-void CV_GetQuadSubPixTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images )
-{
- CV_ImgWarpBaseTest::get_timing_test_array_types_and_sizes( test_case_idx, sizes, types,
- whole_sizes, are_images );
-
- sizes[INPUT][1] = whole_sizes[INPUT][1] = cvSize(3,2);
- sizes[TEMP][0] = whole_sizes[TEMP][0] =
- sizes[TEMP][1] = whole_sizes[TEMP][1] = cvSize(0,0);
- types[INPUT][1] = CV_64FC1;
-
- interpolation = CV_INTER_LINEAR;
-}
-
-
-void CV_GetQuadSubPixTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- double coeffs[4];
- const CvFileNode* node = find_timing_param( "rotate_scale" );
- assert( node && CV_NODE_IS_SEQ(node->tag) );
- cvReadRawData( ts->get_file_storage(), node, coeffs, "4d" );
-
- sprintf( ptr, "fx=%.2f,fy=%.2f,angle=%.1fdeg,scale=%.1f,", coeffs[0], coeffs[1], coeffs[2], coeffs[3] );
- ptr += strlen(ptr);
- params_left -= 4;
-
- CV_ImgWarpBaseTest::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-
-void CV_GetQuadSubPixTest::run_func()
-{
- cvGetQuadrangleSubPix( test_array[INPUT][0],
- test_array[INPUT_OUTPUT][0], &test_mat[INPUT][1] );
-}
-
-
-double CV_GetQuadSubPixTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- int in_depth = CV_MAT_DEPTH(test_mat[INPUT][0].type);
- //int out_depth = CV_MAT_DEPTH(test_mat[INPUT_OUTPUT][0].type);
-
- return in_depth >= CV_32F ? 1e-2 : 4;
-}
-
-
-int CV_GetQuadSubPixTest::prepare_test_case( int test_case_idx )
-{
- CvRNG* rng = ts->get_rng();
- int code = CV_ImgWarpBaseTest::prepare_test_case( test_case_idx );
- const CvMat* src = &test_mat[INPUT][0];
- CvMat* mat = &test_mat[INPUT][1];
- CvPoint2D32f center;
- double scale, angle;
-
- if( code <= 0 )
- return code;
-
- if( ts->get_testing_mode() == CvTS::CORRECTNESS_CHECK_MODE )
- {
- double a[6];
- CvMat A = cvMat( 2, 3, CV_64FC1, a );
-
- center.x = (float)((cvTsRandReal(rng)*1.2 - 0.1)*src->cols);
- center.y = (float)((cvTsRandReal(rng)*1.2 - 0.1)*src->rows);
- angle = cvTsRandReal(rng)*360;
- scale = cvTsRandReal(rng)*0.2 + 0.9;
-
- // y = Ax + b -> x = A^-1(y - b) = A^-1*y - A^-1*b
- scale = 1./scale;
- angle = angle*(CV_PI/180.);
- a[0] = a[4] = cos(angle)*scale;
- a[1] = sin(angle)*scale;
- a[3] = -a[1];
- a[2] = center.x - a[0]*center.x - a[1]*center.y;
- a[5] = center.y - a[3]*center.x - a[4]*center.y;
- cvTsConvert( &A, mat );
- }
-
- return code;
-}
-
-
-void CV_GetQuadSubPixTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- CvMat* src0 = &test_mat[INPUT][0];
- CvMat* dst0 = &test_mat[REF_INPUT_OUTPUT][0];
- CvMat* src = src0, *dst = dst0;
- int ftype = CV_MAKETYPE(CV_32F,CV_MAT_CN(src0->type));
- double a[6], dx = (dst0->cols - 1)*0.5, dy = (dst0->rows - 1)*0.5;
- CvMat A = cvMat( 2, 3, CV_64F, a );
-
- if( CV_MAT_DEPTH(src->type) != CV_32F )
- {
- src = cvCreateMat( src0->rows, src0->cols, ftype );
- cvTsConvert( src0, src );
- }
-
- if( CV_MAT_DEPTH(dst->type) != CV_32F )
- dst = cvCreateMat( dst0->rows, dst0->cols, ftype );
-
- cvTsConvert( &test_mat[INPUT][1], &A );
- a[2] -= a[0]*dx + a[1]*dy;
- a[5] -= a[3]*dx + a[4]*dy;
- cvTsGetQuadrangeSubPix( src, dst, a );
-
- if( dst != dst0 )
- {
- cvTsConvert( dst, dst0 );
- cvReleaseMat( &dst );
- }
-
- if( src != src0 )
- cvReleaseMat( &src );
-}
-
-
-CV_GetQuadSubPixTest warp_subpix_quad_test;
-
-/* End of file. */
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-class CV_KalmanTest : public CvTest
-{
-public:
- CV_KalmanTest();
-protected:
- void run(int);
-};
-
-
-CV_KalmanTest::CV_KalmanTest():
- CvTest( "kalman", "cvKalmanPredict, cvKalmanCorrect" )
-{
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;
-}
-
-void CV_KalmanTest::run( int )
-{
- int code = CvTS::OK;
- const int Dim = 7;
- const int Steps = 100;
- const double max_init = 1;
- const double max_noise = 0.1;
-
- const double EPSILON = 1.000;
- CvRNG* rng = ts->get_rng();
- CvKalman* Kalm;
- int i, j;
-
- CvMat* Sample = cvCreateMat(Dim,1,CV_32F);
- CvMat* Temp = cvCreateMat(Dim,1,CV_32F);
-
- Kalm = cvCreateKalman(Dim, Dim);
- CvMat Dyn = cvMat(Dim,Dim,CV_32F,Kalm->DynamMatr);
- CvMat Mes = cvMat(Dim,Dim,CV_32F,Kalm->MeasurementMatr);
- CvMat PNC = cvMat(Dim,Dim,CV_32F,Kalm->PNCovariance);
- CvMat MNC = cvMat(Dim,Dim,CV_32F,Kalm->MNCovariance);
- CvMat PriErr = cvMat(Dim,Dim,CV_32F,Kalm->PriorErrorCovariance);
- CvMat PostErr = cvMat(Dim,Dim,CV_32F,Kalm->PosterErrorCovariance);
- CvMat PriState = cvMat(Dim,1,CV_32F,Kalm->PriorState);
- CvMat PostState = cvMat(Dim,1,CV_32F,Kalm->PosterState);
- cvSetIdentity(&PNC);
- cvSetIdentity(&PriErr);
- cvSetIdentity(&PostErr);
- cvSetZero(&MNC);
- cvSetZero(&PriState);
- cvSetZero(&PostState);
- cvSetIdentity(&Mes);
- cvSetIdentity(&Dyn);
- cvRandArr(rng, Sample, CV_RAND_UNI, cvScalarAll(-max_init), cvScalarAll(max_init));
- cvKalmanCorrect(Kalm, Sample);
- for(i = 0; i<Steps; i++)
- {
- cvKalmanPredict(Kalm);
- for(j = 0; j<Dim; j++)
- {
- float t = 0;
- for(int k=0; k<Dim; k++)
- {
- t += Dyn.data.fl[j*Dim+k]*Sample->data.fl[k];
- }
- Temp->data.fl[j]= (float)(t+(cvTsRandReal(rng)*2-1)*max_noise);
- }
- cvCopy( Temp, Sample );
- cvKalmanCorrect(Kalm,Temp);
- }
-
- code = cvTsCmpEps2( ts, Sample, Kalm->state_post, EPSILON, false, "The final estimated state" );
-
- cvReleaseMat(&Sample);
- cvReleaseMat(&Temp);
- cvReleaseKalman(&Kalm);
-
- if( code < 0 )
- ts->set_failed_test_info( code );
-}
-
-CV_KalmanTest kalman_test;
-
-
-/* End of file. */
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-#if 0
-
-/* Testing parameters */
-static char test_desc[] = "KMeans clustering";
-static char* func_name[] =
-{
- "cvKMeans"
-};
-
-//based on Ara Nefian's implementation
-float distance(float* vector_1, float *vector_2, int VecSize)
-{
- int i;
- float dist;
-
- dist = 0.0;
- for (i = 0; i < VecSize; i++)
- {
- //printf ("%f, %f\n", vector_1[i], vector_2[i]);
- dist = dist + (vector_1[i] - vector_2[i])*(vector_1[i] - vector_2[i]);
- }
- return dist;
-}
-
-//returns number of made iterations
-int _real_kmeans( int numClusters, float **sample, int numSamples,
- int VecSize, int* a_class, double eps, int iter )
-
-{
- int i, k, n;
- int *counter;
- float minDist;
- float *dist;
- float **curr_cluster;
- float **prev_cluster;
-
- float error;
-
- //printf("* numSamples = %d, numClusters = %d, VecSize = %d\n", numSamples, numClusters, VecSize);
-
- //memory allocation
- dist = new float[numClusters];
- counter = new int[numClusters];
-
- //allocate memory for curr_cluster and prev_cluster
- curr_cluster = new float*[numClusters];
- prev_cluster = new float*[numClusters];
- for (k = 0; k < numClusters; k++){
- curr_cluster[k] = new float[VecSize];
- prev_cluster[k] = new float[VecSize];
- }
-
- //pick initial cluster centers
- for (k = 0; k < numClusters; k++)
- {
- for (n = 0; n < VecSize; n++)
- {
- curr_cluster[k][n] = sample[k*(numSamples/numClusters)][n];
- prev_cluster[k][n] = sample[k*(numSamples/numClusters)][n];
- }
- }
-
-
- int NumIter = 0;
- error = FLT_MAX;
- while ((error > eps) && (NumIter < iter))
- {
- NumIter++;
- //printf("NumIter = %d, error = %lf, \n", NumIter, error);
-
- //assign samples to clusters
- for (i = 0; i < numSamples; i++)
- {
- for (k = 0; k < numClusters; k++)
- {
- dist[k] = distance(sample[i], curr_cluster[k], VecSize);
- }
- minDist = dist[0];
- a_class[i] = 0;
- for (k = 1; k < numClusters; k++)
- {
- if (dist[k] < minDist)
- {
- minDist = dist[k];
- a_class[i] = k;
- }
- }
- }
-
- //reset clusters and counters
- for (k = 0; k < numClusters; k++){
- counter[k] = 0;
- for (n = 0; n < VecSize; n++){
- curr_cluster[k][n] = 0.0;
- }
- }
- for (i = 0; i < numSamples; i++){
- for (n = 0; n < VecSize; n++){
- curr_cluster[a_class[i]][n] = curr_cluster[a_class[i]][n] + sample[i][n];
- }
- counter[a_class[i]]++;
- }
-
- for (k = 0; k < numClusters; k++){
- for (n = 0; n < VecSize; n++){
- curr_cluster[k][n] = curr_cluster[k][n]/(float)counter[k];
- }
- }
-
- error = 0.0;
- for (k = 0; k < numClusters; k++){
- for (n = 0; n < VecSize; n++){
- error = error + (curr_cluster[k][n] - prev_cluster[k][n])*(curr_cluster[k][n] - prev_cluster[k][n]);
- }
- }
- //error = error/(double)(numClusters*VecSize);
-
- //copy curr_clusters to prev_clusters
- for (k = 0; k < numClusters; k++){
- for (n =0; n < VecSize; n++){
- prev_cluster[k][n] = curr_cluster[k][n];
- }
- }
-
- }
-
- //deallocate memory for curr_cluster and prev_cluster
- for (k = 0; k < numClusters; k++){
- delete curr_cluster[k];
- delete prev_cluster[k];
- }
- delete curr_cluster;
- delete prev_cluster;
-
- delete counter;
- delete dist;
- return NumIter;
-
-}
-
-static int fmaKMeans(void)
-{
- CvTermCriteria crit;
- float** vectors;
- int* output;
- int* etalon_output;
-
- int lErrors = 0;
- int lNumVect = 0;
- int lVectSize = 0;
- int lNumClust = 0;
- int lMaxNumIter = 0;
- float flEpsilon = 0;
-
- int i,j;
- static int read_param = 0;
-
- /* Initialization global parameters */
- if( !read_param )
- {
- read_param = 1;
- /* Read test-parameters */
- trsiRead( &lNumVect, "1000", "Number of vectors" );
- trsiRead( &lVectSize, "10", "Number of vectors" );
- trsiRead( &lNumClust, "20", "Number of clusters" );
- trsiRead( &lMaxNumIter,"100","Maximal number of iterations");
- trssRead( &flEpsilon, "0.5", "Accuracy" );
- }
-
- crit = cvTermCriteria( CV_TERMCRIT_EPS|CV_TERMCRIT_ITER, lMaxNumIter, flEpsilon );
-
- //allocate vectors
- vectors = (float**)cvAlloc( lNumVect * sizeof(float*) );
- for( i = 0; i < lNumVect; i++ )
- {
- vectors[i] = (float*)cvAlloc( lVectSize * sizeof( float ) );
- }
-
- output = (int*)cvAlloc( lNumVect * sizeof(int) );
- etalon_output = (int*)cvAlloc( lNumVect * sizeof(int) );
-
- //fill input vectors
- for( i = 0; i < lNumVect; i++ )
- {
- ats1flInitRandom( -2000, 2000, vectors[i], lVectSize );
- }
-
- /* run etalon kmeans */
- /* actually it is the simpliest realization of kmeans */
-
- int ni = _real_kmeans( lNumClust, vectors, lNumVect, lVectSize, etalon_output, crit.epsilon, crit.max_iter );
-
- trsWrite( ATS_CON, "%d iterations done\n", ni );
-
- /* Run OpenCV function */
-#define _KMEANS_TIME 0
-
-#if _KMEANS_TIME
- //timing section
- trsTimerStart(0);
- __int64 tics = atsGetTickCount();
-#endif
-
- cvKMeans( lNumClust, vectors, lNumVect, lVectSize,
- crit, output );
-
-#if _KMEANS_TIME
- tics = atsGetTickCount() - tics;
- trsTimerStop(0);
- //output result
- //double dbUsecs =ATS_TICS_TO_USECS((double)tics);
- trsWrite( ATS_CON, "Tics per iteration %d\n", tics/ni );
-
-#endif
-
- //compare results
- for( j = 0; j < lNumVect; j++ )
- {
- if ( output[j] != etalon_output[j] )
- {
- lErrors++;
- }
- }
-
- //free memory
- for( i = 0; i < lNumVect; i++ )
- {
- cvFree( &(vectors[i]) );
- }
- cvFree(&vectors);
- cvFree(&output);
- cvFree(&etalon_output);
-
- if( lErrors == 0 ) return trsResult( TRS_OK, "No errors fixed for this text" );
- else return trsResult( TRS_FAIL, "Detected %d errors", lErrors );
-
-}
-
-
-
-void InitAKMeans()
-{
- /* Register test function */
- trsReg( func_name[0], test_desc, atsAlgoClass, fmaKMeans );
-
-} /* InitAKMeans */
-
-#endif
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-#if 0
-/*#include "conio.h" */
-
-static char cTestName[] = "Matching Contour trees";
-static char cTestClass[] = "Algorithm";
-static char cFuncName[] = "cvMatchContourTrees";
-
-static int aMatchContourTrees(void)
-{
- CvSeqBlock contour_blk1, contour_blk2;
- CvContour contour_h1, contour_h2;
- CvContourTree *tree1, *tree2;
- CvMemStorage *storage; /* storage for contour and tree writing */
- int block_size = 10000;
-
- CvRandState state;
- double lower, upper;
- int seed;
- float fr;
- int type_seq;
- int method;
- int nPoints1 = 12, nPoints2 = 12;
- int xc,yc,a1 = 10, b1 = 20, a2 = 10, b2 =20, fi = 0;
- int xmin,ymin,xmax,ymax;
- double error_test,rezult, eps_rez = 0.8;
- double pi = 3.1415926;
- double threshold = 1.e-7;
- double threshold2 = 5.;
- int i;
- int code = TRS_OK;
-
- int width=256,height=256;
- CvPoint *cp1,*cp2;
-
-/* read tests params */
-
- if (!trsiRead(&nPoints1,"20","Number of points first contour"))
- return TRS_UNDEF;
- if (!trsiRead(&nPoints2,"20","Number of points second contour"))
- return TRS_UNDEF;
-
- if(nPoints1>0&&nPoints2>0)
- {
- if (!trsiRead(&a1,"10","first radius of the first elipse"))
- return TRS_UNDEF;
- if (!trsiRead(&b1,"20","second radius of the first elipse"))
- return TRS_UNDEF;
- if (!trsiRead(&a2,"15","first radius of the second elipse"))
- return TRS_UNDEF;
- if (!trsiRead(&b2,"30","second radius of the second elipse"))
- return TRS_UNDEF;
- if (!trsiRead(&fi,"0","second radius of the second elipse"))
- return TRS_UNDEF;
-
- if (!trsdRead(&upper,"3","noise amplidude"))
- return TRS_UNDEF;
-
- xc = (int)(width/2.);
- yc = (int)(height/2.);
- xmin = width;
- ymin = height;
- xmax = 0;
- ymax = 0;
-
- cp1 = (CvPoint*) trsmAlloc(nPoints1*sizeof(CvPoint));
- cp2 = (CvPoint*) trsmAlloc(nPoints2*sizeof(CvPoint));
-
- for(i=0;i<nPoints1;i++)
- {
- cp1[i].x = (int)(a1*cos(2*pi*i/nPoints1))+xc;
- cp1[i].y = (int)(b1*sin(2*pi*i/nPoints1))+yc;
- if(xmin> cp1[i].x) xmin = cp1[i].x;
- if(xmax< cp1[i].x) xmax = cp1[i].x;
- if(ymin> cp1[i].y) ymin = cp1[i].y;
- if(ymax< cp1[i].y) ymax = cp1[i].y;
- }
-
- if(xmax>width||xmin<0||ymax>height||ymin<0) return TRS_FAIL;
-
- lower = -upper;
-/* upper = 3;*/
- seed = 345753;
- cvRandInit(&state, (float)lower,(float)upper, seed );
- for(i=0;i<nPoints2;i++)
- {
- cvbRand( &state, &fr, 1 );
- cp2[i].x =(int)fr+(int)(a2*cos(2*pi*i/nPoints2)*cos(2*pi*fi/360.))-
- (int)(b2*sin(2*pi*i/nPoints2)*sin(2*pi*fi/360.))+xc;
- cvbRand( &state, &fr, 1 );
- cp2[i].y =(int)fr+(int)(a2*cos(2*pi*i/nPoints2)*sin(2*pi*fi/360.))+
- (int)(b2*sin(2*pi*i/nPoints2)*cos(2*pi*fi/360.))+yc;
-
- if(xmin> cp2[i].x) xmin = cp2[i].x;
- if(xmax< cp2[i].x) xmax = cp2[i].x;
- if(ymin> cp2[i].y) ymin = cp2[i].y;
- if(ymax< cp2[i].y) ymax = cp2[i].y;
- }
- if(xmax>width||xmin<0||ymax>height||ymin<0) return TRS_FAIL;
-
-/* contours initialazing */
- type_seq = CV_SEQ_POLYGON;
- cvMakeSeqHeaderForArray( type_seq, sizeof(CvContour), sizeof(CvPoint),
- (char*)cp1, nPoints1, (CvSeq*)&contour_h1, &contour_blk1);
-
- cvMakeSeqHeaderForArray( type_seq, sizeof(CvContour), sizeof(CvPoint),
- (char*)cp2, nPoints2, (CvSeq*)&contour_h2, &contour_blk2);
-
-/* contour trees created*/
- storage = cvCreateMemStorage( block_size );
-
- tree1 = cvCreateContourTree ((CvSeq*)&contour_h1, storage, threshold);
- tree2 = cvCreateContourTree ((CvSeq*)&contour_h2, storage, threshold);
-
-
-/* countours matchig */
- error_test = 0.;
- method = 1;
-
- rezult = cvMatchContourTrees (tree1, tree2, (CvContourTreesMatchMethod)method,threshold2);
- error_test+=rezult;
-
- if(error_test > eps_rez ) code = TRS_FAIL;
- else code = TRS_OK;
-
- trsWrite( ATS_CON | ATS_LST | ATS_SUM, "contours matching error_test =%f \n",
- error_test);
-
- cvReleaseMemStorage ( &storage );
-
- trsFree (cp2);
- trsFree (cp1);
-
- }
-
-
-/* _getch(); */
- return code;
-}
-
-void InitAMatchContourTrees( void )
-{
-/* Test Registartion */
- trsReg(cFuncName,cTestName,cTestClass,aMatchContourTrees);
-
-} /* InitAMatchContourTrees */
-
-/* End of file. */
-
-#endif
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-#include "cvtest.h"
-
-static const char* moments_param_names[] = { "size", "depth", 0 };
-static const int moments_depths[] = { CV_8U, CV_32F, -1 };
-
-static const CvSize moments_sizes[] = {{30,30}, {320, 240}, {720,480}, {-1,-1}};
-static const CvSize moments_whole_sizes[] = {{320,240}, {320, 240}, {720,480}, {-1,-1}};
-
-// image moments
-class CV_MomentsTest : public CvArrTest
-{
-public:
- CV_MomentsTest();
-
-protected:
-
- enum { MOMENT_COUNT = 25 };
- int prepare_test_case( int test_case_idx );
- void prepare_to_validation( int /*test_case_idx*/ );
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void get_timing_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types,
- CvSize** whole_sizes, bool *are_images );
- void get_minmax_bounds( int i, int j, int type, CvScalar* low, CvScalar* high );
- double get_success_error_level( int test_case_idx, int i, int j );
- void run_func();
- int coi;
- bool is_binary;
-};
-
-
-CV_MomentsTest::CV_MomentsTest()
- : CvArrTest( "moments-raster", "cvMoments, cvGetNormalizedCentralMoment", "" )
-{
- test_array[INPUT].push(NULL);
- test_array[OUTPUT].push(NULL);
- test_array[REF_OUTPUT].push(NULL);
- coi = -1;
- is_binary = false;
- //element_wise_relative_error = false;
-
- default_timing_param_names = moments_param_names;
- depth_list = moments_depths;
- size_list = moments_sizes;
- whole_size_list = moments_whole_sizes;
-
- cn_list = 0;
-}
-
-
-void CV_MomentsTest::get_minmax_bounds( int i, int j, int type, CvScalar* low, CvScalar* high )
-{
- CvArrTest::get_minmax_bounds( i, j, type, low, high );
- int depth = CV_MAT_DEPTH(type);
-
- if( depth == CV_16U )
- {
- *low = cvScalarAll(0);
- *high = cvScalarAll(1000);
- }
- else if( depth == CV_16S )
- {
- *low = cvScalarAll(-1000);
- *high = cvScalarAll(1000);
- }
- else if( depth == CV_32F )
- {
- *low = cvScalarAll(-1);
- *high = cvScalarAll(1);
- }
-}
-
-
-void CV_MomentsTest::get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- CvArrTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- int cn = cvTsRandInt(rng) % 4 + 1;
- int depth = cvTsRandInt(rng) % 4;
- depth = depth == 0 ? CV_8U : depth == 1 ? CV_16U : depth == 2 ? CV_16S : CV_32F;
- if( cn == 2 )
- cn = 1;
-
- types[INPUT][0] = CV_MAKETYPE(depth, cn);
- types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_64FC1;
- sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = cvSize(MOMENT_COUNT,1);
-
- is_binary = cvTsRandInt(rng) % 2 != 0;
- coi = 0;
- cvmat_allowed = true;
- if( cn > 1 )
- {
- coi = cvTsRandInt(rng) % cn;
- cvmat_allowed = false;
- }
-}
-
-
-void CV_MomentsTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images )
-{
- CvArrTest::get_timing_test_array_types_and_sizes( test_case_idx, sizes, types,
- whole_sizes, are_images );
- types[OUTPUT][0] = CV_64FC1;
- sizes[OUTPUT][0] = whole_sizes[OUTPUT][0] = cvSize(MOMENT_COUNT,1);
-}
-
-
-double CV_MomentsTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- int depth = CV_MAT_DEPTH(test_mat[INPUT][0].type);
- return depth != CV_32F ? FLT_EPSILON*10 : FLT_EPSILON*100;
-}
-
-
-
-int CV_MomentsTest::prepare_test_case( int test_case_idx )
-{
- int code = CvArrTest::prepare_test_case( test_case_idx );
- if( code > 0 )
- {
- int cn = CV_MAT_CN(test_mat[INPUT][0].type);
- if( cn > 1 )
- cvSetImageCOI( (IplImage*)test_array[INPUT][0], coi + 1 );
- }
-
- return code;
-}
-
-
-void CV_MomentsTest::run_func()
-{
- CvMoments* m = (CvMoments*)test_mat[OUTPUT][0].data.db;
- double* others = (double*)(m + 1);
- cvMoments( test_array[INPUT][0], m, is_binary );
- others[0] = cvGetNormalizedCentralMoment( m, 2, 0 );
- others[1] = cvGetNormalizedCentralMoment( m, 1, 1 );
- others[2] = cvGetNormalizedCentralMoment( m, 0, 2 );
- others[3] = cvGetNormalizedCentralMoment( m, 3, 0 );
- others[4] = cvGetNormalizedCentralMoment( m, 2, 1 );
- others[5] = cvGetNormalizedCentralMoment( m, 1, 2 );
- others[6] = cvGetNormalizedCentralMoment( m, 0, 3 );
-}
-
-
-void CV_MomentsTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- CvMat* src = &test_mat[INPUT][0];
- CvMoments m;
- double* mdata = test_mat[REF_OUTPUT][0].data.db;
- int depth = CV_MAT_DEPTH(src->type);
- int cn = CV_MAT_CN(src->type);
- int i, y, x, cols = src->cols;
- double xc = 0., yc = 0.;
-
- memset( &m, 0, sizeof(m));
-
- for( y = 0; y < src->rows; y++ )
- {
- double s0 = 0, s1 = 0, s2 = 0, s3 = 0;
- uchar* ptr = src->data.ptr + y*src->step;
- for( x = 0; x < cols; x++ )
- {
- double val;
- if( depth == CV_8U )
- val = ptr[x*cn + coi];
- else if( depth == CV_16U )
- val = ((ushort*)ptr)[x*cn + coi];
- else if( depth == CV_16S )
- val = ((short*)ptr)[x*cn + coi];
- else
- val = ((float*)ptr)[x*cn + coi];
-
- if( is_binary )
- val = val != 0;
-
- s0 += val;
- s1 += val*x;
- s2 += val*x*x;
- s3 += ((val*x)*x)*x;
- }
-
- m.m00 += s0;
- m.m01 += s0*y;
- m.m02 += (s0*y)*y;
- m.m03 += ((s0*y)*y)*y;
-
- m.m10 += s1;
- m.m11 += s1*y;
- m.m12 += (s1*y)*y;
-
- m.m20 += s2;
- m.m21 += s2*y;
-
- m.m30 += s3;
- }
-
- if( m.m00 != 0 )
- {
- xc = m.m10/m.m00, yc = m.m01/m.m00;
- m.inv_sqrt_m00 = 1./sqrt(fabs(m.m00));
- }
-
- for( y = 0; y < src->rows; y++ )
- {
- double s0 = 0, s1 = 0, s2 = 0, s3 = 0, y1 = y - yc;
- uchar* ptr = src->data.ptr + y*src->step;
- for( x = 0; x < cols; x++ )
- {
- double val, x1 = x - xc;
- if( depth == CV_8U )
- val = ptr[x*cn + coi];
- else if( depth == CV_16U )
- val = ((ushort*)ptr)[x*cn + coi];
- else if( depth == CV_16S )
- val = ((short*)ptr)[x*cn + coi];
- else
- val = ((float*)ptr)[x*cn + coi];
-
- if( is_binary )
- val = val != 0;
-
- s0 += val;
- s1 += val*x1;
- s2 += val*x1*x1;
- s3 += ((val*x1)*x1)*x1;
- }
-
- m.mu02 += s0*y1*y1;
- m.mu03 += ((s0*y1)*y1)*y1;
-
- m.mu11 += s1*y1;
- m.mu12 += (s1*y1)*y1;
-
- m.mu20 += s2;
- m.mu21 += s2*y1;
-
- m.mu30 += s3;
- }
-
- memcpy( mdata, &m, sizeof(m));
- mdata += sizeof(m)/sizeof(m.m00);
-
- /* calc normalized moments */
- {
- double inv_m00 = m.inv_sqrt_m00*m.inv_sqrt_m00;
- double s2 = inv_m00*inv_m00; /* 1./(m00 ^ (2/2 + 1)) */
- double s3 = s2*m.inv_sqrt_m00; /* 1./(m00 ^ (3/2 + 1)) */
-
- mdata[0] = m.mu20 * s2;
- mdata[1] = m.mu11 * s2;
- mdata[2] = m.mu02 * s2;
-
- mdata[3] = m.mu30 * s3;
- mdata[4] = m.mu21 * s3;
- mdata[5] = m.mu12 * s3;
- mdata[6] = m.mu03 * s3;
- }
-
- {
- double* a = test_mat[REF_OUTPUT][0].data.db;
- double* b = test_mat[OUTPUT][0].data.db;
- for( i = 0; i < MOMENT_COUNT; i++ )
- {
- if( fabs(a[i]) < 1e-3 )
- a[i] = 0;
- if( fabs(b[i]) < 1e-3 )
- b[i] = 0;
- }
- }
-}
-
-
-CV_MomentsTest img_moments_test;
-
-
-// Hu invariants
-class CV_HuMomentsTest : public CvArrTest
-{
-public:
- CV_HuMomentsTest();
-
-protected:
-
- enum { MOMENT_COUNT = 18, HU_MOMENT_COUNT = 7 };
-
- int prepare_test_case( int test_case_idx );
- void prepare_to_validation( int /*test_case_idx*/ );
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void get_minmax_bounds( int i, int j, int type, CvScalar* low, CvScalar* high );
- double get_success_error_level( int test_case_idx, int i, int j );
- void run_func();
-};
-
-
-CV_HuMomentsTest::CV_HuMomentsTest()
- : CvArrTest( "moments-hu", "cvHuMoments", "" )
-{
- test_array[INPUT].push(NULL);
- test_array[OUTPUT].push(NULL);
- test_array[REF_OUTPUT].push(NULL);
-
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE; // for now disable the timing test
-}
-
-
-void CV_HuMomentsTest::get_minmax_bounds( int i, int j, int type, CvScalar* low, CvScalar* high )
-{
- CvArrTest::get_minmax_bounds( i, j, type, low, high );
- *low = cvScalarAll(-10000);
- *high = cvScalarAll(10000);
-}
-
-
-void CV_HuMomentsTest::get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types )
-{
- CvArrTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- types[INPUT][0] = types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_64FC1;
- sizes[INPUT][0] = cvSize(MOMENT_COUNT,1);
- sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = cvSize(HU_MOMENT_COUNT,1);
-}
-
-
-double CV_HuMomentsTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- return FLT_EPSILON;
-}
-
-
-
-int CV_HuMomentsTest::prepare_test_case( int test_case_idx )
-{
- int code = CvArrTest::prepare_test_case( test_case_idx );
- if( code > 0 )
- {
- // ...
- }
-
- return code;
-}
-
-
-void CV_HuMomentsTest::run_func()
-{
- cvGetHuMoments( (CvMoments*)test_mat[INPUT][0].data.db,
- (CvHuMoments*)test_mat[OUTPUT][0].data.db );
-}
-
-
-void CV_HuMomentsTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- CvMoments* m = (CvMoments*)test_mat[INPUT][0].data.db;
- CvHuMoments* hu = (CvHuMoments*)test_mat[REF_OUTPUT][0].data.db;
-
- double inv_m00 = m->inv_sqrt_m00*m->inv_sqrt_m00;
- double s2 = inv_m00*inv_m00; /* 1./(m00 ^ (2/2 + 1)) */
- double s3 = s2*m->inv_sqrt_m00; /* 1./(m00 ^ (3/2 + 1)) */
-
- double nu20 = m->mu20 * s2;
- double nu11 = m->mu11 * s2;
- double nu02 = m->mu02 * s2;
-
- double nu30 = m->mu30 * s3;
- double nu21 = m->mu21 * s3;
- double nu12 = m->mu12 * s3;
- double nu03 = m->mu03 * s3;
-
- #undef sqr
- #define sqr(a) ((a)*(a))
-
- hu->hu1 = nu20 + nu02;
- hu->hu2 = sqr(nu20 - nu02) + 4*sqr(nu11);
- hu->hu3 = sqr(nu30 - 3*nu12) + sqr(3*nu21 - nu03);
- hu->hu4 = sqr(nu30 + nu12) + sqr(nu21 + nu03);
- hu->hu5 = (nu30 - 3*nu12)*(nu30 + nu12)*(sqr(nu30 + nu12) - 3*sqr(nu21 + nu03)) +
- (3*nu21 - nu03)*(nu21 + nu03)*(3*sqr(nu30 + nu12) - sqr(nu21 + nu03));
- hu->hu6 = (nu20 - nu02)*(sqr(nu30 + nu12) - sqr(nu21 + nu03)) +
- 4*nu11*(nu30 + nu12)*(nu21 + nu03);
- hu->hu7 = (3*nu21 - nu03)*(nu30 + nu12)*(sqr(nu30 + nu12) - 3*sqr(nu21 + nu03)) +
- (3*nu12 - nu30)*(nu21 + nu03)*(3*sqr(nu30 + nu12) - sqr(nu21 + nu03));
-}
-
-
-CV_HuMomentsTest hu_moments_test;
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-static const int motempl_silh_ratio[] = { 10, 50 };
-static const int motempl_duration[] = { 200, 2000 };
-static const int motempl_gradient_aperture[] = { 3, 5 };
-static const char* motempl_update_param_names[] = { "silh_ratio", "duration", "size", 0 };
-static const char* motempl_gradient_param_names[] = { "silh_ratio", "duration", "aperture", "size", 0 };
-static const char* motempl_global_param_names[] = { "silh_ratio", "duration", "size", 0 };
-static const CvSize motempl_sizes[] = {{320, 240}, {720,480}, {-1,-1}};
-
-///////////////////// base MHI class ///////////////////////
-class CV_MHIBaseTest : public CvArrTest
-{
-public:
- CV_MHIBaseTest( const char* test_name, const char* test_funcs );
-
-protected:
- int write_default_params(CvFileStorage* fs);
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void get_timing_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types,
- CvSize** whole_sizes, bool *are_images );
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
- void get_minmax_bounds( int i, int j, int type, CvScalar* low, CvScalar* high );
- int prepare_test_case( int test_case_idx );
- double timestamp, duration, max_log_duration;
- int mhi_i, mhi_ref_i;
- double silh_ratio;
-};
-
-
-CV_MHIBaseTest::CV_MHIBaseTest( const char* test_name, const char* test_funcs )
- : CvArrTest( test_name, test_funcs )
-{
- timestamp = duration = 0;
- max_log_duration = 9;
- mhi_i = mhi_ref_i = -1;
-
- size_list = whole_size_list = strcmp( test_funcs, "" ) == 0 ? motempl_sizes : 0;
- depth_list = 0;
- cn_list = 0;
- default_timing_param_names = 0;
-
- silh_ratio = 0.25;
-}
-
-
-int CV_MHIBaseTest::write_default_params( CvFileStorage* fs )
-{
- int code = CvArrTest::write_default_params( fs );
- if( code < 0 )
- return code;
-
- if( ts->get_testing_mode() == CvTS::TIMING_MODE && strcmp(tested_functions, "") == 0 )
- {
- start_write_param( fs );
- write_int_list( fs, "silh_ratio", motempl_silh_ratio, CV_DIM(motempl_silh_ratio) );
- write_int_list( fs, "duration", motempl_duration, CV_DIM(motempl_duration) );
- }
-
- return code;
-}
-
-
-void CV_MHIBaseTest::get_minmax_bounds( int i, int j, int type, CvScalar* low, CvScalar* high )
-{
- CvArrTest::get_minmax_bounds( i, j, type, low, high );
- if( i == INPUT && CV_MAT_DEPTH(type) == CV_8U )
- {
- *low = cvScalarAll(cvRound(-1./silh_ratio)+2.);
- *high = cvScalarAll(2);
- }
- else if( i == mhi_i || i == mhi_ref_i )
- {
- *low = cvScalarAll(-exp(max_log_duration));
- *high = cvScalarAll(0.);
- }
-}
-
-
-void CV_MHIBaseTest::get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- CvArrTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
-
- types[INPUT][0] = CV_8UC1;
- types[mhi_i][0] = types[mhi_ref_i][0] = CV_32FC1;
- duration = exp(cvTsRandReal(rng)*max_log_duration);
- timestamp = duration + cvTsRandReal(rng)*30.-10.;
-}
-
-
-void CV_MHIBaseTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images )
-{
- CvArrTest::get_timing_test_array_types_and_sizes( test_case_idx, sizes, types,
- whole_sizes, are_images );
- types[INPUT][0] = CV_8UC1;
- types[mhi_i][0] = CV_32FC1;
- duration = cvReadInt( find_timing_param( "duration" ), 500 );
- silh_ratio = cvReadInt( find_timing_param( "silh_ratio" ), 25 )*0.01;
- timestamp = duration;
-}
-
-
-void CV_MHIBaseTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- sprintf( ptr, "ratio=%d%%,duration=%dms,", cvRound(silh_ratio*100), cvRound(duration) );
- ptr += strlen(ptr);
- params_left -= 2;
-
- CvArrTest::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-
-int CV_MHIBaseTest::prepare_test_case( int test_case_idx )
-{
- int code = CvArrTest::prepare_test_case( test_case_idx );
- if( code > 0 )
- {
- CvMat* mat = &test_mat[mhi_i][0];
- cvTsAdd( mat, cvScalarAll(1.), 0, cvScalarAll(0.), cvScalarAll(duration), mat, 0 );
- cvTsMinMaxS( mat, 0, mat, CV_TS_MAX );
- if( ts->get_testing_mode() == CvTS::CORRECTNESS_CHECK_MODE && mhi_i != mhi_ref_i )
- {
- CvMat* mat0 = &test_mat[mhi_ref_i][0];
- cvTsCopy( mat, mat0 );
- }
- }
-
- return code;
-}
-
-
-CV_MHIBaseTest mhi_base_test( "mhi", "" );
-
-
-///////////////////// update motion history ////////////////////////////
-
-static void cvTsUpdateMHI( const CvMat* silh, CvMat* mhi, double timestamp, double duration )
-{
- int i, j;
- float delbound = (float)(timestamp - duration);
- for( i = 0; i < mhi->rows; i++ )
- {
- const uchar* silh_row = silh->data.ptr + i*silh->step;
- float* mhi_row = (float*)(mhi->data.ptr + i*mhi->step);
-
- for( j = 0; j < mhi->cols; j++ )
- {
- if( silh_row[j] )
- mhi_row[j] = (float)timestamp;
- else if( mhi_row[j] < delbound )
- mhi_row[j] = 0.f;
- }
- }
-}
-
-
-class CV_UpdateMHITest : public CV_MHIBaseTest
-{
-public:
- CV_UpdateMHITest();
-
-protected:
- double get_success_error_level( int test_case_idx, int i, int j );
- void run_func();
- void prepare_to_validation( int );
-};
-
-
-CV_UpdateMHITest::CV_UpdateMHITest()
- : CV_MHIBaseTest( "mhi-update", "cvUpdateMotionHistory" )
-{
- test_array[INPUT].push(NULL);
- test_array[INPUT_OUTPUT].push(NULL);
- test_array[REF_INPUT_OUTPUT].push(NULL);
- mhi_i = INPUT_OUTPUT; mhi_ref_i = REF_INPUT_OUTPUT;
-
- default_timing_param_names = motempl_update_param_names;
-}
-
-
-double CV_UpdateMHITest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- return 0;
-}
-
-
-void CV_UpdateMHITest::run_func()
-{
- cvUpdateMotionHistory( test_array[INPUT][0], test_array[INPUT_OUTPUT][0], timestamp, duration );
-}
-
-
-void CV_UpdateMHITest::prepare_to_validation( int /*test_case_idx*/ )
-{
- cvTsUpdateMHI( &test_mat[INPUT][0], &test_mat[REF_INPUT_OUTPUT][0], timestamp, duration );
-}
-
-
-CV_UpdateMHITest mhi_update_test;
-
-
-///////////////////// calc motion gradient ////////////////////////////
-
-static void cvTsMHIGradient( const CvMat* mhi, CvMat* mask, CvMat* orientation,
- double delta1, double delta2, int aperture_size )
-{
- CvPoint anchor = { aperture_size/2, aperture_size/2 };
- CvMat* src = cvCreateMat( mhi->rows + aperture_size - 1, mhi->cols + aperture_size - 1, CV_32FC1 );
- CvMat* kernel = cvCreateMat( aperture_size, aperture_size, CV_32FC1 );
- CvMat* dx = cvCreateMat( mhi->rows, mhi->cols, CV_32FC1 );
- CvMat* dy = cvCreateMat( mhi->rows, mhi->cols, CV_32FC1 );
- CvMat* min_mhi = cvCreateMat( mhi->rows, mhi->cols, CV_32FC1 );
- CvMat* max_mhi = cvCreateMat( mhi->rows, mhi->cols, CV_32FC1 );
- IplConvKernel* element = cvCreateStructuringElementEx( aperture_size, aperture_size,
- aperture_size/2, aperture_size/2, CV_SHAPE_RECT );
- int i, j;
- double limit = 1e-4*aperture_size*aperture_size;
-
- cvTsPrepareToFilter( mhi, src, anchor );
- cvTsCalcSobelKernel2D( 1, 0, aperture_size, 0, kernel );
- cvTsConvolve2D( src, dx, kernel, anchor );
- cvTsCalcSobelKernel2D( 0, 1, aperture_size, 0, kernel );
- cvTsConvolve2D( src, dy, kernel, anchor );
- cvReleaseMat( &kernel );
-
- cvTsMinMaxFilter( src, min_mhi, element, CV_TS_MIN );
- cvTsMinMaxFilter( src, max_mhi, element, CV_TS_MAX );
- cvReleaseMat( &src );
- cvReleaseStructuringElement( &element );
-
- if( delta1 > delta2 )
- {
- double t;
- CV_SWAP( delta1, delta2, t );
- }
-
- for( i = 0; i < mhi->rows; i++ )
- {
- uchar* mask_row = mask->data.ptr + i*mask->step;
- float* orient_row = (float*)(orientation->data.ptr + i*orientation->step);
- const float* dx_row = (float*)(dx->data.ptr + i*dx->step);
- const float* dy_row = (float*)(dy->data.ptr + i*dy->step);
- const float* min_row = (float*)(min_mhi->data.ptr + i*min_mhi->step);
- const float* max_row = (float*)(max_mhi->data.ptr + i*max_mhi->step);
-
- for( j = 0; j < mhi->cols; j++ )
- {
- double delta = max_row[j] - min_row[j];
- double _dx = dx_row[j], _dy = dy_row[j];
-
- if( delta1 <= delta && delta <= delta2 &&
- (fabs(_dx) > limit || fabs(_dy) > limit) )
- {
- mask_row[j] = 1;
- double angle = atan2( _dy, _dx ) * (180/CV_PI);
- if( angle < 0 )
- angle += 360.;
- orient_row[j] = (float)angle;
- }
- else
- {
- mask_row[j] = 0;
- orient_row[j] = 0.f;
- }
- }
- }
-
- cvReleaseMat( &dx );
- cvReleaseMat( &dy );
- cvReleaseMat( &min_mhi );
- cvReleaseMat( &max_mhi );
-}
-
-
-class CV_MHIGradientTest : public CV_MHIBaseTest
-{
-public:
- CV_MHIGradientTest();
-
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void get_timing_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types,
- CvSize** whole_sizes, bool *are_images );
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
- double get_success_error_level( int test_case_idx, int i, int j );
- void run_func();
- void prepare_to_validation( int );
- int write_default_params(CvFileStorage* fs);
-
- double delta1, delta2, delta_range_log;
- int aperture_size;
-};
-
-
-CV_MHIGradientTest::CV_MHIGradientTest()
- : CV_MHIBaseTest( "mhi-gradient", "cvCalcMotionGradient" )
-{
- mhi_i = mhi_ref_i = INPUT;
- test_array[INPUT].push(NULL);
- test_array[OUTPUT].push(NULL);
- test_array[OUTPUT].push(NULL);
- test_array[REF_OUTPUT].push(NULL);
- test_array[REF_OUTPUT].push(NULL);
- delta1 = delta2 = 0;
- aperture_size = 0;
- delta_range_log = 4;
-
- default_timing_param_names = motempl_gradient_param_names;
-}
-
-
-int CV_MHIGradientTest::write_default_params( CvFileStorage* fs )
-{
- int code = CvArrTest::write_default_params( fs );
- if( code < 0 )
- return code;
-
- if( ts->get_testing_mode() == CvTS::TIMING_MODE )
- {
- start_write_param( fs );
- write_int_list( fs, "aperture", motempl_gradient_aperture, CV_DIM(motempl_gradient_aperture) );
- }
-
- return code;
-}
-
-
-void CV_MHIGradientTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- CV_MHIBaseTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
-
- types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_8UC1;
- types[OUTPUT][1] = types[REF_OUTPUT][1] = CV_32FC1;
- delta1 = exp(cvTsRandReal(rng)*delta_range_log + 1.);
- delta2 = exp(cvTsRandReal(rng)*delta_range_log + 1.);
- aperture_size = (cvTsRandInt(rng)%3)*2+3;
- //duration = exp(cvTsRandReal(rng)*max_log_duration);
- //timestamp = duration + cvTsRandReal(rng)*30.-10.;
-}
-
-
-void CV_MHIGradientTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images )
-{
- CV_MHIBaseTest::get_timing_test_array_types_and_sizes( test_case_idx, sizes, types,
- whole_sizes, are_images );
- types[OUTPUT][0] = CV_8UC1;
- types[OUTPUT][1] = CV_32FC1;
- aperture_size = cvReadInt( find_timing_param( "aperture" ), 3 );
- delta1 = duration*0.02;
- delta2 = duration*0.2;
-}
-
-
-void CV_MHIGradientTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- sprintf( ptr, "aperture=%d,", aperture_size );
- ptr += strlen(ptr);
- params_left--;
-
- CV_MHIBaseTest::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-
-double CV_MHIGradientTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int j )
-{
- return j == 0 ? 0 : 2e-1;
-}
-
-
-void CV_MHIGradientTest::run_func()
-{
- cvCalcMotionGradient( test_array[INPUT][0], test_array[OUTPUT][0],
- test_array[OUTPUT][1], delta1, delta2, aperture_size );
-}
-
-
-void CV_MHIGradientTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- cvTsMHIGradient( &test_mat[INPUT][0], &test_mat[REF_OUTPUT][0],
- &test_mat[REF_OUTPUT][1], delta1, delta2, aperture_size );
- cvTsAdd( &test_mat[REF_OUTPUT][1], cvScalarAll(1.), 0, cvScalarAll(0.),
- cvScalarAll(1.), &test_mat[REF_OUTPUT][1], 0 );
- cvTsAdd( &test_mat[OUTPUT][1], cvScalarAll(1.), 0, cvScalarAll(0.),
- cvScalarAll(1.), &test_mat[OUTPUT][1], 0 );
-}
-
-
-CV_MHIGradientTest mhi_gradient_test;
-
-
-////////////////////// calc global orientation /////////////////////////
-
-static double
-cvTsCalcGlobalOrientation( const CvMat* orient, const CvMat* mask, const CvMat* mhi,
- double timestamp, double duration )
-{
- const int HIST_SIZE = 12;
- int y, x;
- int histogram[HIST_SIZE];
- int max_bin = 0;
-
- double base_orientation = 0, delta_orientation = 0, weight = 0;
- double low_time, global_orientation;
-
- memset( histogram, 0, sizeof( histogram ));
- timestamp = 0;
-
- for( y = 0; y < orient->rows; y++ )
- {
- const float* orient_data = (const float*)(orient->data.ptr + y*orient->step);
- const uchar* mask_data = mask->data.ptr + y*mask->step;
- const float* mhi_data = (const float*)(mhi->data.ptr + y*mhi->step);
- for( x = 0; x < orient->cols; x++ )
- if( mask_data[x] )
- {
- int bin = cvFloor( (orient_data[x]*HIST_SIZE)/360 );
- histogram[bin < 0 ? 0 : bin >= HIST_SIZE ? HIST_SIZE-1 : bin]++;
- if( mhi_data[x] > timestamp )
- timestamp = mhi_data[x];
- }
- }
-
- low_time = timestamp - duration;
-
- for( x = 1; x < HIST_SIZE; x++ )
- {
- if( histogram[x] > histogram[max_bin] )
- max_bin = x;
- }
-
- base_orientation = ((double)max_bin*360)/HIST_SIZE;
-
- for( y = 0; y < orient->rows; y++ )
- {
- const float* orient_data = (const float*)(orient->data.ptr + y*orient->step);
- const float* mhi_data = (const float*)(mhi->data.ptr + y*mhi->step);
- const uchar* mask_data = mask->data.ptr + y*mask->step;
-
- for( x = 0; x < orient->cols; x++ )
- {
- if( mask_data[x] && mhi_data[x] > low_time )
- {
- double diff = orient_data[x] - base_orientation;
- double delta_weight = (((mhi_data[x] - low_time)/duration)*254 + 1)/255;
-
- if( diff < -180 ) diff += 360;
- if( diff > 180 ) diff -= 360;
-
- if( delta_weight > 0 && fabs(diff) < 45 )
- {
- delta_orientation += diff*delta_weight;
- weight += delta_weight;
- }
- }
- }
- }
-
- if( weight == 0 )
- global_orientation = base_orientation;
- else
- {
- global_orientation = base_orientation + delta_orientation/weight;
- if( global_orientation < 0 ) global_orientation += 360;
- if( global_orientation > 360 ) global_orientation -= 360;
- }
-
- return global_orientation;
-}
-
-
-class CV_MHIGlobalOrientTest : public CV_MHIBaseTest
-{
-public:
- CV_MHIGlobalOrientTest();
-
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void get_timing_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types,
- CvSize** whole_sizes, bool *are_images );
- void get_minmax_bounds( int i, int j, int type, CvScalar* low, CvScalar* high );
- double get_success_error_level( int test_case_idx, int i, int j );
- int validate_test_results( int test_case_idx );
- void run_func();
- double angle, min_angle, max_angle;
-};
-
-
-CV_MHIGlobalOrientTest::CV_MHIGlobalOrientTest()
- : CV_MHIBaseTest( "mhi-global", "cvCalcGlobalOrientation" )
-{
- mhi_i = mhi_ref_i = INPUT;
- test_array[INPUT].push(NULL);
- test_array[INPUT].push(NULL);
- test_array[INPUT].push(NULL);
- min_angle = max_angle = 0;
-
- default_timing_param_names = motempl_global_param_names;
-}
-
-
-void CV_MHIGlobalOrientTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- CV_MHIBaseTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- CvSize size = sizes[INPUT][0];
-
- size.width = MAX( size.width, 16 );
- size.height = MAX( size.height, 16 );
- sizes[INPUT][0] = sizes[INPUT][1] = sizes[INPUT][2] = size;
-
- types[INPUT][1] = CV_8UC1; // mask
- types[INPUT][2] = CV_32FC1; // orientation
-
- min_angle = cvTsRandReal(rng)*359.9;
- max_angle = cvTsRandReal(rng)*359.9;
- if( min_angle >= max_angle )
- {
- double t;
- CV_SWAP( min_angle, max_angle, t );
- }
- max_angle += 0.1;
- duration = exp(cvTsRandReal(rng)*max_log_duration);
- timestamp = duration + cvTsRandReal(rng)*30.-10.;
-}
-
-
-void CV_MHIGlobalOrientTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images )
-{
- CV_MHIBaseTest::get_timing_test_array_types_and_sizes( test_case_idx, sizes, types,
- whole_sizes, are_images );
- types[INPUT][1] = CV_8UC1;
- types[INPUT][2] = CV_32FC1;
-}
-
-
-void CV_MHIGlobalOrientTest::get_minmax_bounds( int i, int j, int type, CvScalar* low, CvScalar* high )
-{
- CV_MHIBaseTest::get_minmax_bounds( i, j, type, low, high );
- if( i == INPUT && j == 2 )
- {
- *low = cvScalarAll(min_angle);
- *high = cvScalarAll(max_angle);
- }
-}
-
-
-double CV_MHIGlobalOrientTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- return 15;
-}
-
-
-void CV_MHIGlobalOrientTest::run_func()
-{
- angle = cvCalcGlobalOrientation( test_array[INPUT][2], test_array[INPUT][1],
- test_array[INPUT][0], timestamp, duration );
-}
-
-
-int CV_MHIGlobalOrientTest::validate_test_results( int test_case_idx )
-{
- //printf("%d. rows=%d, cols=%d, nzmask=%d\n", test_case_idx, test_mat[INPUT][1].rows, test_mat[INPUT][1].cols,
- // cvCountNonZero(test_array[INPUT][1]));
-
- double ref_angle = cvTsCalcGlobalOrientation( &test_mat[INPUT][2], &test_mat[INPUT][1],
- &test_mat[INPUT][0], timestamp, duration );
- double err_level = get_success_error_level( test_case_idx, 0, 0 );
- int code = CvTS::OK;
- int nz = cvCountNonZero( test_array[INPUT][1] );
-
- if( nz > 32 && !(min_angle - err_level <= angle &&
- max_angle + err_level >= angle) &&
- !(min_angle - err_level <= angle+360 &&
- max_angle + err_level >= angle+360) )
- {
- ts->printf( CvTS::LOG, "The angle=%g is outside (%g,%g) range\n",
- angle, min_angle - err_level, max_angle + err_level );
- code = CvTS::FAIL_BAD_ACCURACY;
- }
- else if( fabs(angle - ref_angle) > err_level &&
- fabs(360 - fabs(angle - ref_angle)) > err_level )
- {
- ts->printf( CvTS::LOG, "The angle=%g differs too much from reference value=%g\n",
- angle, ref_angle );
- code = CvTS::FAIL_BAD_ACCURACY;
- }
-
- if( code < 0 )
- ts->set_failed_test_info( code );
- return code;
-}
-
-
-CV_MHIGlobalOrientTest mhi_global_orient_test;
-
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-#if 0
-
-#define PUSHC(Y,X) { CurStack[CStIn].y=Y; \
- CurStack[CStIn].x=X; \
- CStIn++;}
-#define PUSHN(Y,X) { NextStack[NStIn].y=Y; \
- NextStack[NStIn].x=X; \
- NStIn++;}
-
-#define POP(Y,X) { CStIn--; \
- Y=CurStack[CStIn].y; \
- X=CurStack[CStIn].x;}
-
-void testFill( float* img,
- int step,
- CvSize imgSize,
- CvPoint seed_point,
- float nv,
- float* RP,
- int itsstep,
- float SegThresh,
- CvConnectedComp* region)
-{
- CvPoint* CurStack = (CvPoint*)cvAlloc(imgSize.height*imgSize.width*sizeof(CvPoint));
- CvPoint* NextStack = (CvPoint*)cvAlloc(imgSize.height*imgSize.width*sizeof(CvPoint));
- CvPoint* Temp;
- int ownstep=step/4;
- int RPstep=itsstep/4;
- float thr = -SegThresh;
- float nthr = thr*2;
- int CStIn=0;
- int NStIn=0;
- int TempIn;
- int x,y;
- int XMax=0;
- int YMax=0;
- int XMin = imgSize.width;
- int YMin = imgSize.height;
- int Sum=0;
-
- PUSHC(seed_point.y,seed_point.x);
-again:
- while(CStIn)
- {
- POP(y,x);
- XMax = MAX(XMax,x);
- YMax = MAX(YMax,y);
- XMin = MIN(XMin,x);
- YMin = MIN(YMin,y);
- if((y>0)&&(!RP[(y-1)*RPstep+x])&&
- (((img[(y-1)*ownstep+x]-img[y*ownstep+x])<0)&&
- ((img[(y-1)*ownstep+x]-img[y*ownstep+x])>=thr)))PUSHC(y-1,x);
- if((y>0)&&(!RP[(y-1)*RPstep+x])&&
- (((img[(y-1)*ownstep+x]-img[y*ownstep+x])<=thr)&&
- ((img[(y-1)*ownstep+x]-img[y*ownstep+x])>=nthr)))PUSHN(y-1,x);
- if((y<imgSize.height-1)&&(!RP[(y+1)*RPstep+x])&&
- (((img[(y+1)*ownstep+x]-img[y*ownstep+x])<=0)&&
- ((img[(y+1)*ownstep+x]-img[y*ownstep+x])>=thr)))PUSHC(y+1,x);
- if((y<imgSize.height-1)&&(!RP[(y+1)*RPstep+x])&&
- (((img[(y+1)*ownstep+x]-img[y*ownstep+x])<=thr)&&
- ((img[(y+1)*ownstep+x]-img[y*ownstep+x])>=nthr)))PUSHN(y+1,x);
- if((x>0)&&(!RP[y*RPstep+x-1])&&
- (((img[y*ownstep+x-1]-img[y*ownstep+x])<=0)&&
- ((img[y*ownstep+x-1]-img[y*ownstep+x])>=thr)))PUSHC(y,x-1);
- if((x>0)&&(!RP[y*RPstep+x-1])&&
- (((img[y*ownstep+x-1]-img[y*ownstep+x])<=thr)&&
- ((img[y*ownstep+x-1]-img[y*ownstep+x])>=nthr)))PUSHN(y,x-1);
- if((x<imgSize.width-1)&&(!RP[y*RPstep+x+1])&&
- (((img[y*ownstep+x+1]-img[y*ownstep+x])<=0)&&
- ((img[y*ownstep+x+1]-img[y*ownstep+x])>=thr)))PUSHC(y,x+1);
- if((x<imgSize.width-1)&&(!RP[y*RPstep+x+1])&&
- (((img[y*ownstep+x+1]-img[y*ownstep+x])<=thr)&&
- ((img[y*ownstep+x+1]-img[y*ownstep+x])>=nthr)))PUSHN(y,x+1);
- Sum++;
- RP[y*RPstep+x]=nv;
- img[y*ownstep+x] = -255;
- }
- if(NStIn)
- {
- Temp=CurStack;
- CurStack=NextStack;
- NextStack=Temp;
- TempIn=CStIn;
- CStIn=NStIn;
- NStIn=TempIn;
- goto again;
- }
- region->area = Sum;
- region->rect.x = XMin;
- region->rect.y = YMin;
- region->rect.width = XMax - XMin + 1;
- region->rect.height = YMax - YMin + 1;
- region->value = cvScalar(nv);
- cvFree(&CurStack);
- cvFree(&NextStack);
- return;
-}
-
-/* Testing parameters */
-static char TestName[] = "Checking MotionSegmentation";
-static char TestClass[] = "Algorithm";
-static int lImageWidth;
-static int lImageHeight;
-
-static int read_param = 0;
-static int data_types = 0;
-static float thresh = 0;
-static double EPSILON = 3;
-
-
-static int fcaMotSeg( void )
-{
- int step;
- float* src;
- AtsRandState state;
- double Error = 0;
- int color = 1;
- CvSize roi;
-
- IplImage* mhi;
- IplImage* mask32f;
- IplImage* test32f;
- CvSeq* seq1 = NULL;
- CvSeq* seq2 = NULL;
- CvMemStorage* storage;
- CvSeqWriter writer;
-
- CvConnectedComp ConComp;
-
- storage = cvCreateMemStorage( 0 );
- cvClearMemStorage( storage );
-
- /* Initialization global parameters */
- if( !read_param )
- {
- read_param = 1;
- /* Determining which test are needed to run */
- trsCaseRead( &data_types,"/u/s/f/a", "a",
- "u - unsigned char, s - signed char, f - float, a - all" );
- /* Reading test-parameters */
- trsiRead( &lImageHeight, "20", "Image height" );
- trsiRead( &lImageWidth, "20", "Image width" );
- trssRead( &thresh, "10", "Segmentation Threshold" );
- }
- if( data_types != 3 && data_types != 0 ) return TRS_UNDEF;
-
- /* Creating images for testing */
- mhi = cvCreateImage(cvSize(lImageWidth, lImageHeight), IPL_DEPTH_32F, 1);
- mask32f = cvCreateImage(cvSize(lImageWidth, lImageHeight), IPL_DEPTH_32F, 1);
- test32f = cvCreateImage(cvSize(lImageWidth, lImageHeight), IPL_DEPTH_32F, 1);
-
- atsRandInit(&state,40,100,60);
- atsFillRandomImageEx(mhi, &state );
- src = (float*)mhi->imageData;
- step = mhi->widthStep/4;
- int i;
- for(i=0; i<lImageHeight;i++)
- {
- for(int j=0; j<lImageWidth;j++)
- {
- if(src[i*step+j]>80)src[i*step+j]=80;
- }
- }
- cvZero(test32f);
- seq1 = cvSegmentMotion(mhi,mask32f,storage,80,thresh);
- cvStartWriteSeq( 0, sizeof( CvSeq ), sizeof( CvConnectedComp ), storage, &writer );
- roi.width = lImageWidth;
- roi.height = lImageHeight;
- for(i=1;i<lImageHeight-1;i++)
- {
- for(int j=1;j<lImageWidth-1;j++)
- {
- if(src[i*step+j]==80)
- {
- if((src[(i-1)*step+j]>=(80-thresh))&&(src[(i-1)*step+j]<80))
- {
- CvPoint MinPoint;
- MinPoint.x=j;
- MinPoint.y=i-1;
- testFill(src,
- step*4,
- roi,
- MinPoint,
- (float)color,
- (float*)test32f->imageData,
- test32f->widthStep,
- thresh,
- &ConComp);
- ConComp.value = cvScalar(color);
- CV_WRITE_SEQ_ELEM( ConComp, writer );
- color+=1;
- }
-
- if((src[i*step+j-1]>=(80-thresh))&&(src[i*step+j-1]<80))
- {
- CvPoint MinPoint;
- MinPoint.x=j-1;
- MinPoint.y=i;
- testFill(src,
- step*4,
- roi,
- MinPoint,
- (float)color,
- (float*)test32f->imageData,
- test32f->widthStep,
- thresh,
- &ConComp);
- ConComp.value = cvScalar(color);
- CV_WRITE_SEQ_ELEM( ConComp, writer );
- color+=1;
- }
- if((src[i*step+j+1]>=(80-thresh))&&(src[i*step+j+1]<80))
- {
- CvPoint MinPoint;
- MinPoint.x=j+1;
- MinPoint.y=i;
- testFill(src,
- step*4,
- roi,
- MinPoint,
- (float)color,
- (float*)test32f->imageData,
- test32f->widthStep,
- thresh,
- &ConComp);
- ConComp.value = cvScalar(color);
- CV_WRITE_SEQ_ELEM( ConComp, writer );
- color+=1;
- }
- if((src[(i+1)*step+j]>=(80-thresh))&&(src[(i+1)*step+j]<80))
- {
- CvPoint MinPoint;
- MinPoint.x=j;
- MinPoint.y=i+1;
- testFill(src,
- step*4,
- roi,
- MinPoint,
- (float)color,
- (float*)test32f->imageData,
- test32f->widthStep,
- thresh,
- &ConComp);
- ConComp.value = cvScalar(color);
- CV_WRITE_SEQ_ELEM( ConComp, writer );
- color+=1;
- }
-
- }
- }
- }
- seq2 = cvEndWriteSeq( &writer );
- Error += cvNorm(test32f,mask32f,CV_C);
- cvReleaseMemStorage(&storage);
- cvReleaseImage(&mhi);
- cvReleaseImage(&test32f);
- cvReleaseImage(&mask32f);
- /* Free Memory */
-
- if(Error>=EPSILON)return TRS_FAIL;
- return TRS_OK;
-} /* fcaSobel8uC1R */
-
-void InitAMotSeg(void)
-{
- trsReg( "cvMotSeg", TestName, TestClass, fcaMotSeg);
-} /* InitASobel */
-
-#endif
-
-/* End of file. */
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
-// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of the copyright holders may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-#include <vector>
-#include <string>
-using namespace std;
-using namespace cv;
-
-class CV_MserTest : public CvTest
-{
-public:
- CV_MserTest();
-protected:
- void run(int);
- int LoadBoxes(const char* path, vector<CvBox2D>& boxes);
- int SaveBoxes(const char* path, const vector<CvBox2D>& boxes);
- int CompareBoxes(const vector<CvBox2D>& boxes1,const vector<CvBox2D>& boxes2, float max_rel_diff = 0.01f);
-};
-
-CV_MserTest::CV_MserTest() : CvTest("MSER","cvExtractMSER")
-{
-}
-
-int CV_MserTest::LoadBoxes(const char* path, vector<CvBox2D>& boxes)
-{
- boxes.clear();
- FILE* f = fopen(path,"r");
-
- if (f==NULL)
- {
- return 0;
- }
-
- while (!feof(f))
- {
- CvBox2D box;
- fscanf(f,"%f,%f,%f,%f,%f\n",&box.angle,&box.center.x,&box.center.y,&box.size.width,&box.size.height);
- boxes.push_back(box);
- }
- fclose(f);
- return 1;
-}
-
-int CV_MserTest::SaveBoxes(const char* path, const vector<CvBox2D>& boxes)
-{
- FILE* f = fopen(path,"w");
- if (f==NULL)
- {
- return 0;
- }
- for (int i=0;i<(int)boxes.size();i++)
- {
- fprintf(f,"%f,%f,%f,%f,%f\n",boxes[i].angle,boxes[i].center.x,boxes[i].center.y,boxes[i].size.width,boxes[i].size.height);
- }
- fclose(f);
- return 1;
-}
-
-int CV_MserTest::CompareBoxes(const vector<CvBox2D>& boxes1,const vector<CvBox2D>& boxes2, float max_rel_diff)
-{
- if (boxes1.size() != boxes2.size())
- return 0;
-
- for (int i=0; i<(int)boxes1.size();i++)
- {
- float rel_diff;
- if (!((boxes1[i].angle == 0.0f) && (abs(boxes2[i].angle) < max_rel_diff)))
- {
- rel_diff = abs(boxes1[i].angle-boxes2[i].angle)/abs(boxes1[i].angle);
- if (rel_diff > max_rel_diff)
- return i;
- }
-
- if (!((boxes1[i].center.x == 0.0f) && (abs(boxes2[i].center.x) < max_rel_diff)))
- {
- rel_diff = abs(boxes1[i].center.x-boxes2[i].center.x)/abs(boxes1[i].center.x);
- if (rel_diff > max_rel_diff)
- return i;
- }
-
- if (!((boxes1[i].center.y == 0.0f) && (abs(boxes2[i].center.y) < max_rel_diff)))
- {
- rel_diff = abs(boxes1[i].center.y-boxes2[i].center.y)/abs(boxes1[i].center.y);
- if (rel_diff > max_rel_diff)
- return i;
- }
- if (!((boxes1[i].size.width == 0.0f) && (abs(boxes2[i].size.width) < max_rel_diff)))
- {
- rel_diff = abs(boxes1[i].size.width-boxes2[i].size.width)/abs(boxes1[i].size.width);
- if (rel_diff > max_rel_diff)
- return i;
- }
-
- if (!((boxes1[i].size.height == 0.0f) && (abs(boxes2[i].size.height) < max_rel_diff)))
- {
- rel_diff = abs(boxes1[i].size.height-boxes2[i].size.height)/abs(boxes1[i].size.height);
- if (rel_diff > max_rel_diff)
- return i;
- }
- }
-
- return -1;
-}
-
-void CV_MserTest::run(int)
-{
- string image_path = string(ts->get_data_path()) + "mser/puzzle.png";
-
- IplImage* img = cvLoadImage( image_path.c_str());
- if (!img)
- {
- ts->printf( CvTS::LOG, "Unable to open image mser/puzzle.png\n");
- ts->set_failed_test_info(CvTS::FAIL_MISSING_TEST_DATA);
- return;
- }
-
- CvSeq* contours;
- CvMemStorage* storage= cvCreateMemStorage();
- IplImage* hsv = cvCreateImage( cvGetSize( img ), IPL_DEPTH_8U, 3 );
- cvCvtColor( img, hsv, CV_BGR2YCrCb );
- CvMSERParams params = cvMSERParams();//cvMSERParams( 5, 60, cvRound(.2*img->width*img->height), .25, .2 );
- cvExtractMSER( hsv, NULL, &contours, storage, params );
-
- vector<CvBox2D> boxes;
- vector<CvBox2D> boxes_orig;
- for ( int i = 0; i < contours->total; i++ )
- {
- CvContour* r = *(CvContour**)cvGetSeqElem( contours, i );
- CvBox2D box = cvFitEllipse2( r );
- box.angle=(float)CV_PI/2-box.angle;
- boxes.push_back(box);
- }
-
- string boxes_path = string(ts->get_data_path()) + "mser/boxes.txt";
-
- if (!LoadBoxes(boxes_path.c_str(),boxes_orig))
- {
- SaveBoxes(boxes_path.c_str(),boxes);
- ts->printf( CvTS::LOG, "Unable to open data file mser/boxes.txt\n");
- ts->set_failed_test_info(CvTS::FAIL_MISSING_TEST_DATA);
- return;
- }
-
- const float dissimularity = 0.01f;
- int n_box = CompareBoxes(boxes_orig,boxes,dissimularity);
- if (n_box < 0)
- {
- ts->set_failed_test_info(CvTS::OK);
- }
- else
- {
- ts->set_failed_test_info(CvTS::FAIL_BAD_ACCURACY);
- ts->printf( CvTS::LOG, "Incorrect correspondence in %d box\n",n_box);
- }
-
- cvReleaseMemStorage(&storage);
- cvReleaseImage(&hsv);
- cvReleaseImage(&img);
-}
-
-CV_MserTest mser_test;
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
-// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of the copyright holders may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-#include <algorithm>
-#include <vector>
-#include <iostream>
-
-using namespace cv;
-using namespace cv::flann;
-
-//--------------------------------------------------------------------------------
-class NearestNeighborTest : public CvTest
-{
-public:
- NearestNeighborTest( const char* test_name, const char* test_funcs )
- : CvTest( test_name, test_funcs ) {}
-protected:
- static const int minValue = 0;
- static const int maxValue = 1;
- static const int dims = 30;
- static const int featuresCount = 2000;
- static const int K = 1; // * should also test 2nd nn etc.?
-
-
- virtual void run( int start_from );
- virtual void createModel( const Mat& data ) = 0;
- virtual int findNeighbors( Mat& points, Mat& neighbors ) = 0;
- virtual int checkGetPoins( const Mat& data );
- virtual int checkFindBoxed();
- virtual int checkFind( const Mat& data );
- virtual void releaseModel() = 0;
-};
-
-int NearestNeighborTest::checkGetPoins( const Mat& )
-{
- return CvTS::OK;
-}
-
-int NearestNeighborTest::checkFindBoxed()
-{
- return CvTS::OK;
-}
-
-int NearestNeighborTest::checkFind( const Mat& data )
-{
- int code = CvTS::OK;
- int pointsCount = 1000;
- float noise = 0.2f;
-
- RNG rng;
- Mat points( pointsCount, dims, CV_32FC1 );
- Mat results( pointsCount, K, CV_32SC1 );
-
- std::vector<int> fmap( pointsCount );
- for( int pi = 0; pi < pointsCount; pi++ )
- {
- int fi = rng.next() % featuresCount;
- fmap[pi] = fi;
- for( int d = 0; d < dims; d++ )
- points.at<float>(pi, d) = data.at<float>(fi, d) + rng.uniform(0.0f, 1.0f) * noise;
- }
-
- code = findNeighbors( points, results );
-
- if( code == CvTS::OK )
- {
- int correctMatches = 0;
- for( int pi = 0; pi < pointsCount; pi++ )
- {
- if( fmap[pi] == results.at<int>(pi, 0) )
- correctMatches++;
- }
-
- double correctPerc = correctMatches / (double)pointsCount;
- if (correctPerc < .75)
- {
- ts->printf( CvTS::LOG, "correct_perc = %d\n", correctPerc );
- code = CvTS::FAIL_BAD_ACCURACY;
- }
- }
-
- return code;
-}
-
-void NearestNeighborTest::run( int /*start_from*/ ) {
- int code = CvTS::OK, tempCode;
- Mat desc( featuresCount, dims, CV_32FC1 );
- randu( desc, Scalar(minValue), Scalar(maxValue) );
-
- createModel( desc );
-
- tempCode = checkGetPoins( desc );
- if( tempCode != CvTS::OK )
- {
- ts->printf( CvTS::LOG, "bad accuracy of GetPoints \n" );
- code = tempCode;
- }
-
- tempCode = checkFindBoxed();
- if( tempCode != CvTS::OK )
- {
- ts->printf( CvTS::LOG, "bad accuracy of FindBoxed \n" );
- code = tempCode;
- }
-
- tempCode = checkFind( desc );
- if( tempCode != CvTS::OK )
- {
- ts->printf( CvTS::LOG, "bad accuracy of Find \n" );
- code = tempCode;
- }
-
- releaseModel();
-
- ts->set_failed_test_info( code );
-}
-
-//--------------------------------------------------------------------------------
-class CV_LSHTest : public NearestNeighborTest
-{
-public:
- CV_LSHTest() : NearestNeighborTest( "lsh", "cvLSHQuery" ) {}
-protected:
- virtual void createModel( const Mat& data );
- virtual int findNeighbors( Mat& points, Mat& neighbors );
- virtual void releaseModel();
- struct CvLSH* lsh;
- CvMat desc;
-};
-
-void CV_LSHTest::createModel( const Mat& data )
-{
- desc = data;
- lsh = cvCreateMemoryLSH( data.cols, data.rows, 70, 20, CV_32FC1 );
- cvLSHAdd( lsh, &desc );
-}
-
-int CV_LSHTest::findNeighbors( Mat& points, Mat& neighbors )
-{
- const int emax = 20;
- Mat dist( points.rows, neighbors.cols, CV_64FC1);
- CvMat _dist = dist, _points = points, _neighbors = neighbors;
- cvLSHQuery( lsh, &_points, &_neighbors, &_dist, neighbors.cols, emax );
- return CvTS::OK;
-}
-
-void CV_LSHTest::releaseModel()
-{
- cvReleaseLSH( &lsh );
-}
-
-//--------------------------------------------------------------------------------
-class CV_FeatureTreeTest_C : public NearestNeighborTest
-{
-public:
- CV_FeatureTreeTest_C( const char* test_name, const char* test_funcs )
- : NearestNeighborTest( test_name, test_funcs ) {}
-protected:
- virtual int findNeighbors( Mat& points, Mat& neighbors );
- virtual void releaseModel();
- CvFeatureTree* tr;
- CvMat desc;
-};
-
-int CV_FeatureTreeTest_C::findNeighbors( Mat& points, Mat& neighbors )
-{
- const int emax = 20;
- Mat dist( points.rows, neighbors.cols, CV_64FC1);
- CvMat _dist = dist, _points = points, _neighbors = neighbors;
- cvFindFeatures( tr, &_points, &_neighbors, &_dist, neighbors.cols, emax );
- return CvTS::OK;
-}
-
-void CV_FeatureTreeTest_C::releaseModel()
-{
- cvReleaseFeatureTree( tr );
-}
-
-//--------------------------------------
-class CV_SpillTreeTest_C : public CV_FeatureTreeTest_C
-{
-public:
- CV_SpillTreeTest_C(): CV_FeatureTreeTest_C( "spilltree_c", "cvFindFeatures-spill" ) {}
-protected:
- virtual void createModel( const Mat& data );
-};
-
-void CV_SpillTreeTest_C::createModel( const Mat& data )
-{
- desc = data;
- tr = cvCreateSpillTree( &desc );
-}
-
-//--------------------------------------
-class CV_KDTreeTest_C : public CV_FeatureTreeTest_C
-{
-public:
- CV_KDTreeTest_C(): CV_FeatureTreeTest_C( "kdtree_c", "cvFindFeatures-kd" ) {}
-protected:
- virtual void createModel( const Mat& data );
- virtual int checkFindBoxed();
-};
-
-void CV_KDTreeTest_C::createModel( const Mat& data )
-{
- desc = data;
- tr = cvCreateKDTree( &desc );
-}
-
-int CV_KDTreeTest_C::checkFindBoxed()
-{
- Mat min(1, dims, CV_32FC1 ), max(1, dims, CV_32FC1 ), indices( 1, 1, CV_32SC1 );
- float l = minValue, r = maxValue;
- min.setTo(Scalar(l)), max.setTo(Scalar(r));
- CvMat _min = min, _max = max, _indices = indices;
- // TODO check indices
- if( cvFindFeaturesBoxed( tr, &_min, &_max, &_indices ) != featuresCount )
- return CvTS::FAIL_BAD_ACCURACY;
- return CvTS::OK;
-}
-
-//--------------------------------------------------------------------------------
-class CV_KDTreeTest_CPP : public NearestNeighborTest
-{
-public:
- CV_KDTreeTest_CPP() : NearestNeighborTest( "kdtree_cpp", "cv::KDTree funcs" ) {}
-protected:
- virtual void createModel( const Mat& data );
- virtual int checkGetPoins( const Mat& data );
- virtual int findNeighbors( Mat& points, Mat& neighbors );
- virtual int checkFindBoxed();
- virtual void releaseModel();
- KDTree* tr;
-};
-
-
-void CV_KDTreeTest_CPP::createModel( const Mat& data )
-{
- tr = new KDTree( data, false );
-}
-
-int CV_KDTreeTest_CPP::checkGetPoins( const Mat& data )
-{
- Mat res1( data.size(), data.type() ),
- res2( data.size(), data.type() ),
- res3( data.size(), data.type() );
- Mat idxs( 1, data.rows, CV_32SC1 );
- for( int pi = 0; pi < data.rows; pi++ )
- {
- idxs.at<int>(0, pi) = pi;
- // 1st way
- const float* point = tr->getPoint(pi);
- for( int di = 0; di < data.cols; di++ )
- res1.at<float>(pi, di) = point[di];
- }
- // 2nd way
- tr->getPoints( idxs.ptr<int>(0), data.rows, res2 );
-
- // 3d way
- tr->getPoints( idxs, res3 );
-
- if( norm( res1, data, NORM_L1) != 0 ||
- norm( res2, data, NORM_L1) != 0 ||
- norm( res3, data, NORM_L1) != 0)
- return CvTS::FAIL_BAD_ACCURACY;
- return CvTS::OK;
-}
-
-int CV_KDTreeTest_CPP::checkFindBoxed()
-{
- vector<float> min( dims, minValue), max(dims, maxValue);
- vector<int> indices;
- tr->findOrthoRange( &min[0], &max[0], &indices );
- // TODO check indices
- if( (int)indices.size() != featuresCount)
- return CvTS::FAIL_BAD_ACCURACY;
- return CvTS::OK;
-}
-
-int CV_KDTreeTest_CPP::findNeighbors( Mat& points, Mat& neighbors )
-{
- const int emax = 20;
- Mat neighbors2( neighbors.size(), CV_32SC1 );
- int j;
- vector<float> min(points.cols, minValue);
- vector<float> max(points.cols, maxValue);
- for( int pi = 0; pi < points.rows; pi++ )
- {
- // 1st way
- tr->findNearest( points.ptr<float>(pi), neighbors.cols, emax, neighbors.ptr<int>(pi) );
-
- // 2nd way
- vector<int> neighborsIdx2( neighbors2.cols, 0 );
- tr->findNearest( points.ptr<float>(pi), neighbors2.cols, emax, &neighborsIdx2 );
- vector<int>::const_iterator it2 = neighborsIdx2.begin();
- for( j = 0; it2 != neighborsIdx2.end(); ++it2, j++ )
- neighbors2.at<int>(pi,j) = *it2;
- }
-
- // compare results
- if( norm( neighbors, neighbors2, NORM_L1 ) != 0 )
- return CvTS::FAIL_BAD_ACCURACY;
-
- return CvTS::OK;
-}
-
-void CV_KDTreeTest_CPP::releaseModel()
-{
- delete tr;
-}
-
-//--------------------------------------------------------------------------------
-class CV_FlannTest : public NearestNeighborTest
-{
-public:
- CV_FlannTest( const char* test_name, const char* test_funcs )
- : NearestNeighborTest( test_name, test_funcs ) {}
-protected:
- void createIndex( const Mat& data, const IndexParams& params );
- int knnSearch( Mat& points, Mat& neighbors );
- int radiusSearch( Mat& points, Mat& neighbors );
- virtual void releaseModel();
- Index* index;
-};
-
-void CV_FlannTest::createIndex( const Mat& data, const IndexParams& params )
-{
- index = new Index( data, params );
-}
-
-int CV_FlannTest::knnSearch( Mat& points, Mat& neighbors )
-{
- Mat dist( points.rows, neighbors.cols, CV_32FC1);
- int knn = 1, j;
-
- // 1st way
- index->knnSearch( points, neighbors, dist, knn, SearchParams() );
-
- // 2nd way
- Mat neighbors1( neighbors.size(), CV_32SC1 );
- for( int i = 0; i < points.rows; i++ )
- {
- float* fltPtr = points.ptr<float>(i);
- vector<float> query( fltPtr, fltPtr + points.cols );
- vector<int> indices( neighbors1.cols, 0 );
- vector<float> dists( dist.cols, 0 );
- index->knnSearch( query, indices, dists, knn, SearchParams() );
- vector<int>::const_iterator it = indices.begin();
- for( j = 0; it != indices.end(); ++it, j++ )
- neighbors1.at<int>(i,j) = *it;
- }
-
- // compare results
- if( norm( neighbors, neighbors1, NORM_L1 ) != 0 )
- return CvTS::FAIL_BAD_ACCURACY;
-
- return CvTS::OK;
-}
-
-int CV_FlannTest::radiusSearch( Mat& points, Mat& neighbors )
-{
- Mat dist( 1, neighbors.cols, CV_32FC1);
- Mat neighbors1( neighbors.size(), CV_32SC1 );
- float radius = 10.0f;
- int j;
-
- // radiusSearch can only search one feature at a time for range search
- for( int i = 0; i < points.rows; i++ )
- {
- // 1st way
- Mat p( 1, points.cols, CV_32FC1, points.ptr<float>(i) ),
- n( 1, neighbors.cols, CV_32SC1, neighbors.ptr<int>(i) );
- index->radiusSearch( p, n, dist, radius, SearchParams() );
-
- // 2nd way
- float* fltPtr = points.ptr<float>(i);
- vector<float> query( fltPtr, fltPtr + points.cols );
- vector<int> indices( neighbors1.cols, 0 );
- vector<float> dists( dist.cols, 0 );
- index->radiusSearch( query, indices, dists, radius, SearchParams() );
- vector<int>::const_iterator it = indices.begin();
- for( j = 0; it != indices.end(); ++it, j++ )
- neighbors1.at<int>(i,j) = *it;
- }
- // compare results
- if( norm( neighbors, neighbors1, NORM_L1 ) != 0 )
- return CvTS::FAIL_BAD_ACCURACY;
-
- return CvTS::OK;
-}
-
-void CV_FlannTest::releaseModel()
-{
- delete index;
-}
-
-//---------------------------------------
-class CV_FlannLinearIndexTest : public CV_FlannTest
-{
-public:
- CV_FlannLinearIndexTest() : CV_FlannTest( "flann_linear", "LinearIndex" ) {}
-protected:
- virtual void createModel( const Mat& data ) { createIndex( data, LinearIndexParams() ); }
- virtual int findNeighbors( Mat& points, Mat& neighbors ) { return knnSearch( points, neighbors ); }
-};
-
-//---------------------------------------
-class CV_FlannKMeansIndexTest : public CV_FlannTest
-{
-public:
- CV_FlannKMeansIndexTest() : CV_FlannTest( "flann_kmeans", "KMeansIndex" ) {}
-protected:
- virtual void createModel( const Mat& data ) { createIndex( data, KMeansIndexParams() ); }
- virtual int findNeighbors( Mat& points, Mat& neighbors ) { return radiusSearch( points, neighbors ); }
-};
-
-//---------------------------------------
-class CV_FlannKDTreeIndexTest : public CV_FlannTest
-{
-public:
- CV_FlannKDTreeIndexTest() : CV_FlannTest( "flann_kdtree", "KDTreeIndex" ) {}
-protected:
- virtual void createModel( const Mat& data ) { createIndex( data, KDTreeIndexParams() ); }
- virtual int findNeighbors( Mat& points, Mat& neighbors ) { return radiusSearch( points, neighbors ); }
-};
-
-//----------------------------------------
-class CV_FlannCompositeIndexTest : public CV_FlannTest
-{
-public:
- CV_FlannCompositeIndexTest() : CV_FlannTest( "flann_composite", "CompositeIndex" ) {}
-protected:
- virtual void createModel( const Mat& data ) { createIndex( data, CompositeIndexParams() ); }
- virtual int findNeighbors( Mat& points, Mat& neighbors ) { return knnSearch( points, neighbors ); }
-};
-
-//----------------------------------------
-class CV_FlannAutotunedIndexTest : public CV_FlannTest
-{
-public:
- CV_FlannAutotunedIndexTest() : CV_FlannTest( "flann_autotuned", "AutotunedIndex" ) {}
-protected:
- virtual void createModel( const Mat& data ) { createIndex( data, AutotunedIndexParams() ); }
- virtual int findNeighbors( Mat& points, Mat& neighbors ) { return knnSearch( points, neighbors ); }
-};
-//----------------------------------------
-class CV_FlannSavedIndexTest : public CV_FlannTest
-{
-public:
- CV_FlannSavedIndexTest() : CV_FlannTest( "flann_saved", "SavedIndex" ) {}
-protected:
- virtual void createModel( const Mat& data );
- virtual int findNeighbors( Mat& points, Mat& neighbors ) { return knnSearch( points, neighbors ); }
-};
-
-void CV_FlannSavedIndexTest::createModel(const cv::Mat &data)
-{
- switch ( cvRandInt(ts->get_rng()) % 2 )
- {
- //case 0: createIndex( data, LinearIndexParams() ); break; // nothing to save for linear search
- case 0: createIndex( data, KMeansIndexParams() ); break;
- case 1: createIndex( data, KDTreeIndexParams() ); break;
- //case 2: createIndex( data, CompositeIndexParams() ); break; // nothing to save for linear search
- //case 2: createIndex( data, AutotunedIndexParams() ); break; // possible linear index !
- default: assert(0);
- }
- char filename[50];
- tmpnam( filename );
- if(filename[0] == '\\') filename[0] = '_';
- index->save( filename );
-
- createIndex( data, SavedIndexParams(filename));
- remove( filename );
-}
-
-CV_LSHTest lsh_test;
-CV_SpillTreeTest_C spilltree_test_c;
-CV_KDTreeTest_C kdtree_test_c;
-CV_KDTreeTest_CPP kdtree_test_cpp;
-CV_FlannLinearIndexTest flann_linear_test;
-CV_FlannKMeansIndexTest flann_kmeans_test;
-CV_FlannKDTreeIndexTest flann_kdtree_test;
-CV_FlannCompositeIndexTest flann_composite_test;
-CV_FlannAutotunedIndexTest flann_autotuned_test;
-CV_FlannSavedIndexTest flann_saved_test;
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-#if 0
-
-/* Testing parameters */
-static char FuncName[] = "cvCalcOpticalFlowHS";
-static char TestName[] = "Optical flow (Horn & Schunck)";
-static char TestClass[] = "Algorithm";
-
-static long lImageWidth;
-static long lImageHeight;
-static float lambda;
-
-#define EPSILON 0.0001f
-
-static int fmaCalcOpticalFlowHS( void )
-{
- /* Some Variables */
- int i,j,k;
-
- uchar* roiA;
- uchar* roiB;
-
- float* VelocityX;
- float* VelocityY;
-
- float* auxVelocityX;
- float* auxVelocityY;
-
- float* DerX;
- float* DerY;
- float* DerT;
-
- long lErrors = 0;
-
- CvTermCriteria criteria;
-
- int usePrevious;
-
- int Stop = 0;
- int iteration = 0;
- float epsilon = 0;
-
- static int read_param = 0;
-
- /* Initialization global parameters */
- if( !read_param )
- {
- read_param = 1;
- /* Reading test-parameters */
- trslRead( &lImageHeight, "300", "Image height" );
- trslRead( &lImageWidth, "300", "Image width" );
- trssRead( &lambda, "20", "lambda" );
- }
-
- /* initialization - for warning disable */
- criteria.epsilon = 0;
- criteria.max_iter = 0;
- criteria.type = 1;
-
- /* Allocating memory for all frames */
- IplImage* imgA = cvCreateImage( cvSize(lImageWidth,lImageHeight), IPL_DEPTH_8U, 1 );
- IplImage* imgB = cvCreateImage( cvSize(lImageWidth,lImageHeight), IPL_DEPTH_8U, 1 );
-
- IplImage* testVelocityX = cvCreateImage( cvSize(lImageWidth,lImageHeight), IPL_DEPTH_32F, 1 );
- IplImage* testVelocityY = cvCreateImage( cvSize(lImageWidth,lImageHeight), IPL_DEPTH_32F, 1 );
-
- VelocityX = (float*)cvAlloc( lImageWidth*lImageHeight * sizeof(float) );
- VelocityY = (float*)cvAlloc( lImageWidth*lImageHeight * sizeof(float) );
-
- auxVelocityX = (float*)cvAlloc( lImageWidth*lImageHeight * sizeof(float) );
- auxVelocityY = (float*)cvAlloc( lImageWidth*lImageHeight * sizeof(float) );
-
- DerX = (float*)cvAlloc( lImageWidth*lImageHeight * sizeof(float) );
- DerY = (float*)cvAlloc( lImageWidth*lImageHeight * sizeof(float) );
- DerT = (float*)cvAlloc( lImageWidth*lImageHeight * sizeof(float) );
-
- /* Filling images */
- ats1bInitRandom( 0, 255, (uchar*)imgA->imageData, lImageWidth * lImageHeight );
- ats1bInitRandom( 0, 255, (uchar*)imgB->imageData, lImageWidth * lImageHeight );
-
- /* set ROI of images */
- roiA = (uchar*)imgA->imageData;
- roiB = (uchar*)imgB->imageData;
-
- /* example of 3*3 ROI*/
- /*roiA[0] = 0;
- roiA[1] = 1;
- roiA[2] = 2;
- roiA[lImageWidth] = 0;
- roiA[lImageWidth+1] = 1;
- roiA[lImageWidth+2] = 2;
- roiA[2*lImageWidth] = 0;
- roiA[2*lImageWidth+1] = 1;
- roiA[2*lImageWidth+2] = 2;
-
- roiB[0] = 1;
- roiB[1] = 2;
- roiB[2] = 3;
- roiB[lImageWidth] = 1;
- roiB[lImageWidth+1] = 2;
- roiB[lImageWidth+2] = 3;
- roiB[2*lImageWidth] = 1;
- roiB[2*lImageWidth+1] = 2;
- roiB[2*lImageWidth+2] = 3;*/
-/****************************************************************************************\
-* Calculate derivatives *
-\****************************************************************************************/
- for (i=0; i<lImageHeight; i++)
- {
- for(j=0; j<lImageWidth; j++)
- {
- int jr,jl,it,ib;
-
- if ( j==lImageWidth-1 )
- jr = lImageWidth-1;
- else jr = j + 1;
-
- if ( j==0 )
- jl = 0;
- else jl = j - 1;
-
- if ( i==(lImageHeight - 1) )
- ib = lImageHeight - 1;
- else ib = i + 1;
-
- if ( i==0 )
- it = 0;
- else it = i - 1;
-
- DerX[ i*lImageWidth + j ] = (float)
- (roiA[ (it)*imgA->widthStep + jr ]
- - roiA[ (it)*imgA->widthStep + jl ]
- + 2*roiA[ (i)*imgA->widthStep + jr ]
- - 2*roiA[ (i)*imgA->widthStep + jl ]
- + roiA[ (ib)*imgA->widthStep + jr ]
- - roiA[ (ib)*imgA->widthStep + jl ])/8 ;
-
- DerY[ i*lImageWidth + j ] = (float)
- ( roiA[ (ib)*imgA->widthStep + jl ]
- + 2*roiA[ (ib)*imgA->widthStep + j ]
- + roiA[ (ib)*imgA->widthStep + jr ]
- - roiA[ (it)*imgA->widthStep + jl ]
- - 2*roiA[ (it)*imgA->widthStep + j ]
- - roiA[ (it)*imgA->widthStep + jr ])/8 ;
-
- DerT[ i*lImageWidth + j ] = (float)
- (roiB[i*imgB->widthStep + j] - roiA[i*imgA->widthStep + j]);
- }
- }
-for( usePrevious = 0; usePrevious < 2; usePrevious++ )
-{
-/****************************************************************************************\
-* Cases *
-\****************************************************************************************/
- for ( k = 0; k < 4; k++ )
- {
- switch (k)
- {
- case 0:
- {
- criteria.type = CV_TERMCRIT_ITER;
- criteria.max_iter = 3;
-
- trsWrite( ATS_LST|ATS_CON,
- "usePrevious = %d, criteria = ITER, max_iter = %d\n",
- usePrevious, criteria.max_iter);
-
- break;
- }
- case 1:
- {
- criteria.type = CV_TERMCRIT_EPS;
- criteria.epsilon = 0.001f;
- trsWrite( ATS_LST|ATS_CON,
- "usePrevious = %d, criteria = EPS, epsilon = %f\n",
- usePrevious, criteria.epsilon);
-
- break;
- }
- case 2:
- {
- criteria.type = CV_TERMCRIT_EPS | CV_TERMCRIT_ITER;
- criteria.epsilon = 0.0001f;
- criteria.max_iter = 3;
- trsWrite( ATS_LST|ATS_CON,
- "usePrevious = %d,"
- "criteria = EPS|ITER,"
- "epsilon = %f, max_iter = %d\n",
- usePrevious, criteria.epsilon, criteria.max_iter);
-
- break;
- }
- case 3:
- {
- criteria.type = CV_TERMCRIT_EPS | CV_TERMCRIT_ITER;
- criteria.epsilon = 0.00001f;
- criteria.max_iter = 100;
- trsWrite( ATS_LST|ATS_CON,
- "usePrevious = %d,"
- "criteria = EPS|ITER,"
- "epsilon = %f, max_iter = %d\n",
- usePrevious, criteria.epsilon, criteria.max_iter);
-
- break;
- }
- }
- Stop = 0;
-
- /* Run CVL function */
- cvCalcOpticalFlowHS( imgA , imgB, usePrevious,
- testVelocityX, testVelocityY,
- lambda, criteria );
-
- /* Calc by other way */
- if (!usePrevious)
- {
- /* Filling initial velocity with zero */
- for (i = 0; i < lImageWidth * lImageHeight; i++ )
- {
- VelocityX[i] = 0 ;
- VelocityY[i] = 0 ;
- }
- }
- iteration = 0;
- while ( !Stop )
- {
- float* oldX;
- float* oldY;
- float* newX;
- float* newY;
-
- iteration++;
-
- if ( iteration & 1 )
- {
- oldX = VelocityX;
- oldY = VelocityY;
- newX = auxVelocityX;
- newY = auxVelocityY;
- }
- else
- {
- oldX = auxVelocityX;
- oldY = auxVelocityY;
- newX = VelocityX;
- newY = VelocityY;
- }
-
- for( i = 0; i < lImageHeight; i++)
- {
- for(j = 0; j< lImageWidth; j++)
- {
- float aveX = 0;
- float aveY = 0;
- float dx,dy,dt;
-
- aveX +=(j==0) ? oldX[ i*lImageWidth + j ] : oldX[ i*lImageWidth + j-1 ];
- aveX +=(j==lImageWidth-1) ? oldX[ i*lImageWidth + j ] :
- oldX[ i*lImageWidth + j+1 ];
- aveX +=(i==0) ? oldX[ i*lImageWidth + j ] : oldX[ (i-1)*lImageWidth + j ];
- aveX +=(i==lImageHeight-1) ? oldX[ i*lImageWidth + j ] :
- oldX[ (i+1)*lImageWidth + j ];
- aveX /=4;
-
- aveY +=(j==0) ? oldY[ i*lImageWidth + j ] : oldY[ i*lImageWidth + j-1 ];
- aveY +=(j==lImageWidth-1) ? oldY[ i*lImageWidth + j ] :
- oldY[ i*lImageWidth + j+1 ];
- aveY +=(i==0) ? oldY[ i*lImageWidth + j ] : oldY[ (i-1)*lImageWidth + j ];
- aveY +=(i==lImageHeight-1) ? oldY[ i*lImageWidth + j ] :
- oldY[ (i+1)*lImageWidth + j ];
- aveY /=4;
-
- dx = DerX[ i*lImageWidth + j ];
- dy = DerY[ i*lImageWidth + j ];
- dt = DerT[ i*lImageWidth + j ];
-
- /* Horn & Schunck pure formulas */
- newX[ i*lImageWidth + j ] = aveX - ( dx * aveX +
- dy * aveY + dt ) * lambda * dx /
- (1 + lambda * ( dx*dx + dy*dy ));
-
- newY[ i*lImageWidth + j ] = aveY - ( dx * aveX +
- dy * aveY + dt ) * lambda * dy /
- (1 + lambda * ( dx*dx + dy*dy ));
- }
- }
- /* evaluate epsilon */
- epsilon = 0;
- for ( i = 0; i < lImageHeight; i++)
- {
- for ( j = 0; j < lImageWidth; j++)
- {
- epsilon = MAX((float)fabs(newX[i*lImageWidth + j]
- - oldX[i*lImageWidth + j]), epsilon );
- epsilon = MAX((float)fabs(newY[i*lImageWidth + j]
- - oldY[i*lImageWidth + j]), epsilon );
- }
- }
-
- switch (criteria.type)
- {
- case CV_TERMCRIT_ITER:
- Stop = (criteria.max_iter == iteration );break;
- case CV_TERMCRIT_EPS:
- Stop = (criteria.epsilon > epsilon );break;
- case CV_TERMCRIT_ITER|CV_TERMCRIT_EPS:
- Stop = ( ( criteria.epsilon > epsilon ) ||
- ( criteria.max_iter == iteration ));
- break;
- }
- if (Stop)
- {
- if ( (newX != VelocityX) && (newY != VelocityY) )
- {
- memcpy( VelocityX, newX, lImageWidth * lImageHeight * sizeof(float) );
- memcpy( VelocityY, newY, lImageWidth * lImageHeight * sizeof(float) );
- }
- }
- }
- trsWrite( ATS_LST|ATS_CON,
- "%d iterations are made\n", iteration );
-
- for( i = 0; i < lImageHeight; i++)
- {
- for(j = 0; j< lImageWidth; j++)
- {
- float tvx = ((float*)(testVelocityX->imageData + i*testVelocityX->widthStep))[j];
- float tvy = ((float*)(testVelocityY->imageData + i*testVelocityY->widthStep))[j];
-
- if (( fabs( tvx - VelocityX[i*lImageWidth + j])>EPSILON )||
- ( fabs( tvy - VelocityY[i*lImageWidth + j])>EPSILON ) )
- {
- //trsWrite( ATS_LST | ATS_CON, " ValueX %f \n",
- // testVelocityX[i*lROIWidth + j] );
- //trsWrite( ATS_LST | ATS_CON, " mustX %f \n",
- // VelocityX[i*lROIWidth + j] );
-
- //trsWrite( ATS_LST | ATS_CON, " ValueY %f \n",
- // testVelocityY[i*lROIWidth + j] );
- //trsWrite( ATS_LST | ATS_CON, " mustY %f \n",
- // VelocityY[i*lROIWidth + j] );
-
- //trsWrite( ATS_LST | ATS_CON, " Coordinates %d %d\n", i, j );
-
- lErrors++;
- }
- }
- }
- }/* for */
- /* Filling initial velocity with zero */
- cvZero( testVelocityX );
- cvZero( testVelocityY );
- for (i = 0; i < lImageWidth * lImageHeight; i++ )
- {
- VelocityX[i] = 0 ;
- VelocityY[i] = 0 ;
- }
-}
-
- /* Free memory */
- cvFree( &VelocityX );
- cvFree( &VelocityY );
- cvFree( &auxVelocityX );
- cvFree( &auxVelocityY );
-
-
- cvFree( &DerX );
- cvFree( &DerY );
- cvFree( &DerT );
-
- cvReleaseImage( &imgA );
- cvReleaseImage( &imgB );
- cvReleaseImage( &testVelocityX );
- cvReleaseImage( &testVelocityY );
-
-
- if( lErrors == 0 ) return trsResult( TRS_OK, "No errors fixed for this text" );
- else return trsResult( TRS_FAIL, "Total fixed %d errors", lErrors );
-} /*fmaCalcOpticalFlowHS*/
-
-void InitACalcOpticalFlowHS( void )
-{
- /* Registering test function */
- trsReg( FuncName, TestName, TestClass, fmaCalcOpticalFlowHS );
-} /* InitACalcOpticalFlowHS */
-
-#endif
-
-/* End of file. */
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-#if 0
-
-/* Testing parameters */
-static char FuncName[] = "cvCalcOpticalFlowLK";
-static char TestName[] = "Optical flow (Lucas & Kanade)";
-static char TestClass[] = "Algorithm";
-
-static long lImageWidth;
-static long lImageHeight;
-static long lWinWidth;
-static long lWinHeight;
-
-#define EPSILON 0.00001f
-
-static int fmaCalcOpticalFlowLK( void )
-{
- /* Some Variables */
- int* WH = NULL;
- int* WV = NULL;
-
- int W3[3] = { 1, 2, 1 };
- int W5[5] = { 1, 4, 6, 4, 1 };
- int W7[7] = { 1, 6, 15, 20, 15, 6, 1 };
- int W9[9] = { 1, 8, 28, 56, 70, 56, 28, 8, 1 };
- int W11[11] = {1, 10, 45, 120, 210, 252, 210, 120, 45, 10, 1 };
-
- int i,j,m,k;
- uchar* roiA;
- uchar* roiB;
-
- float* VelocityX;
- float* VelocityY;
-
- float* DerivativeX;
- float* DerivativeY;
- float* DerivativeT;
-
- long lErrors = 0;
- CvSize winSize;
-
- int HRad;
- int VRad;
-
- float A1, A2, B1, B2, C1, C2;
-
- static int read_param = 0;
-
- /* Initialization global parameters */
- if( !read_param )
- {
- read_param = 1;
- /* Reading test-parameters */
- trslRead( &lImageHeight, "563", "Image height" );
- trslRead( &lImageWidth, "345", "Image width" );
- trslRead( &lWinHeight, "7", "win height 3/5/7/9/11 " );
- trslRead( &lWinWidth, "9", "win width 3/5/7/9/11 " );
- }
-
- /* Checking all sizes of source histogram in ranges */
- IplImage* imgA = cvCreateImage( cvSize(lImageWidth,lImageHeight), IPL_DEPTH_8U, 1 );
- IplImage* imgB = cvCreateImage( cvSize(lImageWidth,lImageHeight), IPL_DEPTH_8U, 1 );
-
- IplImage* testVelocityX = cvCreateImage( cvSize(lImageWidth,lImageHeight), IPL_DEPTH_32F, 1 );
- IplImage* testVelocityY = cvCreateImage( cvSize(lImageWidth,lImageHeight), IPL_DEPTH_32F, 1 );
-
- VelocityX = (float*)cvAlloc( lImageWidth * lImageHeight * sizeof(float) );
- VelocityY = (float*)cvAlloc( lImageWidth * lImageHeight * sizeof(float) );
-
- DerivativeX = (float*)cvAlloc( lImageWidth * lImageHeight * sizeof(float) );
- DerivativeY = (float*)cvAlloc( lImageWidth * lImageHeight * sizeof(float) );
- DerivativeT = (float*)cvAlloc( lImageWidth * lImageHeight * sizeof(float) );
-
- winSize.height = lWinHeight;
- winSize.width = lWinWidth;
-
- switch (lWinHeight)
- {
- case 3:
- WV = W3; break;
- case 5:
- WV = W5; break;
- case 7:
- WV = W7; break;
- case 9:
- WV = W9; break;
- case 11:
- WV = W11; break;
- }
- switch (lWinWidth)
- {
- case 3:
- WH = W3; break;
- case 5:
- WH = W5; break;
- case 7:
- WH = W7; break;
- case 9:
- WH = W9; break;
- case 11:
- WH = W11; break;
-
- }
-
- HRad = (winSize.width - 1)/2;
- VRad = (winSize.height - 1)/2;
-
- /* Filling images */
- ats1bInitRandom( 0, 255, (uchar*)imgA->imageData, lImageHeight * imgA->widthStep );
- ats1bInitRandom( 0, 255, (uchar*)imgB->imageData, imgA->widthStep * lImageHeight );
-
- /* Run CVL function */
- cvCalcOpticalFlowLK( imgA , imgB, winSize,
- testVelocityX, testVelocityY );
-
-
- /* Calc by other way */
- roiA = (uchar*)imgA->imageData;
- roiB = (uchar*)imgB->imageData;
-
- /* Calculate derivatives */
- for (i=0; i<imgA->height; i++)
- {
- for(j=0; j<imgA->width; j++)
- {
- int jr,jl,it,ib;
-
- if ( j==imgA->width-1 )
- jr = imgA->width-1;
- else jr = j + 1;
-
- if ( j==0 )
- jl = 0;
- else jl = j - 1;
-
- if ( i==(imgA->height - 1) )
- ib = imgA->height - 1;
- else ib = i + 1;
-
- if ( i==0 )
- it = 0;
- else it = i - 1;
-
- DerivativeX[ i*lImageWidth + j ] = (float)
- (roiA[ (it)*imgA->widthStep + jr ]
- - roiA[ (it)*imgA->widthStep + jl ]
- + 2*roiA[ (i)*imgA->widthStep + jr ]
- - 2*roiA[ (i)*imgA->widthStep + jl ]
- + roiA[ (ib)*imgA->widthStep + jr ]
- - roiA[ (ib)*imgA->widthStep + jl ]) ;
-
- DerivativeY[ i*lImageWidth + j ] = (float)
- ( roiA[ (ib)*imgA->widthStep + jl ]
- + 2*roiA[ (ib)*imgA->widthStep + j ]
- + roiA[ (ib)*imgA->widthStep + jr ]
- - roiA[ (it)*imgA->widthStep + jl ]
- - 2*roiA[ (it)*imgA->widthStep + j ]
- - roiA[ (it)*imgA->widthStep + jr ]) ;
-
- DerivativeT[ i*lImageWidth + j ] = (float)
- (roiB[i*imgB->widthStep + j] - roiA[i*imgA->widthStep + j])*8;
- }
- }
-
- for( i = 0; i < lImageHeight; i++)
- {
- for(j = 0; j< lImageWidth; j++)
- {
- A1 =0;
- A2 =0;
- B1 =0;
- B2 =0;
- C1= 0;
- C2= 0;
-
- for( k = -VRad ; k <= VRad ; k++ )
- {
- for( m = - HRad; m <= HRad ; m++ )
- {
- int coord = (i+k)*lImageWidth + (j+m);
- if ( (j+m<0) ||
- (j+m >lImageWidth-1) ||
- ( (k+i)<0 ) ||
- ( (k+i)>lImageHeight-1) )
- {continue;}
-
- A1+=WV[k+VRad]*WH[m+HRad]* DerivativeX[coord]*DerivativeY[coord];
- A2+=WV[k+VRad]*WH[m+HRad]* DerivativeX[coord]*DerivativeX[coord];
- B1+=WV[k+VRad]*WH[m+HRad]* DerivativeY[coord]*DerivativeY[coord];
- B2+=WV[k+VRad]*WH[m+HRad]* DerivativeX[coord]*DerivativeY[coord];
- C1+=WV[k+VRad]*WH[m+HRad]* DerivativeY[coord]*DerivativeT[coord];
- C2+=WV[k+VRad]*WH[m+HRad]* DerivativeX[coord]*DerivativeT[coord];
- }
- }
- if (A1*B2 - A2*B1)
- {
- VelocityX[i*lImageWidth + j] = - (C1*B2 - C2*B1)/(A1*B2 - A2*B1);
- VelocityY[i*lImageWidth + j] = - (A1*C2 - A2*C1)/(A1*B2 - A2*B1);
- }
- else if ( (A1+A2)*(A1+A2) + (B1+B2)*(B1+B2) )
- { /* Calculate Normal flow */
- VelocityX[i*lImageWidth + j] = -(A1+A2)*(C1+C2)/((A1+A2)*(A1+A2)+(B1+B2)*(B1+B2));
- VelocityY[i*lImageWidth + j] = -(B1+B2)*(C1+C2)/((A1+A2)*(A1+A2)+(B1+B2)*(B1+B2));
- }
- else
- {
- VelocityX[i*lImageWidth + j] = 0;
- VelocityY[i*lImageWidth + j] = 0;
- }
- }
- }
-
- for( i = 0; i < lImageHeight; i++)
- {
- for(j = 0; j< lImageWidth; j++)
- {
- float tvx = ((float*)(testVelocityX->imageData + i*testVelocityX->widthStep))[j];
- float tvy = ((float*)(testVelocityY->imageData + i*testVelocityY->widthStep))[j];
-
-
-
- if (( fabs(tvx - VelocityX[i*lImageWidth + j])>EPSILON )||
- ( fabs(tvy - VelocityY[i*lImageWidth + j])>EPSILON ) )
- {
- //trsWrite( ATS_LST | ATS_CON, " ValueX %f \n", tvx );
- //trsWrite( ATS_LST | ATS_CON, " mustX %f \n", VelocityX[i*lImageWidth + j] );
-
- //trsWrite( ATS_LST | ATS_CON, " ValueY %f \n", tvy );
- //trsWrite( ATS_LST | ATS_CON, " mustY %f \n", VelocityY[i*lImageWidth + j] );
-
- //trsWrite( ATS_LST | ATS_CON, " Coordinates %d %d\n", i, j );
-
- lErrors++;
- }
- }
- }
- cvFree( &VelocityX );
- cvFree( &VelocityY );
-
- cvFree( &DerivativeX );
- cvFree( &DerivativeY );
- cvFree( &DerivativeT );
-
- cvReleaseImage( &imgA );
- cvReleaseImage( &imgB );
- cvReleaseImage( &testVelocityX );
- cvReleaseImage( &testVelocityY );
-
-
- if( lErrors == 0 ) return trsResult( TRS_OK, "No errors fixed for this text" );
- else return trsResult( TRS_FAIL, "Total fixed %d errors", lErrors );
-} /*fmaCalcOpticalFlowLK*/
-
-void InitACalcOpticalFlowLK( void )
-{
- /* Registering test function */
- trsReg( FuncName, TestName, TestClass, fmaCalcOpticalFlowLK );
-} /* InitAACalcOpticalFlowLK */
-
-#endif
-
-/* End of file. */
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-/* ///////////////////// pyrlk_test ///////////////////////// */
-
-class CV_OptFlowPyrLKTest : public CvTest
-{
-public:
- CV_OptFlowPyrLKTest();
-protected:
- void run(int);
-};
-
-
-CV_OptFlowPyrLKTest::CV_OptFlowPyrLKTest():
- CvTest( "optflow-pyrlk", "cvCalcOpticalFlowPyrLK" )
-{
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;
-}
-
-void CV_OptFlowPyrLKTest::run( int )
-{
- int code = CvTS::OK;
-
- const double success_error_level = 0.2;
- const int bad_points_max = 2;
-
- /* test parameters */
- double max_err = 0., sum_err = 0;
- int pt_cmpd = 0;
- int pt_exceed = 0;
- int merr_i = 0, merr_j = 0, merr_k = 0;
- char filename[1000];
-
- CvPoint2D32f *u = 0, *v = 0, *v2 = 0;
- CvMat *_u = 0, *_v = 0, *_v2 = 0;
- char* status = 0;
-
- IplImage* imgI = 0;
- IplImage* imgJ = 0;
-
- int n = 0, i = 0;
-
- sprintf( filename, "%soptflow/%s", ts->get_data_path(), "lk_prev.dat" );
- _u = (CvMat*)cvLoad( filename );
-
- if( !_u )
- {
- ts->printf( CvTS::LOG, "could not read %s\n", filename );
- code = CvTS::FAIL_MISSING_TEST_DATA;
- goto _exit_;
- }
-
- sprintf( filename, "%soptflow/%s", ts->get_data_path(), "lk_next.dat" );
- _v = (CvMat*)cvLoad( filename );
-
- if( !_v )
- {
- ts->printf( CvTS::LOG, "could not read %s\n", filename );
- code = CvTS::FAIL_MISSING_TEST_DATA;
- goto _exit_;
- }
-
- if( _u->cols != 2 || CV_MAT_TYPE(_u->type) != CV_32F ||
- _v->cols != 2 || CV_MAT_TYPE(_v->type) != CV_32F || _v->rows != _u->rows )
- {
- ts->printf( CvTS::LOG, "the loaded matrices of points are not valid\n" );
- code = CvTS::FAIL_MISSING_TEST_DATA;
- goto _exit_;
-
- }
-
- u = (CvPoint2D32f*)_u->data.fl;
- v = (CvPoint2D32f*)_v->data.fl;
-
- /* allocate adidtional buffers */
- _v2 = cvCloneMat( _u );
- v2 = (CvPoint2D32f*)_v2->data.fl;
-
- /* read first image */
- sprintf( filename, "%soptflow/%s", ts->get_data_path(), "rock_1.bmp" );
- imgI = cvLoadImage( filename, -1 );
-
- if( !imgI )
- {
- ts->printf( CvTS::LOG, "could not read %s\n", filename );
- code = CvTS::FAIL_MISSING_TEST_DATA;
- goto _exit_;
- }
-
- /* read second image */
- sprintf( filename, "%soptflow/%s", ts->get_data_path(), "rock_2.bmp" );
- imgJ = cvLoadImage( filename, -1 );
-
- if( !imgJ )
- {
- ts->printf( CvTS::LOG, "could not read %s\n", filename );
- code = CvTS::FAIL_MISSING_TEST_DATA;
- goto _exit_;
- }
-
- n = _u->rows;
- status = (char*)cvAlloc(n*sizeof(status[0]));
-
- /* calculate flow */
- cvCalcOpticalFlowPyrLK( imgI, imgJ, 0, 0, u, v2, n, cvSize( 20, 20 ),
- 4, status, 0, cvTermCriteria( CV_TERMCRIT_ITER|
- CV_TERMCRIT_EPS, 30, 0.01f ), 0 );
-
- /* compare results */
- for( i = 0; i < n; i++ )
- {
- if( status[i] != 0 )
- {
- double err;
- if( cvIsNaN(v[i].x) )
- {
- merr_j++;
- continue;
- }
-
- err = fabs(v2[i].x - v[i].x) + fabs(v2[i].y - v[i].y);
- if( err > max_err )
- {
- max_err = err;
- merr_i = i;
- }
-
- pt_exceed += err > success_error_level;
- if( pt_exceed > bad_points_max )
- {
- ts->printf( CvTS::LOG,
- "The number of poorly tracked points is too big (>=%d)\n", pt_exceed );
- code = CvTS::FAIL_BAD_ACCURACY;
- goto _exit_;
- }
-
- sum_err += err;
- pt_cmpd++;
- }
- else
- {
- if( !cvIsNaN( v[i].x ))
- {
- merr_i = i;
- merr_k++;
- ts->printf( CvTS::LOG, "The algorithm lost the point #%d\n", i );
- code = CvTS::FAIL_BAD_ACCURACY;
- goto _exit_;
- }
- }
- }
-
- if( max_err > 1 )
- {
- ts->printf( CvTS::LOG, "Maximum tracking error is too big (=%g)\n", max_err );
- code = CvTS::FAIL_BAD_ACCURACY;
- goto _exit_;
- }
-
-_exit_:
-
- cvFree( &status );
- cvReleaseMat( &_u );
- cvReleaseMat( &_v );
- cvReleaseMat( &_v2 );
-
- cvReleaseImage( &imgI );
- cvReleaseImage( &imgJ );
-
- if( code < 0 )
- ts->set_failed_test_info( code );
-}
-
-CV_OptFlowPyrLKTest optflow_pyr_lk_test;
-
-/* End of file. */
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-
-class CV_POSITTest : public CvTest
-{
-public:
- CV_POSITTest();
-protected:
- void run(int);
-};
-
-
-CV_POSITTest::CV_POSITTest():
- CvTest( "posit", "cvPOSIT" )
-{
- test_case_count = 20;
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;
-}
-
-void CV_POSITTest::run( int start_from )
-{
- int code = CvTS::OK;
-
- /* fixed parameters output */
- /*float rot[3][3]={ 0.49010f, 0.85057f, 0.19063f,
- -0.56948f, 0.14671f, 0.80880f,
- 0.65997f, -0.50495f, 0.55629f };
-
- float trans[3] = { 0.0f, 0.0f, 40.02637f };
- */
-
- /* Some variables */
- int i, counter;
-
- CvTermCriteria criteria;
- CvPoint3D32f* obj_points;
- CvPoint2D32f* img_points;
- CvPOSITObject* object;
-
- float angleX, angleY, angleZ;
- CvRNG* rng = ts->get_rng();
- int progress = 0;
-
- CvMat* true_rotationX = cvCreateMat( 3, 3, CV_32F );
- CvMat* true_rotationY = cvCreateMat( 3, 3, CV_32F );
- CvMat* true_rotationZ = cvCreateMat( 3, 3, CV_32F );
- CvMat* tmp_matrix = cvCreateMat( 3, 3, CV_32F );
- CvMat* true_rotation = cvCreateMat( 3, 3, CV_32F );
- CvMat* rotation = cvCreateMat( 3, 3, CV_32F );
- CvMat* translation = cvCreateMat( 3, 1, CV_32F );
- CvMat* true_translation = cvCreateMat( 3, 1, CV_32F );
-
- const float flFocalLength = 760.f;
- const float flEpsilon = 0.5f;
-
- /* Initilization */
- criteria.type = CV_TERMCRIT_EPS|CV_TERMCRIT_ITER;
- criteria.epsilon = flEpsilon;
- criteria.max_iter = 10000;
-
- /* Allocating source arrays; */
- obj_points = (CvPoint3D32f*)cvAlloc( 8 * sizeof(CvPoint3D32f) );
- img_points = (CvPoint2D32f*)cvAlloc( 8 * sizeof(CvPoint2D32f) );
-
- /* Fill points arrays with values */
-
- /* cube model with edge size 10 */
- obj_points[0].x = 0; obj_points[0].y = 0; obj_points[0].z = 0;
- obj_points[1].x = 10; obj_points[1].y = 0; obj_points[1].z = 0;
- obj_points[2].x = 10; obj_points[2].y = 10; obj_points[2].z = 0;
- obj_points[3].x = 0; obj_points[3].y = 10; obj_points[3].z = 0;
- obj_points[4].x = 0; obj_points[4].y = 0; obj_points[4].z = 10;
- obj_points[5].x = 10; obj_points[5].y = 0; obj_points[5].z = 10;
- obj_points[6].x = 10; obj_points[6].y = 10; obj_points[6].z = 10;
- obj_points[7].x = 0; obj_points[7].y = 10; obj_points[7].z = 10;
-
- /* Loop for test some random object positions */
- for( counter = start_from; counter < test_case_count; counter++ )
- {
- ts->update_context( this, counter, true );
- progress = update_progress( progress, counter, test_case_count, 0 );
-
- /* set all rotation matrix to zero */
- cvZero( true_rotationX );
- cvZero( true_rotationY );
- cvZero( true_rotationZ );
-
- /* fill random rotation matrix */
- angleX = (float)(cvTsRandReal(rng)*2*CV_PI);
- angleY = (float)(cvTsRandReal(rng)*2*CV_PI);
- angleZ = (float)(cvTsRandReal(rng)*2*CV_PI);
-
- true_rotationX->data.fl[0 *3+ 0] = 1;
- true_rotationX->data.fl[1 *3+ 1] = (float)cos(angleX);
- true_rotationX->data.fl[2 *3+ 2] = true_rotationX->data.fl[1 *3+ 1];
- true_rotationX->data.fl[1 *3+ 2] = -(float)sin(angleX);
- true_rotationX->data.fl[2 *3+ 1] = -true_rotationX->data.fl[1 *3+ 2];
-
- true_rotationY->data.fl[1 *3+ 1] = 1;
- true_rotationY->data.fl[0 *3+ 0] = (float)cos(angleY);
- true_rotationY->data.fl[2 *3+ 2] = true_rotationY->data.fl[0 *3+ 0];
- true_rotationY->data.fl[0 *3+ 2] = -(float)sin(angleY);
- true_rotationY->data.fl[2 *3+ 0] = -true_rotationY->data.fl[0 *3+ 2];
-
- true_rotationZ->data.fl[2 *3+ 2] = 1;
- true_rotationZ->data.fl[0 *3+ 0] = (float)cos(angleZ);
- true_rotationZ->data.fl[1 *3+ 1] = true_rotationZ->data.fl[0 *3+ 0];
- true_rotationZ->data.fl[0 *3+ 1] = -(float)sin(angleZ);
- true_rotationZ->data.fl[1 *3+ 0] = -true_rotationZ->data.fl[0 *3+ 1];
-
- cvMatMul( true_rotationX, true_rotationY, tmp_matrix);
- cvMatMul( tmp_matrix, true_rotationZ, true_rotation);
-
- /* fill translation vector */
- true_translation->data.fl[2] = (float)(cvRandReal(rng)*(2*flFocalLength-40) + 60);
- true_translation->data.fl[0] = (float)((cvRandReal(rng)*2-1)*true_translation->data.fl[2]);
- true_translation->data.fl[1] = (float)((cvRandReal(rng)*2-1)*true_translation->data.fl[2]);
-
- /* calculate perspective projection */
- for ( i = 0; i < 8; i++ )
- {
- float vec[3];
- CvMat Vec = cvMat( 3, 1, CV_32F, vec );
- CvMat Obj_point = cvMat( 3, 1, CV_32F, &obj_points[i].x );
-
- cvMatMul( true_rotation, &Obj_point, &Vec );
-
- vec[0] += true_translation->data.fl[0];
- vec[1] += true_translation->data.fl[1];
- vec[2] += true_translation->data.fl[2];
-
- img_points[i].x = flFocalLength * vec[0] / vec[2];
- img_points[i].y = flFocalLength * vec[1] / vec[2];
- }
-
- /*img_points[0].x = 0 ; img_points[0].y = 0;
- img_points[1].x = 80; img_points[1].y = -93;
- img_points[2].x = 245;img_points[2].y = -77;
- img_points[3].x = 185;img_points[3].y = 32;
- img_points[4].x = 32; img_points[4].y = 135;
- img_points[5].x = 99; img_points[5].y = 35;
- img_points[6].x = 247; img_points[6].y = 62;
- img_points[7].x = 195; img_points[7].y = 179;
- */
-
- object = cvCreatePOSITObject( obj_points, 8 );
- cvPOSIT( object, img_points, flFocalLength, criteria,
- rotation->data.fl, translation->data.fl );
- cvReleasePOSITObject( &object );
-
- code = cvTsCmpEps2( ts, rotation, true_rotation, flEpsilon, false, "rotation matrix" );
- if( code < 0 )
- goto _exit_;
-
- code = cvTsCmpEps2( ts, translation, true_translation, flEpsilon, false, "translation vector" );
- if( code < 0 )
- goto _exit_;
- }
-
-_exit_:
-
- cvFree( &obj_points );
- cvFree( &img_points );
-
- cvReleaseMat( &true_rotationX );
- cvReleaseMat( &true_rotationY );
- cvReleaseMat( &true_rotationZ );
- cvReleaseMat( &tmp_matrix );
- cvReleaseMat( &true_rotation );
- cvReleaseMat( &rotation );
- cvReleaseMat( &translation );
- cvReleaseMat( &true_translation );
-
- if( code < 0 )
- ts->set_failed_test_info( code );
-}
-
-CV_POSITTest posit_test;
-
-/* End of file. */
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-class CV_PyrSegmentationTest : public CvTest
-{
-public:
- CV_PyrSegmentationTest();
-protected:
- void run(int);
-};
-
-#define SCAN 0
-
-CV_PyrSegmentationTest::CV_PyrSegmentationTest():
- CvTest( "segmentation-pyramid", "cvPyrSegmentation" )
-{
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;
-}
-
-void CV_PyrSegmentationTest::run( int /*start_from*/ )
-{
- const int level = 5;
- const double range = 15;
-
- int code = CvTS::OK;
-
- CvPoint _cp[] ={{33,33}, {43,33}, {43,43}, {33,43}};
- CvPoint _cp2[] ={{50,50}, {70,50}, {70,70}, {50,70}};
- CvPoint* cp = _cp;
- CvPoint* cp2 = _cp2;
- CvConnectedComp *dst_comp[3];
- CvRect rect[3] = {{50,50,21,21}, {0,0,128,128}, {33,33,11,11}};
- double a[3] = {441.0, 15822.0, 121.0};
-
-/* ippiPoint cp3[] ={130,130, 150,130, 150,150, 130,150}; */
-/* CvPoint cp[] ={0,0, 5,5, 5,0, 10,5, 10,0, 15,5, 15,0}; */
- int nPoints = 4;
- int block_size = 1000;
-
- CvMemStorage *storage; /* storage for connected component writing */
- CvSeq *comp;
-
- CvRNG* rng = ts->get_rng();
- int i, j, iter;
-
- IplImage *image, *image_f, *image_s;
- CvSize size = {128, 128};
- const int threshold1 = 50, threshold2 = 50;
-
- rect[1].width = size.width;
- rect[1].height = size.height;
- a[1] = size.width*size.height - a[0] - a[2];
-
- OPENCV_CALL( storage = cvCreateMemStorage( block_size ) );
-
- for( iter = 0; iter < 2; iter++ )
- {
- int channels = iter == 0 ? 1 : 3;
- int mask[] = {0,0,0};
-
- image = cvCreateImage(size, 8, channels );
- image_s = cvCloneImage( image );
- image_f = cvCloneImage( image );
-
- if( channels == 1 )
- {
- int color1 = 30, color2 = 110, color3 = 190;
-
- cvSet( image, cvScalarAll(color1));
- cvFillPoly( image, &cp, &nPoints, 1, cvScalar(color2));
- cvFillPoly( image, &cp2, &nPoints, 1, cvScalar(color3));
- }
- else
- {
- CvScalar color1 = CV_RGB(30,30,30), color2 = CV_RGB(255,0,0), color3 = CV_RGB(0,255,0);
-
- assert( channels == 3 );
- cvSet( image, color1 );
- cvFillPoly( image, &cp, &nPoints, 1, color2);
- cvFillPoly( image, &cp2, &nPoints, 1, color3);
- }
-
- cvRandArr( rng, image_f, CV_RAND_UNI, cvScalarAll(0), cvScalarAll(range*2) );
- cvAddWeighted( image, 1, image_f, 1, -range, image_f );
-
- cvPyrSegmentation( image_f, image_s,
- storage, &comp,
- level, threshold1, threshold2 );
-
- if(comp->total != 3)
- {
- ts->printf( CvTS::LOG,
- "The segmentation function returned %d (not 3) components\n", comp->total );
- code = CvTS::FAIL_INVALID_OUTPUT;
- goto _exit_;
- }
- /* read the connected components */
- dst_comp[0] = (CvConnectedComp*)CV_GET_SEQ_ELEM( CvConnectedComp, comp, 0 );
- dst_comp[1] = (CvConnectedComp*)CV_GET_SEQ_ELEM( CvConnectedComp, comp, 1 );
- dst_comp[2] = (CvConnectedComp*)CV_GET_SEQ_ELEM( CvConnectedComp, comp, 2 );
-
- /*{
- for( i = 0; i < 3; i++ )
- {
- CvRect r = dst_comp[i]->rect;
- cvRectangle( image_s, cvPoint(r.x,r.y), cvPoint(r.x+r.width,r.y+r.height),
- CV_RGB(255,255,255), 3, 8, 0 );
- }
-
- cvNamedWindow( "test", 1 );
- cvShowImage( "test", image_s );
- cvWaitKey(0);
- }*/
-
- code = cvTsCmpEps2( ts, image, image_s, 10, false, "the output image" );
- if( code < 0 )
- goto _exit_;
-
- for( i = 0; i < 3; i++)
- {
- for( j = 0; j < 3; j++ )
- {
- if( !mask[j] && dst_comp[i]->area == a[j] &&
- dst_comp[i]->rect.x == rect[j].x &&
- dst_comp[i]->rect.y == rect[j].y &&
- dst_comp[i]->rect.width == rect[j].width &&
- dst_comp[i]->rect.height == rect[j].height )
- {
- mask[j] = 1;
- break;
- }
- }
- if( j == 3 )
- {
- ts->printf( CvTS::LOG, "The component #%d is incorrect\n", i );
- code = CvTS::FAIL_BAD_ACCURACY;
- goto _exit_;
- }
- }
-
- cvReleaseImage(&image_f);
- cvReleaseImage(&image);
- cvReleaseImage(&image_s);
- }
-
-_exit_:
-
- cvReleaseMemStorage( &storage );
- cvReleaseImage(&image_f);
- cvReleaseImage(&image);
- cvReleaseImage(&image_s);
-
- if( code < 0 )
- ts->set_failed_test_info( code );
-}
-
-CV_PyrSegmentationTest pyr_segmentation_test;
-
-/* End of file. */
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////\r
-//\r
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.\r
-//\r
-// By downloading, copying, installing or using the software you agree to this license.\r
-// If you do not agree to this license, do not download, install,\r
-// copy or use the software.\r
-//\r
-//\r
-// License Agreement\r
-// For Open Source Computer Vision Library\r
-//\r
-// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.\r
-// Copyright (C) 2009, Willow Garage Inc., all rights reserved.\r
-// Third party copyrights are property of their respective owners.\r
-//\r
-// Redistribution and use in source and binary forms, with or without modification,\r
-// are permitted provided that the following conditions are met:\r
-//\r
-// * Redistribution's of source code must retain the above copyright notice,\r
-// this list of conditions and the following disclaimer.\r
-//\r
-// * Redistribution's in binary form must reproduce the above copyright notice,\r
-// this list of conditions and the following disclaimer in the documentation\r
-// and/or other materials provided with the distribution.\r
-//\r
-// * The name of the copyright holders may not be used to endorse or promote products\r
-// derived from this software without specific prior written permission.\r
-//\r
-// This software is provided by the copyright holders and contributors "as is" and\r
-// any express or implied warranties, including, but not limited to, the implied\r
-// warranties of merchantability and fitness for a particular purpose are disclaimed.\r
-// In no event shall the Intel Corporation or contributors be liable for any direct,\r
-// indirect, incidental, special, exemplary, or consequential damages\r
-// (including, but not limited to, procurement of substitute goods or services;\r
-// loss of use, data, or profits; or business interruption) however caused\r
-// and on any theory of liability, whether in contract, strict liability,\r
-// or tort (including negligence or otherwise) arising in any way out of\r
-// the use of this software, even if advised of the possibility of such damage.\r
-//\r
-//M*/\r
-\r
-#include "cvtest.h"\r
-#include <string>\r
-#include <limits>\r
-\r
-using namespace cv;\r
-using namespace std;\r
-\r
-template<class T> double thres() { return 1.0; }\r
-template<> double thres<float>() { return 1e-5; } \r
-\r
-class CV_ReprojectImageTo3DTest : public CvTest\r
-{\r
-public:\r
- CV_ReprojectImageTo3DTest()\r
- : CvTest( "reprojectImageTo3D", "cvReprojectImageTo3D")\r
- {\r
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;\r
- }\r
- ~CV_ReprojectImageTo3DTest() {}\r
-protected: \r
-\r
- \r
- void run(int)\r
- { \r
- ts->set_failed_test_info(CvTS::OK);\r
- int progress = 0;\r
- int caseId = 0;\r
-\r
- progress = update_progress( progress, 1, 14, 0 );\r
- runCase<float, float>(++caseId, -100.f, 100.f);\r
- progress = update_progress( progress, 2, 14, 0 );\r
- runCase<int, float>(++caseId, -100, 100);\r
- progress = update_progress( progress, 3, 14, 0 );\r
- runCase<short, float>(++caseId, -100, 100);\r
- progress = update_progress( progress, 4, 14, 0 );\r
- runCase<unsigned char, float>(++caseId, 10, 100);\r
- progress = update_progress( progress, 5, 14, 0 );\r
-\r
- runCase<float, int>(++caseId, -100.f, 100.f);\r
- progress = update_progress( progress, 6, 14, 0 );\r
- runCase<int, int>(++caseId, -100, 100);\r
- progress = update_progress( progress, 7, 14, 0 );\r
- runCase<short, int>(++caseId, -100, 100);\r
- progress = update_progress( progress, 8, 14, 0 );\r
- runCase<unsigned char, int>(++caseId, 10, 100);\r
- progress = update_progress( progress, 10, 14, 0 );\r
-\r
- runCase<float, short>(++caseId, -100.f, 100.f);\r
- progress = update_progress( progress, 11, 14, 0 );\r
- runCase<int, short>(++caseId, -100, 100);\r
- progress = update_progress( progress, 12, 14, 0 );\r
- runCase<short, short>(++caseId, -100, 100);\r
- progress = update_progress( progress, 13, 14, 0 );\r
- runCase<unsigned char, short>(++caseId, 10, 100); \r
- progress = update_progress( progress, 14, 14, 0 );\r
- }\r
-\r
- template<class U, class V> double error(const Vec<U, 3>& v1, const Vec<V, 3>& v2) const\r
- {\r
- double tmp, sum = 0;\r
- double nsum = 0;\r
- for(int i = 0; i < 3; ++i)\r
- {\r
- tmp = v1[i];\r
- nsum += tmp * tmp; \r
-\r
- tmp = tmp - v2[i];\r
- sum += tmp * tmp;\r
- \r
- } \r
- return sqrt(sum)/(sqrt(nsum)+1.);\r
- }\r
-\r
- template<class InT, class OutT> void runCase(int caseId, InT min, InT max)\r
- { \r
- typedef Vec<OutT, 3> out3d_t;\r
-\r
- bool handleMissingValues = (unsigned)theRNG() % 2 == 0; \r
-\r
- Mat_<InT> disp(Size(320, 240));\r
- randu(disp, Scalar(min), Scalar(max));\r
-\r
- if (handleMissingValues)\r
- disp(disp.rows/2, disp.cols/2) = min - 1;\r
- \r
- Mat_<double> Q(4, 4);\r
- randu(Q, Scalar(-5), Scalar(5));\r
-\r
- Mat_<out3d_t> _3dImg(disp.size());\r
- \r
- CvMat cvdisp = disp; CvMat cv_3dImg = _3dImg; CvMat cvQ = Q;\r
- cvReprojectImageTo3D( &cvdisp, &cv_3dImg, &cvQ, handleMissingValues );\r
-\r
- if (numeric_limits<OutT>::max() == numeric_limits<float>::max())\r
- reprojectImageTo3D(disp, _3dImg, Q, handleMissingValues);\r
- \r
- for(int y = 0; y < disp.rows; ++y)\r
- for(int x = 0; x < disp.cols; ++x)\r
- {\r
- InT d = disp(y, x); \r
-\r
- double from[4] = { x, y, d, 1 };\r
- Mat_<double> res = Q * Mat_<double>(4, 1, from);\r
- res /= res(3, 0);\r
-\r
- out3d_t pixel_exp = *(Vec3d*)res.data;\r
- out3d_t pixel_out = _3dImg(y, x);\r
-\r
- const int largeZValue = 10000; /* see documentation */ \r
-\r
- if (handleMissingValues && y == disp.rows/2 && x == disp.cols/2) \r
- { \r
- if (pixel_out[2] == largeZValue)\r
- continue;\r
-\r
- ts->printf(CvTS::LOG, "Missing values are handled improperly\n");\r
- ts->set_failed_test_info( CvTS::FAIL_BAD_ACCURACY ); \r
- return;\r
- }\r
- else\r
- {\r
- double err = error(pixel_out, pixel_exp), t = thres<OutT>();\r
- if ( err > t )\r
- {\r
- ts->printf(CvTS::LOG, "case %d. too big error at (%d, %d): %g vs expected %g: res = (%g, %g, %g, w=%g) vs pixel_out = (%g, %g, %g)\n",\r
- caseId, x, y, err, t, res(0,0), res(1,0), res(2,0), res(3,0),\r
- (double)pixel_out[0], (double)pixel_out[1], (double)pixel_out[2]);\r
- ts->set_failed_test_info( CvTS::FAIL_BAD_ACCURACY );\r
- return;\r
- }\r
- }\r
- } \r
- }\r
-}; \r
- \r
-CV_ReprojectImageTo3DTest reprojectImageTo3D_test;\r
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-/* This is regression test for Snakes functions of OpenCV.
-// This test will generate fixed figure, read initial position
-// of snake from file, run OpenCV function and compare result
-// position of snake with position(from file) which must be resulting.
-//
-// Test is considered to be succesfull if resultant positions
-// are identical.
-*/
-
-class CV_SnakeTest : public CvTest
-{
-public:
- CV_SnakeTest();
-protected:
- void run(int);
-};
-
-#define SCAN 0
-
-CV_SnakeTest::CV_SnakeTest():
- CvTest( "snakes", "cvSnakeImage" )
-{
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;
-}
-
-void CV_SnakeTest::run( int /*start_from*/ )
-{
- int code = CvTS::OK;
- static const char* file_name[] =
- {
- "ring",
- "square"
- };
-
- const int numfig_image = 1;
- const int numfig_grad = 1;
-
- FILE* file = 0;
-#ifndef _MAX_PATH
-#define _MAX_PATH 1024
-#endif
- char abs_file_name[_MAX_PATH];
- char rel_path[_MAX_PATH];
-
- int i,j;
-
- /* source image */
- IplImage* iplSrc = NULL;
- CvSize win;
- int length;
-
- float alpha,beta,gamma;
- CvTermCriteria criteria;
- long lErrors = 0;
- int progress = 0, test_case_count = numfig_image + numfig_grad;
- CvPoint* Pts = 0;
- CvPoint* resPts = 0;
-
- sprintf( rel_path, "%ssnakes/", ts->get_data_path() );
-
- criteria.type = CV_TERMCRIT_ITER;
- win.height = win.width = 3;
-
- for( i = 0; i < test_case_count; i++ )
- {
- progress = update_progress( progress, i, test_case_count, 0 );
- int num_pos;
- int k;
-
- char tmp[_MAX_PATH];
-
- ts->update_context( this, i, false );
-
- /* create full name of bitmap file */
- strcpy(tmp, rel_path);
- strcat(tmp, file_name[i]);
- strcpy( abs_file_name, tmp );
- strcat( abs_file_name, ".bmp" );
-
- /* read bitmap with 8u image */
- iplSrc = cvLoadImage( abs_file_name, -1 );
-
- if (!iplSrc)
- {
- ts->printf( CvTS::LOG, "can not load %s\n", abs_file_name );
- code = CvTS::FAIL_MISSING_TEST_DATA;
- goto _exit_;
- }
-
- /* init snake reading file with snake */
- strcpy(tmp, rel_path);
- strcat(tmp, file_name[i]);
- strcpy( abs_file_name, tmp );
- strcat( abs_file_name, ".txt" );
-
-#if !SCAN
- file = fopen( abs_file_name, "r" );
-#else
- file = fopen( abs_file_name, "r+" );
-#endif
-
- if (!file)
- {
- ts->printf( CvTS::LOG, "can not load %s\n", abs_file_name );
- code = CvTS::FAIL_MISSING_TEST_DATA;
- goto _exit_;
- }
-
- /* read snake parameters */
- fscanf(file, "%d", &length );
- fscanf(file, "%f", &alpha );
- fscanf(file, "%f", &beta );
- fscanf(file, "%f", &gamma );
-
- /* allocate memory for snakes */
- Pts = (CvPoint*)cvAlloc( length * sizeof(Pts[0]) );
- resPts = (CvPoint*)cvAlloc( length * sizeof(resPts[0]) );
-
- /* get number of snake positions */
- fscanf(file, "%d", &num_pos );
-
- /* get number iterations between two positions */
- fscanf(file, "%d", &criteria.max_iter );
-
- /* read initial snake position */
- for ( j = 0; j < length; j++ )
- {
- fscanf(file, "%d%d", &Pts[j].x, &Pts[j].y );
- }
-
- for ( k = 0; k < num_pos; k++ )
- {
- /* Run CVL function to check it */
- if(i<numfig_image)
- {
- cvSnakeImage( iplSrc, Pts, length,
- &alpha, &beta, &gamma, CV_VALUE, win, criteria, 0 );
- }
- else
- {
- cvSnakeImage( iplSrc, Pts, length,
- &alpha, &beta, &gamma, CV_VALUE, win, criteria, 1 /*usegrad*/ );
- }
-
-#if !SCAN
- for ( j = 0; j < length; j++ )
- {
- fscanf(file, "%d%d", &resPts[j].x, &resPts[j].y );
-
- lErrors += (Pts[j].x != resPts[j].x);
- lErrors += (Pts[j].y != resPts[j].y);
- }
-#else
- fseek( file, 0, SEEK_CUR );
- fprintf(file, "\n");
- for ( j = 0; j < length; j++ )
- {
- fprintf(file, "\n%d %d", Pts[j].x, Pts[j].y );
- }
-#endif
- }
- fclose(file);
- file = 0;
- cvFree(&Pts);
- cvFree(&resPts);
- cvReleaseImage(&iplSrc);
- }
-
- if( lErrors > 0 )
- {
- ts->printf( CvTS::LOG, "Total fixed %d errors", lErrors );
- code = CvTS::FAIL_BAD_ACCURACY;
- goto _exit_;
- }
-
-_exit_:
-
- if( file )
- fclose(file);
- cvFree(&Pts);
- cvFree(&resPts);
- cvReleaseImage(&iplSrc);
-
- if( code < 0 )
- ts->set_failed_test_info( code );
-}
-
-CV_SnakeTest snake_test;
-
-/* End of file. */
+++ /dev/null
-#include "cvtest.h"
-
-#if 0
-
-#define debug //enables showing images.
-#define CONSOLEOUTPUT //enables printing rms error and percentage of bad pixels to console.
-
-//#define LOAD //enables skipping computing disparities and load them from images.
-//#define SAVEIMAGES //enables saving computed disparity and red-marked disparity images.
-
-void MarkPixel(const IplImage* markedDisparity, const int h, const int w)
-{
- uchar* data = (uchar*)&markedDisparity->imageData[h*markedDisparity->widthStep + w*3];
- data[0] = 0;
- data[1] = 0;
- data[2] = 255;
-}
-
-int CalculateErrors(const IplImage* disparity,const IplImage* groundTruth, IplImage* markedDisparity,
- double &rms_error, double &percentage_of_bad_pixels,
- const int maxDisparity CV_DEFAULT(16), const int eval_ignore_border CV_DEFAULT(10))
-{
- if (disparity->width != groundTruth->width)
- return CvTS::FAIL_INVALID_TEST_DATA;
- if (disparity->height != groundTruth->height)
- return CvTS::FAIL_INVALID_TEST_DATA;
-
- const double eval_bad_thresh = 1.0;
-
- char* DC = disparity->imageData;
- char* DT = groundTruth->imageData;
-
- double currSum = 0;
- unsigned int bad_pixels_counter=0;
-
- double diff=0;
-
- int w = disparity->width;
- int h = disparity->height;
- unsigned int numPixels = w*h;
-
- for(int i=eval_ignore_border; i<h-eval_ignore_border; i++)
- for(int j=eval_ignore_border; j<w-eval_ignore_border; j++)
- {
- diff = (double)abs(DC[i*disparity->widthStep+j] - DT[i*groundTruth->widthStep+j])/(double)maxDisparity;
- currSum += diff*diff;
-
- if ( diff > eval_bad_thresh )
- {
- bad_pixels_counter++;
- MarkPixel(markedDisparity, i, j);
- }
- }
-
- currSum /=(double)numPixels;
- rms_error = sqrt(currSum);
-
- percentage_of_bad_pixels = (double)bad_pixels_counter/(double)numPixels * 100;
-
- return 0;
-}
-
-class CV_StereoCorrespondenceTestGC : public CvTest
-{
-public:
- CV_StereoCorrespondenceTestGC();
-protected:
- void run(int);
-};
-
-
-CV_StereoCorrespondenceTestGC::CV_StereoCorrespondenceTestGC():
-CvTest( "stereo-gc", "cvFindStereoCorrespondenceGC" )
-{
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;
-}
-
-/* ///////////////////// stereo_correspondece_test ///////////////////////// */
-void CV_StereoCorrespondenceTestGC::run( int )
-{
- int code = CvTS::OK;
-
- const double rms_error_thresh = 1000.0;
- const double percentage_of_bad_pixels_thresh = 90.0;
-
- double rms_error[2];
- double percentage_of_bad_pixels[2];
-
- /* test parameters */
- char filepath[1000];
- char filename[1000];
- //char extension[5];
-
- IplImage* left ;
- IplImage* right;
- IplImage* disparity_left;
- IplImage* disparity_right;
- IplImage* groundTruthLeft;
- IplImage* groundTruthRight;
-
- sprintf( filepath, "%sstereocorrespondence/", ts->get_data_path() );
- sprintf( filename, "%sstereocorrespondence_list.txt", filepath );
-
- FILE* f = fopen(filename,"r");
- int numImages=0;
- fscanf(f,"%d\n",&numImages);
-
- for(int i=0; i<numImages; i++)
- {
- /*Load left and right image from the storage*/
- char dataName[100];
- int maxDisparity=0;
-
- fscanf(f,"%s %d\n",dataName,&maxDisparity);
- sprintf(filename,"%s%sL.png",filepath,dataName);
- left = cvLoadImage(filename,0);
- sprintf(filename,"%s%sR.png",filepath,dataName);
- right = cvLoadImage(filename,0);
-
- if (!left || !right)
- {
- ts->printf( CvTS::LOG, "Left or right image doesn't exist" );
- code = CvTS::FAIL_MISSING_TEST_DATA;
- goto _exit_;
- }
- if ((cvGetSize(left).height != cvGetSize(right).height)
- || ((cvGetSize(left).width != cvGetSize(right).width)))
- {
- ts->printf( CvTS::LOG, "Left and right image sizes aren't equal" );
- code = CvTS::FAIL_MISSING_TEST_DATA;
- goto _exit_;
- }
-
- sprintf(filename,"%s%s_gtL.png",filepath,dataName);
- groundTruthLeft = cvLoadImage(filename,0);
- sprintf(filename,"%s%s_gtR.png",filepath,dataName);
- groundTruthRight = cvLoadImage(filename,0);
-
- if (!groundTruthLeft && !groundTruthRight)
- {
- ts->printf( CvTS::LOG, "Left and right ground truth images don't exist" );
- code = CvTS::FAIL_MISSING_TEST_DATA;
- goto _exit_;
- }
-
- for(int i=0; i<2; i++)
- {
- IplImage*& groundTruth = (i == 0) ? groundTruthLeft : groundTruthRight;
- if (groundTruth)
- if (groundTruth->nChannels != 1)
- {
- IplImage* tmp = groundTruth;
- groundTruth = cvCreateImage(cvGetSize(left),IPL_DEPTH_8U,1);
- cvCvtColor(tmp, groundTruth,CV_BGR2GRAY);
- }
- }
-
- /*Find disparity map for current image pair*/
-#ifndef LOAD
- disparity_left = cvCreateImage( cvGetSize(left), IPL_DEPTH_32S, 1 );
- disparity_right = cvCreateImage( cvGetSize(left), IPL_DEPTH_32S, 1 );
-
- CvStereoGCState* state = cvCreateStereoGCState(maxDisparity, 2);
- cvFindStereoCorrespondenceGC( left, right,
- disparity_left, disparity_right, state);
-
- double scale = 256/maxDisparity ;
- if (!strcmp(dataName,"sawtooth") || !strcmp(dataName,"map") || !strcmp(dataName,"poster")
- || !strcmp(dataName,"bull") || !strcmp(dataName,"barn1") || !strcmp(dataName,"barn2"))
- scale = 8.0;
-
- IplImage* temp;
- temp = disparity_left;
- disparity_left = cvCreateImage(cvGetSize(temp), IPL_DEPTH_8U,1);
- cvConvertScale(temp, disparity_left, -scale);
- temp = disparity_right;
- disparity_right = cvCreateImage(cvGetSize(temp), IPL_DEPTH_8U,1);
- cvConvertScale(temp, disparity_right, scale );
-#endif
-#ifdef LOAD
- disparity_left;
- disparity_right;
- sprintf(filename,"%s%s_dLgc.png",filepath,dataName);
- disparity_left = cvLoadImage(filename,0);
- sprintf(filename,"%s%s_dRgc.png",filepath,dataName);
- disparity_right = cvLoadImage(filename,0);
-#endif
-#ifdef debug
- cvNamedWindow("disparity_left");
- cvNamedWindow("disparity_right");
- cvNamedWindow("ground_truth_left");
- cvNamedWindow("ground_truth_right");
-
- cvShowImage("disparity_left",disparity_left);
- cvShowImage("disparity_right",disparity_right);
- cvShowImage("ground_truth_left", groundTruthLeft);
- cvShowImage("ground_truth_right", groundTruthRight);
-#endif
-
- /*Calculate RMS error and percentage of bad pixels*/
- IplImage* markedDisparity_left = cvCreateImage(cvGetSize(left), IPL_DEPTH_8U, 3);
- IplImage* markedDisparity_right = cvCreateImage(cvGetSize(left), IPL_DEPTH_8U, 3);
- cvCvtColor(disparity_left,markedDisparity_left,CV_GRAY2RGB);
- cvCvtColor(disparity_right,markedDisparity_right,CV_GRAY2RGB);
-
- int eval_ignore_border = 10;
- if (strcmp(dataName,"tsukuba") == 0)
- eval_ignore_border = 18;
-
- /*Left*/
- int retcode[2] = {0,0};
- if (groundTruthLeft)
- retcode[0] = CalculateErrors(disparity_left,groundTruthLeft, markedDisparity_left,
- rms_error[0], percentage_of_bad_pixels[0], maxDisparity, eval_ignore_border);
- /*Right*/
- if (groundTruthRight)
- retcode[1] = CalculateErrors(disparity_right,groundTruthRight, markedDisparity_right,
- rms_error[1], percentage_of_bad_pixels[1], maxDisparity, eval_ignore_border);
-
-#ifdef SAVEIMAGES
-#ifndef LOAD
- sprintf(filename,"%s%s_dLgc.png",filepath,dataName);
- cvSaveImage(filename,disparity_left);
- sprintf(filename,"%s%s_dRgc.png",filepath,dataName);
- cvSaveImage(filename,disparity_right);
-
- sprintf(filename,"%s%s_mdLgc.png",filepath,dataName);
- cvSaveImage(filename,markedDisparity_left);
- sprintf(filename,"%s%s_mdRgc.png",filepath,dataName);
- cvSaveImage(filename,markedDisparity_right);
-#endif
-#endif
-#ifdef debug
- cvNamedWindow("markedDisparity_left");
- cvNamedWindow("markedDisparity_right");
- cvShowImage("markedDisparity_left",markedDisparity_left);
- cvShowImage("markedDisparity_right",markedDisparity_right);
- cvWaitKey(1000);
-#endif
- if (retcode[0])
- {
- ts->printf(CvTS::LOG,"Calculation error");
- code = retcode[0];
- //goto _exit_;
- }
- if (retcode[1])
- {
- ts->printf(CvTS::LOG,"Calculation error");
- code = retcode[1];
- //goto _exit_;
- }
-#ifdef CONSOLEOUTPUT
- printf("\n%s\n",dataName);
- if (groundTruthLeft)
- printf("L rms error = %f\npercentage of bad pixels = %f\n",
- rms_error[0], percentage_of_bad_pixels[0]);
- if(groundTruthRight)
- printf("R rms error = %f\npercentage of bad pixels = %f\n",
- rms_error[1], percentage_of_bad_pixels[1]);
-#endif
- for(int i=0; i<2; i++)
- {
- IplImage* groundTruth = (i == 0) ? groundTruthLeft : groundTruthRight;
- if (groundTruth)
- {
- if (rms_error[i] > rms_error_thresh)
- {
- ts->printf( CvTS::LOG, "Big RMS error" );
- code = CvTS::FAIL_BAD_ACCURACY;
- //goto _exit_;
- }
- if (percentage_of_bad_pixels[i] > percentage_of_bad_pixels_thresh)
- {
- ts->printf( CvTS::LOG, "Big percentage of bad pixels" );
- code = CvTS::FAIL_BAD_ACCURACY;
- //goto _exit_;
- }
- }
- }
- }
-_exit_:
- cvReleaseImage(&left);
- cvReleaseImage(&right);
- cvReleaseImage(&disparity_left);
- cvReleaseImage(&disparity_right);
- cvReleaseImage(&groundTruthLeft);
- cvReleaseImage(&groundTruthRight);
-#ifndef LOAD
- //cvReleaseStereoCorrespondenceGCState(&stereoMatcher);
-#endif
- if( code < 0 )
- ts->set_failed_test_info( code );
-}
-
-CV_StereoCorrespondenceTestGC stereo_correspondece_test_gc;
-
-#endif
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-/*
- This is a regression test for stereo matching algorithms. This test gets some quality metrics
- discribed in "A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms".
- Daniel Scharstein, Richard Szeliski
-*/
-
-#include "cvtest.h"
-#include <limits>
-#include <cstdio>
-
-using namespace std;
-using namespace cv;
-
-const float EVAL_BAD_THRESH = 1.f;
-const int EVAL_TEXTURELESS_WIDTH = 3;
-const float EVAL_TEXTURELESS_THRESH = 4.f;
-const float EVAL_DISP_THRESH = 1.f;
-const float EVAL_DISP_GAP = 2.f;
-const int EVAL_DISCONT_WIDTH = 9;
-const int EVAL_IGNORE_BORDER = 10;
-
-const int ERROR_KINDS_COUNT = 6;
-
-//============================== quality measuring functions =================================================
-
-/*
- Calculate textureless regions of image (regions where the squared horizontal intensity gradient averaged over
- a square window of size=evalTexturelessWidth is below a threshold=evalTexturelessThresh) and textured regions.
-*/
-void computeTextureBasedMasks( const Mat& _img, Mat* texturelessMask, Mat* texturedMask,
- int texturelessWidth = EVAL_TEXTURELESS_WIDTH, float texturelessThresh = EVAL_TEXTURELESS_THRESH )
-{
- if( !texturelessMask && !texturedMask )
- return;
- if( _img.empty() )
- CV_Error( CV_StsBadArg, "img is empty" );
-
- Mat img = _img;
- if( _img.channels() > 1)
- {
- Mat tmp; cvtColor( _img, tmp, CV_BGR2GRAY ); img = tmp;
- }
- Mat dxI; Sobel( img, dxI, CV_32FC1, 1, 0, 3 );
- Mat dxI2; pow( dxI / 8.f/*normalize*/, 2, dxI2 );
- Mat avgDxI2; boxFilter( dxI2, avgDxI2, CV_32FC1, Size(texturelessWidth,texturelessWidth) );
-
- if( texturelessMask )
- *texturelessMask = avgDxI2 < texturelessThresh;
- if( texturedMask )
- *texturedMask = avgDxI2 >= texturelessThresh;
-}
-
-void checkTypeAndSizeOfDisp( const Mat& dispMap, const Size* sz )
-{
- if( dispMap.empty() )
- CV_Error( CV_StsBadArg, "dispMap is empty" );
- if( dispMap.type() != CV_32FC1 )
- CV_Error( CV_StsBadArg, "dispMap must have CV_32FC1 type" );
- if( sz && (dispMap.rows != sz->height || dispMap.cols != sz->width) )
- CV_Error( CV_StsBadArg, "dispMap has incorrect size" );
-}
-
-void checkTypeAndSizeOfMask( const Mat& mask, Size sz )
-{
- if( mask.empty() )
- CV_Error( CV_StsBadArg, "mask is empty" );
- if( mask.type() != CV_8UC1 )
- CV_Error( CV_StsBadArg, "mask must have CV_8UC1 type" );
- if( mask.rows != sz.height || mask.cols != sz.width )
- CV_Error( CV_StsBadArg, "mask has incorrect size" );
-}
-
-void checkDispMapsAndUnknDispMasks( const Mat& leftDispMap, const Mat& rightDispMap,
- const Mat& leftUnknDispMask, const Mat& rightUnknDispMask )
-{
- // check type and size of disparity maps
- checkTypeAndSizeOfDisp( leftDispMap, 0 );
- if( !rightDispMap.empty() )
- {
- Size sz = leftDispMap.size();
- checkTypeAndSizeOfDisp( rightDispMap, &sz );
- }
-
- // check size and type of unknown disparity maps
- if( !leftUnknDispMask.empty() )
- checkTypeAndSizeOfMask( leftUnknDispMask, leftDispMap.size() );
- if( !rightUnknDispMask.empty() )
- checkTypeAndSizeOfMask( rightUnknDispMask, rightDispMap.size() );
-
- // check values of disparity maps (known disparity values musy be positive)
- double leftMinVal = 0, rightMinVal = 0;
- if( leftUnknDispMask.empty() )
- minMaxLoc( leftDispMap, &leftMinVal );
- else
- minMaxLoc( leftDispMap, &leftMinVal, 0, 0, 0, ~leftUnknDispMask );
- if( !rightDispMap.empty() )
- {
- if( rightUnknDispMask.empty() )
- minMaxLoc( rightDispMap, &rightMinVal );
- else
- minMaxLoc( rightDispMap, &rightMinVal, 0, 0, 0, ~rightUnknDispMask );
- }
- if( leftMinVal < 0 || rightMinVal < 0)
- CV_Error( CV_StsBadArg, "known disparity values must be positive" );
-}
-
-/*
- Calculate occluded regions of reference image (left image) (regions that are occluded in the matching image (right image),
- i.e., where the forward-mapped disparity lands at a location with a larger (nearer) disparity) and non occluded regions.
-*/
-void computeOcclusionBasedMasks( const Mat& leftDisp, const Mat& _rightDisp,
- Mat* occludedMask, Mat* nonOccludedMask,
- const Mat& leftUnknDispMask = Mat(), const Mat& rightUnknDispMask = Mat(),
- float dispThresh = EVAL_DISP_THRESH )
-{
- if( !occludedMask && !nonOccludedMask )
- return;
- checkDispMapsAndUnknDispMasks( leftDisp, _rightDisp, leftUnknDispMask, rightUnknDispMask );
-
- Mat rightDisp;
- if( _rightDisp.empty() )
- {
- if( !rightUnknDispMask.empty() )
- CV_Error( CV_StsBadArg, "rightUnknDispMask must be empty if _rightDisp is empty" );
- rightDisp.create(leftDisp.size(), CV_32FC1);
- rightDisp.setTo(Scalar::all(0) );
- for( int leftY = 0; leftY < leftDisp.rows; leftY++ )
- {
- for( int leftX = 0; leftX < leftDisp.cols; leftX++ )
- {
- if( !leftUnknDispMask.empty() && leftUnknDispMask.at<uchar>(leftY,leftX) )
- continue;
- float leftDispVal = leftDisp.at<float>(leftY, leftX);
- int rightX = leftX - cvRound(leftDispVal), rightY = leftY;
- if( rightX >= 0)
- rightDisp.at<float>(rightY,rightX) = max(rightDisp.at<float>(rightY,rightX), leftDispVal);
- }
- }
- }
- else
- _rightDisp.copyTo(rightDisp);
-
- if( occludedMask )
- {
- occludedMask->create(leftDisp.size(), CV_8UC1);
- occludedMask->setTo(Scalar::all(0) );
- }
- if( nonOccludedMask )
- {
- nonOccludedMask->create(leftDisp.size(), CV_8UC1);
- nonOccludedMask->setTo(Scalar::all(0) );
- }
- for( int leftY = 0; leftY < leftDisp.rows; leftY++ )
- {
- for( int leftX = 0; leftX < leftDisp.cols; leftX++ )
- {
- if( !leftUnknDispMask.empty() && leftUnknDispMask.at<uchar>(leftY,leftX) )
- continue;
- float leftDispVal = leftDisp.at<float>(leftY, leftX);
- int rightX = leftX - cvRound(leftDispVal), rightY = leftY;
- if( rightX < 0 && occludedMask )
- occludedMask->at<uchar>(leftY, leftX) = 255;
- else
- {
- if( !rightUnknDispMask.empty() && rightUnknDispMask.at<uchar>(rightY,rightX) )
- continue;
- float rightDispVal = rightDisp.at<float>(rightY, rightX);
- if( rightDispVal > leftDispVal + dispThresh )
- {
- if( occludedMask )
- occludedMask->at<uchar>(leftY, leftX) = 255;
- }
- else
- {
- if( nonOccludedMask )
- nonOccludedMask->at<uchar>(leftY, leftX) = 255;
- }
- }
- }
- }
-}
-
-/*
- Calculate depth discontinuty regions: pixels whose neiboring disparities differ by more than
- dispGap, dilated by window of width discontWidth.
-*/
-void computeDepthDiscontMask( const Mat& disp, Mat& depthDiscontMask, const Mat& unknDispMask = Mat(),
- float dispGap = EVAL_DISP_GAP, int discontWidth = EVAL_DISCONT_WIDTH )
-{
- if( disp.empty() )
- CV_Error( CV_StsBadArg, "disp is empty" );
- if( disp.type() != CV_32FC1 )
- CV_Error( CV_StsBadArg, "disp must have CV_32FC1 type" );
- if( !unknDispMask.empty() )
- checkTypeAndSizeOfMask( unknDispMask, disp.size() );
-
- Mat curDisp; disp.copyTo( curDisp );
- if( !unknDispMask.empty() )
- curDisp.setTo( Scalar(-numeric_limits<float>::max()), unknDispMask );
- Mat maxNeighbDisp; dilate( curDisp, maxNeighbDisp, Mat(3, 3, CV_8UC1, Scalar(1)) );
- if( !unknDispMask.empty() )
- curDisp.setTo( Scalar(numeric_limits<float>::max()), unknDispMask );
- Mat minNeighbDisp; erode( curDisp, minNeighbDisp, Mat(3, 3, CV_8UC1, Scalar(1)) );
- depthDiscontMask = max( (Mat)(maxNeighbDisp-disp), (Mat)(disp-minNeighbDisp) ) > dispGap;
- if( !unknDispMask.empty() )
- depthDiscontMask &= ~unknDispMask;
- dilate( depthDiscontMask, depthDiscontMask, Mat(discontWidth, discontWidth, CV_8UC1, Scalar(1)) );
-}
-
-/*
- Get evaluation masks excluding a border.
-*/
-Mat getBorderedMask( Size maskSize, int border = EVAL_IGNORE_BORDER )
-{
- CV_Assert( border >= 0 );
- Mat mask(maskSize, CV_8UC1, Scalar(0));
- int w = maskSize.width - 2*border, h = maskSize.height - 2*border;
- if( w < 0 || h < 0 )
- mask.setTo(Scalar(0));
- else
- mask( Rect(Point(border,border),Size(w,h)) ).setTo(Scalar(255));
- return mask;
-}
-
-/*
- Calculate root-mean-squared error between the computed disparity map (computedDisp) and ground truth map (groundTruthDisp).
-*/
-float dispRMS( const Mat& computedDisp, const Mat& groundTruthDisp, const Mat& mask )
-{
- checkTypeAndSizeOfDisp( groundTruthDisp, 0 );
- Size sz = groundTruthDisp.size();
- checkTypeAndSizeOfDisp( computedDisp, &sz );
-
- int pointsCount = sz.height*sz.width;
- if( !mask.empty() )
- {
- checkTypeAndSizeOfMask( mask, sz );
- pointsCount = countNonZero(mask);
- }
- return 1.f/sqrt((float)pointsCount) * (float)norm(computedDisp, groundTruthDisp, NORM_L2, mask);
-}
-
-/*
- Calculate fraction of bad matching pixels.
-*/
-float badMatchPxlsFraction( const Mat& computedDisp, const Mat& groundTruthDisp, const Mat& mask,
- float _badThresh = EVAL_BAD_THRESH )
-{
- int badThresh = cvRound(_badThresh);
- checkTypeAndSizeOfDisp( groundTruthDisp, 0 );
- Size sz = groundTruthDisp.size();
- checkTypeAndSizeOfDisp( computedDisp, &sz );
-
- Mat badPxlsMap;
- absdiff( computedDisp, groundTruthDisp, badPxlsMap );
- badPxlsMap = badPxlsMap > badThresh;
- int pointsCount = sz.height*sz.width;
- if( !mask.empty() )
- {
- checkTypeAndSizeOfMask( mask, sz );
- badPxlsMap = badPxlsMap & mask;
- pointsCount = countNonZero(mask);
- }
- return 1.f/pointsCount * countNonZero(badPxlsMap);
-}
-
-//===================== regression test for stereo matching algorithms ==============================
-
-const string ALGORITHMS_DIR = "stereomatching/algorithms/";
-const string DATASETS_DIR = "stereomatching/datasets/";
-const string DATASETS_FILE = "datasets.xml";
-
-const string RUN_PARAMS_FILE = "_params.xml";
-const string RESULT_FILE = "_res.xml";
-
-const string LEFT_IMG_NAME = "im2.png";
-const string RIGHT_IMG_NAME = "im6.png";
-const string TRUE_LEFT_DISP_NAME = "disp2.png";
-const string TRUE_RIGHT_DISP_NAME = "disp6.png";
-
-string ERROR_PREFIXES[] = { "borderedAll",
- "borderedNoOccl",
- "borderedOccl",
- "borderedTextured",
- "borderedTextureless",
- "borderedDepthDiscont" }; // size of ERROR_KINDS_COUNT
-
-
-const string RMS_STR = "RMS";
-const string BAD_PXLS_FRACTION_STR = "BadPxlsFraction";
-
-class QualityEvalParams
-{
-public:
- QualityEvalParams() { setDefaults(); }
- QualityEvalParams( int _ignoreBorder )
- {
- setDefaults();
- ignoreBorder = _ignoreBorder;
- }
- void setDefaults()
- {
- badThresh = EVAL_BAD_THRESH;
- texturelessWidth = EVAL_TEXTURELESS_WIDTH;
- texturelessThresh = EVAL_TEXTURELESS_THRESH;
- dispThresh = EVAL_DISP_THRESH;
- dispGap = EVAL_DISP_GAP;
- discontWidth = EVAL_DISCONT_WIDTH;
- ignoreBorder = EVAL_IGNORE_BORDER;
- }
- float badThresh;
- int texturelessWidth;
- float texturelessThresh;
- float dispThresh;
- float dispGap;
- int discontWidth;
- int ignoreBorder;
-};
-
-class CV_StereoMatchingTest : public CvTest
-{
-public:
- CV_StereoMatchingTest( const char* testName ) : CvTest( testName, "stereo-matching" )
- { rmsEps.resize( ERROR_KINDS_COUNT, 0.01f ); fracEps.resize( ERROR_KINDS_COUNT, 1.e-6f ); }
-protected:
- // assumed that left image is a reference image
- virtual int runStereoMatchingAlgorithm( const Mat& leftImg, const Mat& rightImg,
- Mat& leftDisp, Mat& rightDisp, int caseIdx ) = 0; // return ignored border width
-
- int readDatasetsParams( FileStorage& fs );
- virtual int readRunParams( FileStorage& fs );
- void writeErrors( const string& errName, const vector<float>& errors, FileStorage* fs = 0 );
- void readErrors( FileNode& fn, const string& errName, vector<float>& errors );
- int compareErrors( const vector<float>& calcErrors, const vector<float>& validErrors,
- const vector<float>& eps, const string& errName );
- int processStereoMatchingResults( FileStorage& fs, int caseIdx, bool isWrite,
- const Mat& leftImg, const Mat& rightImg,
- const Mat& trueLeftDisp, const Mat& trueRightDisp,
- const Mat& leftDisp, const Mat& rightDisp,
- const QualityEvalParams& qualityEvalParams );
- void run( int );
-
- vector<float> rmsEps;
- vector<float> fracEps;
-
- struct DatasetParams
- {
- int dispScaleFactor;
- int dispUnknVal;
- };
- map<string, DatasetParams> datasetsParams;
-
- vector<string> caseNames;
- vector<string> caseDatasets;
-};
-
-void CV_StereoMatchingTest::run(int)
-{
- string dataPath = ts->get_data_path();
- string algorithmName = name;
- assert( !algorithmName.empty() );
- if( dataPath.empty() )
- {
- ts->printf( CvTS::LOG, "dataPath is empty" );
- ts->set_failed_test_info( CvTS::FAIL_BAD_ARG_CHECK );
- return;
- }
-
- FileStorage datasetsFS( dataPath + DATASETS_DIR + DATASETS_FILE, FileStorage::READ );
- int code = readDatasetsParams( datasetsFS );
- if( code != CvTS::OK )
- {
- ts->set_failed_test_info( code );
- return;
- }
- FileStorage runParamsFS( dataPath + ALGORITHMS_DIR + algorithmName + RUN_PARAMS_FILE, FileStorage::READ );
- code = readRunParams( runParamsFS );
- if( code != CvTS::OK )
- {
- ts->set_failed_test_info( code );
- return;
- }
-
- string fullResultFilename = dataPath + ALGORITHMS_DIR + algorithmName + RESULT_FILE;
- FileStorage resFS( fullResultFilename, FileStorage::READ );
- bool isWrite = true; // write or compare results
- if( resFS.isOpened() )
- isWrite = false;
- else
- {
- resFS.open( fullResultFilename, FileStorage::WRITE );
- if( !resFS.isOpened() )
- {
- ts->printf( CvTS::LOG, "file %s can not be read or written\n", fullResultFilename.c_str() );
- ts->set_failed_test_info( CvTS::FAIL_BAD_ARG_CHECK );
- return;
- }
- resFS << "stereo_matching" << "{";
- }
-
- int progress = 0, caseCount = (int)caseNames.size();
- for( int ci = 0; ci < caseCount; ci++)
- {
- progress = update_progress( progress, ci, caseCount, 0 );
-
- string datasetName = caseDatasets[ci];
- string datasetFullDirName = dataPath + DATASETS_DIR + datasetName + "/";
- Mat leftImg = imread(datasetFullDirName + LEFT_IMG_NAME);
- Mat rightImg = imread(datasetFullDirName + RIGHT_IMG_NAME);
- Mat trueLeftDisp = imread(datasetFullDirName + TRUE_LEFT_DISP_NAME, 0);
- Mat trueRightDisp = imread(datasetFullDirName + TRUE_RIGHT_DISP_NAME, 0);
-
- if( leftImg.empty() || rightImg.empty() || trueLeftDisp.empty() )
- {
- ts->printf( CvTS::LOG, "images or left ground-truth disparities of dataset %s can not be read", datasetName.c_str() );
- code = CvTS::FAIL_INVALID_TEST_DATA;
- continue;
- }
- int dispScaleFactor = datasetsParams[datasetName].dispScaleFactor;
- Mat tmp; trueLeftDisp.convertTo( tmp, CV_32FC1, 1.f/dispScaleFactor ); trueLeftDisp = tmp; tmp.release();
- if( !trueRightDisp.empty() )
- trueRightDisp.convertTo( tmp, CV_32FC1, 1.f/dispScaleFactor ); trueRightDisp = tmp; tmp.release();
-
- Mat leftDisp, rightDisp;
- int ignBorder = max(runStereoMatchingAlgorithm(leftImg, rightImg, leftDisp, rightDisp, ci), EVAL_IGNORE_BORDER);
- leftDisp.convertTo( tmp, CV_32FC1 ); leftDisp = tmp; tmp.release();
- rightDisp.convertTo( tmp, CV_32FC1 ); rightDisp = tmp; tmp.release();
-
- int tempCode = processStereoMatchingResults( resFS, ci, isWrite,
- leftImg, rightImg, trueLeftDisp, trueRightDisp, leftDisp, rightDisp, QualityEvalParams(ignBorder));
- code = tempCode==CvTS::OK ? code : tempCode;
- }
-
- if( isWrite )
- resFS << "}"; // "stereo_matching"
-
- ts->set_failed_test_info( code );
-}
-
-void calcErrors( const Mat& leftImg, const Mat& /*rightImg*/,
- const Mat& trueLeftDisp, const Mat& trueRightDisp,
- const Mat& trueLeftUnknDispMask, const Mat& trueRightUnknDispMask,
- const Mat& calcLeftDisp, const Mat& /*calcRightDisp*/,
- vector<float>& rms, vector<float>& badPxlsFractions,
- const QualityEvalParams& qualityEvalParams )
-{
- Mat texturelessMask, texturedMask;
- computeTextureBasedMasks( leftImg, &texturelessMask, &texturedMask,
- qualityEvalParams.texturelessWidth, qualityEvalParams.texturelessThresh );
- Mat occludedMask, nonOccludedMask;
- computeOcclusionBasedMasks( trueLeftDisp, trueRightDisp, &occludedMask, &nonOccludedMask,
- trueLeftUnknDispMask, trueRightUnknDispMask, qualityEvalParams.dispThresh);
- Mat depthDiscontMask;
- computeDepthDiscontMask( trueLeftDisp, depthDiscontMask, trueLeftUnknDispMask,
- qualityEvalParams.dispGap, qualityEvalParams.discontWidth);
-
- Mat borderedKnownMask = getBorderedMask( leftImg.size(), qualityEvalParams.ignoreBorder ) & ~trueLeftUnknDispMask;
-
- nonOccludedMask &= borderedKnownMask;
- occludedMask &= borderedKnownMask;
- texturedMask &= nonOccludedMask; // & borderedKnownMask
- texturelessMask &= nonOccludedMask; // & borderedKnownMask
- depthDiscontMask &= nonOccludedMask; // & borderedKnownMask
-
- rms.resize(ERROR_KINDS_COUNT);
- rms[0] = dispRMS( calcLeftDisp, trueLeftDisp, borderedKnownMask );
- rms[1] = dispRMS( calcLeftDisp, trueLeftDisp, nonOccludedMask );
- rms[2] = dispRMS( calcLeftDisp, trueLeftDisp, occludedMask );
- rms[3] = dispRMS( calcLeftDisp, trueLeftDisp, texturedMask );
- rms[4] = dispRMS( calcLeftDisp, trueLeftDisp, texturelessMask );
- rms[5] = dispRMS( calcLeftDisp, trueLeftDisp, depthDiscontMask );
-
- badPxlsFractions.resize(ERROR_KINDS_COUNT);
- badPxlsFractions[0] = badMatchPxlsFraction( calcLeftDisp, trueLeftDisp, borderedKnownMask, qualityEvalParams.badThresh );
- badPxlsFractions[1] = badMatchPxlsFraction( calcLeftDisp, trueLeftDisp, nonOccludedMask, qualityEvalParams.badThresh );
- badPxlsFractions[2] = badMatchPxlsFraction( calcLeftDisp, trueLeftDisp, occludedMask, qualityEvalParams.badThresh );
- badPxlsFractions[3] = badMatchPxlsFraction( calcLeftDisp, trueLeftDisp, texturedMask, qualityEvalParams.badThresh );
- badPxlsFractions[4] = badMatchPxlsFraction( calcLeftDisp, trueLeftDisp, texturelessMask, qualityEvalParams.badThresh );
- badPxlsFractions[5] = badMatchPxlsFraction( calcLeftDisp, trueLeftDisp, depthDiscontMask, qualityEvalParams.badThresh );
-}
-
-int CV_StereoMatchingTest::processStereoMatchingResults( FileStorage& fs, int caseIdx, bool isWrite,
- const Mat& leftImg, const Mat& rightImg,
- const Mat& trueLeftDisp, const Mat& trueRightDisp,
- const Mat& leftDisp, const Mat& rightDisp,
- const QualityEvalParams& qualityEvalParams )
-{
- // rightDisp is not used in current test virsion
- int code = CvTS::OK;
- assert( fs.isOpened() );
- assert( trueLeftDisp.type() == CV_32FC1 && trueRightDisp.type() == CV_32FC1 );
- assert( leftDisp.type() == CV_32FC1 && rightDisp.type() == CV_32FC1 );
-
- // get masks for unknown ground truth disparity values
- Mat leftUnknMask, rightUnknMask;
- DatasetParams params = datasetsParams[caseDatasets[caseIdx]];
- absdiff( trueLeftDisp, Scalar(params.dispUnknVal), leftUnknMask );
- leftUnknMask = leftUnknMask < numeric_limits<float>::epsilon();
- assert(leftUnknMask.type() == CV_8UC1);
- if( !trueRightDisp.empty() )
- {
- absdiff( trueRightDisp, Scalar(params.dispUnknVal), rightUnknMask );
- rightUnknMask = rightUnknMask < numeric_limits<float>::epsilon();
- assert(leftUnknMask.type() == CV_8UC1);
- }
-
- // calculate errors
- vector<float> rmss, badPxlsFractions;
- calcErrors( leftImg, rightImg, trueLeftDisp, trueRightDisp, leftUnknMask, rightUnknMask,
- leftDisp, rightDisp, rmss, badPxlsFractions, qualityEvalParams );
-
- if( isWrite )
- {
- fs << caseNames[caseIdx] << "{";
- cvWriteComment( fs.fs, RMS_STR.c_str(), 0 );
- writeErrors( RMS_STR, rmss, &fs );
- cvWriteComment( fs.fs, BAD_PXLS_FRACTION_STR.c_str(), 0 );
- writeErrors( BAD_PXLS_FRACTION_STR, badPxlsFractions, &fs );
- fs << "}"; // datasetName
- }
- else // compare
- {
- ts->printf( CvTS::LOG, "\nquality of case named %s\n", caseNames[caseIdx].c_str() );
- ts->printf( CvTS::LOG, "%s\n", RMS_STR.c_str() );
- writeErrors( RMS_STR, rmss );
- ts->printf( CvTS::LOG, "%s\n", BAD_PXLS_FRACTION_STR.c_str() );
- writeErrors( BAD_PXLS_FRACTION_STR, badPxlsFractions );
-
- FileNode fn = fs.getFirstTopLevelNode()[caseNames[caseIdx]];
- vector<float> validRmss, validBadPxlsFractions;
-
- readErrors( fn, RMS_STR, validRmss );
- readErrors( fn, BAD_PXLS_FRACTION_STR, validBadPxlsFractions );
- int tempCode = compareErrors( rmss, validRmss, rmsEps, RMS_STR );
- code = tempCode==CvTS::OK ? code : tempCode;
- tempCode = compareErrors( badPxlsFractions, validBadPxlsFractions, fracEps, BAD_PXLS_FRACTION_STR );
- code = tempCode==CvTS::OK ? code : tempCode;
- }
- return code;
-}
-
-int CV_StereoMatchingTest::readDatasetsParams( FileStorage& fs )
-{
- if( !fs.isOpened() )
- {
- ts->printf( CvTS::LOG, "datasetsParams can not be read " );
- return CvTS::FAIL_INVALID_TEST_DATA;
- }
- datasetsParams.clear();
- FileNode fn = fs.getFirstTopLevelNode();
- assert(fn.isSeq());
- for( int i = 0; i < (int)fn.size(); i+=3 )
- {
- string name = fn[i];
- DatasetParams params;
- string sf = fn[i+1]; params.dispScaleFactor = atoi(sf.c_str());
- string uv = fn[i+2]; params.dispUnknVal = atoi(uv.c_str());
- datasetsParams[name] = params;
- }
- return CvTS::OK;
-}
-
-int CV_StereoMatchingTest::readRunParams( FileStorage& fs )
-{
- if( !fs.isOpened() )
- {
- ts->printf( CvTS::LOG, "runParams can not be read " );
- return CvTS::FAIL_INVALID_TEST_DATA;
- }
- caseNames.clear();;
- caseDatasets.clear();
- return CvTS::OK;
-}
-
-void CV_StereoMatchingTest::writeErrors( const string& errName, const vector<float>& errors, FileStorage* fs )
-{
- assert( (int)errors.size() == ERROR_KINDS_COUNT );
- vector<float>::const_iterator it = errors.begin();
- if( fs )
- for( int i = 0; i < ERROR_KINDS_COUNT; i++, ++it )
- *fs << ERROR_PREFIXES[i] + errName << *it;
- else
- for( int i = 0; i < ERROR_KINDS_COUNT; i++, ++it )
- ts->printf( CvTS::LOG, "%s = %f\n", string(ERROR_PREFIXES[i]+errName).c_str(), *it );
-}
-
-void CV_StereoMatchingTest::readErrors( FileNode& fn, const string& errName, vector<float>& errors )
-{
- errors.resize( ERROR_KINDS_COUNT );
- vector<float>::iterator it = errors.begin();
- for( int i = 0; i < ERROR_KINDS_COUNT; i++, ++it )
- fn[ERROR_PREFIXES[i]+errName] >> *it;
-}
-
-int CV_StereoMatchingTest::compareErrors( const vector<float>& calcErrors, const vector<float>& validErrors,
- const vector<float>& eps, const string& errName )
-{
- assert( (int)calcErrors.size() == ERROR_KINDS_COUNT );
- assert( (int)validErrors.size() == ERROR_KINDS_COUNT );
- assert( (int)eps.size() == ERROR_KINDS_COUNT );
- vector<float>::const_iterator calcIt = calcErrors.begin(),
- validIt = validErrors.begin(),
- epsIt = eps.begin();
- bool ok = true;
- for( int i = 0; i < ERROR_KINDS_COUNT; i++, ++calcIt, ++validIt, ++epsIt )
- if( *calcIt - *validIt > *epsIt )
- {
- ts->printf( CvTS::LOG, "bad accuracy of %s (valid=%f; calc=%f)\n", string(ERROR_PREFIXES[i]+errName).c_str(), *validIt, *calcIt );
- ok = false;
- }
- return ok ? CvTS::OK : CvTS::FAIL_BAD_ACCURACY;
-}
-
-//----------------------------------- StereoBM test -----------------------------------------------------
-
-class CV_StereoBMTest : public CV_StereoMatchingTest
-{
-public:
- CV_StereoBMTest() : CV_StereoMatchingTest( "stereobm" )
- { fill(rmsEps.begin(), rmsEps.end(), 0.4f); fill(fracEps.begin(), fracEps.end(), 0.022f); }
-
-protected:
- struct RunParams
- {
- int ndisp;
- int winSize;
- };
- vector<RunParams> caseRunParams;
-
- virtual int readRunParams( FileStorage& fs )
- {
- int code = CV_StereoMatchingTest::readRunParams( fs );
- FileNode fn = fs.getFirstTopLevelNode();
- assert(fn.isSeq());
- for( int i = 0; i < (int)fn.size(); i+=4 )
- {
- string caseName = fn[i], datasetName = fn[i+1];
- RunParams params;
- string ndisp = fn[i+2]; params.ndisp = atoi(ndisp.c_str());
- string winSize = fn[i+3]; params.winSize = atoi(winSize.c_str());
- caseNames.push_back( caseName );
- caseDatasets.push_back( datasetName );
- caseRunParams.push_back( params );
- }
- return code;
- }
-
- virtual int runStereoMatchingAlgorithm( const Mat& _leftImg, const Mat& _rightImg,
- Mat& leftDisp, Mat& /*rightDisp*/, int caseIdx )
- {
- RunParams params = caseRunParams[caseIdx];
- assert( params.ndisp%16 == 0 );
- assert( _leftImg.type() == CV_8UC3 && _rightImg.type() == CV_8UC3 );
- Mat leftImg; cvtColor( _leftImg, leftImg, CV_BGR2GRAY );
- Mat rightImg; cvtColor( _rightImg, rightImg, CV_BGR2GRAY );
-
- StereoBM bm( StereoBM::BASIC_PRESET, params.ndisp, params.winSize );
- bm( leftImg, rightImg, leftDisp, CV_32F );
- return params.winSize/2;
- }
-};
-
-CV_StereoBMTest stereoBM;
-
-//----------------------------------- StereoGC test -----------------------------------------------------
-
-class CV_StereoGCTest : public CV_StereoMatchingTest
-{
-public:
- CV_StereoGCTest() : CV_StereoMatchingTest( "stereogc" )
- {
- fill(rmsEps.begin(), rmsEps.end(), 3.f);
- fracEps[0] = 0.05f; // all
- fracEps[1] = 0.05f; // noOccl
- fracEps[2] = 0.25f; // occl
- fracEps[3] = 0.05f; // textured
- fracEps[4] = 0.10f; // textureless
- fracEps[5] = 0.10f; // borderedDepthDiscont
- }
-protected:
- struct RunParams
- {
- int ndisp;
- int iterCount;
- };
- vector<RunParams> caseRunParams;
-
- virtual int readRunParams( FileStorage& fs )
- {
- int code = CV_StereoMatchingTest::readRunParams(fs);
- FileNode fn = fs.getFirstTopLevelNode();
- assert(fn.isSeq());
- for( int i = 0; i < (int)fn.size(); i+=4 )
- {
- string caseName = fn[i], datasetName = fn[i+1];
- RunParams params;
- string ndisp = fn[i+2]; params.ndisp = atoi(ndisp.c_str());
- string iterCount = fn[i+3]; params.iterCount = atoi(iterCount.c_str());
- caseNames.push_back( caseName );
- caseDatasets.push_back( datasetName );
- caseRunParams.push_back( params );
- }
- return code;
- }
-
- virtual int runStereoMatchingAlgorithm( const Mat& _leftImg, const Mat& _rightImg,
- Mat& leftDisp, Mat& rightDisp, int caseIdx )
- {
- RunParams params = caseRunParams[caseIdx];
- assert( _leftImg.type() == CV_8UC3 && _rightImg.type() == CV_8UC3 );
- Mat leftImg, rightImg, tmp;
- cvtColor( _leftImg, leftImg, CV_BGR2GRAY );
- cvtColor( _rightImg, rightImg, CV_BGR2GRAY );
-
- leftDisp.create( leftImg.size(), CV_16SC1 );
- rightDisp.create( rightImg.size(), CV_16SC1 );
-
- CvMat _limg = leftImg, _rimg = rightImg, _ldisp = leftDisp, _rdisp = rightDisp;
- CvStereoGCState *state = cvCreateStereoGCState( params.ndisp, params.iterCount );
- cvFindStereoCorrespondenceGC( &_limg, &_rimg, &_ldisp, &_rdisp, state );
- cvReleaseStereoGCState( &state );
-
- leftDisp = - leftDisp;
- return 0;
- }
-
-};
-
-CV_StereoGCTest stereoGC;
-
-//----------------------------------- StereoSGBM test -----------------------------------------------------
-
-class CV_StereoSGBMTest : public CV_StereoMatchingTest
-{
-public:
- CV_StereoSGBMTest() : CV_StereoMatchingTest( "stereosgbm" )
- { fill(rmsEps.begin(), rmsEps.end(), 0.25f); fill(fracEps.begin(), fracEps.end(), 0.01f); }
-
-protected:
- struct RunParams
- {
- int ndisp;
- int winSize;
- bool fullDP;
- };
- vector<RunParams> caseRunParams;
-
- virtual int readRunParams( FileStorage& fs )
- {
- int code = CV_StereoMatchingTest::readRunParams(fs);
- FileNode fn = fs.getFirstTopLevelNode();
- assert(fn.isSeq());
- for( int i = 0; i < (int)fn.size(); i+=5 )
- {
- string caseName = fn[i], datasetName = fn[i+1];
- RunParams params;
- string ndisp = fn[i+2]; params.ndisp = atoi(ndisp.c_str());
- string winSize = fn[i+3]; params.winSize = atoi(winSize.c_str());
- string fullDP = fn[i+4]; params.fullDP = atoi(fullDP.c_str()) == 0 ? false : true;
- caseNames.push_back( caseName );
- caseDatasets.push_back( datasetName );
- caseRunParams.push_back( params );
- }
- return code;
- }
-
- virtual int runStereoMatchingAlgorithm( const Mat& leftImg, const Mat& rightImg,
- Mat& leftDisp, Mat& /*rightDisp*/, int caseIdx )
- {
- RunParams params = caseRunParams[caseIdx];
- assert( params.ndisp%16 == 0 );
- StereoSGBM sgbm( 0, params.ndisp, params.winSize, 10*params.winSize*params.winSize, 40*params.winSize*params.winSize,
- 1, 63, 10, 100, 32, params.fullDP );
- sgbm( leftImg, rightImg, leftDisp );
- assert( leftDisp.type() == CV_16SC1 );
- leftDisp/=16;
- return 0;
- }
-};
-
-CV_StereoSGBMTest stereoSGBM;
-
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-
-class CV_SubdivTest : public CvTest
-{
-public:
- CV_SubdivTest();
- ~CV_SubdivTest();
- int write_default_params(CvFileStorage* fs);
- void clear();
-
-protected:
- int read_params( CvFileStorage* fs );
- int prepare_test_case( int test_case_idx );
- int validate_test_results( int test_case_idx );
- void run_func();
-
- int min_log_img_size, max_log_img_size;
- CvSize img_size;
- int min_log_point_count;
- int max_log_point_count;
- int point_count;
- CvSubdiv2D* subdiv;
- CvMemStorage* storage;
-};
-
-
-CV_SubdivTest::CV_SubdivTest() :
- CvTest( "subdiv",
- "cvCreateSubdivDelaunay2D, cvSubdivDelaunay2DInsert, cvSubdiv2DLocate, "
- "cvCalcSubdivVoronoi2D, cvFindNearestPoint2D" )
-{
- test_case_count = 100;
- min_log_point_count = 1;
- max_log_point_count = 10;
- min_log_img_size = 1;
- max_log_img_size = 10;
-
- storage = 0;
-}
-
-
-CV_SubdivTest::~CV_SubdivTest()
-{
- clear();
-}
-
-
-void CV_SubdivTest::clear()
-{
- CvTest::clear();
- cvReleaseMemStorage( &storage );
-}
-
-
-int CV_SubdivTest::write_default_params( CvFileStorage* fs )
-{
- CvTest::write_default_params( fs );
- if( ts->get_testing_mode() != CvTS::TIMING_MODE )
- {
- write_param( fs, "test_case_count", test_case_count );
- write_param( fs, "min_log_point_count", min_log_point_count );
- write_param( fs, "max_log_point_count", max_log_point_count );
- write_param( fs, "min_log_img_size", min_log_img_size );
- write_param( fs, "max_log_img_size", max_log_img_size );
- }
- return 0;
-}
-
-
-int CV_SubdivTest::read_params( CvFileStorage* fs )
-{
- int code = CvTest::read_params( fs );
- int t;
-
- if( code < 0 )
- return code;
-
- test_case_count = cvReadInt( find_param( fs, "test_case_count" ), test_case_count );
- min_log_point_count = cvReadInt( find_param( fs, "min_log_point_count" ), min_log_point_count );
- max_log_point_count = cvReadInt( find_param( fs, "max_log_point_count" ), max_log_point_count );
- min_log_img_size = cvReadInt( find_param( fs, "min_log_img_size" ), min_log_img_size );
- max_log_img_size = cvReadInt( find_param( fs, "max_log_img_size" ), max_log_img_size );
-
- min_log_point_count = cvTsClipInt( min_log_point_count, 1, 10 );
- max_log_point_count = cvTsClipInt( max_log_point_count, 1, 10 );
- if( min_log_point_count > max_log_point_count )
- CV_SWAP( min_log_point_count, max_log_point_count, t );
-
- min_log_img_size = cvTsClipInt( min_log_img_size, 1, 10 );
- max_log_img_size = cvTsClipInt( max_log_img_size, 1, 10 );
- if( min_log_img_size > max_log_img_size )
- CV_SWAP( min_log_img_size, max_log_img_size, t );
-
- return 0;
-}
-
-
-int CV_SubdivTest::prepare_test_case( int test_case_idx )
-{
- CvRNG* rng = ts->get_rng();
- int code = CvTest::prepare_test_case( test_case_idx );
- if( code < 0 )
- return code;
-
- clear();
-
- point_count = cvRound(exp((cvTsRandReal(rng)*
- (max_log_point_count - min_log_point_count) + min_log_point_count)*CV_LOG2));
- img_size.width = cvRound(exp((cvTsRandReal(rng)*
- (max_log_img_size - min_log_img_size) + min_log_img_size)*CV_LOG2));
- img_size.height = cvRound(exp((cvTsRandReal(rng)*
- (max_log_img_size - min_log_img_size) + min_log_img_size)*CV_LOG2));
-
- storage = cvCreateMemStorage( 1 << 10 );
- return 1;
-}
-
-
-void CV_SubdivTest::run_func()
-{
-}
-
-
-// the whole testing is done here, run_func() is not utilized in this test
-int CV_SubdivTest::validate_test_results( int /*test_case_idx*/ )
-{
- int code = CvTS::OK;
- CvRNG* rng = ts->get_rng();
- int j, k, real_count = point_count;
- double xrange = img_size.width*(1 - FLT_EPSILON);
- double yrange = img_size.height*(1 - FLT_EPSILON);
-
- subdiv = subdiv = cvCreateSubdivDelaunay2D(
- cvRect( 0, 0, img_size.width, img_size.height ), storage );
-
- CvSeq* seq = cvCreateSeq( 0, sizeof(*seq), sizeof(CvPoint2D32f), storage );
- CvSeqWriter writer;
- cvStartAppendToSeq( seq, &writer );
-
- // insert random points
- for( j = 0; j < point_count; j++ )
- {
- CvPoint2D32f pt;
- CvSubdiv2DPoint* point;
-
- pt.x = (float)(cvTsRandReal(rng)*xrange);
- pt.y = (float)(cvTsRandReal(rng)*yrange);
-
- CvSubdiv2DPointLocation loc =
- cvSubdiv2DLocate( subdiv, pt, 0, &point );
-
- if( loc == CV_PTLOC_VERTEX )
- {
- int index = cvSeqElemIdx( (CvSeq*)subdiv, point );
- CvPoint2D32f* pt1;
- cvFlushSeqWriter( &writer );
- pt1 = (CvPoint2D32f*)cvGetSeqElem( seq, index - 3 );
-
- if( !pt1 ||
- fabs(pt1->x - pt.x) > FLT_EPSILON ||
- fabs(pt1->y - pt.y) > FLT_EPSILON )
- {
- ts->printf( CvTS::LOG, "The point #%d: (%.1f,%.1f) is said to coinside with a subdivision vertex, "
- "however it could be found in a sequence of inserted points\n", j, pt.x, pt.y );
- code = CvTS::FAIL_INVALID_OUTPUT;
- goto _exit_;
- }
- real_count--;
- }
-
- point = cvSubdivDelaunay2DInsert( subdiv, pt );
- if( point->pt.x != pt.x || point->pt.y != pt.y )
- {
- ts->printf( CvTS::LOG, "The point #%d: (%.1f,%.1f) has been incorrectly added\n", j, pt.x, pt.y );
- code = CvTS::FAIL_INVALID_OUTPUT;
- goto _exit_;
- }
-
- if( (j + 1) % 10 == 0 || j == point_count - 1 )
- {
- if( !icvSubdiv2DCheck( subdiv ))
- {
- ts->printf( CvTS::LOG, "Subdivision consistency check failed after inserting the point #%d\n", j );
- code = CvTS::FAIL_INVALID_OUTPUT;
- goto _exit_;
- }
- }
-
- if( loc != CV_PTLOC_VERTEX )
- {
- CV_WRITE_SEQ_ELEM( pt, writer );
- }
- }
-
- if( code < 0 )
- goto _exit_;
-
- cvCalcSubdivVoronoi2D( subdiv );
- seq = cvEndWriteSeq( &writer );
-
- if( !icvSubdiv2DCheck( subdiv ))
- {
- ts->printf( CvTS::LOG, "The subdivision failed consistency check after building the Voronoi tesselation\n" );
- code = CvTS::FAIL_INVALID_OUTPUT;
- goto _exit_;
- }
-
- for( j = 0; j < MAX((point_count - 5)/10 + 5, 10); j++ )
- {
- CvPoint2D32f pt;
- double minDistance;
-
- pt.x = (float)(cvTsRandReal(rng)*xrange);
- pt.y = (float)(cvTsRandReal(rng)*yrange);
-
- CvSubdiv2DPoint* point = cvFindNearestPoint2D( subdiv, pt );
- CvSeqReader reader;
-
- if( !point )
- {
- ts->printf( CvTS::LOG, "There is no nearest point (?!) for the point (%.1f, %.1f) in the subdivision\n",
- pt.x, pt.y );
- code = CvTS::FAIL_INVALID_OUTPUT;
- goto _exit_;
- }
-
- cvStartReadSeq( seq, &reader );
- minDistance = icvSqDist2D32f( pt, point->pt );
-
- for( k = 0; k < seq->total; k++ )
- {
- CvPoint2D32f ptt;
- CV_READ_SEQ_ELEM( ptt, reader );
-
- double distance = icvSqDist2D32f( pt, ptt );
- if( minDistance > distance && icvSqDist2D32f(ptt, point->pt) > FLT_EPSILON*1000 )
- {
- ts->printf( CvTS::LOG, "The triangulation vertex (%.3f,%.3f) was said to be nearest to (%.3f,%.3f),\n"
- "whereas another vertex (%.3f,%.3f) is closer\n",
- point->pt.x, point->pt.y, pt.x, pt.y, ptt.x, ptt.y );
- code = CvTS::FAIL_BAD_ACCURACY;
- goto _exit_;
- }
- }
- }
-
-_exit_:
- if( code < 0 )
- ts->set_failed_test_info( code );
-
- return code;
-}
-
-CV_SubdivTest subdiv_test;
-
-/* End of file. */
-
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-static const char* templmatch_param_names[] = { "template_size", "method", "size", "channels", "depth", 0 };
-static const int templmatch_depths[] = { CV_8U, CV_32F, -1 };
-static const int templmatch_channels[] = { 1, 3, -1 };
-
-static const CvSize templmatch_sizes[] = {{320, 240}, {1024,768}, {-1,-1}};
-static const CvSize templmatch_whole_sizes[] = {{320,240}, {1024,768}, {-1,-1}};
-static const CvSize templmatch_template_sizes[] = {{15,15}, {60,60}, {-1,-1}};
-static const char* templmatch_methods[] = { "sqdiff", "sqdiff_norm", "ccorr", "ccorr_normed", "ccoeff", "ccoeff_normed", 0 };
-
-class CV_TemplMatchTest : public CvArrTest
-{
-public:
- CV_TemplMatchTest();
-
-protected:
- int read_params( CvFileStorage* fs );
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void get_minmax_bounds( int i, int j, int type, CvScalar* low, CvScalar* high );
- double get_success_error_level( int test_case_idx, int i, int j );
- void run_func();
- void prepare_to_validation( int );
-
- int write_default_params(CvFileStorage* fs);
- void get_timing_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types,
- CvSize** whole_sizes, bool *are_images );
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
-
- int max_template_size;
- int method;
- bool test_cpp;
-};
-
-
-CV_TemplMatchTest::CV_TemplMatchTest()
- : CvArrTest( "match-template", "cvMatchTemplate", "" )
-{
- test_array[INPUT].push(NULL);
- test_array[INPUT].push(NULL);
- test_array[OUTPUT].push(NULL);
- test_array[REF_OUTPUT].push(NULL);
- element_wise_relative_error = false;
- max_template_size = 100;
- method = 0;
-
- size_list = templmatch_sizes;
- whole_size_list = templmatch_whole_sizes;
- cn_list = templmatch_channels;
- depth_list = templmatch_depths;
-
- default_timing_param_names = templmatch_param_names;
- test_cpp = false;
-}
-
-
-int CV_TemplMatchTest::read_params( CvFileStorage* fs )
-{
- int code = CvArrTest::read_params( fs );
- if( code < 0 )
- return code;
-
- if( ts->get_testing_mode() == CvTS::CORRECTNESS_CHECK_MODE )
- {
- max_template_size = cvReadInt( find_param( fs, "max_template_size" ), max_template_size );
- max_template_size = cvTsClipInt( max_template_size, 1, 100 );
- }
-
- return code;
-}
-
-
-int CV_TemplMatchTest::write_default_params( CvFileStorage* fs )
-{
- int code = CvArrTest::write_default_params( fs );
- if( code < 0 )
- return code;
-
- if( ts->get_testing_mode() == CvTS::CORRECTNESS_CHECK_MODE )
- {
- write_param( fs, "max_template_size", max_template_size );
- }
- else
- {
- int i;
- start_write_param( fs );
-
- cvStartWriteStruct( fs, "template_size", CV_NODE_SEQ+CV_NODE_FLOW );
- for( i = 0; templmatch_template_sizes[i].width >= 0; i++ )
- {
- cvStartWriteStruct( fs, 0, CV_NODE_SEQ+CV_NODE_FLOW );
- cvWriteInt( fs, 0, templmatch_template_sizes[i].width );
- cvWriteInt( fs, 0, templmatch_template_sizes[i].height );
- cvEndWriteStruct(fs);
- }
- cvEndWriteStruct(fs);
-
- write_string_list( fs, "method", templmatch_methods );
- }
-
- return code;
-}
-
-
-void CV_TemplMatchTest::get_minmax_bounds( int i, int j, int type, CvScalar* low, CvScalar* high )
-{
- CvArrTest::get_minmax_bounds( i, j, type, low, high );
- int depth = CV_MAT_DEPTH(type);
- if( depth == CV_32F )
- {
- *low = cvScalarAll(-10.);
- *high = cvScalarAll(10.);
- }
-}
-
-
-void CV_TemplMatchTest::get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- int depth = cvTsRandInt(rng) % 2, cn = cvTsRandInt(rng) & 1 ? 3 : 1;
- CvArrTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- depth = depth == 0 ? CV_8U : CV_32F;
-
- types[INPUT][0] = types[INPUT][1] = CV_MAKETYPE(depth,cn);
- types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_32FC1;
-
- sizes[INPUT][1].width = cvTsRandInt(rng)%MIN(sizes[INPUT][1].width,max_template_size) + 1;
- sizes[INPUT][1].height = cvTsRandInt(rng)%MIN(sizes[INPUT][1].height,max_template_size) + 1;
- sizes[OUTPUT][0].width = sizes[INPUT][0].width - sizes[INPUT][1].width + 1;
- sizes[OUTPUT][0].height = sizes[INPUT][0].height - sizes[INPUT][1].height + 1;
- sizes[REF_OUTPUT][0] = sizes[OUTPUT][0];
-
- method = cvTsRandInt(rng)%6;
- test_cpp = (cvTsRandInt(rng) & 256) == 0;
-}
-
-
-void CV_TemplMatchTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images )
-{
- CvArrTest::get_timing_test_array_types_and_sizes( test_case_idx, sizes, types,
- whole_sizes, are_images );
- const char* method_str = cvReadString( find_timing_param( "method" ), "ccorr" );
- const CvFileNode* node = find_timing_param( "template_size" );
- CvSize templ_size, result_size;
-
- assert( node && CV_NODE_IS_SEQ( node->tag ));
-
- method = strncmp( method_str, "sqdiff", 6 ) == 0 ? CV_TM_SQDIFF :
- strncmp( method_str, "ccorr", 5 ) == 0 ? CV_TM_CCORR : CV_TM_CCOEFF;
- method += strstr( method_str, "_normed" ) != 0;
-
- cvReadRawData( ts->get_file_storage(), node, &templ_size, "2i" );
-
- sizes[INPUT][1] = whole_sizes[INPUT][1] = templ_size;
- result_size.width = sizes[INPUT][0].width - templ_size.width + 1;
- result_size.height = sizes[INPUT][0].height - templ_size.height + 1;
- assert( result_size.width > 0 && result_size.height > 0 );
- sizes[OUTPUT][0] = whole_sizes[OUTPUT][0] = result_size;
-
- types[OUTPUT][0] = CV_32FC1;
-}
-
-
-void CV_TemplMatchTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- sprintf( ptr, "%s,", cvReadString( find_timing_param( "method" ), "ccorr" ) );
- ptr += strlen(ptr);
- sprintf( ptr, "templ_size=%dx%d,", test_mat[INPUT][1].width, test_mat[INPUT][1].height );
- ptr += strlen(ptr);
- params_left -= 2;
-
- CvArrTest::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-
-double CV_TemplMatchTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- if( CV_MAT_DEPTH(test_mat[INPUT][1].type) == CV_8U ||
- (method >= CV_TM_CCOEFF && test_mat[INPUT][1].cols*test_mat[INPUT][1].rows <= 2) )
- return 1e-2;
- else
- return 1e-3;
-}
-
-
-void CV_TemplMatchTest::run_func()
-{
- if(!test_cpp)
- cvMatchTemplate( test_array[INPUT][0], test_array[INPUT][1], test_array[OUTPUT][0], method );
- else
- {
- cv::Mat _out = cv::cvarrToMat(test_array[OUTPUT][0]);
- cv::matchTemplate(cv::cvarrToMat(test_array[INPUT][0]), cv::cvarrToMat(test_array[INPUT][1]), _out, method);
- }
-}
-
-
-static void cvTsMatchTemplate( const CvMat* img, const CvMat* templ, CvMat* result, int method )
-{
- int i, j, k, l;
- int depth = CV_MAT_DEPTH(img->type), cn = CV_MAT_CN(img->type);
- int width_n = templ->cols*cn, height = templ->rows;
- int a_step = img->step / CV_ELEM_SIZE(img->type & CV_MAT_DEPTH_MASK);
- int b_step = templ->step / CV_ELEM_SIZE(templ->type & CV_MAT_DEPTH_MASK);
- CvScalar b_mean, b_sdv;
- double b_denom = 1., b_sum2 = 0;
- int area = templ->rows*templ->cols;
-
- cvTsMeanStdDevNonZero( templ, 0, &b_mean, &b_sdv, 0 );
-
- for( i = 0; i < cn; i++ )
- b_sum2 += (b_sdv.val[i]*b_sdv.val[i] + b_mean.val[i]*b_mean.val[i])*area;
-
- if( CV_SQR(b_sdv.val[0]) + CV_SQR(b_sdv.val[1]) +
- CV_SQR(b_sdv.val[2]) + CV_SQR(b_sdv.val[3]) < DBL_EPSILON &&
- method == CV_TM_CCOEFF_NORMED )
- {
- cvSet( result, cvScalarAll(1.) );
- return;
- }
-
- if( method & 1 )
- {
- b_denom = 0;
- if( method != CV_TM_CCOEFF_NORMED )
- {
- b_denom = b_sum2;
- }
- else
- {
- for( i = 0; i < cn; i++ )
- b_denom += b_sdv.val[i]*b_sdv.val[i]*area;
- }
- b_denom = sqrt(b_denom);
- if( b_denom == 0 )
- b_denom = 1.;
- }
-
- assert( CV_TM_SQDIFF <= method && method <= CV_TM_CCOEFF_NORMED );
-
- for( i = 0; i < result->rows; i++ )
- {
- for( j = 0; j < result->cols; j++ )
- {
- CvScalar a_sum = {{ 0, 0, 0, 0 }}, a_sum2 = {{ 0, 0, 0, 0 }};
- CvScalar ccorr = {{ 0, 0, 0, 0 }};
- double value = 0.;
-
- if( depth == CV_8U )
- {
- const uchar* a = img->data.ptr + i*img->step + j*cn;
- const uchar* b = templ->data.ptr;
-
- if( cn == 1 || method < CV_TM_CCOEFF )
- {
- for( k = 0; k < height; k++, a += a_step, b += b_step )
- for( l = 0; l < width_n; l++ )
- {
- ccorr.val[0] += a[l]*b[l];
- a_sum.val[0] += a[l];
- a_sum2.val[0] += a[l]*a[l];
- }
- }
- else
- {
- for( k = 0; k < height; k++, a += a_step, b += b_step )
- for( l = 0; l < width_n; l += 3 )
- {
- ccorr.val[0] += a[l]*b[l];
- ccorr.val[1] += a[l+1]*b[l+1];
- ccorr.val[2] += a[l+2]*b[l+2];
- a_sum.val[0] += a[l];
- a_sum.val[1] += a[l+1];
- a_sum.val[2] += a[l+2];
- a_sum2.val[0] += a[l]*a[l];
- a_sum2.val[1] += a[l+1]*a[l+1];
- a_sum2.val[2] += a[l+2]*a[l+2];
- }
- }
- }
- else
- {
- const float* a = (const float*)(img->data.ptr + i*img->step) + j*cn;
- const float* b = (const float*)templ->data.ptr;
-
- if( cn == 1 || method < CV_TM_CCOEFF )
- {
- for( k = 0; k < height; k++, a += a_step, b += b_step )
- for( l = 0; l < width_n; l++ )
- {
- ccorr.val[0] += a[l]*b[l];
- a_sum.val[0] += a[l];
- a_sum2.val[0] += a[l]*a[l];
- }
- }
- else
- {
- for( k = 0; k < height; k++, a += a_step, b += b_step )
- for( l = 0; l < width_n; l += 3 )
- {
- ccorr.val[0] += a[l]*b[l];
- ccorr.val[1] += a[l+1]*b[l+1];
- ccorr.val[2] += a[l+2]*b[l+2];
- a_sum.val[0] += a[l];
- a_sum.val[1] += a[l+1];
- a_sum.val[2] += a[l+2];
- a_sum2.val[0] += a[l]*a[l];
- a_sum2.val[1] += a[l+1]*a[l+1];
- a_sum2.val[2] += a[l+2]*a[l+2];
- }
- }
- }
-
- switch( method )
- {
- case CV_TM_CCORR:
- case CV_TM_CCORR_NORMED:
- value = ccorr.val[0];
- break;
- case CV_TM_SQDIFF:
- case CV_TM_SQDIFF_NORMED:
- value = (a_sum2.val[0] + b_sum2 - 2*ccorr.val[0]);
- break;
- default:
- value = (ccorr.val[0] - a_sum.val[0]*b_mean.val[0]+
- ccorr.val[1] - a_sum.val[1]*b_mean.val[1]+
- ccorr.val[2] - a_sum.val[2]*b_mean.val[2]);
- }
-
- if( method & 1 )
- {
- double denom;
-
- // calc denominator
- if( method != CV_TM_CCOEFF_NORMED )
- {
- denom = a_sum2.val[0] + a_sum2.val[1] + a_sum2.val[2];
- }
- else
- {
- denom = a_sum2.val[0] - (a_sum.val[0]*a_sum.val[0])/area;
- denom += a_sum2.val[1] - (a_sum.val[1]*a_sum.val[1])/area;
- denom += a_sum2.val[2] - (a_sum.val[2]*a_sum.val[2])/area;
- }
- denom = sqrt(MAX(denom,0))*b_denom;
- if( fabs(value) < denom )
- value /= denom;
- else if( fabs(value) < denom*1.125 )
- value = value > 0 ? 1 : -1;
- else
- value = method != CV_TM_SQDIFF_NORMED ? 0 : 1;
- }
-
- ((float*)(result->data.ptr + result->step*i))[j] = (float)value;
- }
- }
-}
-
-
-void CV_TemplMatchTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- cvTsMatchTemplate( &test_mat[INPUT][0], &test_mat[INPUT][1],
- &test_mat[REF_OUTPUT][0], method );
-
- //if( ts->get_current_test_info()->test_case_idx == 0 )
- /*{
- CvFileStorage* fs = cvOpenFileStorage( "_match_template.yml", 0, CV_STORAGE_WRITE );
- cvWrite( fs, "image", &test_mat[INPUT][0] );
- cvWrite( fs, "template", &test_mat[INPUT][1] );
- cvWrite( fs, "ref", &test_mat[REF_OUTPUT][0] );
- cvWrite( fs, "opencv", &test_mat[OUTPUT][0] );
- cvWriteInt( fs, "method", method );
- cvReleaseFileStorage( &fs );
- }*/
-
- if( method >= CV_TM_CCOEFF )
- {
- // avoid numerical stability problems in singular cases (when the results are near to 0)
- const double delta = 10.;
- cvTsAdd( &test_mat[REF_OUTPUT][0], cvScalar(1.), 0, cvScalar(0.),
- cvScalar(delta), &test_mat[REF_OUTPUT][0], 0 );
- cvTsAdd( &test_mat[OUTPUT][0], cvScalar(1.), 0, cvScalar(0.),
- cvScalar(delta), &test_mat[OUTPUT][0], 0 );
- }
-}
-
-
-CV_TemplMatchTest templ_match;
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-static const char* thresh_param_names[] = { "size", "depth", "thresh_type", 0 };
-static const CvSize thresh_sizes[] = {{30,30}, {320, 240}, {720,480}, {-1,-1}};
-static const CvSize thresh_whole_sizes[] = {{320,240}, {320, 240}, {720,480}, {-1,-1}};
-static const int thresh_depths[] = { CV_8U, CV_32F, -1 };
-static const char* thresh_types[] = { "binary", "binary_inv", "trunc", "tozero", "tozero_inv", 0 };
-
-class CV_ThreshTest : public CvArrTest
-{
-public:
- CV_ThreshTest();
-
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- double get_success_error_level( int test_case_idx, int i, int j );
- void run_func();
- void prepare_to_validation( int );
-
- int write_default_params(CvFileStorage* fs);
- void get_timing_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types,
- CvSize** whole_sizes, bool *are_images );
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
-
- int thresh_type;
- float thresh_val;
- float max_val;
-};
-
-
-CV_ThreshTest::CV_ThreshTest()
- : CvArrTest( "thresh-simple", "cvThreshold", "" )
-{
- test_array[INPUT].push(NULL);
- test_array[OUTPUT].push(NULL);
- test_array[REF_OUTPUT].push(NULL);
- optional_mask = false;
- element_wise_relative_error = true;
-
- default_timing_param_names = thresh_param_names;
- depth_list = thresh_depths;
- size_list = thresh_sizes;
- whole_size_list = thresh_whole_sizes;
- cn_list = 0;
-}
-
-
-void CV_ThreshTest::get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- int depth = cvTsRandInt(rng) % 2, cn = cvTsRandInt(rng) % 4 + 1;
- CvArrTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- depth = depth == 0 ? CV_8U : CV_32F;
-
- types[INPUT][0] = types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_MAKETYPE(depth,cn);
- thresh_type = cvTsRandInt(rng) % 5;
-
- if( depth == CV_8U )
- {
- thresh_val = (float)(cvTsRandReal(rng)*350. - 50.);
- max_val = (float)(cvTsRandReal(rng)*350. - 50.);
- if( cvTsRandInt(rng)%4 == 0 )
- max_val = 255;
- }
- else
- {
- thresh_val = (float)(cvTsRandReal(rng)*1000. - 500.);
- max_val = (float)(cvTsRandReal(rng)*1000. - 500.);
- }
-}
-
-
-double CV_ThreshTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- return FLT_EPSILON*10;
-}
-
-
-void CV_ThreshTest::run_func()
-{
- cvThreshold( test_array[INPUT][0], test_array[OUTPUT][0],
- thresh_val, max_val, thresh_type );
-}
-
-
-static void cvTsThreshold( const CvMat* _src, CvMat* _dst,
- float thresh, float maxval, int thresh_type )
-{
- int i, j;
- int depth = CV_MAT_DEPTH(_src->type), cn = CV_MAT_CN(_src->type);
- int width_n = _src->cols*cn, height = _src->rows;
- int ithresh = cvFloor(thresh), ithresh2, imaxval = cvRound(maxval);
- const uchar* src = _src->data.ptr;
- uchar* dst = _dst->data.ptr;
-
- ithresh2 = CV_CAST_8U(ithresh);
- imaxval = CV_CAST_8U(imaxval);
-
- assert( depth == CV_8U || depth == CV_32F );
-
- switch( thresh_type )
- {
- case CV_THRESH_BINARY:
- for( i = 0; i < height; i++, src += _src->step, dst += _dst->step )
- {
- if( depth == CV_8U )
- for( j = 0; j < width_n; j++ )
- dst[j] = (uchar)(src[j] > ithresh ? imaxval : 0);
- else
- for( j = 0; j < width_n; j++ )
- ((float*)dst)[j] = ((const float*)src)[j] > thresh ? maxval : 0.f;
- }
- break;
- case CV_THRESH_BINARY_INV:
- for( i = 0; i < height; i++, src += _src->step, dst += _dst->step )
- {
- if( depth == CV_8U )
- for( j = 0; j < width_n; j++ )
- dst[j] = (uchar)(src[j] > ithresh ? 0 : imaxval);
- else
- for( j = 0; j < width_n; j++ )
- ((float*)dst)[j] = ((const float*)src)[j] > thresh ? 0.f : maxval;
- }
- break;
- case CV_THRESH_TRUNC:
- for( i = 0; i < height; i++, src += _src->step, dst += _dst->step )
- {
- if( depth == CV_8U )
- for( j = 0; j < width_n; j++ )
- {
- int s = src[j];
- dst[j] = (uchar)(s > ithresh ? ithresh2 : s);
- }
- else
- for( j = 0; j < width_n; j++ )
- {
- float s = ((const float*)src)[j];
- ((float*)dst)[j] = s > thresh ? thresh : s;
- }
- }
- break;
- case CV_THRESH_TOZERO:
- for( i = 0; i < height; i++, src += _src->step, dst += _dst->step )
- {
- if( depth == CV_8U )
- for( j = 0; j < width_n; j++ )
- {
- int s = src[j];
- dst[j] = (uchar)(s > ithresh ? s : 0);
- }
- else
- for( j = 0; j < width_n; j++ )
- {
- float s = ((const float*)src)[j];
- ((float*)dst)[j] = s > thresh ? s : 0.f;
- }
- }
- break;
- case CV_THRESH_TOZERO_INV:
- for( i = 0; i < height; i++, src += _src->step, dst += _dst->step )
- {
- if( depth == CV_8U )
- for( j = 0; j < width_n; j++ )
- {
- int s = src[j];
- dst[j] = (uchar)(s > ithresh ? 0 : s);
- }
- else
- for( j = 0; j < width_n; j++ )
- {
- float s = ((const float*)src)[j];
- ((float*)dst)[j] = s > thresh ? 0.f : s;
- }
- }
- break;
- default:
- assert(0);
- }
-}
-
-
-void CV_ThreshTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- cvTsThreshold( &test_mat[INPUT][0], &test_mat[REF_OUTPUT][0],
- thresh_val, max_val, thresh_type );
-}
-
-
-int CV_ThreshTest::write_default_params( CvFileStorage* fs )
-{
- int code = CvArrTest::write_default_params( fs );
- if( code < 0 )
- return code;
-
- if( ts->get_testing_mode() == CvTS::TIMING_MODE )
- {
- start_write_param( fs );
- write_string_list( fs, "thresh_type", thresh_types );
- }
-
- return code;
-}
-
-
-void CV_ThreshTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images )
-{
- CvArrTest::get_timing_test_array_types_and_sizes( test_case_idx, sizes, types,
- whole_sizes, are_images );
- const char* thresh_str = cvReadString( find_timing_param( "thresh_type" ), "binary" );
- thresh_type = strcmp( thresh_str, "binary" ) == 0 ? CV_THRESH_BINARY :
- strcmp( thresh_str, "binary_inv" ) == 0 ? CV_THRESH_BINARY_INV :
- strcmp( thresh_str, "trunc" ) == 0 ? CV_THRESH_TRUNC :
- strcmp( thresh_str, "tozero" ) == 0 ? CV_THRESH_TOZERO :
- CV_THRESH_TOZERO_INV;
-
- if( CV_MAT_DEPTH(types[INPUT][0]) == CV_8U )
- {
- thresh_val = 128;
- max_val = 255;
- }
- else
- {
- thresh_val = 500.;
- max_val = 1.;
- }
-}
-
-
-void CV_ThreshTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- sprintf( ptr, "%s,", cvReadString( find_timing_param( "thresh_type" ), "binary" ) );
- ptr += strlen(ptr);
- params_left--;
-
- CvArrTest::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-
-CV_ThreshTest thresh_test;
-
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
-// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of the copyright holders may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-
-class CV_DefaultNewCameraMatrixTest : public CvArrTest
-{
-public:
- CV_DefaultNewCameraMatrixTest();
-protected:
- int prepare_test_case (int test_case_idx);
- void prepare_to_validation( int test_case_idx );
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void run_func();
-
-private:
- cv::Size img_size;
- cv::Mat camera_mat;
- cv::Mat new_camera_mat;
-
- int matrix_type;
-
- bool center_principal_point;
-
- static const int MAX_X = 2048;
- static const int MAX_Y = 2048;
- static const int MAX_VAL = 10000;
-};
-
-CV_DefaultNewCameraMatrixTest::CV_DefaultNewCameraMatrixTest() : CvArrTest("undistort-getDefaultNewCameraMatrix","getDefaultNewCameraMatrix")
-{
- test_array[INPUT].push(NULL);
- test_array[OUTPUT].push(NULL);
- test_array[REF_OUTPUT].push(NULL);
-}
-
-void CV_DefaultNewCameraMatrixTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CvArrTest::get_test_array_types_and_sizes(test_case_idx,sizes,types);
- CvRNG* rng = ts->get_rng();
- matrix_type = types[INPUT][0] = types[OUTPUT][0]= types[REF_OUTPUT][0] = cvTsRandInt(rng)%2 ? CV_64F : CV_32F;
- sizes[INPUT][0] = sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = cvSize(3,3);
-}
-
-int CV_DefaultNewCameraMatrixTest::prepare_test_case(int test_case_idx)
-{
- int code = CvArrTest::prepare_test_case( test_case_idx );
-
- if (code <= 0)
- return code;
-
- CvRNG* rng = ts->get_rng();
-
- img_size.width = cvTsRandInt(rng) % MAX_X + 1;
- img_size.height = cvTsRandInt(rng) % MAX_Y + 1;
-
- center_principal_point = ((cvTsRandInt(rng) % 2)!=0);
-
- // Generating camera_mat matrix
- double sz = MAX(img_size.width, img_size.height);
- double aspect_ratio = cvTsRandReal(rng)*0.6 + 0.7;
- double a[9] = {0,0,0,0,0,0,0,0,1};
- CvMat _a = cvMat(3,3,CV_64F,a);
- a[2] = (img_size.width - 1)*0.5 + cvTsRandReal(rng)*10 - 5;
- a[5] = (img_size.height - 1)*0.5 + cvTsRandReal(rng)*10 - 5;
- a[0] = sz/(0.9 - cvTsRandReal(rng)*0.6);
- a[4] = aspect_ratio*a[0];
-
- //Copying into input array
- CvMat* _a0 = &test_mat[INPUT][0];
- cvTsConvert( &_a, _a0 );
- camera_mat = _a0;
- //new_camera_mat = camera_mat;
-
- return code;
-
-}
-
-void CV_DefaultNewCameraMatrixTest::run_func()
-{
- new_camera_mat = cv::getDefaultNewCameraMatrix(camera_mat,img_size,center_principal_point);
-}
-
-void CV_DefaultNewCameraMatrixTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- const CvMat* src = &test_mat[INPUT][0];
- CvMat* dst = &test_mat[REF_OUTPUT][0];
- CvMat* test_output = &test_mat[OUTPUT][0];
- CvMat output = new_camera_mat;
- cvTsConvert( &output, test_output );
- if (!center_principal_point)
- {
- cvCopy(src,dst);
- }
- else
- {
- double a[9] = {0,0,0,0,0,0,0,0,1};
- CvMat _a = cvMat(3,3,CV_64F,a);
- if (matrix_type == CV_64F)
- {
- a[0] = ((double*)(src->data.ptr + src->step*0))[0];
- a[4] = ((double*)(src->data.ptr + src->step*1))[1];
- }
- else
- {
- a[0] = (double)((float*)(src->data.ptr + src->step*0))[0];
- a[4] = (double)((float*)(src->data.ptr + src->step*1))[1];
- }
- a[2] = (img_size.width - 1)*0.5;
- a[5] = (img_size.height - 1)*0.5;
- cvTsConvert( &_a, dst );
- }
-}
-
-CV_DefaultNewCameraMatrixTest default_new_camera_matrix_test;
-
-//---------
-
-class CV_UndistortPointsTest : public CvArrTest
-{
-public:
- CV_UndistortPointsTest();
-protected:
- int prepare_test_case (int test_case_idx);
- void prepare_to_validation( int test_case_idx );
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- double get_success_error_level( int test_case_idx, int i, int j );
- void run_func();
- void cvTsDistortPoints(const CvMat* _src, CvMat* _dst, const CvMat* _cameraMatrix,
- const CvMat* _distCoeffs,
- const CvMat* matR, const CvMat* matP);
-
-private:
- bool useCPlus;
- bool useDstMat;
- static const int N_POINTS = 10;
- static const int MAX_X = 2048;
- static const int MAX_Y = 2048;
-
- bool zero_new_cam;
- bool zero_distortion;
- bool zero_R;
-
- cv::Size img_size;
- cv::Mat dst_points_mat;
-
- cv::Mat camera_mat;
- cv::Mat R;
- cv::Mat P;
- cv::Mat distortion_coeffs;
- cv::Mat src_points;
- std::vector<cv::Point2f> dst_points;
-};
-
-CV_UndistortPointsTest::CV_UndistortPointsTest() : CvArrTest("undistort-points","cvUndistortPoints")
-{
- test_array[INPUT].push(NULL); // points matrix
- test_array[INPUT].push(NULL); // camera matrix
- test_array[INPUT].push(NULL); // distortion coeffs
- test_array[INPUT].push(NULL); // R matrix
- test_array[INPUT].push(NULL); // P matrix
- test_array[OUTPUT].push(NULL); // distorted dst points
- test_array[TEMP].push(NULL); // dst points
- test_array[REF_OUTPUT].push(NULL);
-}
-
-void CV_UndistortPointsTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CvArrTest::get_test_array_types_and_sizes(test_case_idx,sizes,types);
- CvRNG* rng = ts->get_rng();
- useCPlus = ((cvTsRandInt(rng) % 2)!=0);
- //useCPlus = 0;
- if (useCPlus)
- {
- types[INPUT][0] = types[OUTPUT][0] = types[REF_OUTPUT][0] = types[TEMP][0]= CV_32FC2;
- }
- else
- {
- types[INPUT][0] = types[OUTPUT][0] = types[REF_OUTPUT][0] = types[TEMP][0]= cvTsRandInt(rng)%2 ? CV_64FC2 : CV_32FC2;
- }
- types[INPUT][1] = cvTsRandInt(rng)%2 ? CV_64F : CV_32F;
- types[INPUT][2] = cvTsRandInt(rng)%2 ? CV_64F : CV_32F;
- types[INPUT][3] = cvTsRandInt(rng)%2 ? CV_64F : CV_32F;
- types[INPUT][4] = cvTsRandInt(rng)%2 ? CV_64F : CV_32F;
-
- sizes[INPUT][0] = sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = sizes[TEMP][0]= cvTsRandInt(rng)%2 ? cvSize(1,N_POINTS) : cvSize(N_POINTS,1);
- sizes[INPUT][1] = sizes[INPUT][3] = cvSize(3,3);
- sizes[INPUT][4] = cvTsRandInt(rng)%2 ? cvSize(3,3) : cvSize(4,3);
-
- if (cvTsRandInt(rng)%2)
- {
- if (cvTsRandInt(rng)%2)
- {
- sizes[INPUT][2] = cvSize(1,4);
- }
- else
- {
- sizes[INPUT][2] = cvSize(1,5);
- }
- }
- else
- {
- if (cvTsRandInt(rng)%2)
- {
- sizes[INPUT][2] = cvSize(4,1);
- }
- else
- {
- sizes[INPUT][2] = cvSize(5,1);
- }
- }
-}
-
-int CV_UndistortPointsTest::prepare_test_case(int test_case_idx)
-{
- CvRNG* rng = ts->get_rng();
- int code = CvArrTest::prepare_test_case( test_case_idx );
-
- if (code <= 0)
- return code;
-
- useDstMat = (cvTsRandInt(rng) % 2) == 0;
-
- img_size.width = cvTsRandInt(rng) % MAX_X + 1;
- img_size.height = cvTsRandInt(rng) % MAX_Y + 1;
- int dist_size = test_mat[INPUT][2].cols > test_mat[INPUT][2].rows ? test_mat[INPUT][2].cols : test_mat[INPUT][2].rows;
- double cam[9] = {0,0,0,0,0,0,0,0,1};
- double* dist = new double[dist_size ];
- double* proj = new double[test_mat[INPUT][4].cols * test_mat[INPUT][4].rows];
- double* points = new double[N_POINTS*2];
-
- CvMat _camera = cvMat(3,3,CV_64F,cam);
- CvMat _distort = cvMat(test_mat[INPUT][2].rows,test_mat[INPUT][2].cols,CV_64F,dist);
- CvMat _proj = cvMat(test_mat[INPUT][4].rows,test_mat[INPUT][4].cols,CV_64F,proj);
- CvMat _points= cvMat(test_mat[INPUT][0].rows,test_mat[INPUT][0].cols,CV_64FC2, points);
-
- for (int i=0;i<test_mat[INPUT][4].cols * test_mat[INPUT][4].rows;i++)
- {
- proj[i] = 0;
- }
-
- //Generating points
- for (int i=0;i<N_POINTS;i++)
- {
- points[2*i] = cvTsRandReal(rng)*img_size.width;
- points[2*i+1] = cvTsRandReal(rng)*img_size.height;
- }
-
-
-
- //Generating camera matrix
- double sz = MAX(img_size.width,img_size.height);
- double aspect_ratio = cvTsRandReal(rng)*0.6 + 0.7;
- cam[2] = (img_size.width - 1)*0.5 + cvTsRandReal(rng)*10 - 5;
- cam[5] = (img_size.height - 1)*0.5 + cvTsRandReal(rng)*10 - 5;
- cam[0] = sz/(0.9 - cvTsRandReal(rng)*0.6);
- cam[4] = aspect_ratio*cam[0];
-
- //Generating distortion coeffs
- dist[0] = cvTsRandReal(rng)*0.06 - 0.03;
- dist[1] = cvTsRandReal(rng)*0.06 - 0.03;
- if( dist[0]*dist[1] > 0 )
- dist[1] = -dist[1];
- if( cvTsRandInt(rng)%4 != 0 )
- {
- dist[2] = cvTsRandReal(rng)*0.004 - 0.002;
- dist[3] = cvTsRandReal(rng)*0.004 - 0.002;
- if (dist_size > 4)
- dist[4] = cvTsRandReal(rng)*0.004 - 0.002;
- }
- else
- {
- dist[2] = dist[3] = 0;
- if (dist_size > 4)
- dist[4] = 0;
- }
-
- //Generating P matrix (projection)
- if ( test_mat[INPUT][4].cols != 4)
- {
- proj[8] = 1;
- if (cvTsRandInt(rng)%2 == 0) // use identity new camera matrix
- {
- proj[0] = 1;
- proj[4] = 1;
- }
- else
- {
- proj[0] = cam[0] + (cvTsRandReal(rng) - (double)0.5)*0.2*cam[0]; //10%
- proj[4] = cam[4] + (cvTsRandReal(rng) - (double)0.5)*0.2*cam[4]; //10%
- proj[2] = cam[2] + (cvTsRandReal(rng) - (double)0.5)*0.3*img_size.width; //15%
- proj[5] = cam[5] + (cvTsRandReal(rng) - (double)0.5)*0.3*img_size.height; //15%
- }
- }
- else
- {
- proj[10] = 1;
- proj[0] = cam[0] + (cvTsRandReal(rng) - (double)0.5)*0.2*cam[0]; //10%
- proj[5] = cam[4] + (cvTsRandReal(rng) - (double)0.5)*0.2*cam[4]; //10%
- proj[2] = cam[2] + (cvTsRandReal(rng) - (double)0.5)*0.3*img_size.width; //15%
- proj[6] = cam[5] + (cvTsRandReal(rng) - (double)0.5)*0.3*img_size.height; //15%
-
- proj[3] = (img_size.height + img_size.width - 1)*0.5 + cvTsRandReal(rng)*10 - 5;
- proj[7] = (img_size.height + img_size.width - 1)*0.5 + cvTsRandReal(rng)*10 - 5;
- proj[11] = (img_size.height + img_size.width - 1)*0.5 + cvTsRandReal(rng)*10 - 5;
- }
-
- //Generating R matrix
- CvMat* _rot = cvCreateMat(3,3,CV_64F);
- CvMat* rotation = cvCreateMat(1,3,CV_64F);
- rotation->data.db[0] = CV_PI*(cvTsRandReal(rng) - (double)0.5); // phi
- rotation->data.db[1] = CV_PI*(cvTsRandReal(rng) - (double)0.5); // ksi
- rotation->data.db[2] = CV_PI*(cvTsRandReal(rng) - (double)0.5); //khi
- cvRodrigues2(rotation,_rot);
- cvReleaseMat(&rotation);
-
- //copying data
- //src_points = &_points;
- CvMat* dst = &test_mat[INPUT][0];
- cvTsConvert( &_points, dst);
- dst = &test_mat[INPUT][1];
- cvTsConvert( &_camera, dst);
- dst = &test_mat[INPUT][2];
- cvTsConvert( &_distort, dst);
- dst = &test_mat[INPUT][3];
- cvTsConvert( _rot, dst);
- dst = &test_mat[INPUT][4];
- cvTsConvert( &_proj, dst);
-
- zero_distortion = (cvRandInt(rng)%2) == 0 ? false : true;
- zero_new_cam = (cvRandInt(rng)%2) == 0 ? false : true;
- zero_R = (cvRandInt(rng)%2) == 0 ? false : true;
-
-
- cvReleaseMat(&_rot);
-
- if (useCPlus)
- {
- CvMat* temp = cvCreateMat(test_mat[INPUT][0].rows,test_mat[INPUT][0].cols,CV_32FC2);
- for (int i=0;i<test_mat[INPUT][0].rows*test_mat[INPUT][0].cols*2;i++)
- temp->data.fl[i] = (float)_points.data.db[i];
-
-
- src_points = cv::Mat(temp,true);
-
- cvReleaseMat(&temp);
-
- camera_mat = &test_mat[INPUT][1];
- distortion_coeffs = &test_mat[INPUT][2];
- R = &test_mat[INPUT][3];
- P = &test_mat[INPUT][4];
- }
- delete[] dist;
- delete[] proj;
- delete[] points;
-
- return code;
-}
-
-void CV_UndistortPointsTest::prepare_to_validation(int /*test_case_idx*/)
-{
- int dist_size = test_mat[INPUT][2].cols > test_mat[INPUT][2].rows ? test_mat[INPUT][2].cols : test_mat[INPUT][2].rows;
- double cam[9] = {0,0,0,0,0,0,0,0,1};
- double rot[9] = {1,0,0,0,1,0,0,0,1};
- double* dist = new double[dist_size ];
- double* proj = new double[test_mat[INPUT][4].cols * test_mat[INPUT][4].rows];
- double* points = new double[N_POINTS*2];
- double* r_points = new double[N_POINTS*2];
- //Run reference calculations
- CvMat ref_points= cvMat(test_mat[INPUT][0].rows,test_mat[INPUT][0].cols,CV_64FC2,r_points);
- CvMat _camera = cvMat(3,3,CV_64F,cam);
- CvMat _rot = cvMat(3,3,CV_64F,rot);
- CvMat _distort = cvMat(test_mat[INPUT][2].rows,test_mat[INPUT][2].cols,CV_64F,dist);
- CvMat _proj = cvMat(test_mat[INPUT][4].rows,test_mat[INPUT][4].cols,CV_64F,proj);
- CvMat _points= cvMat(test_mat[TEMP][0].rows,test_mat[TEMP][0].cols,CV_64FC2,points);
-
-
- cvTsConvert(&test_mat[INPUT][1],&_camera);
- cvTsConvert(&test_mat[INPUT][2],&_distort);
- cvTsConvert(&test_mat[INPUT][3],&_rot);
- cvTsConvert(&test_mat[INPUT][4],&_proj);
-
- if (useCPlus)
- {
- if (useDstMat)
- {
- CvMat temp = dst_points_mat;
- for (int i=0;i<N_POINTS*2;i++)
- {
- points[i] = temp.data.fl[i];
- }
- }
-
- else
- {
-
- for (int i=0;i<N_POINTS;i++)
- {
- points[2*i] = dst_points[i].x;
- points[2*i+1] = dst_points[i].y;
- }
- }
- }
- else
- {
- cvTsConvert(&test_mat[TEMP][0],&_points);
- }
-
- CvMat* input2;
- CvMat* input3;
- CvMat* input4;
- input2 = zero_distortion ? 0 : &_distort;
- input3 = zero_R ? 0 : &_rot;
- input4 = zero_new_cam ? 0 : &_proj;
- cvTsDistortPoints(&_points,&ref_points,&_camera,input2,input3,input4);
-
- CvMat* dst = &test_mat[REF_OUTPUT][0];
- cvTsConvert(&ref_points,dst);
-
- cvCopy(&test_mat[INPUT][0],&test_mat[OUTPUT][0]);
-
- delete[] dist;
- delete[] proj;
- delete[] points;
- delete[] r_points;
-}
-
-void CV_UndistortPointsTest::run_func()
-{
-
- if (useCPlus)
- {
- cv::Mat input2,input3,input4;
- input2 = zero_distortion ? cv::Mat() : cv::Mat(&test_mat[INPUT][2]);
- input3 = zero_R ? cv::Mat() : cv::Mat(&test_mat[INPUT][3]);
- input4 = zero_new_cam ? cv::Mat() : cv::Mat(&test_mat[INPUT][4]);
-
- if (useDstMat)
- {
- //cv::undistortPoints(src_points,dst_points_mat,camera_mat,distortion_coeffs,R,P);
- cv::undistortPoints(src_points,dst_points_mat,camera_mat,input2,input3,input4);
- }
- else
- {
- //cv::undistortPoints(src_points,dst_points,camera_mat,distortion_coeffs,R,P);
- cv::undistortPoints(src_points,dst_points,camera_mat,input2,input3,input4);
- }
- }
- else
- {
- CvMat* input2;
- CvMat* input3;
- CvMat* input4;
- input2 = zero_distortion ? 0 : &test_mat[INPUT][2];
- input3 = zero_R ? 0 : &test_mat[INPUT][3];
- input4 = zero_new_cam ? 0 : &test_mat[INPUT][4];
- cvUndistortPoints(&test_mat[INPUT][0],&test_mat[TEMP][0],&test_mat[INPUT][1],input2,input3,input4);
- }
-
-}
-
-void CV_UndistortPointsTest::cvTsDistortPoints(const CvMat* _src, CvMat* _dst, const CvMat* _cameraMatrix,
- const CvMat* _distCoeffs,
- const CvMat* matR, const CvMat* matP)
-{
- double a[9];
-
- CvMat* __P;
- if ((!matP)||(matP->cols == 3))
- __P = cvCreateMat(3,3,CV_64F);
- else
- __P = cvCreateMat(3,4,CV_64F);
- if (matP)
- {
- cvTsConvert(matP,__P);
- }
- else
- {
- cvZero(__P);
- __P->data.db[0] = 1;
- __P->data.db[4] = 1;
- __P->data.db[8] = 1;
- }
- CvMat* __R = cvCreateMat(3,3,CV_64F);;
- if (matR)
- {
- cvCopy(matR,__R);
- }
- else
- {
- cvZero(__R);
- __R->data.db[0] = 1;
- __R->data.db[4] = 1;
- __R->data.db[8] = 1;
- }
- for (int i=0;i<N_POINTS;i++)
- {
- int movement = __P->cols > 3 ? 1 : 0;
- double x = (_src->data.db[2*i]-__P->data.db[2])/__P->data.db[0];
- double y = (_src->data.db[2*i+1]-__P->data.db[5+movement])/__P->data.db[4+movement];
- CvMat inverse = cvMat(3,3,CV_64F,a);
- cvInvert(__R,&inverse);
- double w1 = x*inverse.data.db[6]+y*inverse.data.db[7]+inverse.data.db[8];
- double _x = (x*inverse.data.db[0]+y*inverse.data.db[1]+inverse.data.db[2])/w1;
- double _y = (x*inverse.data.db[3]+y*inverse.data.db[4]+inverse.data.db[5])/w1;
-
- //Distortions
-
- double __x = _x;
- double __y = _y;
- if (_distCoeffs)
- {
- double r2 = _x*_x+_y*_y;
-
- __x = _x*(1+_distCoeffs->data.db[0]*r2+_distCoeffs->data.db[1]*r2*r2)+
- 2*_distCoeffs->data.db[2]*_x*_y+_distCoeffs->data.db[3]*(r2+2*_x*_x);
- __y = _y*(1+_distCoeffs->data.db[0]*r2+_distCoeffs->data.db[1]*r2*r2)+
- 2*_distCoeffs->data.db[3]*_x*_y+_distCoeffs->data.db[2]*(r2+2*_y*_y);
- if ((_distCoeffs->cols > 4) || (_distCoeffs->rows > 4))
- {
- __x+=_x*_distCoeffs->data.db[4]*r2*r2*r2;
- __y+=_y*_distCoeffs->data.db[4]*r2*r2*r2;
- }
- }
-
-
- _dst->data.db[2*i] = __x*_cameraMatrix->data.db[0]+_cameraMatrix->data.db[2];
- _dst->data.db[2*i+1] = __y*_cameraMatrix->data.db[4]+_cameraMatrix->data.db[5];
-
- }
-
- cvReleaseMat(&__R);
- cvReleaseMat(&__P);
-
-}
-
-double CV_UndistortPointsTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- return 5e-2;
-}
-
-CV_UndistortPointsTest undistort_points_test;
-
-//------------------------------------------------------
-
-class CV_InitUndistortRectifyMapTest : public CvArrTest
-{
-public:
- CV_InitUndistortRectifyMapTest();
-protected:
- int prepare_test_case (int test_case_idx);
- void prepare_to_validation( int test_case_idx );
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- double get_success_error_level( int test_case_idx, int i, int j );
- void run_func();
-
-private:
- bool useCPlus;
- static const int N_POINTS = 100;
- static const int MAX_X = 2048;
- static const int MAX_Y = 2048;
- bool zero_new_cam;
- bool zero_distortion;
- bool zero_R;
-
-
- cv::Size img_size;
-
- cv::Mat camera_mat;
- cv::Mat R;
- cv::Mat new_camera_mat;
- cv::Mat distortion_coeffs;
- cv::Mat mapx;
- cv::Mat mapy;
- CvMat* _mapx;
- CvMat* _mapy;
- int mat_type;
-};
-
-CV_InitUndistortRectifyMapTest::CV_InitUndistortRectifyMapTest() : CvArrTest("undistort-undistort_rectify_map","cvInitUndistortRectifyMap")
-{
- test_array[INPUT].push(NULL); // test points matrix
- test_array[INPUT].push(NULL); // camera matrix
- test_array[INPUT].push(NULL); // distortion coeffs
- test_array[INPUT].push(NULL); // R matrix
- test_array[INPUT].push(NULL); // new camera matrix
- test_array[OUTPUT].push(NULL); // distorted dst points
- test_array[REF_OUTPUT].push(NULL);
-}
-
-void CV_InitUndistortRectifyMapTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CvArrTest::get_test_array_types_and_sizes(test_case_idx,sizes,types);
- CvRNG* rng = ts->get_rng();
- useCPlus = ((cvTsRandInt(rng) % 2)!=0);
- //useCPlus = 0;
- types[INPUT][0] = types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_64FC2;
-
- types[INPUT][1] = cvTsRandInt(rng)%2 ? CV_64F : CV_32F;
- types[INPUT][2] = cvTsRandInt(rng)%2 ? CV_64F : CV_32F;
- types[INPUT][3] = cvTsRandInt(rng)%2 ? CV_64F : CV_32F;
- types[INPUT][4] = cvTsRandInt(rng)%2 ? CV_64F : CV_32F;
-
- sizes[INPUT][0] = sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = cvSize(N_POINTS,1);
- sizes[INPUT][1] = sizes[INPUT][3] = cvSize(3,3);
- sizes[INPUT][4] = cvSize(3,3);
-
- if (cvTsRandInt(rng)%2)
- {
- if (cvTsRandInt(rng)%2)
- {
- sizes[INPUT][2] = cvSize(1,4);
- }
- else
- {
- sizes[INPUT][2] = cvSize(1,5);
- }
- }
- else
- {
- if (cvTsRandInt(rng)%2)
- {
- sizes[INPUT][2] = cvSize(4,1);
- }
- else
- {
- sizes[INPUT][2] = cvSize(5,1);
- }
- }
-}
-
-int CV_InitUndistortRectifyMapTest::prepare_test_case(int test_case_idx)
-{
- CvRNG* rng = ts->get_rng();
- int code = CvArrTest::prepare_test_case( test_case_idx );
-
- if (code <= 0)
- return code;
-
- img_size.width = cvTsRandInt(rng) % MAX_X + 1;
- img_size.height = cvTsRandInt(rng) % MAX_Y + 1;
-
- if (useCPlus)
- {
- mat_type = (cvTsRandInt(rng) % 2) == 0 ? CV_32FC1 : CV_16SC2;
- if ((cvTsRandInt(rng) % 4) == 0)
- mat_type = -1;
- if ((cvTsRandInt(rng) % 4) == 0)
- mat_type = CV_32FC2;
- _mapx = 0;
- _mapy = 0;
- }
- else
- {
- int typex = (cvTsRandInt(rng) % 2) == 0 ? CV_32FC1 : CV_16SC2;
- //typex = CV_32FC1; ///!!!!!!!!!!!!!!!!
- int typey = (typex == CV_32FC1) ? CV_32FC1 : CV_16UC1;
-
- _mapx = cvCreateMat(img_size.height,img_size.width,typex);
- _mapy = cvCreateMat(img_size.height,img_size.width,typey);
-
-
- }
-
- int dist_size = test_mat[INPUT][2].cols > test_mat[INPUT][2].rows ? test_mat[INPUT][2].cols : test_mat[INPUT][2].rows;
- double cam[9] = {0,0,0,0,0,0,0,0,1};
- double* dist = new double[dist_size ];
- double* new_cam = new double[test_mat[INPUT][4].cols * test_mat[INPUT][4].rows];
- double* points = new double[N_POINTS*2];
-
- CvMat _camera = cvMat(3,3,CV_64F,cam);
- CvMat _distort = cvMat(test_mat[INPUT][2].rows,test_mat[INPUT][2].cols,CV_64F,dist);
- CvMat _new_cam = cvMat(test_mat[INPUT][4].rows,test_mat[INPUT][4].cols,CV_64F,new_cam);
- CvMat _points= cvMat(test_mat[INPUT][0].rows,test_mat[INPUT][0].cols,CV_64FC2, points);
-
- for (int i=0;i<test_mat[INPUT][4].cols * test_mat[INPUT][4].rows;i++)
- {
- new_cam[i] = 0;
- }
-
- //Generating points
- for (int i=0;i<N_POINTS;i++)
- {
- points[2*i] = cvTsRandReal(rng)*img_size.width;
- points[2*i+1] = cvTsRandReal(rng)*img_size.height;
- }
-
-
-
- //Generating camera matrix
- double sz = MAX(img_size.width,img_size.height);
- double aspect_ratio = cvTsRandReal(rng)*0.6 + 0.7;
- cam[2] = (img_size.width - 1)*0.5 + cvTsRandReal(rng)*10 - 5;
- cam[5] = (img_size.height - 1)*0.5 + cvTsRandReal(rng)*10 - 5;
- cam[0] = sz/(0.9 - cvTsRandReal(rng)*0.6);
- cam[4] = aspect_ratio*cam[0];
-
- //Generating distortion coeffs
- dist[0] = cvTsRandReal(rng)*0.06 - 0.03;
- dist[1] = cvTsRandReal(rng)*0.06 - 0.03;
- if( dist[0]*dist[1] > 0 )
- dist[1] = -dist[1];
- if( cvTsRandInt(rng)%4 != 0 )
- {
- dist[2] = cvTsRandReal(rng)*0.004 - 0.002;
- dist[3] = cvTsRandReal(rng)*0.004 - 0.002;
- if (dist_size > 4)
- dist[4] = cvTsRandReal(rng)*0.004 - 0.002;
- }
- else
- {
- dist[2] = dist[3] = 0;
- if (dist_size > 4)
- dist[4] = 0;
- }
-
- //Generating new camera matrix
-
- new_cam[8] = 1;
-
- //new_cam[0] = cam[0];
- //new_cam[4] = cam[4];
- //new_cam[2] = cam[2];
- //new_cam[5] = cam[5];
-
- new_cam[0] = cam[0] + (cvTsRandReal(rng) - (double)0.5)*0.2*cam[0]; //10%
- new_cam[4] = cam[4] + (cvTsRandReal(rng) - (double)0.5)*0.2*cam[4]; //10%
- new_cam[2] = cam[2] + (cvTsRandReal(rng) - (double)0.5)*0.3*img_size.width; //15%
- new_cam[5] = cam[5] + (cvTsRandReal(rng) - (double)0.5)*0.3*img_size.height; //15%
-
-
- //Generating R matrix
- CvMat* _rot = cvCreateMat(3,3,CV_64F);
- CvMat* rotation = cvCreateMat(1,3,CV_64F);
- rotation->data.db[0] = CV_PI/8*(cvTsRandReal(rng) - (double)0.5); // phi
- rotation->data.db[1] = CV_PI/8*(cvTsRandReal(rng) - (double)0.5); // ksi
- rotation->data.db[2] = CV_PI/3*(cvTsRandReal(rng) - (double)0.5); //khi
- cvRodrigues2(rotation,_rot);
- cvReleaseMat(&rotation);
-
- //cvSetIdentity(_rot);
- //copying data
- CvMat* dst = &test_mat[INPUT][0];
- cvTsConvert( &_points, dst);
- dst = &test_mat[INPUT][1];
- cvTsConvert( &_camera, dst);
- dst = &test_mat[INPUT][2];
- cvTsConvert( &_distort, dst);
- dst = &test_mat[INPUT][3];
- cvTsConvert( _rot, dst);
- dst = &test_mat[INPUT][4];
- cvTsConvert( &_new_cam, dst);
-
- zero_distortion = (cvRandInt(rng)%2) == 0 ? false : true;
- zero_new_cam = (cvRandInt(rng)%2) == 0 ? false : true;
- zero_R = (cvRandInt(rng)%2) == 0 ? false : true;
-
- cvReleaseMat(&_rot);
-
- if (useCPlus)
- {
- camera_mat = &test_mat[INPUT][1];
- distortion_coeffs = &test_mat[INPUT][2];
- R = &test_mat[INPUT][3];
- new_camera_mat = &test_mat[INPUT][4];
- }
- delete[] dist;
- delete[] new_cam;
- delete[] points;
-
- return code;
-}
-
-void CV_InitUndistortRectifyMapTest::prepare_to_validation(int/* test_case_idx*/)
-{
- int dist_size = test_mat[INPUT][2].cols > test_mat[INPUT][2].rows ? test_mat[INPUT][2].cols : test_mat[INPUT][2].rows;
- double cam[9] = {0,0,0,0,0,0,0,0,1};
- double rot[9] = {1,0,0,0,1,0,0,0,1};
- double* dist = new double[dist_size ];
- double* new_cam = new double[test_mat[INPUT][4].cols * test_mat[INPUT][4].rows];
- double* points = new double[N_POINTS*2];
- double* r_points = new double[N_POINTS*2];
- //Run reference calculations
- CvMat ref_points= cvMat(test_mat[INPUT][0].rows,test_mat[INPUT][0].cols,CV_64FC2,r_points);
- CvMat _camera = cvMat(3,3,CV_64F,cam);
- CvMat _rot = cvMat(3,3,CV_64F,rot);
- CvMat _distort = cvMat(test_mat[INPUT][2].rows,test_mat[INPUT][2].cols,CV_64F,dist);
- CvMat _new_cam = cvMat(test_mat[INPUT][4].rows,test_mat[INPUT][4].cols,CV_64F,new_cam);
- CvMat _points= cvMat(test_mat[INPUT][0].rows,test_mat[INPUT][0].cols,CV_64FC2,points);
-
- cvTsConvert(&test_mat[INPUT][1],&_camera);
- cvTsConvert(&test_mat[INPUT][2],&_distort);
- cvTsConvert(&test_mat[INPUT][3],&_rot);
- cvTsConvert(&test_mat[INPUT][4],&_new_cam);
-
- //Applying precalculated undistort rectify map
- if (!useCPlus)
- {
- mapx = cv::Mat(_mapx);
- mapy = cv::Mat(_mapy);
- }
- cv::Mat map1,map2;
- cv::convertMaps(mapx,mapy,map1,map2,CV_32FC1);
- CvMat _map1 = map1;
- CvMat _map2 = map2;
- for (int i=0;i<N_POINTS;i++)
- {
- double u = test_mat[INPUT][0].data.db[2*i];
- double v = test_mat[INPUT][0].data.db[2*i+1];
- _points.data.db[2*i] = (double)_map1.data.fl[(int)v*_map1.cols+(int)u];
- _points.data.db[2*i+1] = (double)_map2.data.fl[(int)v*_map2.cols+(int)u];
- }
-
- //---
-
- cvUndistortPoints(&_points,&ref_points,&_camera,
- zero_distortion ? 0 : &_distort, zero_R ? 0 : &_rot, zero_new_cam ? &_camera : &_new_cam);
- //cvTsDistortPoints(&_points,&ref_points,&_camera,&_distort,&_rot,&_new_cam);
- CvMat* dst = &test_mat[REF_OUTPUT][0];
- cvTsConvert(&ref_points,dst);
-
- cvCopy(&test_mat[INPUT][0],&test_mat[OUTPUT][0]);
-
- delete[] dist;
- delete[] new_cam;
- delete[] points;
- delete[] r_points;
- if (_mapx)
- {
- cvReleaseMat(&_mapx);
- _mapx = 0;
- }
- if (_mapy)
- {
- cvReleaseMat(&_mapy);
- _mapy = 0;
- }
-}
-
-void CV_InitUndistortRectifyMapTest::run_func()
-{
- if (useCPlus)
- {
- cv::Mat input2,input3,input4;
- input2 = zero_distortion ? cv::Mat() : cv::Mat(&test_mat[INPUT][2]);
- input3 = zero_R ? cv::Mat() : cv::Mat(&test_mat[INPUT][3]);
- input4 = zero_new_cam ? cv::Mat() : cv::Mat(&test_mat[INPUT][4]);
- cv::initUndistortRectifyMap(camera_mat,input2,input3,input4,img_size,mat_type,mapx,mapy);
- }
- else
- {
- CvMat* input2;
- CvMat* input3;
- CvMat* input4;
- input2 = zero_distortion ? 0 : &test_mat[INPUT][2];
- input3 = zero_R ? 0 : &test_mat[INPUT][3];
- input4 = zero_new_cam ? 0 : &test_mat[INPUT][4];
- cvInitUndistortRectifyMap(&test_mat[INPUT][1],input2,input3,input4,_mapx,_mapy);
- }
-}
-
-double CV_InitUndistortRectifyMapTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- return 8;
-}
-
-CV_InitUndistortRectifyMapTest init_undistort_rectify_map_test;
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////\r
-//\r
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.\r
-//\r
-// By downloading, copying, installing or using the software you agree to this license.\r
-// If you do not agree to this license, do not download, install,\r
-// copy or use the software.\r
-//\r
-//\r
-// Intel License Agreement\r
-// For Open Source Computer Vision Library\r
-//\r
-// Copyright (C) 2000, Intel Corporation, all rights reserved.\r
-// Third party copyrights are property of their respective owners.\r
-//\r
-// Redistribution and use in source and binary forms, with or without modification,\r
-// are permitted provided that the following conditions are met:\r
-//\r
-// * Redistribution's of source code must retain the above copyright notice,\r
-// this list of conditions and the following disclaimer.\r
-//\r
-// * Redistribution's in binary form must reproduce the above copyright notice,\r
-// this list of conditions and the following disclaimer in the documentation\r
-// and/or other materials provided with the distribution.\r
-//\r
-// * The name of Intel Corporation may not be used to endorse or promote products\r
-// derived from this software without specific prior written permission.\r
-//\r
-// This software is provided by the copyright holders and contributors "as is" and\r
-// any express or implied warranties, including, but not limited to, the implied\r
-// warranties of merchantability and fitness for a particular purpose are disclaimed.\r
-// In no event shall the Intel Corporation or contributors be liable for any direct,\r
-// indirect, incidental, special, exemplary, or consequential damages\r
-// (including, but not limited to, procurement of substitute goods or services;\r
-// loss of use, data, or profits; or business interruption) however caused\r
-// and on any theory of liability, whether in contract, strict liability,\r
-// or tort (including negligence or otherwise) arising in any way out of\r
-// the use of this software, even if advised of the possibility of such damage.\r
-//\r
-//M*/\r
-\r
-#include "cvtest.h"\r
-#include "cvchessboardgenerator.h"\r
-\r
-#include <iostream>\r
-\r
-using namespace cv;\r
-using namespace std;\r
-\r
-class CV_CameraCalibrationBadArgTest : public CvBadArgTest\r
-{\r
-public:\r
- CV_CameraCalibrationBadArgTest() : CvBadArgTest("calibrate-camera-c-badarg", "cvCalibrateCamera2"), \r
- imgSize(800, 600) \r
- { \r
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE; \r
- };\r
- ~CV_CameraCalibrationBadArgTest() {} ;\r
-protected: \r
- void run(int); \r
- void run_func(void) {};\r
-\r
- const static int M = 1;\r
-\r
- Size imgSize;\r
- Size corSize;\r
- Mat chessBoard; \r
- Mat corners;\r
-\r
- struct C_Caller\r
- {\r
- CvMat* objPts;\r
- CvMat* imgPts;\r
- CvMat* npoints; \r
- Size imageSize;\r
- CvMat *cameraMatrix;\r
- CvMat *distCoeffs;\r
- CvMat *rvecs;\r
- CvMat *tvecs; \r
- int flags;\r
-\r
- void operator()() const \r
- { \r
- cvCalibrateCamera2(objPts, imgPts, npoints, imageSize, \r
- cameraMatrix, distCoeffs, rvecs, tvecs, flags );\r
- }\r
- };\r
-};\r
-\r
-\r
-void CV_CameraCalibrationBadArgTest::run( int /* start_from */ )\r
-{ \r
- Mat_<float> camMat(3, 3);\r
- Mat_<float> distCoeffs0(1, 5);\r
- \r
- camMat << 300.f, 0.f, imgSize.width/2.f, 0, 300.f, imgSize.height/2.f, 0.f, 0.f, 1.f; \r
- distCoeffs0 << 1.2f, 0.2f, 0.f, 0.f, 0.f;\r
- \r
- ChessBoardGenerator cbg(Size(8,6));\r
- corSize = cbg.cornersSize();\r
- vector<Point2f> exp_corn; \r
- chessBoard = cbg(Mat(imgSize, CV_8U, Scalar(0)), camMat, distCoeffs0, exp_corn);\r
- Mat_<Point2f>(corSize.height, corSize.width, (Point2f*)&exp_corn[0]).copyTo(corners);\r
- \r
- CvMat objPts, imgPts, npoints, cameraMatrix, distCoeffs, rvecs, tvecs;\r
- Mat zeros(1, sizeof(CvMat), CV_8U, Scalar(0));\r
-\r
- C_Caller caller, bad_caller;\r
- caller.imageSize = imgSize; \r
- caller.objPts = &objPts;\r
- caller.imgPts = &imgPts;\r
- caller.npoints = &npoints; \r
- caller.cameraMatrix = &cameraMatrix;\r
- caller.distCoeffs = &distCoeffs;\r
- caller.rvecs = &rvecs;\r
- caller.tvecs = &tvecs; \r
-\r
- ///////////////////////////// \r
- Mat objPts_cpp;\r
- Mat imgPts_cpp;\r
- Mat npoints_cpp; \r
- Mat cameraMatrix_cpp;\r
- Mat distCoeffs_cpp;\r
- Mat rvecs_cpp;\r
- Mat tvecs_cpp; \r
- \r
- objPts_cpp.create(corSize, CV_32FC3);\r
- for(int j = 0; j < corSize.height; ++j)\r
- for(int i = 0; i < corSize.width; ++i)\r
- objPts_cpp.at<Point3f>(j, i) = Point3i(i, j, 0);\r
- objPts_cpp = objPts_cpp.reshape(3, 1);\r
-\r
- imgPts_cpp = corners.clone().reshape(2, 1);\r
- npoints_cpp = Mat_<int>(M, 1, corSize.width * corSize.height);\r
- cameraMatrix_cpp.create(3, 3, CV_32F);\r
- distCoeffs_cpp.create(5, 1, CV_32F);\r
- rvecs_cpp.create(M, 1, CV_32FC3);\r
- tvecs_cpp.create(M, 1, CV_32FC3);\r
- \r
- caller.flags = 0;\r
- //CV_CALIB_USE_INTRINSIC_GUESS; //CV_CALIB_FIX_ASPECT_RATIO\r
- //CV_CALIB_USE_INTRINSIC_GUESS //CV_CALIB_FIX_ASPECT_RATIO\r
- //CV_CALIB_FIX_PRINCIPAL_POINT //CV_CALIB_ZERO_TANGENT_DIST\r
- //CV_CALIB_FIX_FOCAL_LENGTH //CV_CALIB_FIX_K1 //CV_CALIB_FIX_K2 //CV_CALIB_FIX_K3\r
- \r
- objPts = objPts_cpp;\r
- imgPts = imgPts_cpp;\r
- npoints = npoints_cpp; \r
- cameraMatrix = cameraMatrix_cpp;\r
- distCoeffs = distCoeffs_cpp;\r
- rvecs = rvecs_cpp;\r
- tvecs = tvecs_cpp; \r
-\r
- /* /*//*/ */\r
- int errors = 0;\r
- \r
- bad_caller = caller;\r
- bad_caller.objPts = 0;\r
- errors += run_test_case( CV_StsBadArg, "Zero passed in objPts", bad_caller); \r
-\r
- bad_caller = caller;\r
- bad_caller.imgPts = 0;\r
- errors += run_test_case( CV_StsBadArg, "Zero passed in imgPts", bad_caller ); \r
-\r
- bad_caller = caller;\r
- bad_caller.npoints = 0;\r
- errors += run_test_case( CV_StsBadArg, "Zero passed in npoints", bad_caller ); \r
-\r
- bad_caller = caller;\r
- bad_caller.cameraMatrix = 0;\r
- errors += run_test_case( CV_StsBadArg, "Zero passed in cameraMatrix", bad_caller );\r
-\r
- bad_caller = caller;\r
- bad_caller.distCoeffs = 0;\r
- errors += run_test_case( CV_StsBadArg, "Zero passed in distCoeffs", bad_caller );\r
-\r
- bad_caller = caller;\r
- bad_caller.imageSize.width = -1;\r
- errors += run_test_case( CV_StsOutOfRange, "Bad image width", bad_caller );\r
-\r
- bad_caller = caller;\r
- bad_caller.imageSize.height = -1;\r
- errors += run_test_case( CV_StsOutOfRange, "Bad image height", bad_caller );\r
-\r
- Mat bad_nts_cpp1 = Mat_<float>(M, 1, 1.f);\r
- Mat bad_nts_cpp2 = Mat_<int>(3, 3, corSize.width * corSize.height); \r
- CvMat bad_npts_c1 = bad_nts_cpp1;\r
- CvMat bad_npts_c2 = bad_nts_cpp2;\r
- \r
- bad_caller = caller; \r
- bad_caller.npoints = &bad_npts_c1;\r
- errors += run_test_case( CV_StsUnsupportedFormat, "Bad npoints format", bad_caller );\r
-\r
- bad_caller = caller; \r
- bad_caller.npoints = &bad_npts_c2;\r
- errors += run_test_case( CV_StsUnsupportedFormat, "Bad npoints size", bad_caller );\r
- \r
- bad_caller = caller; \r
- bad_caller.rvecs = (CvMat*)zeros.ptr();\r
- errors += run_test_case( CV_StsBadArg, "Bad rvecs header", bad_caller );\r
-\r
- bad_caller = caller; \r
- bad_caller.tvecs = (CvMat*)zeros.ptr();\r
- errors += run_test_case( CV_StsBadArg, "Bad tvecs header", bad_caller );\r
-\r
- Mat bad_rvecs_cpp1(M+1, 1, CV_32FC3); CvMat bad_rvecs_c1 = bad_rvecs_cpp1;\r
- Mat bad_tvecs_cpp1(M+1, 1, CV_32FC3); CvMat bad_tvecs_c1 = bad_tvecs_cpp1; \r
-\r
- \r
-\r
- Mat bad_rvecs_cpp2(M, 2, CV_32FC3); CvMat bad_rvecs_c2 = bad_rvecs_cpp2;\r
- Mat bad_tvecs_cpp2(M, 2, CV_32FC3); CvMat bad_tvecs_c2 = bad_tvecs_cpp2; \r
-\r
- bad_caller = caller; \r
- bad_caller.rvecs = &bad_rvecs_c1;\r
- errors += run_test_case( CV_StsBadArg, "Bad tvecs header", bad_caller );\r
-\r
- bad_caller = caller; \r
- bad_caller.rvecs = &bad_rvecs_c2;\r
- errors += run_test_case( CV_StsBadArg, "Bad tvecs header", bad_caller );\r
-\r
- bad_caller = caller; \r
- bad_caller.tvecs = &bad_tvecs_c1;\r
- errors += run_test_case( CV_StsBadArg, "Bad tvecs header", bad_caller );\r
-\r
- bad_caller = caller; \r
- bad_caller.tvecs = &bad_tvecs_c2;\r
- errors += run_test_case( CV_StsBadArg, "Bad tvecs header", bad_caller );\r
- \r
- Mat bad_cameraMatrix_cpp1(3, 3, CV_32S); CvMat bad_cameraMatrix_c1 = bad_cameraMatrix_cpp1;\r
- Mat bad_cameraMatrix_cpp2(2, 3, CV_32F); CvMat bad_cameraMatrix_c2 = bad_cameraMatrix_cpp2;\r
- Mat bad_cameraMatrix_cpp3(3, 2, CV_64F); CvMat bad_cameraMatrix_c3 = bad_cameraMatrix_cpp3;\r
-\r
- \r
-\r
- bad_caller = caller; \r
- bad_caller.cameraMatrix = &bad_cameraMatrix_c1;\r
- errors += run_test_case( CV_StsBadArg, "Bad camearaMatrix header", bad_caller );\r
-\r
- bad_caller = caller; \r
- bad_caller.cameraMatrix = &bad_cameraMatrix_c2;\r
- errors += run_test_case( CV_StsBadArg, "Bad camearaMatrix header", bad_caller );\r
-\r
- bad_caller = caller; \r
- bad_caller.cameraMatrix = &bad_cameraMatrix_c3;\r
- errors += run_test_case( CV_StsBadArg, "Bad camearaMatrix header", bad_caller );\r
-\r
- Mat bad_distCoeffs_cpp1(1, 5, CV_32S); CvMat bad_distCoeffs_c1 = bad_distCoeffs_cpp1;\r
- Mat bad_distCoeffs_cpp2(2, 2, CV_64F); CvMat bad_distCoeffs_c2 = bad_distCoeffs_cpp2;\r
- Mat bad_distCoeffs_cpp3(1, 6, CV_64F); CvMat bad_distCoeffs_c3 = bad_distCoeffs_cpp3;\r
-\r
- \r
-\r
- bad_caller = caller; \r
- bad_caller.distCoeffs = &bad_distCoeffs_c1;\r
- errors += run_test_case( CV_StsBadArg, "Bad distCoeffs header", bad_caller );\r
-\r
- bad_caller = caller; \r
- bad_caller.distCoeffs = &bad_distCoeffs_c2;\r
- errors += run_test_case( CV_StsBadArg, "Bad distCoeffs header", bad_caller );\r
-\r
- \r
- bad_caller = caller; \r
- bad_caller.distCoeffs = &bad_distCoeffs_c3;\r
- errors += run_test_case( CV_StsBadArg, "Bad distCoeffs header", bad_caller ); \r
-\r
- double CM[] = {0, 0, 0, /**/0, 0, 0, /**/0, 0, 0};\r
- Mat bad_cameraMatrix_cpp4(3, 3, CV_64F, CM); CvMat bad_cameraMatrix_c4 = bad_cameraMatrix_cpp4; \r
-\r
- bad_caller = caller; \r
- bad_caller.flags |= CV_CALIB_USE_INTRINSIC_GUESS;\r
- bad_caller.cameraMatrix = &bad_cameraMatrix_c4;\r
- CM[0] = 0; //bad fx\r
- errors += run_test_case( CV_StsOutOfRange, "Bad camearaMatrix data", bad_caller ); \r
-\r
- CM[0] = 500; CM[4] = 0; //bad fy\r
- errors += run_test_case( CV_StsOutOfRange, "Bad camearaMatrix data", bad_caller ); \r
-\r
- CM[0] = 500; CM[4] = 500; CM[2] = -1; //bad cx\r
- errors += run_test_case( CV_StsOutOfRange, "Bad camearaMatrix data", bad_caller ); \r
-\r
- CM[0] = 500; CM[4] = 500; CM[2] = imgSize.width*2; //bad cx\r
- errors += run_test_case( CV_StsOutOfRange, "Bad camearaMatrix data", bad_caller ); \r
-\r
- CM[0] = 500; CM[4] = 500; CM[2] = imgSize.width/2; CM[5] = -1; //bad cy\r
- errors += run_test_case( CV_StsOutOfRange, "Bad camearaMatrix data", bad_caller ); \r
-\r
- CM[0] = 500; CM[4] = 500; CM[2] = imgSize.width/2; CM[5] = imgSize.height*2; //bad cy\r
- errors += run_test_case( CV_StsOutOfRange, "Bad camearaMatrix data", bad_caller ); \r
-\r
- CM[0] = 500; CM[4] = 500; CM[2] = imgSize.width/2; CM[5] = imgSize.height/2;\r
- CM[1] = 0.1; //Non-zero skew \r
- errors += run_test_case( CV_StsOutOfRange, "Bad camearaMatrix data", bad_caller );\r
-\r
- CM[1] = 0;\r
- CM[3] = 0.1; /* mad matrix shape */ \r
- errors += run_test_case( CV_StsOutOfRange, "Bad camearaMatrix data", bad_caller );\r
-\r
- CM[3] = 0; CM[6] = 0.1; /* mad matrix shape */ \r
- errors += run_test_case( CV_StsOutOfRange, "Bad camearaMatrix data", bad_caller );\r
-\r
- CM[3] = 0; CM[6] = 0; CM[7] = 0.1; /* mad matrix shape */ \r
- errors += run_test_case( CV_StsOutOfRange, "Bad camearaMatrix data", bad_caller );\r
-\r
- CM[3] = 0; CM[6] = 0; CM[7] = 0; CM[8] = 1.1; /* mad matrix shape */ \r
- errors += run_test_case( CV_StsOutOfRange, "Bad camearaMatrix data", bad_caller ); \r
- CM[8] = 1.0;\r
-\r
- /////////////////////////////////////////////////////////////////////////////////////\r
- bad_caller = caller; \r
- Mat bad_objPts_cpp5 = objPts_cpp.clone(); CvMat bad_objPts_c5 = bad_objPts_cpp5;\r
- bad_caller.objPts = &bad_objPts_c5;\r
-\r
- cv::RNG& rng = theRNG();\r
- for(int i = 0; i < bad_objPts_cpp5.rows; ++i)\r
- bad_objPts_cpp5.at<Point3f>(0, i).z += ((float)rng - 0.5f);\r
-\r
- errors += run_test_case( CV_StsBadArg, "Bad objPts data", bad_caller ); \r
-\r
- if (errors)\r
- ts->set_failed_test_info(CvTS::FAIL_MISMATCH);\r
- else\r
- ts->set_failed_test_info(CvTS::OK); \r
-\r
- //try { caller(); }\r
- //catch (...)\r
- //{ \r
- // ts->set_failed_test_info(CvTS::FAIL_MISMATCH); \r
- // printf("+!");\r
- //}\r
-}\r
-\r
-CV_CameraCalibrationBadArgTest camera_calibration_bad_arg_test;\r
-\r
-\r
-class CV_Rodrigues2BadArgTest : public CvBadArgTest\r
-{\r
-public:\r
- CV_Rodrigues2BadArgTest() : CvBadArgTest("_3d-rodrigues-badarg", "cvRodrigues2") { };\r
- ~CV_Rodrigues2BadArgTest() {} ;\r
-protected: \r
- void run_func(void) {};\r
-\r
- struct C_Caller\r
- { \r
- CvMat* src;\r
- CvMat* dst;\r
- CvMat* jacobian;\r
-\r
- void operator()() { cvRodrigues2(src, dst, jacobian); }\r
- };\r
-\r
- void run(int /* start_from */ )\r
- {\r
- Mat zeros(1, sizeof(CvMat), CV_8U, Scalar(0));\r
- CvMat src_c, dst_c, jacobian_c;\r
-\r
- Mat src_cpp(3, 1, CV_32F); src_c = src_cpp; \r
- Mat dst_cpp(3, 3, CV_32F); dst_c = dst_cpp; \r
- Mat jacobian_cpp(3, 9, CV_32F); jacobian_c = jacobian_cpp;\r
- \r
- C_Caller caller, bad_caller;\r
- caller.src = &src_c;\r
- caller.dst = &dst_c;\r
- caller.jacobian = &jacobian_c;\r
-\r
- /* try { caller(); } \r
- catch (...)\r
- {\r
- printf("badasfas");\r
- }*/\r
- \r
- /*/*//*/*/\r
- int errors = 0;\r
-\r
- bad_caller = caller;\r
- bad_caller.src = 0;\r
- errors += run_test_case( CV_StsNullPtr, "Src is zero pointer", bad_caller );\r
-\r
- bad_caller = caller;\r
- bad_caller.dst = 0;\r
- errors += run_test_case( CV_StsNullPtr, "Dst is zero pointer", bad_caller );\r
-\r
- Mat bad_src_cpp1(3, 1, CV_8U); CvMat bad_src_c1 = bad_src_cpp1;\r
- Mat bad_dst_cpp1(3, 1, CV_8U); CvMat bad_dst_c1 = bad_dst_cpp1;\r
- Mat bad_jac_cpp1(3, 1, CV_8U); CvMat bad_jac_c1 = bad_jac_cpp1;\r
- Mat bad_jac_cpp2(3, 1, CV_32FC2); CvMat bad_jac_c2 = bad_jac_cpp2;\r
- Mat bad_jac_cpp3(3, 1, CV_32F); CvMat bad_jac_c3 = bad_jac_cpp3;\r
-\r
- bad_caller = caller;\r
- bad_caller.src = &bad_src_c1;\r
- errors += run_test_case( CV_StsUnsupportedFormat, "Bad src formart", bad_caller );\r
-\r
- bad_caller = caller;\r
- bad_caller.dst = &bad_dst_c1;\r
- errors += run_test_case( CV_StsUnmatchedFormats, "Bad dst formart", bad_caller );\r
-\r
- bad_caller = caller;\r
- bad_caller.jacobian = (CvMat*)zeros.ptr();\r
- errors += run_test_case( CV_StsBadArg, "Bad jacobian ", bad_caller );\r
-\r
- bad_caller = caller;\r
- bad_caller.jacobian = &bad_jac_c1;\r
- errors += run_test_case( CV_StsUnmatchedFormats, "Bad jacobian format", bad_caller );\r
-\r
- bad_caller = caller;\r
- bad_caller.jacobian = &bad_jac_c2;\r
- errors += run_test_case( CV_StsUnmatchedFormats, "Bad jacobian format", bad_caller );\r
- \r
- bad_caller = caller;\r
- bad_caller.jacobian = &bad_jac_c3;\r
- errors += run_test_case( CV_StsBadSize, "Bad jacobian format", bad_caller );\r
-\r
- Mat bad_src_cpp2(1, 1, CV_32F); CvMat bad_src_c2 = bad_src_cpp2;\r
-\r
- bad_caller = caller;\r
- bad_caller.src = &bad_src_c2;\r
- errors += run_test_case( CV_StsBadSize, "Bad src format", bad_caller );\r
-\r
- Mat bad_dst_cpp2(2, 1, CV_32F); CvMat bad_dst_c2 = bad_dst_cpp2;\r
- Mat bad_dst_cpp3(3, 2, CV_32F); CvMat bad_dst_c3 = bad_dst_cpp3;\r
- Mat bad_dst_cpp4(3, 3, CV_32FC2); CvMat bad_dst_c4 = bad_dst_cpp4;\r
-\r
- bad_caller = caller;\r
- bad_caller.dst = &bad_dst_c2;\r
- errors += run_test_case( CV_StsBadSize, "Bad dst format", bad_caller );\r
-\r
- bad_caller = caller;\r
- bad_caller.dst = &bad_dst_c3;\r
- errors += run_test_case( CV_StsBadSize, "Bad dst format", bad_caller );\r
-\r
- bad_caller = caller;\r
- bad_caller.dst = &bad_dst_c4;\r
- errors += run_test_case( CV_StsBadSize, "Bad dst format", bad_caller );\r
-\r
-\r
- /********/\r
- src_cpp.create(3, 3, CV_32F); src_c = src_cpp; \r
- dst_cpp.create(3, 1, CV_32F); dst_c = dst_cpp; \r
-\r
-\r
- Mat bad_dst_cpp5(5, 5, CV_32F); CvMat bad_dst_c5 = bad_dst_cpp5;\r
- \r
- bad_caller = caller;\r
- bad_caller.dst = &bad_dst_c5;\r
- errors += run_test_case( CV_StsBadSize, "Bad dst format", bad_caller );\r
- \r
- \r
- if (errors)\r
- ts->set_failed_test_info(CvTS::FAIL_MISMATCH);\r
- else\r
- ts->set_failed_test_info(CvTS::OK); \r
- }\r
-};\r
-\r
-CV_Rodrigues2BadArgTest cv_rodrigues2_badarg_test;\r
-\r
-\r
-\r
-//////////////////////////////////////////////////////////////////////////////////\r
-//////////////////////////////////////////////////////////////////////////////////\r
-class CV_ProjectPoints2BadArgTest : public CvBadArgTest\r
-{\r
-public:\r
- CV_ProjectPoints2BadArgTest() : CvBadArgTest("projectPoints-badarg", "cvProjectPoints2"),\r
- camMat(3, 3), distCoeffs(1, 5)\r
- { \r
- Size imsSize(800, 600);\r
- camMat << 300.f, 0.f, imsSize.width/2.f, 0, 300.f, imsSize.height/2.f, 0.f, 0.f, 1.f; \r
- distCoeffs << 1.2f, 0.2f, 0.f, 0.f, 0.f;\r
- };\r
- ~CV_ProjectPoints2BadArgTest() {} ;\r
-protected: \r
- void run_func(void) {};\r
-\r
- Mat_<float> camMat;\r
- Mat_<float> distCoeffs;\r
- \r
- struct C_Caller\r
- { \r
- CvMat* objectPoints;\r
- CvMat* r_vec;\r
- CvMat* t_vec;\r
- CvMat* A;\r
- CvMat* distCoeffs;\r
- CvMat* imagePoints; \r
- CvMat* dpdr;\r
- CvMat* dpdt; \r
- CvMat* dpdf;\r
- CvMat* dpdc; \r
- CvMat* dpdk;\r
- double aspectRatio;\r
-\r
- void operator()() \r
- { \r
- cvProjectPoints2( objectPoints, r_vec, t_vec, A, distCoeffs, imagePoints, \r
- dpdr, dpdt, dpdf, dpdc, dpdk, aspectRatio ); \r
- }\r
- };\r
-\r
- void run(int /* start_from */ )\r
- { \r
- CvMat zeros;\r
- memset(&zeros, 0, sizeof(zeros));\r
-\r
- C_Caller caller, bad_caller;\r
- CvMat objectPoints_c, r_vec_c, t_vec_c, A_c, distCoeffs_c, imagePoints_c, \r
- dpdr_c, dpdt_c, dpdf_c, dpdc_c, dpdk_c;\r
-\r
- const int n = 10;\r
-\r
- Mat imagePoints_cpp(1, n, CV_32FC2); imagePoints_c = imagePoints_cpp;\r
-\r
- Mat objectPoints_cpp(1, n, CV_32FC3);\r
- randu(objectPoints_cpp, Scalar::all(1), Scalar::all(10));\r
- objectPoints_c = objectPoints_cpp; \r
-\r
- Mat t_vec_cpp(Mat::zeros(1, 3, CV_32F)); t_vec_c = t_vec_cpp;\r
- Mat r_vec_cpp; \r
- Rodrigues(Mat::eye(3, 3, CV_32F), r_vec_cpp); r_vec_c = r_vec_cpp; \r
- \r
- Mat A_cpp = camMat.clone(); A_c = A_cpp;\r
- Mat distCoeffs_cpp = distCoeffs.clone(); distCoeffs_c = distCoeffs_cpp;\r
- \r
- Mat dpdr_cpp(2*n, 3, CV_32F); dpdr_c = dpdr_cpp;\r
- Mat dpdt_cpp(2*n, 3, CV_32F); dpdt_c = dpdt_cpp;\r
- Mat dpdf_cpp(2*n, 2, CV_32F); dpdf_c = dpdf_cpp;\r
- Mat dpdc_cpp(2*n, 2, CV_32F); dpdc_c = dpdc_cpp;\r
- Mat dpdk_cpp(2*n, 4, CV_32F); dpdk_c = dpdk_cpp;\r
- \r
- caller.aspectRatio = 1.0;\r
- caller.objectPoints = &objectPoints_c;\r
- caller.r_vec = &r_vec_c;\r
- caller.t_vec = &t_vec_c;\r
- caller.A = &A_c;\r
- caller.distCoeffs = &distCoeffs_c;\r
- caller.imagePoints = &imagePoints_c; \r
- caller.dpdr = &dpdr_c;\r
- caller.dpdt = &dpdt_c; \r
- caller.dpdf = &dpdf_c;\r
- caller.dpdc = &dpdc_c; \r
- caller.dpdk = &dpdk_c; \r
- \r
- /********************/\r
- int errors = 0;\r
- \r
-\r
- bad_caller = caller; \r
- bad_caller.objectPoints = 0;\r
- errors += run_test_case( CV_StsBadArg, "Zero objectPoints", bad_caller ); \r
-\r
- bad_caller = caller; \r
- bad_caller.r_vec = 0;\r
- errors += run_test_case( CV_StsBadArg, "Zero r_vec", bad_caller ); \r
-\r
- bad_caller = caller; \r
- bad_caller.t_vec = 0;\r
- errors += run_test_case( CV_StsBadArg, "Zero t_vec", bad_caller ); \r
-\r
- bad_caller = caller; \r
- bad_caller.A = 0;\r
- errors += run_test_case( CV_StsBadArg, "Zero camMat", bad_caller ); \r
-\r
- bad_caller = caller; \r
- bad_caller.imagePoints = 0;\r
- errors += run_test_case( CV_StsBadArg, "Zero imagePoints", bad_caller ); \r
-\r
- /****************************/\r
- Mat bad_r_vec_cpp1(r_vec_cpp.size(), CV_32S); CvMat bad_r_vec_c1 = bad_r_vec_cpp1;\r
- Mat bad_r_vec_cpp2(2, 2, CV_32F); CvMat bad_r_vec_c2 = bad_r_vec_cpp2;\r
- Mat bad_r_vec_cpp3(r_vec_cpp.size(), CV_32FC2); CvMat bad_r_vec_c3 = bad_r_vec_cpp3;\r
-\r
- bad_caller = caller; \r
- bad_caller.r_vec = &bad_r_vec_c1;\r
- errors += run_test_case( CV_StsBadArg, "Bad rvec format", bad_caller ); \r
-\r
- bad_caller = caller; \r
- bad_caller.r_vec = &bad_r_vec_c2;\r
- errors += run_test_case( CV_StsBadArg, "Bad rvec format", bad_caller ); \r
-\r
- bad_caller = caller; \r
- bad_caller.r_vec = &bad_r_vec_c3;\r
- errors += run_test_case( CV_StsBadArg, "Bad rvec format", bad_caller ); \r
- \r
- /****************************/\r
- Mat bad_t_vec_cpp1(t_vec_cpp.size(), CV_32S); CvMat bad_t_vec_c1 = bad_t_vec_cpp1;\r
- Mat bad_t_vec_cpp2(2, 2, CV_32F); CvMat bad_t_vec_c2 = bad_t_vec_cpp2;\r
- Mat bad_t_vec_cpp3(1, 1, CV_32FC2); CvMat bad_t_vec_c3 = bad_t_vec_cpp3;\r
-\r
- bad_caller = caller; \r
- bad_caller.t_vec = &bad_t_vec_c1;\r
- errors += run_test_case( CV_StsBadArg, "Bad tvec format", bad_caller ); \r
-\r
- bad_caller = caller; \r
- bad_caller.t_vec = &bad_t_vec_c2;\r
- errors += run_test_case( CV_StsBadArg, "Bad tvec format", bad_caller ); \r
-\r
- bad_caller = caller; \r
- bad_caller.t_vec = &bad_t_vec_c3;\r
- errors += run_test_case( CV_StsBadArg, "Bad tvec format", bad_caller ); \r
- \r
- /****************************/\r
- Mat bad_A_cpp1(A_cpp.size(), CV_32S); CvMat bad_A_c1 = bad_A_cpp1;\r
- Mat bad_A_cpp2(2, 2, CV_32F); CvMat bad_A_c2 = bad_A_cpp2;\r
-\r
- bad_caller = caller; \r
- bad_caller.A = &bad_A_c1;\r
- errors += run_test_case( CV_StsBadArg, "Bad A format", bad_caller ); \r
-\r
- bad_caller = caller; \r
- bad_caller.A = &bad_A_c2;\r
- errors += run_test_case( CV_StsBadArg, "Bad A format", bad_caller ); \r
-\r
- /****************************/\r
- Mat bad_distCoeffs_cpp1(distCoeffs_cpp.size(), CV_32S); CvMat bad_distCoeffs_c1 = bad_distCoeffs_cpp1;\r
- Mat bad_distCoeffs_cpp2(2, 2, CV_32F); CvMat bad_distCoeffs_c2 = bad_distCoeffs_cpp2;\r
- Mat bad_distCoeffs_cpp3(1, 7, CV_32F); CvMat bad_distCoeffs_c3 = bad_distCoeffs_cpp3;\r
-\r
- bad_caller = caller; \r
- bad_caller.distCoeffs = &zeros;\r
- errors += run_test_case( CV_StsBadArg, "Bad distCoeffs format", bad_caller ); \r
-\r
- bad_caller = caller; \r
- bad_caller.distCoeffs = &bad_distCoeffs_c1;\r
- errors += run_test_case( CV_StsBadArg, "Bad distCoeffs format", bad_caller ); \r
-\r
- bad_caller = caller; \r
- bad_caller.distCoeffs = &bad_distCoeffs_c2;\r
- errors += run_test_case( CV_StsBadArg, "Bad distCoeffs format", bad_caller ); \r
-\r
- bad_caller = caller; \r
- bad_caller.distCoeffs = &bad_distCoeffs_c3;\r
- errors += run_test_case( CV_StsBadArg, "Bad distCoeffs format", bad_caller ); \r
-\r
-\r
- /****************************/\r
- Mat bad_dpdr_cpp1(dpdr_cpp.size(), CV_32S); CvMat bad_dpdr_c1 = bad_dpdr_cpp1;\r
- Mat bad_dpdr_cpp2(dpdr_cpp.cols+1, 3, CV_32F); CvMat bad_dpdr_c2 = bad_dpdr_cpp2;\r
- Mat bad_dpdr_cpp3(dpdr_cpp.cols, 7, CV_32F); CvMat bad_dpdr_c3 = bad_dpdr_cpp3;\r
-\r
- bad_caller = caller; \r
- bad_caller.dpdr = &zeros;\r
- errors += run_test_case( CV_StsBadArg, "Bad dpdr format", bad_caller ); \r
-\r
- bad_caller = caller; \r
- bad_caller.dpdr = &bad_dpdr_c1;\r
- errors += run_test_case( CV_StsBadArg, "Bad dpdr format", bad_caller ); \r
-\r
- bad_caller = caller; \r
- bad_caller.dpdr = &bad_dpdr_c2;\r
- errors += run_test_case( CV_StsBadArg, "Bad dpdr format", bad_caller ); \r
-\r
- bad_caller = caller; \r
- bad_caller.dpdr = &bad_dpdr_c3;\r
- errors += run_test_case( CV_StsBadArg, "Bad dpdr format", bad_caller ); \r
-\r
- /****************************/\r
-\r
- bad_caller = caller; \r
- bad_caller.dpdt = &zeros;\r
- errors += run_test_case( CV_StsBadArg, "Bad dpdt format", bad_caller ); \r
-\r
- bad_caller = caller; \r
- bad_caller.dpdt = &bad_dpdr_c1;\r
- errors += run_test_case( CV_StsBadArg, "Bad dpdt format", bad_caller ); \r
-\r
- bad_caller = caller; \r
- bad_caller.dpdt = &bad_dpdr_c2;\r
- errors += run_test_case( CV_StsBadArg, "Bad dpdt format", bad_caller ); \r
-\r
- bad_caller = caller; \r
- bad_caller.dpdt = &bad_dpdr_c3;\r
- errors += run_test_case( CV_StsBadArg, "Bad dpdt format", bad_caller ); \r
-\r
- /****************************/\r
-\r
- Mat bad_dpdf_cpp2(dpdr_cpp.cols+1, 2, CV_32F); CvMat bad_dpdf_c2 = bad_dpdf_cpp2;\r
-\r
- bad_caller = caller; \r
- bad_caller.dpdf = &zeros;\r
- errors += run_test_case( CV_StsBadArg, "Bad dpdf format", bad_caller ); \r
-\r
- bad_caller = caller; \r
- bad_caller.dpdf = &bad_dpdr_c1;\r
- errors += run_test_case( CV_StsBadArg, "Bad dpdf format", bad_caller ); \r
-\r
- bad_caller = caller; \r
- bad_caller.dpdf = &bad_dpdf_c2;\r
- errors += run_test_case( CV_StsBadArg, "Bad dpdf format", bad_caller ); \r
-\r
- bad_caller = caller; \r
- bad_caller.dpdf = &bad_dpdr_c3;\r
- errors += run_test_case( CV_StsBadArg, "Bad dpdf format", bad_caller ); \r
-\r
- /****************************/\r
-\r
- bad_caller = caller; \r
- bad_caller.dpdc = &zeros;\r
- errors += run_test_case( CV_StsBadArg, "Bad dpdc format", bad_caller ); \r
-\r
- bad_caller = caller; \r
- bad_caller.dpdc = &bad_dpdr_c1;\r
- errors += run_test_case( CV_StsBadArg, "Bad dpdc format", bad_caller ); \r
-\r
- bad_caller = caller; \r
- bad_caller.dpdc = &bad_dpdf_c2;\r
- errors += run_test_case( CV_StsBadArg, "Bad dpdc format", bad_caller ); \r
-\r
- bad_caller = caller; \r
- bad_caller.dpdc = &bad_dpdr_c3;\r
- errors += run_test_case( CV_StsBadArg, "Bad dpdc format", bad_caller ); \r
-\r
- /****************************/ \r
-\r
- bad_caller = caller; \r
- bad_caller.dpdk = &zeros;\r
- errors += run_test_case( CV_StsBadArg, "Bad dpdk format", bad_caller ); \r
-\r
- bad_caller = caller; \r
- bad_caller.dpdk = &bad_dpdr_c1;\r
- errors += run_test_case( CV_StsBadArg, "Bad dpdk format", bad_caller ); \r
-\r
- bad_caller = caller; \r
- bad_caller.dpdk = &bad_dpdf_c2;\r
- errors += run_test_case( CV_StsBadArg, "Bad dpdk format", bad_caller ); \r
-\r
- bad_caller = caller; \r
- bad_caller.dpdk = &bad_dpdr_c3;\r
- errors += run_test_case( CV_StsBadArg, "Bad dpdk format", bad_caller ); \r
-\r
- bad_caller = caller; \r
- bad_caller.distCoeffs = 0;\r
- errors += run_test_case( CV_StsNullPtr, "distCoeffs is NULL while dpdk is not", bad_caller ); \r
- \r
- \r
- if (errors)\r
- ts->set_failed_test_info(CvTS::FAIL_MISMATCH);\r
- else\r
- ts->set_failed_test_info(CvTS::OK); \r
- }\r
-};\r
-\r
-CV_ProjectPoints2BadArgTest projectPoints2_badarg_test;\r
-\r
-\r
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////\r
-//\r
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.\r
-//\r
-// By downloading, copying, installing or using the software you agree to this license.\r
-// If you do not agree to this license, do not download, install,\r
-// copy or use the software.\r
-//\r
-//\r
-// Intel License Agreement\r
-// For Open Source Computer Vision Library\r
-//\r
-// Copyright (C) 2000, Intel Corporation, all rights reserved.\r
-// Third party copyrights are property of their respective owners.\r
-//\r
-// Redistribution and use in source and binary forms, with or without modification,\r
-// are permitted provided that the following conditions are met:\r
-//\r
-// * Redistribution's of source code must retain the above copyright notice,\r
-// this list of conditions and the following disclaimer.\r
-//\r
-// * Redistribution's in binary form must reproduce the above copyright notice,\r
-// this list of conditions and the following disclaimer in the documentation\r
-// and/or other materials provided with the distribution.\r
-//\r
-// * The name of Intel Corporation may not be used to endorse or promote products\r
-// derived from this software without specific prior written permission.\r
-//\r
-// This software is provided by the copyright holders and contributors "as is" and\r
-// any express or implied warranties, including, but not limited to, the implied\r
-// warranties of merchantability and fitness for a particular purpose are disclaimed.\r
-// In no event shall the Intel Corporation or contributors be liable for any direct,\r
-// indirect, incidental, special, exemplary, or consequential damages\r
-// (including, but not limited to, procurement of substitute goods or services;\r
-// loss of use, data, or profits; or business interruption) however caused\r
-// and on any theory of liability, whether in contract, strict liability,\r
-// or tort (including negligence or otherwise) arising in any way out of\r
-// the use of this software, even if advised of the possibility of such damage.\r
-//\r
-//M*/\r
-\r
-#include "cvtest.h"\r
-#include "cvchessboardgenerator.h"\r
-\r
-#include <limits>\r
-\r
-using namespace std;\r
-using namespace cv;\r
-\r
-class CV_ChessboardDetectorBadArgTest : public CvBadArgTest\r
-{\r
-public:\r
- CV_ChessboardDetectorBadArgTest();\r
-protected:\r
- void run(int);\r
- bool checkByGenerator();\r
-\r
- bool cpp;\r
-\r
- /* cpp interface */\r
- Mat img;\r
- Size pattern_size; \r
- int flags;\r
- vector<Point2f> corners;\r
- \r
- /* c interface */\r
- CvMat arr;\r
- CvPoint2D32f* out_corners;\r
- int* out_corner_count;\r
-\r
-\r
- /* c interface draw corners */\r
- bool drawCorners;\r
- CvMat drawCorImg;\r
- bool was_found;\r
- \r
- void run_func() \r
- { \r
- if (cpp)\r
- findChessboardCorners(img, pattern_size, corners, flags); \r
- else\r
- if (!drawCorners)\r
- cvFindChessboardCorners( &arr, pattern_size, out_corners, out_corner_count, flags );\r
- else\r
- cvDrawChessboardCorners( &drawCorImg, pattern_size, \r
- (CvPoint2D32f*)&corners[0], (int)corners.size(), was_found);\r
- }\r
-};\r
-\r
-CV_ChessboardDetectorBadArgTest::CV_ChessboardDetectorBadArgTest(): \r
- CvBadArgTest( "chessboard-detector-badarg", "cvFindChessboardCorners" )\r
-{\r
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;\r
-}\r
-\r
-/* ///////////////////// chess_corner_test ///////////////////////// */\r
-void CV_ChessboardDetectorBadArgTest::run( int /*start_from */)\r
-{\r
- Mat bg(800, 600, CV_8U, Scalar(0));\r
- Mat_<float> camMat(3, 3);\r
- camMat << 300.f, 0.f, bg.cols/2.f, 0, 300.f, bg.rows/2.f, 0.f, 0.f, 1.f; \r
- Mat_<float> distCoeffs(1, 5);\r
- distCoeffs << 1.2f, 0.2f, 0.f, 0.f, 0.f;\r
-\r
- ChessBoardGenerator cbg(Size(8,6));\r
- vector<Point2f> exp_corn; \r
- Mat cb = cbg(bg, camMat, distCoeffs, exp_corn);\r
- \r
- /* /*//*/ */\r
- int errors = 0;\r
- flags = CV_CALIB_CB_ADAPTIVE_THRESH | CV_CALIB_CB_NORMALIZE_IMAGE;\r
- cpp = true;\r
-\r
- img = cb.clone();\r
- pattern_size = Size(2,2);\r
- errors += run_test_case( CV_StsOutOfRange, "Invlid pattern size" ); \r
- \r
- pattern_size = cbg.cornersSize(); \r
- cb.convertTo(img, CV_32F);\r
- errors += run_test_case( CV_StsUnsupportedFormat, "Not 8-bit image" );\r
-\r
- cv::merge(vector<Mat>(2, cb), img);\r
- errors += run_test_case( CV_StsUnsupportedFormat, "2 channel image" );\r
-\r
- cpp = false;\r
- drawCorners = false;\r
-\r
- img = cb.clone();\r
- arr = img; \r
- out_corner_count = 0;\r
- out_corners = 0; \r
- errors += run_test_case( CV_StsNullPtr, "Null pointer to corners" );\r
-\r
- drawCorners = true;\r
- Mat cvdrawCornImg(img.size(), CV_8UC2);\r
- drawCorImg = cvdrawCornImg;\r
- was_found = true;\r
- errors += run_test_case( CV_StsUnsupportedFormat, "2 channel image" );\r
- \r
-\r
- if (errors)\r
- ts->set_failed_test_info(CvTS::FAIL_MISMATCH);\r
- else\r
- ts->set_failed_test_info(CvTS::OK);\r
-}\r
-\r
-CV_ChessboardDetectorBadArgTest chessboard_detector_arg_test;\r
-\r
-/* End of file. */\r
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-#include "cvtest.h"
-
-class CV_UndistortPointsBadArgTest : public CvBadArgTest
-{
-public:
- CV_UndistortPointsBadArgTest();
-protected:
- void run(int);
- void run_func();
-
-private:
- //common
- cv::Size img_size;
- bool useCPlus;
- //static const int N_POINTS = 1;
- static const int N_POINTS2 = 2;
-
- //C
- CvMat* _camera_mat;
- CvMat* matR;
- CvMat* matP;
- CvMat* _distortion_coeffs;
- CvMat* _src_points;
- CvMat* _dst_points;
-
-
- //C++
- cv::Mat camera_mat;
- cv::Mat R;
- cv::Mat P;
- cv::Mat distortion_coeffs;
- cv::Mat src_points;
- std::vector<cv::Point2f> dst_points;
-
-};
-
-CV_UndistortPointsBadArgTest::CV_UndistortPointsBadArgTest ():
- CvBadArgTest( "undistort-points-badarg", "cvUndistortPoints" )
-{
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;
-}
-
-void CV_UndistortPointsBadArgTest::run_func()
-{
- if (useCPlus)
- {
- cv::undistortPoints(src_points,dst_points,camera_mat,distortion_coeffs,R,P);
- }
- else
- {
- cvUndistortPoints(_src_points,_dst_points,_camera_mat,_distortion_coeffs,matR,matP);
- }
-}
-
-void CV_UndistortPointsBadArgTest::run(int)
-{
- //CvRNG* rng = ts->get_rng();
- int errcount = 0;
- useCPlus = false;
-//initializing
- img_size.width = 800;
- img_size.height = 600;
- double cam[9] = {150.f, 0.f, img_size.width/2.f, 0, 300.f, img_size.height/2.f, 0.f, 0.f, 1.f};
- double dist[4] = {0.01,0.02,0.001,0.0005};
- double s_points[N_POINTS2] = {img_size.width/4,img_size.height/4};
- double d_points[N_POINTS2];
- double p[9] = {155.f, 0.f, img_size.width/2.f+img_size.width/50.f, 0, 310.f, img_size.height/2.f+img_size.height/50.f, 0.f, 0.f, 1.f};
- double r[9] = {1,0,0,0,1,0,0,0,1};
-
- CvMat _camera_mat_orig = cvMat(3,3,CV_64F,cam);
- CvMat _distortion_coeffs_orig = cvMat(1,4,CV_64F,dist);
- CvMat _P_orig = cvMat(3,3,CV_64F,p);
- CvMat _R_orig = cvMat(3,3,CV_64F,r);
- CvMat _src_points_orig = cvMat(1,4,CV_64FC2,s_points);
- CvMat _dst_points_orig = cvMat(1,4,CV_64FC2,d_points);
-
- _camera_mat = &_camera_mat_orig;
- _distortion_coeffs = &_distortion_coeffs_orig;
- matP = &_P_orig;
- matR = &_R_orig;
- _src_points = &_src_points_orig;
- _dst_points = &_dst_points_orig;
-
-//tests
- CvMat* temp1;
- CvMat* temp;
- IplImage* temp_img = cvCreateImage(cvSize(img_size.width,img_size.height),8,3);
-
-//-----------
- temp = (CvMat*)temp_img;
- _src_points = temp;
- errcount += run_test_case( CV_StsAssert, "Input data is not CvMat*" );
- _src_points = &_src_points_orig;
-
- temp = (CvMat*)temp_img;
- _dst_points = temp;
- errcount += run_test_case( CV_StsAssert, "Output data is not CvMat*" );
- _dst_points = &_dst_points_orig;
-
- temp = cvCreateMat(2,3,CV_64F);
- _src_points = temp;
- errcount += run_test_case( CV_StsAssert, "Invalid input data matrix size" );
- _src_points = &_src_points_orig;
- cvReleaseMat(&temp);
-
- temp = cvCreateMat(2,3,CV_64F);
- _dst_points = temp;
- errcount += run_test_case(CV_StsAssert, "Invalid output data matrix size" );
- _dst_points = &_dst_points_orig;
- cvReleaseMat(&temp);
-
- temp = cvCreateMat(1,3,CV_64F);
- temp1 = cvCreateMat(4,1,CV_64F);
- _dst_points = temp;
- _src_points = temp1;
- errcount += run_test_case(CV_StsAssert, "Output and input data sizes mismatch" );
- _dst_points = &_dst_points_orig;
- _src_points = &_src_points_orig;
- cvReleaseMat(&temp);
- cvReleaseMat(&temp1);
-
- temp = cvCreateMat(1,3,CV_32S);
- _dst_points = temp;
- errcount += run_test_case(CV_StsAssert, "Invalid output data matrix type" );
- _dst_points = &_dst_points_orig;
- cvReleaseMat(&temp);
-
- temp = cvCreateMat(1,3,CV_32S);
- _src_points = temp;
- errcount += run_test_case(CV_StsAssert, "Invalid input data matrix type" );
- _src_points = &_src_points_orig;
- cvReleaseMat(&temp);
-//------------
- temp = cvCreateMat(2,3,CV_64F);
- _camera_mat = temp;
- errcount += run_test_case( CV_StsAssert, "Invalid camera data matrix size" );
- _camera_mat = &_camera_mat_orig;
- cvReleaseMat(&temp);
-
- temp = cvCreateMat(3,4,CV_64F);
- _camera_mat = temp;
- errcount += run_test_case( CV_StsAssert, "Invalid camera data matrix size" );
- _camera_mat = &_camera_mat_orig;
- cvReleaseMat(&temp);
-
- temp = (CvMat*)temp_img;
- _camera_mat = temp;
- errcount += run_test_case( CV_StsAssert, "Camera data is not CvMat*" );
- _camera_mat = &_camera_mat_orig;
-//----------
-
- temp = (CvMat*)temp_img;
- _distortion_coeffs = temp;
- errcount += run_test_case( CV_StsAssert, "Distortion coefficients data is not CvMat*" );
- _distortion_coeffs = &_distortion_coeffs_orig;
-
- temp = cvCreateMat(1,6,CV_64F);
- _distortion_coeffs = temp;
- errcount += run_test_case( CV_StsAssert, "Invalid distortion coefficients data matrix size" );
- _distortion_coeffs = &_distortion_coeffs_orig;
- cvReleaseMat(&temp);
-
- temp = cvCreateMat(3,3,CV_64F);
- _distortion_coeffs = temp;
- errcount += run_test_case( CV_StsAssert, "Invalid distortion coefficients data matrix size" );
- _distortion_coeffs = &_distortion_coeffs_orig;
- cvReleaseMat(&temp);
-//----------
- temp = (CvMat*)temp_img;
- matR = temp;
- errcount += run_test_case( CV_StsAssert, "R data is not CvMat*" );
- matR = &_R_orig;
-
- temp = cvCreateMat(4,3,CV_64F);
- matR = temp;
- errcount += run_test_case( CV_StsAssert, "Invalid R data matrix size" );
- matR = &_R_orig;
- cvReleaseMat(&temp);
-
- temp = cvCreateMat(3,2,CV_64F);
- matR = temp;
- errcount += run_test_case( CV_StsAssert, "Invalid R data matrix size" );
- matR = &_R_orig;
- cvReleaseMat(&temp);
-
-//-----------
- temp = (CvMat*)temp_img;
- matP = temp;
- errcount += run_test_case( CV_StsAssert, "P data is not CvMat*" );
- matP = &_P_orig;
-
- temp = cvCreateMat(4,3,CV_64F);
- matP = temp;
- errcount += run_test_case( CV_StsAssert, "Invalid P data matrix size" );
- matP = &_P_orig;
- cvReleaseMat(&temp);
-
- temp = cvCreateMat(3,2,CV_64F);
- matP = temp;
- errcount += run_test_case( CV_StsAssert, "Invalid P data matrix size" );
- matP = &_P_orig;
- cvReleaseMat(&temp);
-//------------
- //C++ tests
- useCPlus = true;
-
- camera_mat = cv::Mat(&_camera_mat_orig);
- distortion_coeffs = cv::Mat(&_distortion_coeffs_orig);
- P = cv::Mat(&_P_orig);
- R = cv::Mat(&_R_orig);
- src_points = cv::Mat(&_src_points_orig);
-
- temp = cvCreateMat(2,2,CV_32FC2);
- src_points = cv::Mat(temp);
- errcount += run_test_case( CV_StsAssert, "Invalid input data matrix size" );
- src_points = cv::Mat(&_src_points_orig);
- cvReleaseMat(&temp);
-
- temp = cvCreateMat(1,4,CV_64FC2);
- src_points = cv::Mat(temp);
- errcount += run_test_case( CV_StsAssert, "Invalid input data matrix type" );
- src_points = cv::Mat(&_src_points_orig);
- cvReleaseMat(&temp);
-
- src_points = cv::Mat();
- errcount += run_test_case( CV_StsAssert, "Input data matrix is not continuous" );
- src_points = cv::Mat(&_src_points_orig);
- cvReleaseMat(&temp);
-
-
-
-//------------
- cvReleaseImage(&temp_img);
- ts->set_failed_test_info(errcount > 0 ? CvTS::FAIL_BAD_ARG_CHECK : CvTS::OK);
-}
-
-CV_UndistortPointsBadArgTest default_new_camera_matrix_badarg_test;
-//=========
-class CV_InitUndistortRectifyMapBadArgTest : public CvBadArgTest
-{
-public:
- CV_InitUndistortRectifyMapBadArgTest();
-protected:
- void run(int);
- void run_func();
-
-private:
- //common
- cv::Size img_size;
- bool useCPlus;
-
- //C
- CvMat* _camera_mat;
- CvMat* matR;
- CvMat* _new_camera_mat;
- CvMat* _distortion_coeffs;
- CvMat* _mapx;
- CvMat* _mapy;
-
-
- //C++
- cv::Mat camera_mat;
- cv::Mat R;
- cv::Mat new_camera_mat;
- cv::Mat distortion_coeffs;
- cv::Mat mapx;
- cv::Mat mapy;
- int mat_type;
-
-};
-
-CV_InitUndistortRectifyMapBadArgTest::CV_InitUndistortRectifyMapBadArgTest ():
- CvBadArgTest( "undistort-undistort_rectify_map-badarg","cvInitUndistortRectifyMap" )
-{
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;
-}
-
-void CV_InitUndistortRectifyMapBadArgTest::run_func()
-{
- if (useCPlus)
- {
- cv::initUndistortRectifyMap(camera_mat,distortion_coeffs,R,new_camera_mat,img_size,mat_type,mapx,mapy);
- }
- else
- {
- cvInitUndistortRectifyMap(_camera_mat,_distortion_coeffs,matR,_new_camera_mat,_mapx,_mapy);
- }
-}
-
-void CV_InitUndistortRectifyMapBadArgTest::run(int)
-{
- int errcount = 0;
-//initializing
- img_size.width = 800;
- img_size.height = 600;
- double cam[9] = {150.f, 0.f, img_size.width/2.f, 0, 300.f, img_size.height/2.f, 0.f, 0.f, 1.f};
- double dist[4] = {0.01,0.02,0.001,0.0005};
- float* arr_mapx = new float[img_size.width*img_size.height];
- float* arr_mapy = new float[img_size.width*img_size.height];
- double arr_new_camera_mat[9] = {155.f, 0.f, img_size.width/2.f+img_size.width/50.f, 0, 310.f, img_size.height/2.f+img_size.height/50.f, 0.f, 0.f, 1.f};
- double r[9] = {1,0,0,0,1,0,0,0,1};
-
- CvMat _camera_mat_orig = cvMat(3,3,CV_64F,cam);
- CvMat _distortion_coeffs_orig = cvMat(1,4,CV_64F,dist);
- CvMat _new_camera_mat_orig = cvMat(3,3,CV_64F,arr_new_camera_mat);
- CvMat _R_orig = cvMat(3,3,CV_64F,r);
- CvMat _mapx_orig = cvMat(img_size.height,img_size.width,CV_32FC1,arr_mapx);
- CvMat _mapy_orig = cvMat(img_size.height,img_size.width,CV_32FC1,arr_mapy);
- int mat_type_orig = CV_32FC1;
-
- _camera_mat = &_camera_mat_orig;
- _distortion_coeffs = &_distortion_coeffs_orig;
- _new_camera_mat = &_new_camera_mat_orig;
- matR = &_R_orig;
- _mapx = &_mapx_orig;
- _mapy = &_mapy_orig;
- mat_type = mat_type_orig;
-
-//tests
- useCPlus = true;
- CvMat* temp;
-
- //C++ tests
- useCPlus = true;
-
- camera_mat = cv::Mat(&_camera_mat_orig);
- distortion_coeffs = cv::Mat(&_distortion_coeffs_orig);
- new_camera_mat = cv::Mat(&_new_camera_mat_orig);
- R = cv::Mat(&_R_orig);
- mapx = cv::Mat(&_mapx_orig);
- mapy = cv::Mat(&_mapy_orig);
-
-
- mat_type = CV_64F;
- errcount += run_test_case( CV_StsAssert, "Invalid map matrix type" );
- mat_type = mat_type_orig;
-
- temp = cvCreateMat(3,2,CV_32FC1);
- camera_mat = cv::Mat(temp);
- errcount += run_test_case( CV_StsAssert, "Invalid camera data matrix size" );
- camera_mat = cv::Mat(&_camera_mat_orig);
- cvReleaseMat(&temp);
-
- temp = cvCreateMat(4,3,CV_32FC1);
- R = cv::Mat(temp);
- errcount += run_test_case( CV_StsAssert, "Invalid R data matrix size" );
- R = cv::Mat(&_R_orig);
- cvReleaseMat(&temp);
-
- temp = cvCreateMat(6,1,CV_32FC1);
- distortion_coeffs = cv::Mat(temp);
- errcount += run_test_case( CV_StsAssert, "Invalid distortion coefficients data matrix size" );
- distortion_coeffs = cv::Mat(&_distortion_coeffs_orig);
- cvReleaseMat(&temp);
-
-//------------
- delete[] arr_mapx;
- delete[] arr_mapy;
- ts->set_failed_test_info(errcount > 0 ? CvTS::FAIL_BAD_ARG_CHECK : CvTS::OK);
-}
-
-CV_InitUndistortRectifyMapBadArgTest init_undistort_rectify_map_badarg_test;
-
-//=========
-class CV_UndistortBadArgTest : public CvBadArgTest
-{
-public:
- CV_UndistortBadArgTest();
-protected:
- void run(int);
- void run_func();
-
-private:
- //common
- cv::Size img_size;
- bool useCPlus;
-
- //C
- CvMat* _camera_mat;
- CvMat* _new_camera_mat;
- CvMat* _distortion_coeffs;
- CvMat* _src;
- CvMat* _dst;
-
-
- //C++
- cv::Mat camera_mat;
- cv::Mat new_camera_mat;
- cv::Mat distortion_coeffs;
- cv::Mat src;
- cv::Mat dst;
-
-};
-
-CV_UndistortBadArgTest::CV_UndistortBadArgTest ():
- CvBadArgTest( "undistort-badarg","cvUndistort2" )
-{
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;
-}
-
-void CV_UndistortBadArgTest::run_func()
-{
- if (useCPlus)
- {
- cv::undistort(src,dst,camera_mat,distortion_coeffs,new_camera_mat);
- }
- else
- {
- cvUndistort2(_src,_dst,_camera_mat,_distortion_coeffs,_new_camera_mat);
- }
-}
-
-void CV_UndistortBadArgTest::run(int)
-{
- int errcount = 0;
-//initializing
- img_size.width = 800;
- img_size.height = 600;
- double cam[9] = {150.f, 0.f, img_size.width/2.f, 0, 300.f, img_size.height/2.f, 0.f, 0.f, 1.f};
- double dist[4] = {0.01,0.02,0.001,0.0005};
- float* arr_src = new float[img_size.width*img_size.height];
- float* arr_dst = new float[img_size.width*img_size.height];
- double arr_new_camera_mat[9] = {155.f, 0.f, img_size.width/2.f+img_size.width/50.f, 0, 310.f, img_size.height/2.f+img_size.height/50.f, 0.f, 0.f, 1.f};
-
- CvMat _camera_mat_orig = cvMat(3,3,CV_64F,cam);
- CvMat _distortion_coeffs_orig = cvMat(1,4,CV_64F,dist);
- CvMat _new_camera_mat_orig = cvMat(3,3,CV_64F,arr_new_camera_mat);
- CvMat _src_orig = cvMat(img_size.height,img_size.width,CV_32FC1,arr_src);
- CvMat _dst_orig = cvMat(img_size.height,img_size.width,CV_32FC1,arr_dst);
-
- _camera_mat = &_camera_mat_orig;
- _distortion_coeffs = &_distortion_coeffs_orig;
- _new_camera_mat = &_new_camera_mat_orig;
- _src = &_src_orig;
- _dst = &_dst_orig;
-
-//tests
- useCPlus = true;
- CvMat* temp;
- CvMat* temp1;
-
-//C tests
- useCPlus = false;
-
- temp = cvCreateMat(800,600,CV_32F);
- temp1 = cvCreateMat(800,601,CV_32F);
- _src = temp;
- _dst = temp1;
- errcount += run_test_case( CV_StsAssert, "Input and output data matrix sizes mismatch" );
- _src = &_src_orig;
- _dst = &_dst_orig;
- cvReleaseMat(&temp);
- cvReleaseMat(&temp1);
-
- temp = cvCreateMat(800,600,CV_32F);
- temp1 = cvCreateMat(800,600,CV_64F);
- _src = temp;
- _dst = temp1;
- errcount += run_test_case( CV_StsAssert, "Input and output data matrix types mismatch" );
- _src = &_src_orig;
- _dst = &_dst_orig;
- cvReleaseMat(&temp);
- cvReleaseMat(&temp1);
-
- //C++ tests
- useCPlus = true;
-
- camera_mat = cv::Mat(&_camera_mat_orig);
- distortion_coeffs = cv::Mat(&_distortion_coeffs_orig);
- new_camera_mat = cv::Mat(&_new_camera_mat_orig);
- src = cv::Mat(&_src_orig);
- dst = cv::Mat(&_dst_orig);
-
-//------------
- delete[] arr_src;
- delete[] arr_dst;
- ts->set_failed_test_info(errcount > 0 ? CvTS::FAIL_BAD_ARG_CHECK : CvTS::OK);
-}
-
-CV_UndistortBadArgTest undistort_badarg_test;
-
-/* End of file. */
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////\r
- //\r
- // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.\r
- //\r
- // By downloading, copying, installing or using the software you agree to this license.\r
- // If you do not agree to this license, do not download, install,\r
- // copy or use the software.\r
- //\r
- //\r
- // License Agreement\r
- // For Open Source Computer Vision Library\r
- //\r
- // Copyright (C) 2000-2008, Intel Corporation, all rights reserved.\r
- // Copyright (C) 2009, Willow Garage Inc., all rights reserved.\r
- // Third party copyrights are property of their respective owners.\r
- //\r
- // Redistribution and use in source and binary forms, with or without modification,\r
- // are permitted provided that the following conditions are met:\r
- //\r
- // * Redistribution's of source code must retain the above copyright notice,\r
- // this list of conditions and the following disclaimer.\r
- //\r
- // * Redistribution's in binary form must reproduce the above copyright notice,\r
- // this list of conditions and the following disclaimer in the documentation\r
- // and/or other materials provided with the distribution.\r
- //\r
- // * The name of the copyright holders may not be used to endorse or promote products\r
- // derived from this software without specific prior written permission.\r
- //\r
- // This software is provided by the copyright holders and contributors "as is" and\r
- // any express or implied warranties, including, but not limited to, the implied\r
- // warranties of merchantability and fitness for a particular purpose are disclaimed.\r
- // In no event shall the Intel Corporation or contributors be liable for any direct,\r
- // indirect, incidental, special, exemplary, or consequential damages\r
- // (including, but not limited to, procurement of substitute goods or services;\r
- // loss of use, data, or profits; or business interruption) however caused\r
- // and on any theory of liability, whether in contract, strict liability,\r
- // or tort (including negligence or otherwise) arising in any way out of\r
- // the use of this software, even if advised of the possibility of such damage.\r
-//\r
-//M*/\r
-\r
-#include "cvtest.h"\r
-#include "cvchessboardgenerator.h"\r
-\r
-#include <vector>\r
-#include <iterator>\r
-#include <algorithm>\r
-\r
-using namespace cv;\r
-using namespace std;\r
-\r
-ChessBoardGenerator::ChessBoardGenerator(const Size& _patternSize) : sensorWidth(32), sensorHeight(24),\r
- squareEdgePointsNum(200), min_cos(sqrt(2.f)*0.5f), cov(0.5), \r
- patternSize(_patternSize), rendererResolutionMultiplier(4), tvec(Mat::zeros(1, 3, CV_32F))\r
-{ \r
- Rodrigues(Mat::eye(3, 3, CV_32F), rvec);\r
-}\r
-\r
-void cv::ChessBoardGenerator::generateEdge(const Point3f& p1, const Point3f& p2, vector<Point3f>& out) const\r
-{ \r
- Point3f step = (p2 - p1) * (1.f/squareEdgePointsNum); \r
- for(size_t n = 0; n < squareEdgePointsNum; ++n)\r
- out.push_back( p1 + step * (float)n);\r
-} \r
-\r
-Size cv::ChessBoardGenerator::cornersSize() const\r
-{\r
- return Size(patternSize.width-1, patternSize.height-1);\r
-}\r
-\r
-struct Mult\r
-{\r
- float m;\r
- Mult(int mult) : m((float)mult) {}\r
- Point2f operator()(const Point2f& p)const { return p * m; } \r
-};\r
-\r
-void cv::ChessBoardGenerator::generateBasis(Point3f& pb1, Point3f& pb2) const\r
-{\r
- RNG& rng = theRNG();\r
-\r
- Vec3f n;\r
- for(;;)\r
- { \r
- n[0] = rng.uniform(-1.f, 1.f);\r
- n[1] = rng.uniform(-1.f, 1.f);\r
- n[2] = rng.uniform(-1.f, 1.f); \r
- float len = (float)norm(n); \r
- n[0]/=len; \r
- n[1]/=len; \r
- n[2]/=len;\r
- \r
- if (n[2] > min_cos)\r
- break;\r
- }\r
-\r
- Vec3f n_temp = n; n_temp[0] += 100;\r
- Vec3f b1 = n.cross(n_temp); \r
- Vec3f b2 = n.cross(b1);\r
- float len_b1 = (float)norm(b1);\r
- float len_b2 = (float)norm(b2); \r
-\r
- pb1 = Point3f(b1[0]/len_b1, b1[1]/len_b1, b1[2]/len_b1);\r
- pb2 = Point3f(b2[0]/len_b1, b2[1]/len_b2, b2[2]/len_b2);\r
-}\r
-\r
-\r
-Mat cv::ChessBoardGenerator::generateChessBoard(const Mat& bg, const Mat& camMat, const Mat& distCoeffs, \r
- const Point3f& zero, const Point3f& pb1, const Point3f& pb2, \r
- float sqWidth, float sqHeight, const vector<Point3f>& whole,\r
- vector<Point2f>& corners) const\r
-{ \r
- vector< vector<Point> > squares_black; \r
- for(int i = 0; i < patternSize.width; ++i)\r
- for(int j = 0; j < patternSize.height; ++j)\r
- if ( (i % 2 == 0 && j % 2 == 0) || (i % 2 != 0 && j % 2 != 0) ) \r
- { \r
- vector<Point3f> pts_square3d;\r
- vector<Point2f> pts_square2d;\r
-\r
- Point3f p1 = zero + (i + 0) * sqWidth * pb1 + (j + 0) * sqHeight * pb2;\r
- Point3f p2 = zero + (i + 1) * sqWidth * pb1 + (j + 0) * sqHeight * pb2;\r
- Point3f p3 = zero + (i + 1) * sqWidth * pb1 + (j + 1) * sqHeight * pb2;\r
- Point3f p4 = zero + (i + 0) * sqWidth * pb1 + (j + 1) * sqHeight * pb2;\r
- generateEdge(p1, p2, pts_square3d);\r
- generateEdge(p2, p3, pts_square3d);\r
- generateEdge(p3, p4, pts_square3d);\r
- generateEdge(p4, p1, pts_square3d); \r
- \r
- projectPoints(Mat(pts_square3d), rvec, tvec, camMat, distCoeffs, pts_square2d);\r
- squares_black.resize(squares_black.size() + 1); \r
- vector<Point2f> temp; \r
- approxPolyDP(Mat(pts_square2d), temp, 1.0, true); \r
- transform(temp.begin(), temp.end(), back_inserter(squares_black.back()), Mult(rendererResolutionMultiplier)); \r
- } \r
-\r
- /* calculate corners */ \r
- corners3d.clear();\r
- for(int j = 0; j < patternSize.height - 1; ++j)\r
- for(int i = 0; i < patternSize.width - 1; ++i)\r
- corners3d.push_back(zero + (i + 1) * sqWidth * pb1 + (j + 1) * sqHeight * pb2);\r
- corners.clear();\r
- projectPoints(Mat(corners3d), rvec, tvec, camMat, distCoeffs, corners);\r
- \r
- vector<Point3f> whole3d;\r
- vector<Point2f> whole2d;\r
- generateEdge(whole[0], whole[1], whole3d);\r
- generateEdge(whole[1], whole[2], whole3d);\r
- generateEdge(whole[2], whole[3], whole3d);\r
- generateEdge(whole[3], whole[0], whole3d);\r
- projectPoints(Mat(whole3d), rvec, tvec, camMat, distCoeffs, whole2d);\r
- vector<Point2f> temp_whole2d; \r
- approxPolyDP(Mat(whole2d), temp_whole2d, 1.0, true); \r
-\r
- vector< vector<Point > > whole_contour(1);\r
- transform(temp_whole2d.begin(), temp_whole2d.end(), \r
- back_inserter(whole_contour.front()), Mult(rendererResolutionMultiplier)); \r
-\r
- Mat result;\r
- if (rendererResolutionMultiplier == 1)\r
- { \r
- result = bg.clone();\r
- drawContours(result, whole_contour, -1, Scalar::all(255), CV_FILLED, CV_AA); \r
- drawContours(result, squares_black, -1, Scalar::all(0), CV_FILLED, CV_AA);\r
- }\r
- else\r
- {\r
- Mat tmp; \r
- resize(bg, tmp, bg.size() * rendererResolutionMultiplier);\r
- drawContours(tmp, whole_contour, -1, Scalar::all(255), CV_FILLED, CV_AA); \r
- drawContours(tmp, squares_black, -1, Scalar::all(0), CV_FILLED, CV_AA);\r
- resize(tmp, result, bg.size(), 0, 0, INTER_AREA);\r
- } \r
-\r
- return result;\r
-}\r
-\r
-Mat cv::ChessBoardGenerator::operator ()(const Mat& bg, const Mat& camMat, const Mat& distCoeffs, vector<Point2f>& corners) const\r
-{ \r
- cov = min(cov, 0.8);\r
- double fovx, fovy, focalLen;\r
- Point2d principalPoint;\r
- double aspect;\r
- calibrationMatrixValues( camMat, bg.size(), sensorWidth, sensorHeight, \r
- fovx, fovy, focalLen, principalPoint, aspect);\r
-\r
- RNG& rng = theRNG();\r
-\r
- float d1 = static_cast<float>(rng.uniform(0.1, 10.0)); \r
- float ah = static_cast<float>(rng.uniform(-fovx/2 * cov, fovx/2 * cov) * CV_PI / 180);\r
- float av = static_cast<float>(rng.uniform(-fovy/2 * cov, fovy/2 * cov) * CV_PI / 180); \r
- \r
- Point3f p;\r
- p.z = cos(ah) * d1;\r
- p.x = sin(ah) * d1;\r
- p.y = p.z * tan(av); \r
-\r
- Point3f pb1, pb2; \r
- generateBasis(pb1, pb2);\r
- \r
- float cbHalfWidth = static_cast<float>(norm(p) * sin( min(fovx, fovy) * 0.5 * CV_PI / 180));\r
- float cbHalfHeight = cbHalfWidth * patternSize.height / patternSize.width; \r
-\r
- float cbHalfWidthEx = cbHalfWidth * ( patternSize.width + 1) / patternSize.width;\r
- float cbHalfHeightEx = cbHalfHeight * (patternSize.height + 1) / patternSize.height;\r
- \r
- vector<Point3f> pts3d(4);\r
- vector<Point2f> pts2d(4);\r
- for(;;)\r
- { \r
- pts3d[0] = p + pb1 * cbHalfWidthEx + cbHalfHeightEx * pb2;\r
- pts3d[1] = p + pb1 * cbHalfWidthEx - cbHalfHeightEx * pb2;\r
- pts3d[2] = p - pb1 * cbHalfWidthEx - cbHalfHeightEx * pb2;\r
- pts3d[3] = p - pb1 * cbHalfWidthEx + cbHalfHeightEx * pb2;\r
- \r
- /* can remake with better perf */\r
- projectPoints(Mat(pts3d), rvec, tvec, camMat, distCoeffs, pts2d);\r
-\r
- bool inrect1 = pts2d[0].x < bg.cols && pts2d[0].y < bg.rows && pts2d[0].x > 0 && pts2d[0].y > 0;\r
- bool inrect2 = pts2d[1].x < bg.cols && pts2d[1].y < bg.rows && pts2d[1].x > 0 && pts2d[1].y > 0;\r
- bool inrect3 = pts2d[2].x < bg.cols && pts2d[2].y < bg.rows && pts2d[2].x > 0 && pts2d[2].y > 0;\r
- bool inrect4 = pts2d[3].x < bg.cols && pts2d[3].y < bg.rows && pts2d[3].x > 0 && pts2d[3].y > 0;\r
- \r
- if (inrect1 && inrect2 && inrect3 && inrect4)\r
- break;\r
-\r
- cbHalfWidth*=0.8f;\r
- cbHalfHeight = cbHalfWidth * patternSize.height / patternSize.width; \r
- \r
- cbHalfWidthEx = cbHalfWidth * ( patternSize.width + 1) / patternSize.width;\r
- cbHalfHeightEx = cbHalfHeight * (patternSize.height + 1) / patternSize.height;\r
- }\r
- \r
- Point3f zero = p - pb1 * cbHalfWidth - cbHalfHeight * pb2;\r
- float sqWidth = 2 * cbHalfWidth/patternSize.width;\r
- float sqHeight = 2 * cbHalfHeight/patternSize.height;\r
- \r
- return generateChessBoard(bg, camMat, distCoeffs, zero, pb1, pb2, sqWidth, sqHeight, pts3d, corners); \r
-}\r
-\r
-\r
-Mat cv::ChessBoardGenerator::operator ()(const Mat& bg, const Mat& camMat, const Mat& distCoeffs, \r
- const Size2f& squareSize, vector<Point2f>& corners) const\r
-{ \r
- cov = min(cov, 0.8);\r
- double fovx, fovy, focalLen;\r
- Point2d principalPoint;\r
- double aspect;\r
- calibrationMatrixValues( camMat, bg.size(), sensorWidth, sensorHeight, \r
- fovx, fovy, focalLen, principalPoint, aspect);\r
-\r
- RNG& rng = theRNG();\r
-\r
- float d1 = static_cast<float>(rng.uniform(0.1, 10.0)); \r
- float ah = static_cast<float>(rng.uniform(-fovx/2 * cov, fovx/2 * cov) * CV_PI / 180);\r
- float av = static_cast<float>(rng.uniform(-fovy/2 * cov, fovy/2 * cov) * CV_PI / 180); \r
- \r
- Point3f p;\r
- p.z = cos(ah) * d1;\r
- p.x = sin(ah) * d1;\r
- p.y = p.z * tan(av); \r
-\r
- Point3f pb1, pb2; \r
- generateBasis(pb1, pb2); \r
-\r
- float cbHalfWidth = squareSize.width * patternSize.width * 0.5f;\r
- float cbHalfHeight = squareSize.height * patternSize.height * 0.5f;\r
-\r
- float cbHalfWidthEx = cbHalfWidth * ( patternSize.width + 1) / patternSize.width;\r
- float cbHalfHeightEx = cbHalfHeight * (patternSize.height + 1) / patternSize.height;\r
- \r
- vector<Point3f> pts3d(4);\r
- vector<Point2f> pts2d(4);\r
- for(;;)\r
- { \r
- pts3d[0] = p + pb1 * cbHalfWidthEx + cbHalfHeightEx * pb2;\r
- pts3d[1] = p + pb1 * cbHalfWidthEx - cbHalfHeightEx * pb2;\r
- pts3d[2] = p - pb1 * cbHalfWidthEx - cbHalfHeightEx * pb2;\r
- pts3d[3] = p - pb1 * cbHalfWidthEx + cbHalfHeightEx * pb2;\r
- \r
- /* can remake with better perf */\r
- projectPoints(Mat(pts3d), rvec, tvec, camMat, distCoeffs, pts2d);\r
-\r
- bool inrect1 = pts2d[0].x < bg.cols && pts2d[0].y < bg.rows && pts2d[0].x > 0 && pts2d[0].y > 0;\r
- bool inrect2 = pts2d[1].x < bg.cols && pts2d[1].y < bg.rows && pts2d[1].x > 0 && pts2d[1].y > 0;\r
- bool inrect3 = pts2d[2].x < bg.cols && pts2d[2].y < bg.rows && pts2d[2].x > 0 && pts2d[2].y > 0;\r
- bool inrect4 = pts2d[3].x < bg.cols && pts2d[3].y < bg.rows && pts2d[3].x > 0 && pts2d[3].y > 0;\r
- \r
- if ( inrect1 && inrect2 && inrect3 && inrect4)\r
- break;\r
-\r
- p.z *= 1.1f;\r
- }\r
- \r
- Point3f zero = p - pb1 * cbHalfWidth - cbHalfHeight * pb2;\r
- \r
- return generateChessBoard(bg, camMat, distCoeffs, zero, pb1, pb2, \r
- squareSize.width, squareSize.height, pts3d, corners); \r
-}\r
-\r
-Mat cv::ChessBoardGenerator::operator ()(const Mat& bg, const Mat& camMat, const Mat& distCoeffs, \r
- const Size2f& squareSize, const Point3f& pos, vector<Point2f>& corners) const\r
-{ \r
- cov = min(cov, 0.8);\r
- Point3f p = pos; \r
- Point3f pb1, pb2; \r
- generateBasis(pb1, pb2); \r
-\r
- float cbHalfWidth = squareSize.width * patternSize.width * 0.5f;\r
- float cbHalfHeight = squareSize.height * patternSize.height * 0.5f;\r
-\r
- float cbHalfWidthEx = cbHalfWidth * ( patternSize.width + 1) / patternSize.width;\r
- float cbHalfHeightEx = cbHalfHeight * (patternSize.height + 1) / patternSize.height;\r
- \r
- vector<Point3f> pts3d(4);\r
- vector<Point2f> pts2d(4);\r
- \r
- pts3d[0] = p + pb1 * cbHalfWidthEx + cbHalfHeightEx * pb2;\r
- pts3d[1] = p + pb1 * cbHalfWidthEx - cbHalfHeightEx * pb2;\r
- pts3d[2] = p - pb1 * cbHalfWidthEx - cbHalfHeightEx * pb2;\r
- pts3d[3] = p - pb1 * cbHalfWidthEx + cbHalfHeightEx * pb2;\r
- \r
- /* can remake with better perf */\r
- projectPoints(Mat(pts3d), rvec, tvec, camMat, distCoeffs, pts2d);\r
- \r
- Point3f zero = p - pb1 * cbHalfWidth - cbHalfHeight * pb2;\r
- \r
- return generateChessBoard(bg, camMat, distCoeffs, zero, pb1, pb2, \r
- squareSize.width, squareSize.height, pts3d, corners); \r
-}\r
-\r
+++ /dev/null
-#ifndef CV_CHESSBOARDGENERATOR_H143KJTVYM389YTNHKFDHJ89NYVMO3VLMEJNTBGUEIYVCM203P\r
-#define CV_CHESSBOARDGENERATOR_H143KJTVYM389YTNHKFDHJ89NYVMO3VLMEJNTBGUEIYVCM203P\r
-\r
-#include "cv.h"\r
-\r
-namespace cv\r
-{\r
-\r
-class ChessBoardGenerator\r
-{\r
-public:\r
- double sensorWidth; \r
- double sensorHeight; \r
- size_t squareEdgePointsNum;\r
- double min_cos;\r
- mutable double cov;\r
- Size patternSize;\r
- int rendererResolutionMultiplier;\r
-\r
- ChessBoardGenerator(const Size& patternSize = Size(8, 6));\r
- Mat operator()(const Mat& bg, const Mat& camMat, const Mat& distCoeffs, vector<Point2f>& corners) const; \r
- Mat operator()(const Mat& bg, const Mat& camMat, const Mat& distCoeffs, const Size2f& squareSize, vector<Point2f>& corners) const; \r
- Mat operator()(const Mat& bg, const Mat& camMat, const Mat& distCoeffs, const Size2f& squareSize, const Point3f& pos, vector<Point2f>& corners) const;\r
- Size cornersSize() const;\r
-\r
- mutable vector<Point3f> corners3d;\r
-private:\r
- void generateEdge(const Point3f& p1, const Point3f& p2, vector<Point3f>& out) const;\r
- Mat generateChessBoard(const Mat& bg, const Mat& camMat, const Mat& distCoeffs, \r
- const Point3f& zero, const Point3f& pb1, const Point3f& pb2, \r
- float sqWidth, float sqHeight, const vector<Point3f>& whole, vector<Point2f>& corners) const;\r
- void generateBasis(Point3f& pb1, Point3f& pb2) const; \r
- \r
- Mat rvec, tvec;\r
-};\r
-\r
-};\r
-\r
-\r
-#endif\r
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-/* End of file. */
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#ifndef _CVTEST_H_
-#define _CVTEST_H_
-
-#if defined _MSC_VER && _MSC_VER >= 1200
-#pragma warning( disable: 4710 4711 4514 4996 )
-#endif
-
-#include "cxts.h"
-#include "opencv2/legacy/legacy.hpp"
-#include "opencv2/legacy/compat.hpp"
-#include "opencv2/contrib/contrib.hpp"
-#include "opencv2/core/core_c.h"
-#include "opencv2/core/internal.hpp"
-#include "opencv2/imgproc/imgproc.hpp"
-#include "opencv2/imgproc/imgproc_c.h"
-#include "opencv2/calib3d/calib3d.hpp"
-#include "opencv2/highgui/highgui.hpp"
-#include "opencv2/video/tracking.hpp"
-#include "opencv2/features2d/features2d.hpp"
-#include "opencv2/objdetect/objdetect.hpp"
-
-#undef min
-#undef max
-
-void cvTsCalcSobelKernel2D( int dx, int dy, int _aperture_size, int origin, CvMat* kernel );
-int cvTsRodrigues( const CvMat* src, CvMat* dst, CvMat* jacobian=0 );
-void cvTsConvertHomogeneous( const CvMat* src, CvMat* dst );
-
-#endif /* _CVTEST_H_ */
-
-/* End of file. */
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////\r
-//\r
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.\r
-//\r
-// By downloading, copying, installing or using the software you agree to this license.\r
-// If you do not agree to this license, do not download, install,\r
-// copy or use the software.\r
-//\r
-//\r
-// License Agreement\r
-// For Open Source Computer Vision Library\r
-//\r
-// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.\r
-// Copyright (C) 2009, Willow Garage Inc., all rights reserved.\r
-// Third party copyrights are property of their respective owners.\r
-//\r
-// Redistribution and use in source and binary forms, with or without modification,\r
-// are permitted provided that the following conditions are met:\r
-//\r
-// * Redistribution's of source code must retain the above copyright notice,\r
-// this list of conditions and the following disclaimer.\r
-//\r
-// * Redistribution's in binary form must reproduce the above copyright notice,\r
-// this list of conditions and the following disclaimer in the documentation\r
-// and/or other materials provided with the distribution.\r
-//\r
-// * The name of the copyright holders may not be used to endorse or promote products\r
-// derived from this software without specific prior written permission.\r
-//\r
-// This software is provided by the copyright holders and contributors "as is" and\r
-// any express or implied warranties, including, but not limited to, the implied\r
-// warranties of merchantability and fitness for a particular purpose are disclaimed.\r
-// In no event shall the Intel Corporation or contributors be liable for any direct,\r
-// indirect, incidental, special, exemplary, or consequential damages\r
-// (including, but not limited to, procurement of substitute goods or services;\r
-// loss of use, data, or profits; or business interruption) however caused\r
-// and on any theory of liability, whether in contract, strict liability,\r
-// or tort (including negligence or otherwise) arising in any way out of\r
-// the use of this software, even if advised of the possibility of such damage.\r
-//\r
-//M*/\r
-\r
-#include "cvtest.h"\r
-#include <string>\r
-#include <iostream>\r
-#include <iterator>\r
-#include <fstream>\r
-#include <numeric>\r
-#include <algorithm>\r
-#include <iterator>\r
-#include "cvaux.h"\r
-\r
-using namespace cv;\r
-using namespace std;\r
-\r
-class CV_DetectorsTest : public CvTest\r
-{\r
-public:\r
- CV_DetectorsTest();\r
- ~CV_DetectorsTest(); \r
-protected: \r
- void run(int); \r
- template <class T> bool testDetector(const Mat& img, const T& detector, vector<KeyPoint>& expected);\r
-\r
- void LoadExpected(const string& file, vector<KeyPoint>& out);\r
-};\r
-\r
-CV_DetectorsTest::CV_DetectorsTest(): CvTest( "feature-detectors", "?" )\r
-{\r
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;\r
-}\r
-CV_DetectorsTest::~CV_DetectorsTest() {}\r
-\r
-void getRotation(const Mat& img, Mat& aff, Mat& out)\r
-{\r
- Point center(img.cols/2, img.rows/2);\r
- aff = getRotationMatrix2D(center, 30, 1);\r
- warpAffine( img, out, aff, img.size());\r
-}\r
-\r
-void getZoom(const Mat& img, Mat& aff, Mat& out)\r
-{\r
- const double mult = 1.2;\r
-\r
- aff.create(2, 3, CV_64F);\r
- double *data = aff.ptr<double>();\r
- data[0] = mult; data[1] = 0; data[2] = 0;\r
- data[3] = 0; data[4] = mult; data[5] = 0;\r
- \r
- warpAffine( img, out, aff, img.size());\r
-}\r
-\r
-void getBlur(const Mat& img, Mat& aff, Mat& out)\r
-{ \r
- aff.create(2, 3, CV_64F);\r
- double *data = aff.ptr<double>();\r
- data[0] = 1; data[1] = 0; data[2] = 0;\r
- data[3] = 0; data[4] = 1; data[5] = 0;\r
- \r
- GaussianBlur(img, out, Size(5, 5), 2); \r
-}\r
-\r
-void getBrightness(const Mat& img, Mat& aff, Mat& out)\r
-{ \r
- aff.create(2, 3, CV_64F);\r
- double *data = aff.ptr<double>();\r
- data[0] = 1; data[1] = 0; data[2] = 0;\r
- data[3] = 0; data[4] = 1; data[5] = 0;\r
- \r
- add(img, Mat(img.size(), img.type(), Scalar(15)), out); \r
-}\r
-\r
-void showOrig(const Mat& img, const vector<KeyPoint>& orig_pts)\r
-{\r
- \r
- Mat img_color;\r
- cvtColor(img, img_color, CV_GRAY2BGR); \r
- \r
- for(size_t i = 0; i < orig_pts.size(); ++i) \r
- circle(img_color, orig_pts[i].pt, (int)orig_pts[i].size/2, CV_RGB(0, 255, 0)); \r
- \r
- namedWindow("O"); imshow("O", img_color); \r
-}\r
-\r
-void show(const string& name, const Mat& new_img, const vector<KeyPoint>& new_pts, const vector<KeyPoint>& transf_pts)\r
-{\r
- \r
- Mat new_img_color; \r
- cvtColor(new_img, new_img_color, CV_GRAY2BGR); \r
-\r
- for(size_t i = 0; i < transf_pts.size(); ++i)\r
- circle(new_img_color, transf_pts[i].pt, (int)transf_pts[i].size/2, CV_RGB(255, 0, 0));\r
-\r
- for(size_t i = 0; i < new_pts.size(); ++i) \r
- circle(new_img_color, new_pts[i].pt, (int)new_pts[i].size/2, CV_RGB(0, 0, 255));\r
- \r
- namedWindow(name + "_T"); imshow(name + "_T", new_img_color); \r
-}\r
-\r
-struct WrapPoint\r
-{\r
- const double* R;\r
- WrapPoint(const Mat& rmat) : R(rmat.ptr<double>()) { };\r
- \r
- KeyPoint operator()(const KeyPoint& kp) const \r
- { \r
- KeyPoint res = kp;\r
- res.pt.x = static_cast<float>(kp.pt.x * R[0] + kp.pt.y * R[1] + R[2]);\r
- res.pt.y = static_cast<float>(kp.pt.x * R[3] + kp.pt.y * R[4] + R[5]); \r
- return res; \r
- }\r
-};\r
-\r
-struct sortByR { bool operator()(const KeyPoint& kp1, const KeyPoint& kp2) { return norm(kp1.pt) < norm(kp2.pt); } };\r
-\r
-template <class T> bool CV_DetectorsTest::testDetector(const Mat& img, const T& detector, vector<KeyPoint>& exp)\r
-{\r
- vector<KeyPoint> orig_kpts;\r
- detector(img, orig_kpts);\r
-\r
- typedef void (*TransfFunc )(const Mat&, Mat&, Mat& FransfFunc); \r
- const TransfFunc transfFunc[] = { getRotation, getZoom, getBlur, getBrightness };\r
- //const string names[] = { "Rotation", "Zoom", "Blur", "Brightness" };\r
- const size_t case_num = sizeof(transfFunc)/sizeof(transfFunc[0]);\r
-\r
- vector<Mat> affs(case_num);\r
- vector<Mat> new_imgs(case_num);\r
-\r
- vector< vector<KeyPoint> > new_kpts(case_num);\r
- vector< vector<KeyPoint> > transf_kpts(case_num);\r
-\r
- //showOrig(img, orig_kpts);\r
- for(size_t i = 0; i < case_num; ++i) \r
- {\r
- transfFunc[i](img, affs[i], new_imgs[i]);\r
- detector(new_imgs[i], new_kpts[i]);\r
- transform(orig_kpts.begin(), orig_kpts.end(), back_inserter(transf_kpts[i]), WrapPoint(affs[i]));\r
- //show(names[i], new_imgs[i], new_kpts[i], transf_kpts[i]);\r
- }\r
-\r
- const float thres = 3;\r
- const float nthres = 3;\r
-\r
- vector<KeyPoint> result;\r
- for(size_t i = 0; i < orig_kpts.size(); ++i)\r
- {\r
- const KeyPoint& okp = orig_kpts[i];\r
- int foundCounter = 0;\r
- for(size_t j = 0; j < case_num; ++j)\r
- { \r
- const KeyPoint& tkp = transf_kpts[j][i];\r
-\r
- size_t k = 0;\r
- \r
- for(; k < new_kpts[j].size(); ++k)\r
- if (norm(new_kpts[j][k].pt - tkp.pt) < nthres && fabs(new_kpts[j][k].size - tkp.size) < thres)\r
- break;\r
-\r
- if (k != new_kpts[j].size())\r
- ++foundCounter;\r
-\r
- }\r
- if (foundCounter == (int)case_num)\r
- result.push_back(okp);\r
- }\r
-\r
- sort(result.begin(), result.end(), sortByR());\r
- sort(exp.begin(), exp.end(), sortByR());\r
-\r
- if (result.size() != exp.size())\r
- {\r
- ts->set_failed_test_info(CvTS::FAIL_INVALID_TEST_DATA);\r
- return false;\r
- }\r
-\r
- int foundCounter1 = 0;\r
- for(size_t i = 0; i < exp.size(); ++i)\r
- {\r
- const KeyPoint& e = exp[i]; \r
- size_t j = 0;\r
- for(; j < result.size(); ++j)\r
- {\r
- const KeyPoint& r = result[i];\r
- if (norm(r.pt-e.pt) < nthres && fabs(r.size - e.size) < thres)\r
- break;\r
- }\r
- if (j != result.size())\r
- ++foundCounter1;\r
- }\r
-\r
- int foundCounter2 = 0;\r
- for(size_t i = 0; i < result.size(); ++i)\r
- {\r
- const KeyPoint& r = result[i]; \r
- size_t j = 0;\r
- for(; j < exp.size(); ++j)\r
- {\r
- const KeyPoint& e = exp[i];\r
- if (norm(r.pt-e.pt) < nthres && fabs(r.size - e.size) < thres)\r
- break;\r
- }\r
- if (j != exp.size())\r
- ++foundCounter2;\r
- }\r
- //showOrig(img, result); waitKey();\r
-\r
- const float errorRate = 0.9f;\r
- if (float(foundCounter1)/exp.size() < errorRate || float(foundCounter2)/result.size() < errorRate)\r
- {\r
- ts->set_failed_test_info( CvTS::FAIL_MISMATCH);\r
- return false;\r
- }\r
- return true; \r
-}\r
-\r
-struct SurfNoMaskWrap \r
-{\r
- const SURF& detector;\r
- SurfNoMaskWrap(const SURF& surf) : detector(surf) {}\r
- SurfNoMaskWrap& operator=(const SurfNoMaskWrap&);\r
- void operator()(const Mat& img, vector<KeyPoint>& kpts) const { detector(img, Mat(), kpts); }\r
-};\r
-\r
-void CV_DetectorsTest::LoadExpected(const string& file, vector<KeyPoint>& out)\r
-{ \r
- Mat mat_exp;\r
- FileStorage fs(file, FileStorage::READ); \r
- if (fs.isOpened())\r
- {\r
- read( fs["ResultVectorData"], mat_exp, Mat() ); \r
- out.resize(mat_exp.cols / sizeof(KeyPoint));\r
- copy(mat_exp.ptr<KeyPoint>(), mat_exp.ptr<KeyPoint>() + out.size(), out.begin()); \r
- }\r
- else\r
- {\r
- ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA);\r
- out.clear();\r
- } \r
-}\r
-\r
-void CV_DetectorsTest::run( int /*start_from*/ )\r
-{ \r
- Mat img = imread(string(ts->get_data_path()) + "shared/graffiti.png", 0);\r
-\r
- if (img.empty())\r
- {\r
- ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA );\r
- return;\r
- }\r
- \r
- Mat to_test(img.size() * 2, img.type(), Scalar(0));\r
- Mat roi = to_test(Rect(img.rows/2, img.cols/2, img.cols, img.rows));\r
- img.copyTo(roi);\r
- GaussianBlur(to_test, to_test, Size(3, 3), 1.5);\r
- \r
- vector<KeyPoint> exp;\r
- LoadExpected(string(ts->get_data_path()) + "detectors/surf.xml", exp); \r
- if (exp.empty())\r
- return;\r
-\r
- if (!testDetector(to_test, SurfNoMaskWrap(SURF(1536+512+512, 2)), exp))\r
- return;\r
- \r
- LoadExpected(string(ts->get_data_path()) + "detectors/star.xml", exp);\r
- if (exp.empty())\r
- return;\r
-\r
- if (!testDetector(to_test, StarDetector(45, 30, 10, 8, 5), exp))\r
- return;\r
-\r
- ts->set_failed_test_info( CvTS::OK); \r
-}\r
-\r
-\r
-CV_DetectorsTest Detectors_test;\r
-\r
-\r
-\r
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////\r
-//\r
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.\r
-//\r
-// By downloading, copying, installing or using the software you agree to this license.\r
-// If you do not agree to this license, do not download, install,\r
-// copy or use the software.\r
-//\r
-//\r
-// License Agreement\r
-// For Open Source Computer Vision Library\r
-//\r
-// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.\r
-// Copyright (C) 2009, Willow Garage Inc., all rights reserved.\r
-// Third party copyrights are property of their respective owners.\r
-//\r
-// Redistribution and use in source and binary forms, with or without modification,\r
-// are permitted provided that the following conditions are met:\r
-//\r
-// * Redistribution's of source code must retain the above copyright notice,\r
-// this list of conditions and the following disclaimer.\r
-//\r
-// * Redistribution's in binary form must reproduce the above copyright notice,\r
-// this list of conditions and the following disclaimer in the documentation\r
-// and/or other materials provided with the distribution.\r
-//\r
-// * The name of the copyright holders may not be used to endorse or promote products\r
-// derived from this software without specific prior written permission.\r
-//\r
-// This software is provided by the copyright holders and contributors "as is" and\r
-// any express or implied warranties, including, but not limited to, the implied\r
-// warranties of merchantability and fitness for a particular purpose are disclaimed.\r
-// In no event shall the Intel Corporation or contributors be liable for any direct,\r
-// indirect, incidental, special, exemplary, or consequential damages\r
-// (including, but not limited to, procurement of substitute goods or services;\r
-// loss of use, data, or profits; or business interruption) however caused\r
-// and on any theory of liability, whether in contract, strict liability,\r
-// or tort (including negligence or otherwise) arising in any way out of\r
-// the use of this software, even if advised of the possibility of such damage.\r
-//\r
-//M*/\r
-\r
-#include "cvtest.h"\r
-#include <string>\r
-#include "cvaux.h"\r
-\r
-using namespace cv;\r
-\r
-class CV_FastTest : public CvTest\r
-{\r
-public:\r
- CV_FastTest();\r
- ~CV_FastTest(); \r
-protected: \r
- void run(int);\r
-};\r
-\r
-CV_FastTest::CV_FastTest(): CvTest( "features-fast", "cv::FAST" )\r
-{\r
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;\r
-}\r
-CV_FastTest::~CV_FastTest() {}\r
-\r
-void CV_FastTest::run( int )\r
-{\r
- Mat image1 = imread(string(ts->get_data_path()) + "inpaint/orig.jpg"); \r
- Mat image2 = imread(string(ts->get_data_path()) + "cameracalibration/chess9.jpg"); \r
- string xml = string(ts->get_data_path()) + "fast/result.xml";\r
- \r
- if (image1.empty() || image2.empty())\r
- {\r
- ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA ); \r
- return;\r
- }\r
-\r
- Mat gray1, gray2;\r
- cvtColor(image1, gray1, CV_BGR2GRAY);\r
- cvtColor(image2, gray2, CV_BGR2GRAY);\r
-\r
- vector<KeyPoint> keypoints1;\r
- vector<KeyPoint> keypoints2; \r
- FAST(gray1, keypoints1, 30);\r
- FAST(gray2, keypoints2, 30);\r
-\r
- for(size_t i = 0; i < keypoints1.size(); ++i)\r
- {\r
- const KeyPoint& kp = keypoints1[i];\r
- cv::circle(image1, kp.pt, cvRound(kp.size/2), CV_RGB(255, 0, 0)); \r
- }\r
-\r
- for(size_t i = 0; i < keypoints2.size(); ++i)\r
- {\r
- const KeyPoint& kp = keypoints2[i];\r
- cv::circle(image2, kp.pt, cvRound(kp.size/2), CV_RGB(255, 0, 0)); \r
- }\r
-\r
- Mat kps1(1, (int)(keypoints1.size() * sizeof(KeyPoint)), CV_8U, &keypoints1[0]);\r
- Mat kps2(1, (int)(keypoints2.size() * sizeof(KeyPoint)), CV_8U, &keypoints2[0]);\r
-\r
- FileStorage fs(xml, FileStorage::READ);\r
- if (!fs.isOpened())\r
- {\r
- fs.open(xml, FileStorage::WRITE);\r
- fs << "exp_kps1" << kps1;\r
- fs << "exp_kps2" << kps2;\r
- fs.release();\r
- } \r
-\r
- if (!fs.isOpened())\r
- fs.open(xml, FileStorage::READ);\r
- \r
- Mat exp_kps1, exp_kps2; \r
- read( fs["exp_kps1"], exp_kps1, Mat() );\r
- read( fs["exp_kps2"], exp_kps2, Mat() ); \r
- fs.release();\r
-\r
- if ( 0 != norm(exp_kps1, kps1, NORM_L2) || 0 != norm(exp_kps2, kps2, NORM_L2))\r
- {\r
- ts->set_failed_test_info(CvTS::FAIL_MISMATCH);\r
- return;\r
- }\r
- \r
- /* cv::namedWindow("Img1"); cv::imshow("Img1", image1);\r
- cv::namedWindow("Img2"); cv::imshow("Img2", image2);\r
- cv::waitKey(0);*/\r
-\r
- ts->set_failed_test_info(CvTS::OK);\r
-}\r
-\r
-CV_FastTest fast_test;\r
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////\r
-//\r
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.\r
-//\r
-// By downloading, copying, installing or using the software you agree to this license.\r
-// If you do not agree to this license, do not download, install,\r
-// copy or use the software.\r
-//\r
-//\r
-// License Agreement\r
-// For Open Source Computer Vision Library\r
-//\r
-// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.\r
-// Copyright (C) 2009, Willow Garage Inc., all rights reserved.\r
-// Third party copyrights are property of their respective owners.\r
-//\r
-// Redistribution and use in source and binary forms, with or without modification,\r
-// are permitted provided that the following conditions are met:\r
-//\r
-// * Redistribution's of source code must retain the above copyright notice,\r
-// this list of conditions and the following disclaimer.\r
-//\r
-// * Redistribution's in binary form must reproduce the above copyright notice,\r
-// this list of conditions and the following disclaimer in the documentation\r
-// and/or other materials provided with the distribution.\r
-//\r
-// * The name of the copyright holders may not be used to endorse or promote products\r
-// derived from this software without specific prior written permission.\r
-//\r
-// This software is provided by the copyright holders and contributors "as is" and\r
-// any express or implied warranties, including, but not limited to, the implied\r
-// warranties of merchantability and fitness for a particular purpose are disclaimed.\r
-// In no event shall the Intel Corporation or contributors be liable for any direct,\r
-// indirect, incidental, special, exemplary, or consequential damages\r
-// (including, but not limited to, procurement of substitute goods or services;\r
-// loss of use, data, or profits; or business interruption) however caused\r
-// and on any theory of liability, whether in contract, strict liability,\r
-// or tort (including negligence or otherwise) arising in any way out of\r
-// the use of this software, even if advised of the possibility of such damage.\r
-//\r
-//M*/\r
-\r
-#include "cvtest.h"\r
-#include <string>\r
-#include <iostream>\r
-\r
-using namespace std;\r
-using namespace cv;\r
-\r
-class CV_GrabcutTest : public CvTest\r
-{\r
-public:\r
- CV_GrabcutTest();\r
- ~CV_GrabcutTest(); \r
-protected:\r
- bool verify(const Mat& mask, const Mat& exp);\r
- void run(int); \r
-};\r
-\r
-CV_GrabcutTest::CV_GrabcutTest(): CvTest( "segmentation-grabcut", "cv::grabCut" )\r
-{\r
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;\r
-}\r
-CV_GrabcutTest::~CV_GrabcutTest() {}\r
-\r
-bool CV_GrabcutTest::verify(const Mat& mask, const Mat& exp)\r
-{\r
- const float maxDiffRatio = 0.005f;\r
- int expArea = countNonZero( exp );\r
- int nonIntersectArea = countNonZero( mask != exp );\r
-\r
- float curRatio = (float)nonIntersectArea / (float)expArea;\r
- ts->printf( CvTS::LOG, "nonIntersectArea/expArea = %f\n", curRatio );\r
- return curRatio < maxDiffRatio;\r
-}\r
-\r
-void CV_GrabcutTest::run( int /* start_from */)\r
-{ \r
- DefaultRngAuto defRng;\r
- \r
- Mat img = imread(string(ts->get_data_path()) + "shared/airplane.jpg"); \r
- Mat mask_prob = imread(string(ts->get_data_path()) + "grabcut/mask_prob.png", 0);\r
- Mat exp_mask1 = imread(string(ts->get_data_path()) + "grabcut/exp_mask1.png", 0);\r
- Mat exp_mask2 = imread(string(ts->get_data_path()) + "grabcut/exp_mask2.png", 0);\r
- \r
- if (img.empty() || (!mask_prob.empty() && img.size() != mask_prob.size()) ||\r
- (!exp_mask1.empty() && img.size() != exp_mask1.size()) ||\r
- (!exp_mask2.empty() && img.size() != exp_mask2.size()) )\r
- {\r
- ts->set_failed_test_info(CvTS::FAIL_MISSING_TEST_DATA); \r
- return;\r
- }\r
- \r
- Rect rect(Point(24, 126), Point(483, 294));\r
- Mat exp_bgdModel, exp_fgdModel;\r
-\r
- Mat mask;\r
- mask = Scalar(0);\r
- Mat bgdModel, fgdModel;\r
- grabCut( img, mask, rect, bgdModel, fgdModel, 0, GC_INIT_WITH_RECT ); \r
- grabCut( img, mask, rect, bgdModel, fgdModel, 2, GC_EVAL );\r
-\r
- // Multiply images by 255 for more visuality of test data.\r
- if( mask_prob.empty() )\r
- {\r
- mask.copyTo( mask_prob );\r
- imwrite(string(ts->get_data_path()) + "grabcut/mask_prob.png", mask_prob);\r
- }\r
- if( exp_mask1.empty() )\r
- {\r
- exp_mask1 = (mask & 1) * 255;\r
- imwrite(string(ts->get_data_path()) + "grabcut/exp_mask1.png", exp_mask1);\r
- }\r
- \r
- if (!verify((mask & 1) * 255, exp_mask1))\r
- { \r
- ts->set_failed_test_info(CvTS::FAIL_MISMATCH); \r
- return;\r
- }\r
- \r
- mask = mask_prob;\r
- bgdModel.release();\r
- fgdModel.release(); \r
- rect = Rect();\r
- grabCut( img, mask, rect, bgdModel, fgdModel, 0, GC_INIT_WITH_MASK );\r
- grabCut( img, mask, rect, bgdModel, fgdModel, 1, GC_EVAL );\r
-\r
- if( exp_mask2.empty() )\r
- {\r
- exp_mask2 = (mask & 1) * 255;\r
- imwrite(string(ts->get_data_path()) + "grabcut/exp_mask2.png", exp_mask2);\r
- }\r
- \r
- if (!verify((mask & 1) * 255, exp_mask2))\r
- {\r
- ts->set_failed_test_info(CvTS::FAIL_MISMATCH); \r
- return;\r
- } \r
- ts->set_failed_test_info(CvTS::OK); \r
-}\r
-\r
-CV_GrabcutTest grabcut_test;\r
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////\r
-//\r
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.\r
-//\r
-// By downloading, copying, installing or using the software you agree to this license.\r
-// If you do not agree to this license, do not download, install,\r
-// copy or use the software.\r
-//\r
-//\r
-// License Agreement\r
-// For Open Source Computer Vision Library\r
-//\r
-// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.\r
-// Copyright (C) 2009, Willow Garage Inc., all rights reserved.\r
-// Third party copyrights are property of their respective owners.\r
-//\r
-// Redistribution and use in source and binary forms, with or without modification,\r
-// are permitted provided that the following conditions are met:\r
-//\r
-// * Redistribution's of source code must retain the above copyright notice,\r
-// this list of conditions and the following disclaimer.\r
-//\r
-// * Redistribution's in binary form must reproduce the above copyright notice,\r
-// this list of conditions and the following disclaimer in the documentation\r
-// and/or other materials provided with the distribution.\r
-//\r
-// * The name of the copyright holders may not be used to endorse or promote products\r
-// derived from this software without specific prior written permission.\r
-//\r
-// This software is provided by the copyright holders and contributors "as is" and\r
-// any express or implied warranties, including, but not limited to, the implied\r
-// warranties of merchantability and fitness for a particular purpose are disclaimed.\r
-// In no event shall the Intel Corporation or contributors be liable for any direct,\r
-// indirect, incidental, special, exemplary, or consequential damages\r
-// (including, but not limited to, procurement of substitute goods or services;\r
-// loss of use, data, or profits; or business interruption) however caused\r
-// and on any theory of liability, whether in contract, strict liability,\r
-// or tort (including negligence or otherwise) arising in any way out of\r
-// the use of this software, even if advised of the possibility of such damage.\r
-//\r
-//M*/\r
-\r
-#include "cvtest.h"\r
-#include <string>\r
-#include <iostream>\r
-#include <fstream>\r
-#include <iterator>\r
-//#include <iostream>\r
-#include "cvaux.h"\r
-\r
-using namespace cv;\r
-using namespace std;\r
-\r
-#if defined WIN32 || defined _WIN32\r
-//#if 0\r
- \r
-#else\r
-\r
-#define MARKERS1\r
-\r
-#ifdef MARKERS\r
- #define marker(x) cout << (x) << endl\r
-#else\r
- #define marker(x) \r
-#endif\r
-\r
-struct TempDirHolder\r
-{\r
- string temp_folder;\r
- TempDirHolder()\r
- {\r
- char* p = tmpnam(0);\r
- if(p[0] == '\\') p++;\r
- temp_folder = string(p);\r
- exec_cmd("mkdir " + temp_folder);\r
- } \r
- ~TempDirHolder() { exec_cmd("rm -rf " + temp_folder); }\r
- static void exec_cmd(const string& cmd) { marker(cmd); int res = system( cmd.c_str() ); (void)res; }\r
- \r
- TempDirHolder& operator=(const TempDirHolder&);\r
-};\r
-\r
-\r
-class CV_HighGuiTest : public CvTest\r
-{\r
-public:\r
- CV_HighGuiTest();\r
- ~CV_HighGuiTest(); \r
-protected: \r
- void run(int);\r
- \r
- bool ImagesTest(const string& dir, const string& tmp);\r
- bool VideoTest(const string& dir, const string& tmp, int fourcc);\r
- \r
- bool GuiTest(const string& dir, const string& tmp);\r
-};\r
-\r
-CV_HighGuiTest::CV_HighGuiTest(): CvTest( "z-highgui", "?" )\r
-{\r
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;\r
-}\r
-CV_HighGuiTest::~CV_HighGuiTest() {}\r
-\r
-double PSNR(const Mat& m1, const Mat& m2)\r
-{ \r
- Mat tmp;\r
- absdiff( m1.reshape(1), m2.reshape(1), tmp);\r
- multiply(tmp, tmp, tmp);\r
- \r
- double MSE = 1.0/(tmp.cols * tmp.rows) * sum(tmp)[0];\r
- \r
- return 20 * log10(255.0 / sqrt(MSE)); \r
-}\r
-\r
-bool CV_HighGuiTest::ImagesTest(const string& dir, const string& tmp)\r
-{\r
- int code = CvTS::OK;\r
- Mat image = imread(dir + "shared/baboon.jpg");\r
- \r
- if (image.empty())\r
- {\r
- ts->set_failed_test_info(CvTS::FAIL_MISSING_TEST_DATA);\r
- return false;\r
- } \r
- \r
- const string exts[] = {"png", "bmp", "tiff", "jpg", "jp2", "ppm", "ras"}; \r
- const size_t ext_num = sizeof(exts)/sizeof(exts[0]); \r
- \r
- for(size_t i = 0; i < ext_num; ++i)\r
- {\r
- ts->printf(CvTS::LOG, "ext=%s\n", exts[i].c_str());\r
- string ext = exts[i];\r
- string full_name = tmp + "/img." + ext;\r
- marker(exts[i]); \r
- \r
- imwrite(full_name, image); \r
- Mat loaded = imread(full_name); \r
- if (loaded.empty())\r
- {\r
- ts->printf(CvTS::LOG, "Reading failed at fmt=%s\n", ext.c_str());\r
- code = CvTS::FAIL_MISMATCH;\r
- continue;\r
- } \r
- \r
- const double thresDbell = 20;\r
- double psnr = PSNR(loaded, image);\r
- if (psnr < thresDbell)\r
- {\r
- ts->printf(CvTS::LOG, "Reading image from file: too big difference (=%g) with fmt=%s\n", psnr, ext.c_str());\r
- code = CvTS::FAIL_BAD_ACCURACY;\r
- continue; \r
- } \r
- \r
- FILE *f = fopen(full_name.c_str(), "rb");\r
- fseek(f, 0, SEEK_END);\r
- size_t len = ftell(f); \r
- vector<uchar> from_file(len);\r
- fseek(f, 0, SEEK_SET);\r
- size_t read = fread(&from_file[0], len, sizeof(vector<uchar>::value_type), f); (void)read;\r
- fclose(f);\r
-\r
- \r
- vector<uchar> buf; \r
- imencode("." + exts[i], image, buf);\r
- \r
- if (buf != from_file)\r
- {\r
- ts->printf(CvTS::LOG, "Encoding failed with fmt=%s\n", ext.c_str());\r
- code = CvTS::FAIL_MISMATCH;\r
- continue; \r
- } \r
- \r
- Mat buf_loaded = imdecode(Mat(buf), 1);\r
- if (buf_loaded.empty())\r
- {\r
- ts->printf(CvTS::LOG, "Decoding failed with fmt=%s\n", ext.c_str());\r
- code = CvTS::FAIL_MISMATCH;\r
- continue; \r
- }\r
-\r
- \r
- psnr = PSNR(buf_loaded, image);\r
- if (psnr < thresDbell)\r
- {\r
- ts->printf(CvTS::LOG, "Decoding image from memory: too small PSNR (=%gdb) with fmt=%s\n", psnr, ext.c_str());\r
- code = CvTS::FAIL_MISMATCH;\r
- continue; \r
- } \r
- }\r
- ts->set_failed_test_info(code); \r
- return code == CvTS::OK; \r
-}\r
-\r
-bool CV_HighGuiTest::VideoTest(const string& dir, const string& tmp, int fourcc)\r
-{ \r
- string src_file = dir + "shared/video_for_test.avi"; \r
- string tmp_name = tmp + "/video.avi";\r
- \r
- CvCapture* cap = cvCaptureFromFile(src_file.c_str());\r
- \r
- if (!cap)\r
- {\r
- ts->set_failed_test_info(CvTS::FAIL_MISMATCH);\r
- return false;\r
- }\r
- \r
- CvVideoWriter* writer = 0;\r
- \r
- int counter = 0;\r
- for(;;)\r
- {\r
- IplImage* img = cvQueryFrame( cap );\r
-\r
- if (!img)\r
- break;\r
- \r
- if (writer == 0) \r
- {\r
- writer = cvCreateVideoWriter(tmp_name.c_str(), fourcc, 24, cvGetSize(img)); \r
- if (writer == 0)\r
- {\r
- marker("can't craete writer");\r
- cvReleaseCapture( &cap );\r
- ts->set_failed_test_info(CvTS::FAIL_MISMATCH);\r
- return false; \r
- }\r
- }\r
- \r
- cvWriteFrame(writer, img); \r
- } \r
- \r
-\r
- cvReleaseVideoWriter( &writer ); \r
- cvReleaseCapture( &cap );\r
- \r
- marker("mid++");\r
- \r
- cap = cvCaptureFromFile(src_file.c_str());\r
- marker("mid1");\r
- CvCapture *saved = cvCaptureFromFile(tmp_name.c_str()); \r
- if (!saved)\r
- {\r
- ts->set_failed_test_info(CvTS::FAIL_MISMATCH);\r
- return false; \r
- }\r
-\r
-\r
- const double thresDbell = 20; \r
- \r
- bool error = false;\r
- counter = 0;\r
- for(;;)\r
- { \r
-\r
- IplImage* ipl = cvQueryFrame( cap );\r
- IplImage* ipl1 = cvQueryFrame( saved );\r
-\r
- \r
- if (!ipl || !ipl1)\r
- break;\r
- \r
- Mat img(ipl); \r
- Mat img1(ipl1); \r
- \r
- if (PSNR(img1, img) < thresDbell)\r
- { \r
- error = true;\r
- break; \r
- } \r
- } \r
- \r
- cvReleaseCapture( &cap );\r
- cvReleaseCapture( &saved );\r
- \r
- if (error)\r
- {\r
- ts->set_failed_test_info(CvTS::FAIL_MISMATCH);\r
- return false; \r
- }\r
- \r
- return true; \r
-}\r
-\r
-\r
-void CV_HighGuiTest::run( int /*start_from */)\r
-{ \r
- TempDirHolder th;\r
- \r
- if (!ImagesTest(ts->get_data_path(), th.temp_folder))\r
- return;\r
-\r
-#if defined WIN32 || defined __linux__\r
-\r
-#if !defined HAVE_GSTREAMER || defined HAVE_GSTREAMER_APP \r
- if (!VideoTest(ts->get_data_path(), th.temp_folder, CV_FOURCC_DEFAULT))\r
- return; \r
-\r
-\r
- if (!VideoTest(ts->get_data_path(), th.temp_folder, CV_FOURCC('M', 'J', 'P', 'G')))\r
- return;\r
-\r
- \r
- if (!VideoTest(ts->get_data_path(), th.temp_folder, CV_FOURCC('M', 'P', 'G', '2')))\r
- return; \r
-\r
-#endif\r
- //if (!VideoTest(ts->get_data_path(), th.temp_folder, CV_FOURCC('D', 'X', '5', '0'))) return; \r
-#endif\r
- ts->set_failed_test_info(CvTS::OK);\r
-}\r
-CV_HighGuiTest HighGui_test;\r
-\r
-\r
-#endif\r
-\r
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////\r
-//\r
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.\r
-//\r
-// By downloading, copying, installing or using the software you agree to this license.\r
-// If you do not agree to this license, do not download, install,\r
-// copy or use the software.\r
-//\r
-//\r
-// License Agreement\r
-// For Open Source Computer Vision Library\r
-//\r
-// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.\r
-// Copyright (C) 2009, Willow Garage Inc., all rights reserved.\r
-// Third party copyrights are property of their respective owners.\r
-//\r
-// Redistribution and use in source and binary forms, with or without modification,\r
-// are permitted provided that the following conditions are met:\r
-//\r
-// * Redistribution's of source code must retain the above copyright notice,\r
-// this list of conditions and the following disclaimer.\r
-//\r
-// * Redistribution's in binary form must reproduce the above copyright notice,\r
-// this list of conditions and the following disclaimer in the documentation\r
-// and/or other materials provided with the distribution.\r
-//\r
-// * The name of the copyright holders may not be used to endorse or promote products\r
-// derived from this software without specific prior written permission.\r
-//\r
-// This software is provided by the copyright holders and contributors "as is" and\r
-// any express or implied warranties, including, but not limited to, the implied\r
-// warranties of merchantability and fitness for a particular purpose are disclaimed.\r
-// In no event shall the Intel Corporation or contributors be liable for any direct,\r
-// indirect, incidental, special, exemplary, or consequential damages\r
-// (including, but not limited to, procurement of substitute goods or services;\r
-// loss of use, data, or profits; or business interruption) however caused\r
-// and on any theory of liability, whether in contract, strict liability,\r
-// or tort (including negligence or otherwise) arising in any way out of\r
-// the use of this software, even if advised of the possibility of such damage.\r
-//\r
-//M*/\r
-\r
-#include "cvtest.h"\r
-#include <string>\r
-#include <iostream>\r
-#include <fstream>\r
-#include <iterator>\r
-#include <iostream>\r
-#include "cvaux.h"\r
-\r
-using namespace cv;\r
-using namespace std;\r
-\r
-//#if defined WIN32 || defined _WIN32 || defined WIN64 || defined _WIN64\r
-#define MARKERS\r
-\r
-#ifdef MARKERS\r
- #define marker(x) cout << (x) << endl\r
-#else\r
- #define marker(x) \r
-#endif\r
-\r
-\r
-class CV_HighGuiOnlyGuiTest : public CvTest\r
-{\r
-public:\r
- CV_HighGuiOnlyGuiTest();\r
- ~CV_HighGuiOnlyGuiTest(); \r
-protected: \r
- void run(int); \r
-};\r
-\r
-CV_HighGuiOnlyGuiTest::CV_HighGuiOnlyGuiTest(): CvTest( "z-highgui-gui-only", "?" )\r
-{\r
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;\r
-}\r
-CV_HighGuiOnlyGuiTest::~CV_HighGuiOnlyGuiTest() {}\r
-\r
-void Foo(int /*k*/, void* /*z*/) {}\r
-\r
-void CV_HighGuiOnlyGuiTest::run( int /*start_from */)\r
-{ \r
- cout << "GUI 1" << endl;\r
- namedWindow("Win");\r
- cout << "GUI 2" << endl;\r
- Mat m(30, 30, CV_8U); \r
- m = Scalar(128); \r
- cout << "GUI 3" << endl;\r
- imshow("Win", m); \r
- cout << "GUI 4" << endl;\r
- int value = 50;\r
- cout << "GUI 5" << endl;\r
- createTrackbar( "trackbar", "Win", &value, 100, Foo, &value); \r
- cout << "GUI 6" << endl;\r
- getTrackbarPos( "trackbar", "Win" ); \r
- cout << "GUI 7" << endl;\r
- waitKey(500); \r
- cout << "GUI 8" << endl;\r
- cvDestroyAllWindows();\r
- cout << "GUI 9" << endl;\r
- \r
- ts->set_failed_test_info(CvTS::OK);\r
-}\r
-\r
-CV_HighGuiOnlyGuiTest highGuiOnlyGui_test;\r
-\r
-\r
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////\r
-//\r
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.\r
-//\r
-// By downloading, copying, installing or using the software you agree to this license.\r
-// If you do not agree to this license, do not download, install,\r
-// copy or use the software.\r
-//\r
-//\r
-// License Agreement\r
-// For Open Source Computer Vision Library\r
-//\r
-// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.\r
-// Copyright (C) 2009, Willow Garage Inc., all rights reserved.\r
-// Third party copyrights are property of their respective owners.\r
-//\r
-// Redistribution and use in source and binary forms, with or without modification,\r
-// are permitted provided that the following conditions are met:\r
-//\r
-// * Redistribution's of source code must retain the above copyright notice,\r
-// this list of conditions and the following disclaimer.\r
-//\r
-// * Redistribution's in binary form must reproduce the above copyright notice,\r
-// this list of conditions and the following disclaimer in the documentation\r
-// and/or other materials provided with the distribution.\r
-//\r
-// * The name of the copyright holders may not be used to endorse or promote products\r
-// derived from this software without specific prior written permission.\r
-//\r
-// This software is provided by the copyright holders and contributors "as is" and\r
-// any express or implied warranties, including, but not limited to, the implied\r
-// warranties of merchantability and fitness for a particular purpose are disclaimed.\r
-// In no event shall the Intel Corporation or contributors be liable for any direct,\r
-// indirect, incidental, special, exemplary, or consequential damages\r
-// (including, but not limited to, procurement of substitute goods or services;\r
-// loss of use, data, or profits; or business interruption) however caused\r
-// and on any theory of liability, whether in contract, strict liability,\r
-// or tort (including negligence or otherwise) arising in any way out of\r
-// the use of this software, even if advised of the possibility of such damage.\r
-//\r
-//M*/\r
-\r
-#include "cvtest.h"\r
-#include <string>\r
-\r
-using namespace cv;\r
-\r
-class CV_InpaintTest : public CvTest\r
-{\r
-public:\r
- CV_InpaintTest();\r
- ~CV_InpaintTest(); \r
-protected: \r
- void run(int);\r
-};\r
-\r
-CV_InpaintTest::CV_InpaintTest(): CvTest( "inpaint", "cvInpaint" )\r
-{\r
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;\r
-}\r
-CV_InpaintTest::~CV_InpaintTest() {}\r
-\r
-void CV_InpaintTest::run( int )\r
-{\r
- string folder = string(ts->get_data_path()) + "inpaint/"; \r
- Mat orig = imread(folder + "orig.jpg"); \r
- Mat exp1 = imread(folder + "exp1.png");\r
- Mat exp2 = imread(folder + "exp2.png");\r
- Mat mask = imread(folder + "mask.png"); \r
-\r
- if (orig.empty() || exp1.empty() || exp2.empty() || mask.empty())\r
- {\r
- ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA ); \r
- return;\r
- }\r
-\r
- Mat inv_mask; \r
- mask.convertTo(inv_mask, CV_8UC3, -1.0, 255.0);\r
- \r
- Mat mask1ch;\r
- cv::cvtColor(mask, mask1ch, CV_BGR2GRAY);\r
-\r
- Mat test = orig.clone();\r
- test.setTo(Scalar::all(255), mask1ch); \r
-\r
- Mat res1, res2;\r
- inpaint( test, mask1ch, res1, 5, CV_INPAINT_NS );\r
- inpaint( test, mask1ch, res2, 5, CV_INPAINT_TELEA ); \r
- \r
- imwrite("d:/exp1.png", res1);\r
- imwrite("d:/exp2.png", res2);\r
- \r
- Mat diff1, diff2;\r
- absdiff( orig, res1, diff1 );\r
- absdiff( orig, res2, diff2 );\r
- \r
- double n1 = norm(diff1.reshape(1), NORM_INF, inv_mask.reshape(1));\r
- double n2 = norm(diff2.reshape(1), NORM_INF, inv_mask.reshape(1));\r
- \r
- if (n1 != 0 || n2 != 0)\r
- { \r
- ts->set_failed_test_info( CvTS::FAIL_MISMATCH );\r
- return;\r
- }\r
-\r
- absdiff( exp1, res1, diff1 );\r
- absdiff( exp2, res2, diff2 );\r
-\r
- n1 = norm(diff1.reshape(1), NORM_INF, mask.reshape(1));\r
- n2 = norm(diff2.reshape(1), NORM_INF, mask.reshape(1));\r
-\r
- const int jpeg_thres = 3;\r
- if (n1 > jpeg_thres || n2 > jpeg_thres) \r
- {\r
- ts->set_failed_test_info( CvTS::FAIL_BAD_ACCURACY ); \r
- return;\r
- }\r
-\r
- ts->set_failed_test_info(CvTS::OK);\r
-}\r
-\r
-CV_InpaintTest inpaint_test;\r
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////\r
-//\r
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.\r
-//\r
-// By downloading, copying, installing or using the software you agree to this license.\r
-// If you do not agree to this license, do not download, install,\r
-// copy or use the software.\r
-//\r
-//\r
-// License Agreement\r
-// For Open Source Computer Vision Library\r
-//\r
-// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.\r
-// Copyright (C) 2009, Willow Garage Inc., all rights reserved.\r
-// Third party copyrights are property of their respective owners.\r
-//\r
-// Redistribution and use in source and binary forms, with or without modification,\r
-// are permitted provided that the following conditions are met:\r
-//\r
-// * Redistribution's of source code must retain the above copyright notice,\r
-// this list of conditions and the following disclaimer.\r
-//\r
-// * Redistribution's in binary form must reproduce the above copyright notice,\r
-// this list of conditions and the following disclaimer in the documentation\r
-// and/or other materials provided with the distribution.\r
-//\r
-// * The name of the copyright holders may not be used to endorse or promote products\r
-// derived from this software without specific prior written permission.\r
-//\r
-// This software is provided by the copyright holders and contributors "as is" and\r
-// any express or implied warranties, including, but not limited to, the implied\r
-// warranties of merchantability and fitness for a particular purpose are disclaimed.\r
-// In no event shall the Intel Corporation or contributors be liable for any direct,\r
-// indirect, incidental, special, exemplary, or consequential damages\r
-// (including, but not limited to, procurement of substitute goods or services;\r
-// loss of use, data, or profits; or business interruption) however caused\r
-// and on any theory of liability, whether in contract, strict liability,\r
-// or tort (including negligence or otherwise) arising in any way out of\r
-// the use of this software, even if advised of the possibility of such damage.\r
-//\r
-//M*/\r
-\r
-#include "cvtest.h"\r
-#include <string>\r
-\r
-#ifdef HAVE_TBB\r
-#include "tbb/task_scheduler_init.h"\r
-#endif\r
-\r
-using namespace cv;\r
-\r
-const int num_detections = 3;\r
-const float true_scores[3] = {-0.383931f, -0.825876f, -0.959934f};\r
-const float score_thr = 0.05f;\r
-const CvRect true_bounding_boxes[3] = {cvRect(0, 45, 362, 452), cvRect(304, 0, 64, 80), cvRect(236, 0, 108, 59)};\r
-\r
-class CV_LatentSVMDetectorTest : public CvTest\r
-{\r
-public:\r
- CV_LatentSVMDetectorTest();\r
- ~CV_LatentSVMDetectorTest(); \r
-protected: \r
- void run(int);\r
-private:\r
- bool isEqual(CvRect r1, CvRect r2);\r
-};\r
-\r
-CV_LatentSVMDetectorTest::CV_LatentSVMDetectorTest(): CvTest( "latentsvmdetector", "cvLatentSvmDetectObjects" )\r
-{\r
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;\r
-}\r
-\r
-CV_LatentSVMDetectorTest::~CV_LatentSVMDetectorTest() {}\r
-\r
-bool CV_LatentSVMDetectorTest::isEqual(CvRect r1, CvRect r2)\r
-{\r
- return ((r1.x == r2.x) && (r1.y == r2.y) && (r1.width == r2.width) && (r1.height == r2.height));\r
-}\r
-\r
-void CV_LatentSVMDetectorTest::run( int /* start_from */)\r
-{ \r
- int numThreads = -1;\r
-#ifdef HAVE_TBB\r
- numThreads = 2;\r
- tbb::task_scheduler_init init(tbb::task_scheduler_init::deferred);\r
- init.initialize(numThreads);\r
-#endif\r
-\r
- IplImage* image = cvLoadImage(img_path.c_str());\r
- if (!image)\r
- {\r
- ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_TEST_DATA );\r
- return;\r
- }\r
-\r
- CvLatentSvmDetector* detector = cvLoadLatentSvmDetector(model_path.c_str());\r
- if (!detector)\r
- {\r
- ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_TEST_DATA );\r
- cvReleaseImage(&image);\r
- return;\r
- }\r
-\r
- CvMemStorage* storage = cvCreateMemStorage(0);\r
- CvSeq* detections = 0; \r
- detections = cvLatentSvmDetectObjects(image, detector, storage, 0.5f, numThreads);\r
-\r
- if (detections->total != num_detections)\r
- {\r
- ts->set_failed_test_info( CvTS::FAIL_MISMATCH );\r
- }\r
- else\r
- {\r
- ts->set_failed_test_info(CvTS::OK);\r
- for (int i = 0; i < detections->total; i++)\r
- {\r
- CvObjectDetection detection = *(CvObjectDetection*)cvGetSeqElem( detections, i );\r
- CvRect bounding_box = detection.rect;\r
- float score = detection.score;\r
- if ((!isEqual(bounding_box, true_bounding_boxes[i])) || (fabs(score - true_scores[i]) > score_thr))\r
- {\r
- ts->set_failed_test_info( CvTS::FAIL_MISMATCH );\r
- break;\r
- }\r
- }\r
- }\r
-\r
-#ifdef HAVE_TBB\r
- init.terminate();\r
-#endif\r
- cvReleaseMemStorage( &storage );\r
- cvReleaseLatentSvmDetector( &detector );\r
- cvReleaseImage( &image );\r
-}\r
-\r
-CV_LatentSVMDetectorTest latentsvmdetector_test;\r
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
-// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of the copyright holders may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-#include <string>
-#include <iostream>
-#include <fstream>
-#include <iterator>
-#include <limits>
-#include <numeric>
-#include "cvaux.h"
-
-using namespace cv;
-using namespace std;
-
-
-class CV_OperationsTest : public CvTest
-{
-public:
- CV_OperationsTest();
- ~CV_OperationsTest();
-protected:
- void run(int);
-
- struct test_excep
- {
- test_excep(const string& _s=string("")) : s(_s) {};
- string s;
- };
-
- bool SomeMatFunctions();
- bool TestMat();
- bool TestTemplateMat();
- bool TestMatND();
- bool TestSparseMat();
- bool operations1();
-
- void checkDiff(const Mat& m1, const Mat& m2, const string& s) { if (norm(m1, m2, NORM_INF) != 0) throw test_excep(s); }
- void checkDiffF(const Mat& m1, const Mat& m2, const string& s) { if (norm(m1, m2, NORM_INF) > 1e-5) throw test_excep(s); }
-
-};
-
-CV_OperationsTest::CV_OperationsTest(): CvTest( "operations", "?" )
-{
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;
-}
-CV_OperationsTest::~CV_OperationsTest() {}
-
-#define STR(a) STR2(a)
-#define STR2(a) #a
-
-#define CHECK_DIFF(a, b) checkDiff(a, b, "(" #a ") != (" #b ") at l." STR(__LINE__))
-#define CHECK_DIFF_FLT(a, b) checkDiffF(a, b, "(" #a ") !=(eps) (" #b ") at l." STR(__LINE__))
-
-#if defined _MSC_VER && _MSC_VER < 1400
-#define MSVC_OLD 1
-#else
-#define MSVC_OLD 0
-#endif
-
-bool CV_OperationsTest::TestMat()
-{
- try
- {
- Mat one_3x1(3, 1, CV_32F, Scalar(1.0));
- Mat shi_3x1(3, 1, CV_32F, Scalar(1.2));
- Mat shi_2x1(2, 1, CV_32F, Scalar(-1));
- Scalar shift = Scalar::all(15);
-
- float data[] = { sqrt(2.f)/2, -sqrt(2.f)/2, 1.f, sqrt(2.f)/2, sqrt(2.f)/2, 10.f };
- Mat rot_2x3(2, 3, CV_32F, data);
-
- Mat res = one_3x1 + shi_3x1 + shi_3x1 + shi_3x1;
- res = Mat(Mat(2 * rot_2x3) * res - shi_2x1) + shift;
-
- Mat tmp, res2;
- add(one_3x1, shi_3x1, tmp);
- add(tmp, shi_3x1, tmp);
- add(tmp, shi_3x1, tmp);
- gemm(rot_2x3, tmp, 2, shi_2x1, -1, res2, 0);
- add(res2, Mat(2, 1, CV_32F, shift), res2);
-
- CHECK_DIFF(res, res2);
-
- Mat mat4x4(4, 4, CV_32F);
- randu(mat4x4, Scalar(0), Scalar(10));
-
- Mat roi1 = mat4x4(Rect(Point(1, 1), Size(2, 2)));
- Mat roi2 = mat4x4(Range(1, 3), Range(1, 3));
-
- CHECK_DIFF(roi1, roi2);
- CHECK_DIFF(mat4x4, mat4x4(Rect(Point(0,0), mat4x4.size())));
-
- Mat intMat10(3, 3, CV_32S, Scalar(10));
- Mat intMat11(3, 3, CV_32S, Scalar(11));
- Mat resMat(3, 3, CV_8U, Scalar(255));
-
- CHECK_DIFF(resMat, intMat10 == intMat10);
- CHECK_DIFF(resMat, intMat10 < intMat11);
- CHECK_DIFF(resMat, intMat11 > intMat10);
- CHECK_DIFF(resMat, intMat10 <= intMat11);
- CHECK_DIFF(resMat, intMat11 >= intMat10);
- CHECK_DIFF(resMat, intMat11 != intMat10);
-
- CHECK_DIFF(resMat, intMat10 == 10.0);
- CHECK_DIFF(resMat, 10.0 == intMat10);
- CHECK_DIFF(resMat, intMat10 < 11.0);
- CHECK_DIFF(resMat, 11.0 > intMat10);
- CHECK_DIFF(resMat, 10.0 < intMat11);
- CHECK_DIFF(resMat, 11.0 >= intMat10);
- CHECK_DIFF(resMat, 10.0 <= intMat11);
- CHECK_DIFF(resMat, 10.0 != intMat11);
- CHECK_DIFF(resMat, intMat11 != 10.0);
-
- Mat eye = Mat::eye(3, 3, CV_16S);
- Mat maskMat4(3, 3, CV_16S, Scalar(4));
- Mat maskMat1(3, 3, CV_16S, Scalar(1));
- Mat maskMat5(3, 3, CV_16S, Scalar(5));
- Mat maskMat0(3, 3, CV_16S, Scalar(0));
-
- CHECK_DIFF(maskMat0, maskMat4 & maskMat1);
- CHECK_DIFF(maskMat0, Scalar(1) & maskMat4);
- CHECK_DIFF(maskMat0, maskMat4 & Scalar(1));
-
- Mat m;
- m = maskMat4.clone(); m &= maskMat1; CHECK_DIFF(maskMat0, m);
- m = maskMat4.clone(); m &= maskMat1 | maskMat1; CHECK_DIFF(maskMat0, m);
- m = maskMat4.clone(); m &= (2* maskMat1 - maskMat1); CHECK_DIFF(maskMat0, m);
-
- m = maskMat4.clone(); m &= Scalar(1); CHECK_DIFF(maskMat0, m);
- m = maskMat4.clone(); m |= maskMat1; CHECK_DIFF(maskMat5, m);
- m = maskMat5.clone(); m ^= maskMat1; CHECK_DIFF(maskMat4, m);
- m = maskMat4.clone(); m |= (2* maskMat1 - maskMat1); CHECK_DIFF(maskMat5, m);
- m = maskMat5.clone(); m ^= (2* maskMat1 - maskMat1); CHECK_DIFF(maskMat4, m);
-
- m = maskMat4.clone(); m |= Scalar(1); CHECK_DIFF(maskMat5, m);
- m = maskMat5.clone(); m ^= Scalar(1); CHECK_DIFF(maskMat4, m);
-
-
-
- CHECK_DIFF(maskMat0, (maskMat4 | maskMat4) & (maskMat1 | maskMat1));
- CHECK_DIFF(maskMat0, (maskMat4 | maskMat4) & maskMat1);
- CHECK_DIFF(maskMat0, maskMat4 & (maskMat1 | maskMat1));
- CHECK_DIFF(maskMat0, (maskMat1 | maskMat1) & Scalar(4));
- CHECK_DIFF(maskMat0, Scalar(4) & (maskMat1 | maskMat1));
-
- CHECK_DIFF(maskMat0, maskMat5 ^ (maskMat4 | maskMat1));
- CHECK_DIFF(maskMat0, (maskMat4 | maskMat1) ^ maskMat5);
- CHECK_DIFF(maskMat0, (maskMat4 + maskMat1) ^ (maskMat4 + maskMat1));
- CHECK_DIFF(maskMat0, Scalar(5) ^ (maskMat4 | Scalar(1)));
- CHECK_DIFF(maskMat1, Scalar(5) ^ maskMat4);
- CHECK_DIFF(maskMat0, Scalar(5) ^ (maskMat4 + maskMat1));
- CHECK_DIFF(maskMat5, Scalar(5) | (maskMat4 + maskMat1));
- CHECK_DIFF(maskMat0, (maskMat4 + maskMat1) ^ Scalar(5));
-
- CHECK_DIFF(maskMat5, maskMat5 | (maskMat4 ^ maskMat1));
- CHECK_DIFF(maskMat5, (maskMat4 ^ maskMat1) | maskMat5);
- CHECK_DIFF(maskMat5, maskMat5 | (maskMat4 ^ Scalar(1)));
- CHECK_DIFF(maskMat5, (maskMat4 | maskMat4) | Scalar(1));
- CHECK_DIFF(maskMat5, Scalar(1) | (maskMat4 | maskMat4));
- CHECK_DIFF(maskMat5, Scalar(1) | maskMat4);
- CHECK_DIFF(maskMat5, (maskMat5 | maskMat5) | (maskMat4 ^ maskMat1));
-
- CHECK_DIFF(maskMat1, min(maskMat1, maskMat5));
- CHECK_DIFF(maskMat1, min(Mat(maskMat1 | maskMat1), maskMat5 | maskMat5));
- CHECK_DIFF(maskMat5, max(maskMat1, maskMat5));
- CHECK_DIFF(maskMat5, max(Mat(maskMat1 | maskMat1), maskMat5 | maskMat5));
-
- CHECK_DIFF(maskMat1, min(maskMat1, maskMat5 | maskMat5));
- CHECK_DIFF(maskMat1, min(maskMat1 | maskMat1, maskMat5));
- CHECK_DIFF(maskMat5, max(maskMat1 | maskMat1, maskMat5));
- CHECK_DIFF(maskMat5, max(maskMat1, maskMat5 | maskMat5));
-
- CHECK_DIFF(~maskMat1, maskMat1 ^ -1);
- CHECK_DIFF(~(maskMat1 | maskMat1), maskMat1 ^ -1);
-
- CHECK_DIFF(maskMat1, maskMat4/4.0);
-
- /////////////////////////////
-
- CHECK_DIFF(1.0 - (maskMat5 | maskMat5), -maskMat4);
- CHECK_DIFF((maskMat4 | maskMat4) * 1.0 + 1.0, maskMat5);
- CHECK_DIFF(1.0 + (maskMat4 | maskMat4) * 1.0, maskMat5);
- CHECK_DIFF((maskMat5 | maskMat5) * 1.0 - 1.0, maskMat4);
- CHECK_DIFF(5.0 - (maskMat4 | maskMat4) * 1.0, maskMat1);
- CHECK_DIFF((maskMat4 | maskMat4) * 1.0 + 0.5 + 0.5, maskMat5);
- CHECK_DIFF(0.5 + ((maskMat4 | maskMat4) * 1.0 + 0.5), maskMat5);
- CHECK_DIFF(((maskMat4 | maskMat4) * 1.0 + 2.0) - 1.0, maskMat5);
- CHECK_DIFF(5.0 - ((maskMat1 | maskMat1) * 1.0 + 3.0), maskMat1);
- CHECK_DIFF( ( (maskMat1 | maskMat1) * 2.0 + 2.0) * 1.25, maskMat5);
- CHECK_DIFF( 1.25 * ( (maskMat1 | maskMat1) * 2.0 + 2.0), maskMat5);
- CHECK_DIFF( -( (maskMat1 | maskMat1) * (-2.0) + 1.0), maskMat1);
- CHECK_DIFF( maskMat1 * 1.0 + maskMat4 * 0.5 + 2.0, maskMat5);
- CHECK_DIFF( 1.0 + (maskMat1 * 1.0 + maskMat4 * 0.5 + 1.0), maskMat5);
- CHECK_DIFF( (maskMat1 * 1.0 + maskMat4 * 0.5 + 2.0) - 1.0, maskMat4);
- CHECK_DIFF(5.0 - (maskMat1 * 1.0 + maskMat4 * 0.5 + 1.0), maskMat1);
- CHECK_DIFF((maskMat1 * 1.0 + maskMat4 * 0.5 + 1.0)*1.25, maskMat5);
- CHECK_DIFF(1.25 * (maskMat1 * 1.0 + maskMat4 * 0.5 + 1.0), maskMat5);
- CHECK_DIFF(-(maskMat1 * 2.0 + maskMat4 * (-1) + 1.0), maskMat1);
- CHECK_DIFF((maskMat1 * 1.0 + maskMat4), maskMat5);
- CHECK_DIFF((maskMat4 + maskMat1 * 1.0), maskMat5);
- CHECK_DIFF((maskMat1 * 3.0 + 1.0) + maskMat1, maskMat5);
- CHECK_DIFF(maskMat1 + (maskMat1 * 3.0 + 1.0), maskMat5);
- CHECK_DIFF(maskMat1*4.0 + (maskMat1 | maskMat1), maskMat5);
- CHECK_DIFF((maskMat1 | maskMat1) + maskMat1*4.0, maskMat5);
- CHECK_DIFF((maskMat1*3.0 + 1.0) + (maskMat1 | maskMat1), maskMat5);
- CHECK_DIFF((maskMat1 | maskMat1) + (maskMat1*3.0 + 1.0), maskMat5);
- CHECK_DIFF(maskMat1*4.0 + maskMat4*2.0, maskMat1 * 12);
- CHECK_DIFF((maskMat1*3.0 + 1.0) + maskMat4*2.0, maskMat1 * 12);
- CHECK_DIFF(maskMat4*2.0 + (maskMat1*3.0 + 1.0), maskMat1 * 12);
- CHECK_DIFF((maskMat1*3.0 + 1.0) + (maskMat1*2.0 + 2.0), maskMat1 * 8);
-
- CHECK_DIFF(maskMat5*1.0 - maskMat4, maskMat1);
- CHECK_DIFF(maskMat5 - maskMat1 * 4.0, maskMat1);
- CHECK_DIFF((maskMat4 * 1.0 + 4.0)- maskMat4, maskMat4);
- CHECK_DIFF(maskMat5 - (maskMat1 * 2.0 + 2.0), maskMat1);
- CHECK_DIFF(maskMat5*1.0 - (maskMat4 | maskMat4), maskMat1);
- CHECK_DIFF((maskMat5 | maskMat5) - maskMat1 * 4.0, maskMat1);
- CHECK_DIFF((maskMat4 * 1.0 + 4.0)- (maskMat4 | maskMat4), maskMat4);
- CHECK_DIFF((maskMat5 | maskMat5) - (maskMat1 * 2.0 + 2.0), maskMat1);
- CHECK_DIFF(maskMat1*5.0 - maskMat4 * 1.0, maskMat1);
- CHECK_DIFF((maskMat1*5.0 + 3.0)- maskMat4 * 1.0, maskMat4);
- CHECK_DIFF(maskMat4 * 2.0 - (maskMat1*4.0 + 3.0), maskMat1);
- CHECK_DIFF((maskMat1 * 2.0 + 3.0) - (maskMat1*3.0 + 1.0), maskMat1);
-
- CHECK_DIFF((maskMat5 - maskMat4)* 4.0, maskMat4);
- CHECK_DIFF(4.0 * (maskMat5 - maskMat4), maskMat4);
-
- CHECK_DIFF(-((maskMat4 | maskMat4) - (maskMat5 | maskMat5)), maskMat1);
-
- CHECK_DIFF(4.0 * (maskMat1 | maskMat1), maskMat4);
- CHECK_DIFF((maskMat4 | maskMat4)/4.0, maskMat1);
-
-#if !MSVC_OLD
- CHECK_DIFF(2.0 * (maskMat1 * 2.0) , maskMat4);
-#endif
- CHECK_DIFF((maskMat4 / 2.0) / 2.0 , maskMat1);
- CHECK_DIFF(-(maskMat4 - maskMat5) , maskMat1);
- CHECK_DIFF(-((maskMat4 - maskMat5) * 1.0), maskMat1);
-
-
- /////////////////////////////
- CHECK_DIFF(maskMat4 / maskMat4, maskMat1);
-
- ///// Element-wise multiplication
-
- CHECK_DIFF(maskMat4.mul(maskMat4, 0.25), maskMat4);
- CHECK_DIFF(maskMat4.mul(maskMat1 * 4, 0.25), maskMat4);
- CHECK_DIFF(maskMat4.mul(maskMat4 / 4), maskMat4);
- CHECK_DIFF(maskMat4.mul(maskMat4 / 4), maskMat4);
- CHECK_DIFF(maskMat4.mul(maskMat4) * 0.25, maskMat4);
- CHECK_DIFF(0.25 * maskMat4.mul(maskMat4), maskMat4);
-
- ////// Element-wise division
-
- CHECK_DIFF(maskMat4 / maskMat4, maskMat1);
- CHECK_DIFF((maskMat4 & maskMat4) / (maskMat1 * 4), maskMat1);
-
- CHECK_DIFF((maskMat4 & maskMat4) / maskMat4, maskMat1);
- CHECK_DIFF(maskMat4 / (maskMat4 & maskMat4), maskMat1);
- CHECK_DIFF((maskMat1 * 4) / maskMat4, maskMat1);
-
- CHECK_DIFF(maskMat4 / (maskMat1 * 4), maskMat1);
- CHECK_DIFF((maskMat4 * 0.5 )/ (maskMat1 * 2), maskMat1);
-
- CHECK_DIFF(maskMat4 / maskMat4.mul(maskMat1), maskMat1);
- CHECK_DIFF((maskMat4 & maskMat4) / maskMat4.mul(maskMat1), maskMat1);
-
- CHECK_DIFF(4.0 / maskMat4, maskMat1);
- CHECK_DIFF(4.0 / (maskMat4 | maskMat4), maskMat1);
- CHECK_DIFF(4.0 / (maskMat1 * 4.0), maskMat1);
- CHECK_DIFF(4.0 / (maskMat4 / maskMat1), maskMat1);
-
- m = maskMat4.clone(); m/=4.0; CHECK_DIFF(m, maskMat1);
- m = maskMat4.clone(); m/=maskMat4; CHECK_DIFF(m, maskMat1);
- m = maskMat4.clone(); m/=(maskMat1 * 4.0); CHECK_DIFF(m, maskMat1);
- m = maskMat4.clone(); m/=(maskMat4 / maskMat1); CHECK_DIFF(m, maskMat1);
-
- /////////////////////////////
- float matrix_data[] = { 3, 1, -4, -5, 1, 0, 0, 1.1f, 1.5f};
- Mat mt(3, 3, CV_32F, matrix_data);
- Mat mi = mt.inv();
- Mat d1 = Mat::eye(3, 3, CV_32F);
- Mat d2 = d1 * 2;
- MatExpr mt_tr = mt.t();
- MatExpr mi_tr = mi.t();
- Mat mi2 = mi * 2;
-
-
- CHECK_DIFF_FLT( mi2 * mt, d2 );
- CHECK_DIFF_FLT( mi * mt, d1 );
- CHECK_DIFF_FLT( mt_tr * mi_tr, d1 );
-
- m = mi.clone(); m*=mt; CHECK_DIFF_FLT(m, d1);
- m = mi.clone(); m*= (2 * mt - mt) ; CHECK_DIFF_FLT(m, d1);
-
- m = maskMat4.clone(); m+=(maskMat1 * 1.0); CHECK_DIFF(m, maskMat5);
- m = maskMat5.clone(); m-=(maskMat1 * 4.0); CHECK_DIFF(m, maskMat1);
-
- m = maskMat1.clone(); m+=(maskMat1 * 3.0 + 1.0); CHECK_DIFF(m, maskMat5);
- m = maskMat5.clone(); m-=(maskMat1 * 3.0 + 1.0); CHECK_DIFF(m, maskMat1);
-#if !MSVC_OLD
- m = mi.clone(); m+=(3.0 * mi * mt + d1); CHECK_DIFF_FLT(m, mi + d1 * 4);
- m = mi.clone(); m-=(3.0 * mi * mt + d1); CHECK_DIFF_FLT(m, mi - d1 * 4);
- m = mi.clone(); m*=(mt * 1.0); CHECK_DIFF_FLT(m, d1);
- m = mi.clone(); m*=(mt * 1.0 + Mat::eye(m.size(), m.type())); CHECK_DIFF_FLT(m, d1 + mi);
- m = mi.clone(); m*=mt_tr.t(); CHECK_DIFF_FLT(m, d1);
-
- CHECK_DIFF_FLT( (mi * 2) * mt, d2);
- CHECK_DIFF_FLT( mi * (2 * mt), d2);
- CHECK_DIFF_FLT( mt.t() * mi_tr, d1 );
- CHECK_DIFF_FLT( mt_tr * mi.t(), d1 );
- CHECK_DIFF_FLT( (mi * 0.4) * (mt * 5), d2);
-
- CHECK_DIFF_FLT( mt.t() * (mi_tr * 2), d2 );
- CHECK_DIFF_FLT( (mt_tr * 2) * mi.t(), d2 );
-
- CHECK_DIFF_FLT(mt.t() * mi.t(), d1);
- CHECK_DIFF_FLT( (mi * mt) * 2.0, d2);
- CHECK_DIFF_FLT( 2.0 * (mi * mt), d2);
- CHECK_DIFF_FLT( -(mi * mt), -d1);
-
- CHECK_DIFF_FLT( (mi * mt) / 2.0, d1 / 2);
-
- Mat mt_mul_2_plus_1;
- gemm(mt, d1, 2, Mat::ones(3, 3, CV_32F), 1, mt_mul_2_plus_1);
-
- CHECK_DIFF( (mt * 2.0 + 1.0) * mi, mt_mul_2_plus_1 * mi); // (A*alpha + beta)*B
- CHECK_DIFF( mi * (mt * 2.0 + 1.0), mi * mt_mul_2_plus_1); // A*(B*alpha + beta)
- CHECK_DIFF( (mt * 2.0 + 1.0) * (mi * 2), mt_mul_2_plus_1 * mi2); // (A*alpha + beta)*(B*gamma)
- CHECK_DIFF( (mi *2)* (mt * 2.0 + 1.0), mi2 * mt_mul_2_plus_1); // (A*gamma)*(B*alpha + beta)
- CHECK_DIFF_FLT( (mt * 2.0 + 1.0) * mi.t(), mt_mul_2_plus_1 * mi_tr); // (A*alpha + beta)*B^t
- CHECK_DIFF_FLT( mi.t() * (mt * 2.0 + 1.0), mi_tr * mt_mul_2_plus_1); // A^t*(B*alpha + beta)
-
- CHECK_DIFF_FLT( (mi * mt + d2)*5, d1 * 3 * 5);
- CHECK_DIFF_FLT( mi * mt + d2, d1 * 3);
- CHECK_DIFF_FLT( -(mi * mt) + d2, d1);
- CHECK_DIFF_FLT( (mi * mt) + d1, d2);
- CHECK_DIFF_FLT( d1 + (mi * mt), d2);
- CHECK_DIFF_FLT( (mi * mt) - d2, -d1);
- CHECK_DIFF_FLT( d2 - (mi * mt), d1);
-
- CHECK_DIFF_FLT( (mi * mt) + d2 * 0.5, d2);
- CHECK_DIFF_FLT( d2 * 0.5 + (mi * mt), d2);
- CHECK_DIFF_FLT( (mi * mt) - d1 * 2, -d1);
- CHECK_DIFF_FLT( d1 * 2 - (mi * mt), d1);
-
- CHECK_DIFF_FLT( (mi * mt) + mi.t(), mi_tr + d1);
- CHECK_DIFF_FLT( mi.t() + (mi * mt), mi_tr + d1);
- CHECK_DIFF_FLT( (mi * mt) - mi.t(), d1 - mi_tr);
- CHECK_DIFF_FLT( mi.t() - (mi * mt), mi_tr - d1);
-
- CHECK_DIFF_FLT( 2.0 *(mi * mt + d2), d1 * 6);
- CHECK_DIFF_FLT( -(mi * mt + d2), d1 * -3);
-
- CHECK_DIFF_FLT(mt.inv() * mt, d1);
-
- CHECK_DIFF_FLT(mt.inv() * (2*mt - mt), d1);
-#endif
- }
- catch (const test_excep& e)
- {
- ts->printf(CvTS::LOG, "%s\n", e.s.c_str());
- ts->set_failed_test_info(CvTS::FAIL_MISMATCH);
- return false;
- }
- return true;
-}
-
-bool CV_OperationsTest::SomeMatFunctions()
-{
- try
- {
- Mat rgba( 10, 10, CV_8UC4, Scalar(1,2,3,4) );
- Mat bgr( rgba.rows, rgba.cols, CV_8UC3 );
- Mat alpha( rgba.rows, rgba.cols, CV_8UC1 );
- Mat out[] = { bgr, alpha };
- // rgba[0] -> bgr[2], rgba[1] -> bgr[1],
- // rgba[2] -> bgr[0], rgba[3] -> alpha[0]
- int from_to[] = { 0,2, 1,1, 2,0, 3,3 };
- mixChannels( &rgba, 1, out, 2, from_to, 4 );
-
- Mat bgr_exp( rgba.size(), CV_8UC3, Scalar(3,2,1));
- Mat alpha_exp( rgba.size(), CV_8UC1, Scalar(4));
-
- CHECK_DIFF(bgr_exp, bgr);
- CHECK_DIFF(alpha_exp, alpha);
- }
- catch (const test_excep& e)
- {
- ts->printf(CvTS::LOG, "%s\n", e.s.c_str());
- ts->set_failed_test_info(CvTS::FAIL_MISMATCH);
- return false;
- }
- return true;
-
-}
-
-
-bool CV_OperationsTest::TestTemplateMat()
-{
- try
- {
- Mat_<float> one_3x1(3, 1, 1.0f);
- Mat_<float> shi_3x1(3, 1, 1.2f);
- Mat_<float> shi_2x1(2, 1, -2);
- Scalar shift = Scalar::all(15);
-
- float data[] = { sqrt(2.f)/2, -sqrt(2.f)/2, 1.f, sqrt(2.f)/2, sqrt(2.f)/2, 10.f };
- Mat_<float> rot_2x3(2, 3, data);
-
- Mat_<float> res = Mat(Mat(2 * rot_2x3) * Mat(one_3x1 + shi_3x1 + shi_3x1 + shi_3x1) - shi_2x1) + shift;
- Mat_<float> resS = rot_2x3 * one_3x1;
-
- Mat_<float> tmp, res2, resS2;
- add(one_3x1, shi_3x1, tmp);
- add(tmp, shi_3x1, tmp);
- add(tmp, shi_3x1, tmp);
- gemm(rot_2x3, tmp, 2, shi_2x1, -1, res2, 0);
- add(res2, Mat(2, 1, CV_32F, shift), res2);
-
- gemm(rot_2x3, one_3x1, 1, shi_2x1, 0, resS2, 0);
- CHECK_DIFF(res, res2);
- CHECK_DIFF(resS, resS2);
-
-
- Mat_<float> mat4x4(4, 4);
- randu(mat4x4, Scalar(0), Scalar(10));
-
- Mat_<float> roi1 = mat4x4(Rect(Point(1, 1), Size(2, 2)));
- Mat_<float> roi2 = mat4x4(Range(1, 3), Range(1, 3));
-
- CHECK_DIFF(roi1, roi2);
- CHECK_DIFF(mat4x4, mat4x4(Rect(Point(0,0), mat4x4.size())));
-
- Mat_<int> intMat10(3, 3, 10);
- Mat_<int> intMat11(3, 3, 11);
- Mat_<uchar> resMat(3, 3, 255);
-
- CHECK_DIFF(resMat, intMat10 == intMat10);
- CHECK_DIFF(resMat, intMat10 < intMat11);
- CHECK_DIFF(resMat, intMat11 > intMat10);
- CHECK_DIFF(resMat, intMat10 <= intMat11);
- CHECK_DIFF(resMat, intMat11 >= intMat10);
-
- CHECK_DIFF(resMat, intMat10 == 10.0);
- CHECK_DIFF(resMat, intMat10 < 11.0);
- CHECK_DIFF(resMat, intMat11 > 10.0);
- CHECK_DIFF(resMat, intMat10 <= 11.0);
- CHECK_DIFF(resMat, intMat11 >= 10.0);
-
- Mat_<uchar> maskMat4(3, 3, 4);
- Mat_<uchar> maskMat1(3, 3, 1);
- Mat_<uchar> maskMat5(3, 3, 5);
- Mat_<uchar> maskMat0(3, 3, (uchar)0);
-
- CHECK_DIFF(maskMat0, maskMat4 & maskMat1);
- CHECK_DIFF(maskMat0, Scalar(1) & maskMat4);
- CHECK_DIFF(maskMat0, maskMat4 & Scalar(1));
-
- Mat_<uchar> m;
- m = maskMat4.clone(); m&=maskMat1; CHECK_DIFF(maskMat0, m);
- m = maskMat4.clone(); m&=Scalar(1); CHECK_DIFF(maskMat0, m);
-
- m = maskMat4.clone(); m|=maskMat1; CHECK_DIFF(maskMat5, m);
- m = maskMat4.clone(); m^=maskMat1; CHECK_DIFF(maskMat5, m);
-
- CHECK_DIFF(maskMat0, (maskMat4 | maskMat4) & (maskMat1 | maskMat1));
- CHECK_DIFF(maskMat0, (maskMat4 | maskMat4) & maskMat1);
- CHECK_DIFF(maskMat0, maskMat4 & (maskMat1 | maskMat1));
-
- CHECK_DIFF(maskMat0, maskMat5 ^ (maskMat4 | maskMat1));
- CHECK_DIFF(maskMat0, Scalar(5) ^ (maskMat4 | Scalar(1)));
-
- CHECK_DIFF(maskMat5, maskMat5 | (maskMat4 ^ maskMat1));
- CHECK_DIFF(maskMat5, maskMat5 | (maskMat4 ^ Scalar(1)));
-
- CHECK_DIFF(~maskMat1, maskMat1 ^ 0xFF);
- CHECK_DIFF(~(maskMat1 | maskMat1), maskMat1 ^ 0xFF);
-
- CHECK_DIFF(maskMat1 + maskMat4, maskMat5);
- CHECK_DIFF(maskMat1 + Scalar(4), maskMat5);
- CHECK_DIFF(Scalar(4) + maskMat1, maskMat5);
- CHECK_DIFF(Scalar(4) + (maskMat1 & maskMat1), maskMat5);
-
- CHECK_DIFF(maskMat1 + 4.0, maskMat5);
- CHECK_DIFF((maskMat1 & 0xFF) + 4.0, maskMat5);
- CHECK_DIFF(4.0 + maskMat1, maskMat5);
-
- m = maskMat4.clone(); m+=Scalar(1); CHECK_DIFF(m, maskMat5);
- m = maskMat4.clone(); m+=maskMat1; CHECK_DIFF(m, maskMat5);
- m = maskMat4.clone(); m+=(maskMat1 | maskMat1); CHECK_DIFF(m, maskMat5);
-
- CHECK_DIFF(maskMat5 - maskMat1, maskMat4);
- CHECK_DIFF(maskMat5 - Scalar(1), maskMat4);
- CHECK_DIFF((maskMat5 | maskMat5) - Scalar(1), maskMat4);
- CHECK_DIFF(maskMat5 - 1, maskMat4);
- CHECK_DIFF((maskMat5 | maskMat5) - 1, maskMat4);
- CHECK_DIFF((maskMat5 | maskMat5) - (maskMat1 | maskMat1), maskMat4);
-
- CHECK_DIFF(maskMat1, min(maskMat1, maskMat5));
- CHECK_DIFF(maskMat5, max(maskMat1, maskMat5));
-
- m = maskMat5.clone(); m-=Scalar(1); CHECK_DIFF(m, maskMat4);
- m = maskMat5.clone(); m-=maskMat1; CHECK_DIFF(m, maskMat4);
- m = maskMat5.clone(); m-=(maskMat1 | maskMat1); CHECK_DIFF(m, maskMat4);
-
- m = maskMat4.clone(); m |= Scalar(1); CHECK_DIFF(maskMat5, m);
- m = maskMat5.clone(); m ^= Scalar(1); CHECK_DIFF(maskMat4, m);
-
- CHECK_DIFF(maskMat1, maskMat4/4.0);
-
- Mat_<float> negf(3, 3, -3.0);
- Mat_<float> posf = -negf;
- Mat_<float> posf2 = posf * 2;
- Mat_<int> negi(3, 3, -3);
-
- CHECK_DIFF(abs(negf), -negf);
- CHECK_DIFF(abs(posf - posf2), -negf);
- CHECK_DIFF(abs(negi), -(negi & negi));
-
- CHECK_DIFF(5.0 - maskMat4, maskMat1);
-
-
- CHECK_DIFF(maskMat4.mul(maskMat4, 0.25), maskMat4);
- CHECK_DIFF(maskMat4.mul(maskMat1 * 4, 0.25), maskMat4);
- CHECK_DIFF(maskMat4.mul(maskMat4 / 4), maskMat4);
-
-
- ////// Element-wise division
-
- CHECK_DIFF(maskMat4 / maskMat4, maskMat1);
- CHECK_DIFF(4.0 / maskMat4, maskMat1);
- m = maskMat4.clone(); m/=4.0; CHECK_DIFF(m, maskMat1);
-
- ////////////////////////////////
-
- typedef Mat_<int> TestMat_t;
-
- const TestMat_t cnegi = negi.clone();
-
- TestMat_t::iterator beg = negi.begin();
- TestMat_t::iterator end = negi.end();
-
- TestMat_t::const_iterator cbeg = cnegi.begin();
- TestMat_t::const_iterator cend = cnegi.end();
-
- int sum = 0;
- for(; beg!=end; ++beg)
- sum+=*beg;
-
- for(; cbeg!=cend; ++cbeg)
- sum-=*cbeg;
-
- if (sum != 0) throw test_excep();
-
- CHECK_DIFF(negi.col(1), negi.col(2));
- CHECK_DIFF(negi.row(1), negi.row(2));
- CHECK_DIFF(negi.col(1), negi.diag());
-
- if (Mat_<Point2f>(1, 1).elemSize1() != sizeof(float)) throw test_excep();
- if (Mat_<Point2f>(1, 1).elemSize() != 2 * sizeof(float)) throw test_excep();
- if (Mat_<Point2f>(1, 1).depth() != CV_32F) throw test_excep();
- if (Mat_<float>(1, 1).depth() != CV_32F) throw test_excep();
- if (Mat_<int>(1, 1).depth() != CV_32S) throw test_excep();
- if (Mat_<double>(1, 1).depth() != CV_64F) throw test_excep();
- if (Mat_<Point3d>(1, 1).depth() != CV_64F) throw test_excep();
- if (Mat_<signed char>(1, 1).depth() != CV_8S) throw test_excep();
- if (Mat_<unsigned short>(1, 1).depth() != CV_16U) throw test_excep();
- if (Mat_<unsigned short>(1, 1).channels() != 1) throw test_excep();
- if (Mat_<Point2f>(1, 1).channels() != 2) throw test_excep();
- if (Mat_<Point3f>(1, 1).channels() != 3) throw test_excep();
- if (Mat_<Point3d>(1, 1).channels() != 3) throw test_excep();
-
- Mat_<uchar> eye = Mat_<uchar>::zeros(2, 2); CHECK_DIFF(Mat_<uchar>::zeros(Size(2, 2)), eye);
- eye.at<uchar>(Point(0,0)) = 1; eye.at<uchar>(1, 1) = 1;
-
- CHECK_DIFF(Mat_<uchar>::eye(2, 2), eye);
- CHECK_DIFF(eye, Mat_<uchar>::eye(Size(2,2)));
-
- Mat_<uchar> ones(2, 2, (uchar)1);
- CHECK_DIFF(ones, Mat_<uchar>::ones(Size(2,2)));
- CHECK_DIFF(Mat_<uchar>::ones(2, 2), ones);
-
- Mat_<Point2f> pntMat(2, 2, Point2f(1, 0));
- if(pntMat.stepT() != 2) throw test_excep();
-
- uchar uchar_data[] = {1, 0, 0, 1};
-
- Mat_<uchar> matFromData(1, 4, uchar_data);
- const Mat_<uchar> mat2 = matFromData.clone();
- CHECK_DIFF(matFromData, eye.reshape(1));
- if (matFromData(Point(0,0)) != uchar_data[0])throw test_excep();
- if (mat2(Point(0,0)) != uchar_data[0]) throw test_excep();
-
- if (matFromData(0,0) != uchar_data[0])throw test_excep();
- if (mat2(0,0) != uchar_data[0]) throw test_excep();
-
- Mat_<uchar> rect(eye, Rect(0, 0, 1, 1));
- if (rect.cols != 1 || rect.rows != 1 || rect(0,0) != uchar_data[0]) throw test_excep();
-
- //cv::Mat_<_Tp>::adjustROI(int,int,int,int)
- //cv::Mat_<_Tp>::cross(const Mat_&) const
- //cv::Mat_<_Tp>::Mat_(const vector<_Tp>&,bool)
- //cv::Mat_<_Tp>::Mat_(int,int,_Tp*,size_t)
- //cv::Mat_<_Tp>::Mat_(int,int,const _Tp&)
- //cv::Mat_<_Tp>::Mat_(Size,const _Tp&)
- //cv::Mat_<_Tp>::mul(const Mat_<_Tp>&,double) const
- //cv::Mat_<_Tp>::mul(const MatExpr_<MatExpr_Op2_<Mat_<_Tp>,double,Mat_<_Tp>,MatOp_DivRS_<Mat> >,Mat_<_Tp> >&,double) const
- //cv::Mat_<_Tp>::mul(const MatExpr_<MatExpr_Op2_<Mat_<_Tp>,double,Mat_<_Tp>,MatOp_Scale_<Mat> >,Mat_<_Tp> >&,double) const
- //cv::Mat_<_Tp>::operator Mat_<T2>() const
- //cv::Mat_<_Tp>::operator MatExpr_<Mat_<_Tp>,Mat_<_Tp> >() const
- //cv::Mat_<_Tp>::operator()(const Range&,const Range&) const
- //cv::Mat_<_Tp>::operator()(const Rect&) const
-
- //cv::Mat_<_Tp>::operator=(const MatExpr_Base&)
- //cv::Mat_<_Tp>::operator[](int) const
-
-
- ///////////////////////////////
-
- float matrix_data[] = { 3, 1, -4, -5, 1, 0, 0, 1.1f, 1.5f};
- Mat_<float> mt(3, 3, matrix_data);
- Mat_<float> mi = mt.inv();
- Mat_<float> d1 = Mat_<float>::eye(3, 3);
- Mat_<float> d2 = d1 * 2;
- Mat_<float> mt_tr = mt.t();
- Mat_<float> mi_tr = mi.t();
- Mat_<float> mi2 = mi * 2;
-
- CHECK_DIFF_FLT( mi2 * mt, d2 );
- CHECK_DIFF_FLT( mi * mt, d1 );
- CHECK_DIFF_FLT( mt_tr * mi_tr, d1 );
-
- Mat_<float> mf;
- mf = mi.clone(); mf*=mt; CHECK_DIFF_FLT(mf, d1);
-
- ////// typedefs //////
-
- if (Mat1b(1, 1).elemSize() != sizeof(uchar)) throw test_excep();
- if (Mat2b(1, 1).elemSize() != 2 * sizeof(uchar)) throw test_excep();
- if (Mat3b(1, 1).elemSize() != 3 * sizeof(uchar)) throw test_excep();
- if (Mat1f(1, 1).elemSize() != sizeof(float)) throw test_excep();
- if (Mat2f(1, 1).elemSize() != 2 * sizeof(float)) throw test_excep();
- if (Mat3f(1, 1).elemSize() != 3 * sizeof(float)) throw test_excep();
- if (Mat1f(1, 1).depth() != CV_32F) throw test_excep();
- if (Mat3f(1, 1).depth() != CV_32F) throw test_excep();
- if (Mat3f(1, 1).type() != CV_32FC3) throw test_excep();
- if (Mat1i(1, 1).depth() != CV_32S) throw test_excep();
- if (Mat1d(1, 1).depth() != CV_64F) throw test_excep();
- if (Mat1b(1, 1).depth() != CV_8U) throw test_excep();
- if (Mat3b(1, 1).type() != CV_8UC3) throw test_excep();
- if (Mat1w(1, 1).depth() != CV_16U) throw test_excep();
- if (Mat1s(1, 1).depth() != CV_16S) throw test_excep();
- if (Mat1f(1, 1).channels() != 1) throw test_excep();
- if (Mat1b(1, 1).channels() != 1) throw test_excep();
- if (Mat1i(1, 1).channels() != 1) throw test_excep();
- if (Mat1w(1, 1).channels() != 1) throw test_excep();
- if (Mat1s(1, 1).channels() != 1) throw test_excep();
- if (Mat2f(1, 1).channels() != 2) throw test_excep();
- if (Mat2b(1, 1).channels() != 2) throw test_excep();
- if (Mat2i(1, 1).channels() != 2) throw test_excep();
- if (Mat2w(1, 1).channels() != 2) throw test_excep();
- if (Mat2s(1, 1).channels() != 2) throw test_excep();
- if (Mat3f(1, 1).channels() != 3) throw test_excep();
- if (Mat3b(1, 1).channels() != 3) throw test_excep();
- if (Mat3i(1, 1).channels() != 3) throw test_excep();
- if (Mat3w(1, 1).channels() != 3) throw test_excep();
- if (Mat3s(1, 1).channels() != 3) throw test_excep();
-
- }
- catch (const test_excep& e)
- {
- ts->printf(CvTS::LOG, "%s\n", e.s.c_str());
- ts->set_failed_test_info(CvTS::FAIL_MISMATCH);
- return false;
- }
- return true;
-}
-
-bool CV_OperationsTest::TestMatND()
-{
- int sizes[] = { 3, 3, 3};
- cv::MatND nd(3, sizes, CV_32F);
-
- return true;
-}
-
-bool CV_OperationsTest::TestSparseMat()
-{
- try
- {
- int sizes[] = { 10, 10, 10};
- int dims = sizeof(sizes)/sizeof(sizes[0]);
- SparseMat mat(dims, sizes, CV_32FC2);
-
- if (mat.dims() != dims) throw test_excep();
- if (mat.channels() != 2) throw test_excep();
- if (mat.depth() != CV_32F) throw test_excep();
-
- SparseMat mat2 = mat.clone();
- }
- catch (const test_excep&)
- {
- ts->set_failed_test_info(CvTS::FAIL_MISMATCH);
- return false;
- }
- return true;
-}
-
-bool CV_OperationsTest::operations1()
-{
- try
- {
- Point3d p1(1, 1, 1), p2(2, 2, 2), p4(4, 4, 4);
- p1*=2;
- if (!(p1 == p2)) throw test_excep();
- if (!(p2 * 2 == p4)) throw test_excep();
- if (!(p2 * 2.f == p4)) throw test_excep();
- if (!(p2 * 2.f == p4)) throw test_excep();
-
- Point2d pi1(1, 1), pi2(2, 2), pi4(4, 4);
- pi1*=2;
- if (!(pi1 == pi2)) throw test_excep();
- if (!(pi2 * 2 == pi4)) throw test_excep();
- if (!(pi2 * 2.f == pi4)) throw test_excep();
- if (!(pi2 * 2.f == pi4)) throw test_excep();
-
- Vec2d v12(1, 1), v22(2, 2);
- v12*=2.0;
- if (!(v12 == v22)) throw test_excep();
-
- Vec3d v13(1, 1, 1), v23(2, 2, 2);
- v13*=2.0;
- if (!(v13 == v23)) throw test_excep();
-
- Vec4d v14(1, 1, 1, 1), v24(2, 2, 2, 2);
- v14*=2.0;
- if (!(v14 == v24)) throw test_excep();
-
- Size sz(10, 20);
- if (sz.area() != 200) throw test_excep();
- if (sz.width != 10 || sz.height != 20) throw test_excep();
- if (((CvSize)sz).width != 10 || ((CvSize)sz).height != 20) throw test_excep();
-
- Vec<double, 5> v5d(1, 1, 1, 1, 1);
- Vec<double, 6> v6d(1, 1, 1, 1, 1, 1);
- Vec<double, 7> v7d(1, 1, 1, 1, 1, 1, 1);
- Vec<double, 8> v8d(1, 1, 1, 1, 1, 1, 1, 1);
- Vec<double, 9> v9d(1, 1, 1, 1, 1, 1, 1, 1, 1);
- Vec<double,10> v10d(1, 1, 1, 1, 1, 1, 1, 1, 1, 1);
-
- Vec<double,10> v10dzero;
- for (int ii = 0; ii < 10; ++ii) {
- if (!v10dzero[ii] == 0.0)
- throw test_excep();
- }
- }
- catch(const test_excep&)
- {
- ts->set_failed_test_info(CvTS::FAIL_MISMATCH);
- return false;
- }
- return true;
-}
-
-void CV_OperationsTest::run( int /* start_from */)
-{
- if (!TestMat())
- return;
-
- if (!SomeMatFunctions())
- return;
-
- if (!TestTemplateMat())
- return;
-
- /* if (!TestMatND())
- return;*/
-
- if (!TestSparseMat())
- return;
-
- if (!operations1())
- return;
-
- ts->set_failed_test_info(CvTS::OK);
-}
-
-CV_OperationsTest cv_Operations_test;
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////\r
-//\r
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.\r
-//\r
-// By downloading, copying, installing or using the software you agree to this license.\r
-// If you do not agree to this license, do not download, install,\r
-// copy or use the software.\r
-//\r
-//\r
-// License Agreement\r
-// For Open Source Computer Vision Library\r
-//\r
-// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.\r
-// Copyright (C) 2009, Willow Garage Inc., all rights reserved.\r
-// Third party copyrights are property of their respective owners.\r
-//\r
-// Redistribution and use in source and binary forms, with or without modification,\r
-// are permitted provided that the following conditions are met:\r
-//\r
-// * Redistribution's of source code must retain the above copyright notice,\r
-// this list of conditions and the following disclaimer.\r
-//\r
-// * Redistribution's in binary form must reproduce the above copyright notice,\r
-// this list of conditions and the following disclaimer in the documentation\r
-// and/or other materials provided with the distribution.\r
-//\r
-// * The name of the copyright holders may not be used to endorse or promote products\r
-// derived from this software without specific prior written permission.\r
-//\r
-// This software is provided by the copyright holders and contributors "as is" and\r
-// any express or implied warranties, including, but not limited to, the implied\r
-// warranties of merchantability and fitness for a particular purpose are disclaimed.\r
-// In no event shall the Intel Corporation or contributors be liable for any direct,\r
-// indirect, incidental, special, exemplary, or consequential damages\r
-// (including, but not limited to, procurement of substitute goods or services;\r
-// loss of use, data, or profits; or business interruption) however caused\r
-// and on any theory of liability, whether in contract, strict liability,\r
-// or tort (including negligence or otherwise) arising in any way out of\r
-// the use of this software, even if advised of the possibility of such damage.\r
-//\r
-//M*/\r
-\r
-#include "cvtest.h"\r
-#include <string>\r
-#include <iostream>\r
-#include <fstream>\r
-#include <iterator>\r
-#include <limits>\r
-#include "cvaux.h"\r
-\r
-using namespace cv;\r
-using namespace std;\r
-\r
-class CV_OptFlowTest : public CvTest\r
-{\r
-public:\r
- CV_OptFlowTest();\r
- ~CV_OptFlowTest(); \r
-protected: \r
- void run(int);\r
-\r
- bool runDense(const Point& shift = Point(3, 0)); \r
- bool runSparse();\r
-};\r
-\r
-CV_OptFlowTest::CV_OptFlowTest(): CvTest( "optflow-all", "?" )\r
-{\r
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;\r
-}\r
-CV_OptFlowTest::~CV_OptFlowTest() {}\r
-\r
-\r
-Mat copnvert2flow(const Mat& velx, const Mat& vely)\r
-{\r
- Mat flow(velx.size(), CV_32FC2);\r
- for(int y = 0 ; y < flow.rows; ++y)\r
- for(int x = 0 ; x < flow.cols; ++x) \r
- flow.at<Point2f>(y, x) = Point2f(velx.at<float>(y, x), vely.at<float>(y, x)); \r
- return flow;\r
-}\r
-\r
-void calcOpticalFlowLK( const Mat& prev, const Mat& curr, Size winSize, Mat& flow )\r
-{\r
- Mat velx(prev.size(), CV_32F), vely(prev.size(), CV_32F); \r
- CvMat cvvelx = velx; CvMat cvvely = vely;\r
- CvMat cvprev = prev; CvMat cvcurr = curr;\r
- cvCalcOpticalFlowLK( &cvprev, &cvcurr, winSize, &cvvelx, &cvvely );\r
- flow = copnvert2flow(velx, vely);\r
-}\r
-\r
-void calcOpticalFlowBM( const Mat& prev, const Mat& curr, Size bSize, Size shiftSize, Size maxRange, int usePrevious, Mat& flow )\r
-{\r
- Size sz((curr.cols - bSize.width)/shiftSize.width, (curr.rows - bSize.height)/shiftSize.height);\r
- Mat velx(sz, CV_32F), vely(sz, CV_32F); \r
-\r
- CvMat cvvelx = velx; CvMat cvvely = vely;\r
- CvMat cvprev = prev; CvMat cvcurr = curr;\r
- cvCalcOpticalFlowBM( &cvprev, &cvcurr, bSize, shiftSize, maxRange, usePrevious, &cvvelx, &cvvely); \r
- flow = copnvert2flow(velx, vely);\r
-}\r
-\r
-void calcOpticalFlowHS( const Mat& prev, const Mat& curr, int usePrevious, double lambda, TermCriteria criteria, Mat& flow)\r
-{ \r
- Mat velx(prev.size(), CV_32F), vely(prev.size(), CV_32F);\r
- CvMat cvvelx = velx; CvMat cvvely = vely;\r
- CvMat cvprev = prev; CvMat cvcurr = curr;\r
- cvCalcOpticalFlowHS( &cvprev, &cvcurr, usePrevious, &cvvelx, &cvvely, lambda, criteria );\r
- flow = copnvert2flow(velx, vely);\r
-}\r
-\r
-void calcAffineFlowPyrLK( const Mat& prev, const Mat& curr, \r
- const vector<Point2f>& prev_features, vector<Point2f>& curr_features,\r
- vector<uchar>& status, vector<float>& track_error, vector<float>& matrices, \r
- TermCriteria criteria = TermCriteria(TermCriteria::COUNT+TermCriteria::EPS,30, 0.01), \r
- Size win_size = Size(15, 15), int level = 3, int flags = 0)\r
-{\r
- CvMat cvprev = prev;\r
- CvMat cvcurr = curr;\r
-\r
- size_t count = prev_features.size();\r
- curr_features.resize(count);\r
- status.resize(count);\r
- track_error.resize(count);\r
- matrices.resize(count * 6);\r
-\r
- cvCalcAffineFlowPyrLK( &cvprev, &cvcurr, 0, 0, \r
- (const CvPoint2D32f*)&prev_features[0], (CvPoint2D32f*)&curr_features[0], &matrices[0], \r
- (int)count, win_size, level, (char*)&status[0], &track_error[0], criteria, flags );\r
-}\r
-\r
-double showFlowAndCalcError(const string& name, const Mat& gray, const Mat& flow, \r
- const Rect& where, const Point& d, \r
- bool showImages = false, bool writeError = false)\r
-{ \r
- const int mult = 16;\r
-\r
- if (showImages)\r
- {\r
- Mat tmp, cflow; \r
- resize(gray, tmp, gray.size() * mult, 0, 0, INTER_NEAREST); \r
- cvtColor(tmp, cflow, CV_GRAY2BGR); \r
-\r
- const float m2 = 0.3f; \r
- const float minVel = 0.1f;\r
-\r
- for(int y = 0; y < flow.rows; ++y)\r
- for(int x = 0; x < flow.cols; ++x)\r
- {\r
- Point2f f = flow.at<Point2f>(y, x); \r
-\r
- if (f.x * f.x + f.y * f.y > minVel * minVel)\r
- {\r
- Point p1 = Point(x, y) * mult;\r
- Point p2 = Point(cvRound((x + f.x*m2) * mult), cvRound((y + f.y*m2) * mult));\r
-\r
- line(cflow, p1, p2, CV_RGB(0, 255, 0)); \r
- circle(cflow, Point(x, y) * mult, 2, CV_RGB(255, 0, 0));\r
- } \r
- }\r
-\r
- rectangle(cflow, (where.tl() + d) * mult, (where.br() + d - Point(1,1)) * mult, CV_RGB(0, 0, 255)); \r
- namedWindow(name, 1); imshow(name, cflow);\r
- }\r
-\r
- double angle = atan2((float)d.y, (float)d.x);\r
- double error = 0;\r
-\r
- bool all = true;\r
- Mat inner = flow(where);\r
- for(int y = 0; y < inner.rows; ++y)\r
- for(int x = 0; x < inner.cols; ++x)\r
- {\r
- const Point2f f = inner.at<Point2f>(y, x);\r
-\r
- if (f.x == 0 && f.y == 0)\r
- continue;\r
-\r
- all = false;\r
-\r
- double a = atan2(f.y, f.x);\r
- error += fabs(angle - a); \r
- }\r
- double res = all ? numeric_limits<double>::max() : error / (inner.cols * inner.rows);\r
-\r
- if (writeError)\r
- cout << "Error " + name << " = " << res << endl;\r
-\r
- return res;\r
-}\r
-\r
-\r
-Mat generateImage(const Size& sz, bool doBlur = true)\r
-{\r
- RNG rng;\r
- Mat mat(sz, CV_8U);\r
- mat = Scalar(0);\r
- for(int y = 0; y < mat.rows; ++y)\r
- for(int x = 0; x < mat.cols; ++x)\r
- mat.at<uchar>(y, x) = (uchar)rng; \r
- if (doBlur)\r
- blur(mat, mat, Size(3, 3));\r
- return mat;\r
-}\r
-\r
-Mat generateSample(const Size& sz)\r
-{\r
- Mat smpl(sz, CV_8U); \r
- smpl = Scalar(0);\r
- Point sc(smpl.cols/2, smpl.rows/2);\r
- rectangle(smpl, Point(0,0), sc - Point(1,1), Scalar(255), CV_FILLED);\r
- rectangle(smpl, sc, Point(smpl.cols, smpl.rows), Scalar(255), CV_FILLED);\r
- return smpl;\r
-}\r
-\r
-bool CV_OptFlowTest::runDense(const Point& d)\r
-{\r
- Size matSize(40, 40);\r
- Size movSize(8, 8);\r
- \r
- Mat smpl = generateSample(movSize);\r
- Mat prev = generateImage(matSize); \r
- Mat curr = prev.clone();\r
-\r
- Rect rect(Point(prev.cols/2, prev.rows/2) - Point(movSize.width/2, movSize.height/2), movSize);\r
-\r
- Mat flowLK, flowBM, flowHS, flowFB, flowFB_G, flowBM_received, m1;\r
-\r
- m1 = prev(rect); smpl.copyTo(m1);\r
- m1 = curr(Rect(rect.tl() + d, rect.br() + d)); smpl.copyTo(m1); \r
- \r
- calcOpticalFlowLK( prev, curr, Size(15, 15), flowLK); \r
- calcOpticalFlowBM( prev, curr, Size(15, 15), Size(1, 1), Size(15, 15), 0, flowBM_received); \r
- calcOpticalFlowHS( prev, curr, 0, 5, TermCriteria(TermCriteria::MAX_ITER, 400, 0), flowHS); \r
- calcOpticalFlowFarneback( prev, curr, flowFB, 0.5, 3, std::max(d.x, d.y) + 10, 100, 6, 2, 0);\r
- calcOpticalFlowFarneback( prev, curr, flowFB_G, 0.5, 3, std::max(d.x, d.y) + 10, 100, 6, 2, OPTFLOW_FARNEBACK_GAUSSIAN); \r
-\r
- flowBM.create(prev.size(), CV_32FC2);\r
- flowBM = Scalar(0); \r
- Point origin((flowBM.cols - flowBM_received.cols)/2, (flowBM.rows - flowBM_received.rows)/2);\r
- Mat wcp = flowBM(Rect(origin, flowBM_received.size()));\r
- flowBM_received.copyTo(wcp);\r
-\r
- double errorLK = showFlowAndCalcError("LK", prev, flowLK, rect, d);\r
- double errorBM = showFlowAndCalcError("BM", prev, flowBM, rect, d);\r
- double errorFB = showFlowAndCalcError("FB", prev, flowFB, rect, d);\r
- double errorFBG = showFlowAndCalcError("FBG", prev, flowFB_G, rect, d);\r
- double errorHS = showFlowAndCalcError("HS", prev, flowHS, rect, d); (void)errorHS; \r
- //waitKey(); \r
-\r
- const double thres = 0.2;\r
- if (errorLK > thres || errorBM > thres || errorFB > thres || errorFBG > thres /*|| errorHS > thres */)\r
- { \r
- ts->set_failed_test_info(CvTS::FAIL_MISMATCH);\r
- return false;\r
- } \r
- return true;\r
-}\r
-\r
-\r
-bool CV_OptFlowTest::runSparse()\r
-{ \r
- Mat prev = imread(string(ts->get_data_path()) + "optflow/rock_1.bmp", 0);\r
- Mat next = imread(string(ts->get_data_path()) + "optflow/rock_2.bmp", 0);\r
-\r
- if (prev.empty() || next.empty())\r
- {\r
- ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA ); \r
- return false;\r
- }\r
-\r
- Mat cprev, cnext;\r
- cvtColor(prev, cprev, CV_GRAY2BGR);\r
- cvtColor(next, cnext, CV_GRAY2BGR);\r
-\r
- vector<Point2f> prev_pts;\r
- vector<Point2f> next_ptsOpt;\r
- vector<Point2f> next_ptsAff;\r
- vector<uchar> status_Opt;\r
- vector<uchar> status_Aff;\r
- vector<float> error;\r
- vector<float> matrices;\r
-\r
- Size netSize(10, 10);\r
- Point2f center = Point(prev.cols/2, prev.rows/2);\r
-\r
- for(int i = 0 ; i < netSize.width; ++i)\r
- for(int j = 0 ; j < netSize.width; ++j)\r
- {\r
- Point2f p(i * float(prev.cols)/netSize.width, j * float(prev.rows)/netSize.height);\r
- prev_pts.push_back((p - center) * 0.5f + center); \r
- }\r
-\r
- calcOpticalFlowPyrLK( prev, next, prev_pts, next_ptsOpt, status_Opt, error );\r
- calcAffineFlowPyrLK ( prev, next, prev_pts, next_ptsAff, status_Aff, error, matrices);\r
-\r
- const double expected_shift = 25;\r
- const double thres = 1; \r
- for(size_t i = 0; i < prev_pts.size(); ++i) \r
- {\r
- circle(cprev, prev_pts[i], 2, CV_RGB(255, 0, 0)); \r
-\r
- if (status_Opt[i])\r
- { \r
- circle(cnext, next_ptsOpt[i], 2, CV_RGB(0, 0, 255));\r
- Point2f shift = prev_pts[i] - next_ptsOpt[i];\r
- \r
- double n = sqrt(shift.ddot(shift));\r
- if (fabs(n - expected_shift) > thres)\r
- {\r
- ts->set_failed_test_info(CvTS::FAIL_MISMATCH);\r
- return false;\r
- }\r
- }\r
-\r
- if (status_Aff[i])\r
- { \r
- circle(cnext, next_ptsAff[i], 4, CV_RGB(0, 255, 0));\r
- Point2f shift = prev_pts[i] - next_ptsAff[i];\r
-\r
- double n = sqrt(shift.ddot(shift));\r
- if (fabs(n - expected_shift) > thres)\r
- {\r
- ts->set_failed_test_info(CvTS::FAIL_MISMATCH);\r
- return false;\r
- }\r
- }\r
- \r
- }\r
- \r
- /*namedWindow("P"); imshow("P", cprev);\r
- namedWindow("N"); imshow("N", cnext); \r
- waitKey();*/\r
- \r
- return true;\r
-}\r
-\r
-\r
-void CV_OptFlowTest::run( int /* start_from */)\r
-{ \r
-\r
- if (!runDense(Point(3, 0)))\r
- return;\r
-\r
- if (!runDense(Point(0, 3))) \r
- return;\r
-\r
- //if (!runDense(Point(3, 3))) return; //probably LK works incorrectly in this case.\r
-\r
- if (!runSparse()) \r
- return;\r
-\r
- ts->set_failed_test_info(CvTS::OK);\r
-}\r
-\r
-CV_OptFlowTest optFlow_test;\r
-\r
+++ /dev/null
-#include "cvtest.h"
-
-using namespace cv;
-
-class BruteForceMatcherTest : public CvTest
-{
-public:
- BruteForceMatcherTest();
-protected:
- void run( int );
-};
-
-struct CV_EXPORTS L2Fake : public L2<float>
-{
-};
-
-BruteForceMatcherTest::BruteForceMatcherTest() : CvTest( "BruteForceMatcher", "BruteForceMatcher::matchImpl")
-{
- support_testing_modes = CvTS::TIMING_MODE;
-}
-
-void BruteForceMatcherTest::run( int )
-{
- const int dimensions = 64;
- const int descriptorsNumber = 5000;
-
- Mat train = Mat( descriptorsNumber, dimensions, CV_32FC1);
- Mat query = Mat( descriptorsNumber, dimensions, CV_32FC1);
-
- Mat permutation( 1, descriptorsNumber, CV_32SC1 );
- for( int i=0;i<descriptorsNumber;i++ )
- permutation.at<int>( 0, i ) = i;
-
- //RNG rng = RNG( cvGetTickCount() );
- RNG rng = RNG( *ts->get_rng() );
- randShuffle( permutation, 1, &rng );
-
- float boundary = 500.f;
- for( int row=0;row<descriptorsNumber;row++ )
- {
- for( int col=0;col<dimensions;col++ )
- {
- int bit = rng( 2 );
- train.at<float>( permutation.at<int>( 0, row ), col ) = bit*boundary + rng.uniform( 0.f, boundary );
- query.at<float>( row, col ) = bit*boundary + rng.uniform( 0.f, boundary );
- }
- }
-
- vector<DMatch> specMatches, genericMatches;
- BruteForceMatcher<L2<float> > specMatcher;
- BruteForceMatcher<L2Fake > genericMatcher;
-
- int64 time0 = cvGetTickCount();
- specMatcher.match( query, train, specMatches );
- int64 time1 = cvGetTickCount();
- genericMatcher.match( query, train, genericMatches );
- int64 time2 = cvGetTickCount();
-
- float specMatcherTime = float(time1 - time0)/(float)cvGetTickFrequency();
- ts->printf( CvTS::LOG, "Matching by matrix multiplication time s: %f, us per pair: %f\n",
- specMatcherTime*1e-6, specMatcherTime/( descriptorsNumber*descriptorsNumber ) );
-
- float genericMatcherTime = float(time2 - time1)/(float)cvGetTickFrequency();
- ts->printf( CvTS::LOG, "Matching without matrix multiplication time s: %f, us per pair: %f\n",
- genericMatcherTime*1e-6, genericMatcherTime/( descriptorsNumber*descriptorsNumber ) );
-
- if( (int)specMatches.size() != descriptorsNumber || (int)genericMatches.size() != descriptorsNumber )
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- for( int i=0;i<descriptorsNumber;i++ )
- {
- float epsilon = 0.01f;
- bool isEquiv = fabs( specMatches[i].distance - genericMatches[i].distance ) < epsilon &&
- specMatches[i].queryIdx == genericMatches[i].queryIdx &&
- specMatches[i].trainIdx == genericMatches[i].trainIdx;
- if( !isEquiv || specMatches[i].trainIdx != permutation.at<int>( 0, i ) )
- {
- ts->set_failed_test_info( CvTS::FAIL_MISMATCH );
- break;
- }
- }
-
-
- //Test mask
- Mat mask( query.rows, train.rows, CV_8UC1 );
- rng.fill( mask, RNG::UNIFORM, 0, 2 );
-
-
- time0 = cvGetTickCount();
- specMatcher.match( query, train, specMatches, mask );
- time1 = cvGetTickCount();
- genericMatcher.match( query, train, genericMatches, mask );
- time2 = cvGetTickCount();
-
- specMatcherTime = float(time1 - time0)/(float)cvGetTickFrequency();
- ts->printf( CvTS::LOG, "Matching by matrix multiplication time with mask s: %f, us per pair: %f\n",
- specMatcherTime*1e-6, specMatcherTime/( descriptorsNumber*descriptorsNumber ) );
-
- genericMatcherTime = float(time2 - time1)/(float)cvGetTickFrequency();
- ts->printf( CvTS::LOG, "Matching without matrix multiplication time with mask s: %f, us per pair: %f\n",
- genericMatcherTime*1e-6, genericMatcherTime/( descriptorsNumber*descriptorsNumber ) );
-
- if( specMatches.size() != genericMatches.size() )
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
-
- for( size_t i=0;i<specMatches.size();i++ )
- {
- //float epsilon = 1e-2;
- float epsilon = 10000000;
- bool isEquiv = fabs( specMatches[i].distance - genericMatches[i].distance ) < epsilon &&
- specMatches[i].queryIdx == genericMatches[i].queryIdx &&
- specMatches[i].trainIdx == genericMatches[i].trainIdx;
- if( !isEquiv )
- {
- ts->set_failed_test_info( CvTS::FAIL_MISMATCH );
- break;
- }
- }
-}
-
-BruteForceMatcherTest taBruteForceMatcherTest;
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-class CV_ChessboardDetectorTimingTest : public CvTest
-{
-public:
- CV_ChessboardDetectorTimingTest();
-protected:
- void run(int);
-};
-
-
-CV_ChessboardDetectorTimingTest::CV_ChessboardDetectorTimingTest():
- CvTest( "chessboard-detector-timing", "cvFindChessboardCorners" )
-{
- support_testing_modes = CvTS::TIMING_MODE;
-}
-
-/* ///////////////////// chess_corner_test ///////////////////////// */
-void CV_ChessboardDetectorTimingTest::run( int start_from )
-{
- int code = CvTS::OK;
-
- /* test parameters */
- char filepath[1000];
- char filename[1000];
-
- CvMat* _v = 0;
- CvPoint2D32f* v;
-
- IplImage* img = 0;
- IplImage* gray = 0;
- IplImage* thresh = 0;
-
- int idx, max_idx;
- int progress = 0;
-
- sprintf( filepath, "%scameracalibration/", ts->get_data_path() );
- sprintf( filename, "%schessboard_timing_list.dat", filepath );
- printf("Reading file %s\n", filename);
- CvFileStorage* fs = cvOpenFileStorage( filename, 0, CV_STORAGE_READ );
- CvFileNode* board_list = fs ? cvGetFileNodeByName( fs, 0, "boards" ) : 0;
-
- if( !fs || !board_list || !CV_NODE_IS_SEQ(board_list->tag) ||
- board_list->data.seq->total % 4 != 0 )
- {
- ts->printf( CvTS::LOG, "chessboard_timing_list.dat can not be readed or is not valid" );
- code = CvTS::FAIL_MISSING_TEST_DATA;
- goto _exit_;
- }
-
- max_idx = board_list->data.seq->total/4;
-
- for( idx = start_from; idx < max_idx; idx++ )
- {
- int count0 = -1;
- int count = 0;
- CvSize pattern_size;
- int result, result1 = 0;
-
- const char* imgname = cvReadString((CvFileNode*)cvGetSeqElem(board_list->data.seq,idx*4), "dummy.txt");
- int is_chessboard = cvReadInt((CvFileNode*)cvGetSeqElem(board_list->data.seq,idx*4+1), 0);
- pattern_size.width = cvReadInt((CvFileNode*)cvGetSeqElem(board_list->data.seq,idx*4 + 2), -1);
- pattern_size.height = cvReadInt((CvFileNode*)cvGetSeqElem(board_list->data.seq,idx*4 + 3), -1);
-
- ts->update_context( this, idx-1, true );
-
- /* read the image */
- sprintf( filename, "%s%s", filepath, imgname );
-
- img = cvLoadImage( filename );
-
- if( !img )
- {
- ts->printf( CvTS::LOG, "one of chessboard images can't be read: %s\n", filename );
- if( max_idx == 1 )
- {
- code = CvTS::FAIL_MISSING_TEST_DATA;
- goto _exit_;
- }
- continue;
- }
-
- ts->printf(CvTS::LOG, "%s: chessboard %d:\n", imgname, is_chessboard);
-
- gray = cvCreateImage( cvSize( img->width, img->height ), IPL_DEPTH_8U, 1 );
- thresh = cvCreateImage( cvSize( img->width, img->height ), IPL_DEPTH_8U, 1 );
- cvCvtColor( img, gray, CV_BGR2GRAY );
-
-
- count0 = pattern_size.width*pattern_size.height;
-
- /* allocate additional buffers */
- _v = cvCreateMat(1, count0, CV_32FC2);
- count = count0;
-
- v = (CvPoint2D32f*)_v->data.fl;
-
- int64 _time0 = cvGetTickCount();
- result = cvCheckChessboard(gray, pattern_size);
- int64 _time01 = cvGetTickCount();
-
- OPENCV_CALL( result1 = cvFindChessboardCorners(
- gray, pattern_size, v, &count, 15 ));
- int64 _time1 = cvGetTickCount();
-
- if( result != is_chessboard )
- {
- ts->printf( CvTS::LOG, "Error: chessboard was %sdetected in the image %s\n",
- result ? "" : "not ", imgname );
- code = CvTS::FAIL_INVALID_OUTPUT;
- goto _exit_;
- }
- if(result != result1)
- {
- ts->printf( CvTS::LOG, "Warning: results differ cvCheckChessboard %d, cvFindChessboardCorners %d\n",
- result, result1);
- }
-
- int num_pixels = gray->width*gray->height;
- float check_chessboard_time = float(_time01 - _time0)/(float)cvGetTickFrequency(); // in us
- ts->printf(CvTS::LOG, " cvCheckChessboard time s: %f, us per pixel: %f\n",
- check_chessboard_time*1e-6, check_chessboard_time/num_pixels);
-
- float find_chessboard_time = float(_time1 - _time01)/(float)cvGetTickFrequency();
- ts->printf(CvTS::LOG, " cvFindChessboard time s: %f, us per pixel: %f\n",
- find_chessboard_time*1e-6, find_chessboard_time/num_pixels);
-
- cvReleaseMat( &_v );
- cvReleaseImage( &img );
- cvReleaseImage( &gray );
- cvReleaseImage( &thresh );
- progress = update_progress( progress, idx-1, max_idx, 0 );
- }
-
-_exit_:
-
- /* release occupied memory */
- cvReleaseMat( &_v );
- cvReleaseFileStorage( &fs );
- cvReleaseImage( &img );
- cvReleaseImage( &gray );
- cvReleaseImage( &thresh );
-
- if( code < 0 )
- ts->set_failed_test_info( code );
-}
-
-CV_ChessboardDetectorTimingTest chessboard_detector_timing_test;
-
-/* End of file. */
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cvtest.h"
-
-CvTS test_system("cv");
-
-const char* blacklist[] =
-{
- "calibrate-camera-artificial", //ticket 472
- "inpaint", //ticket 570
- "warp-resize", //ticket 429
- "_3d-rodrigues", //ticket 435
- 0
-};
-
-int main(int argC,char *argV[])
-{
- return test_system.run( argC, argV, blacklist );
-}
-
-/* End of file. */
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////\r
-//\r
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.\r
-//\r
-// By downloading, copying, installing or using the software you agree to this license.\r
-// If you do not agree to this license, do not download, install,\r
-// copy or use the software.\r
-//\r
-//\r
-// License Agreement\r
-// For Open Source Computer Vision Library\r
-//\r
-// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.\r
-// Copyright (C) 2009, Willow Garage Inc., all rights reserved.\r
-// Third party copyrights are property of their respective owners.\r
-//\r
-// Redistribution and use in source and binary forms, with or without modification,\r
-// are permitted provided that the following conditions are met:\r
-//\r
-// * Redistribution's of source code must retain the above copyright notice,\r
-// this list of conditions and the following disclaimer.\r
-//\r
-// * Redistribution's in binary form must reproduce the above copyright notice,\r
-// this list of conditions and the following disclaimer in the documentation\r
-// and/or other materials provided with the distribution.\r
-//\r
-// * The name of the copyright holders may not be used to endorse or promote products\r
-// derived from this software without specific prior written permission.\r
-//\r
-// This software is provided by the copyright holders and contributors "as is" and\r
-// any express or implied warranties, including, but not limited to, the implied\r
-// warranties of merchantability and fitness for a particular purpose are disclaimed.\r
-// In no event shall the Intel Corporation or contributors be liable for any direct,\r
-// indirect, incidental, special, exemplary, or consequential damages\r
-// (including, but not limited to, procurement of substitute goods or services;\r
-// loss of use, data, or profits; or business interruption) however caused\r
-// and on any theory of liability, whether in contract, strict liability,\r
-// or tort (including negligence or otherwise) arising in any way out of\r
-// the use of this software, even if advised of the possibility of such damage.\r
-//\r
-//M*/\r
-\r
-#include "cvtest.h"\r
-#include <string>\r
-\r
-using namespace cv;\r
-\r
-class CV_WatershedTest : public CvTest\r
-{\r
-public:\r
- CV_WatershedTest();\r
- ~CV_WatershedTest(); \r
-protected: \r
- void run(int);\r
-};\r
-\r
-CV_WatershedTest::CV_WatershedTest(): CvTest( "segmentation-watershed", "cvWatershed" )\r
-{\r
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;\r
-}\r
-CV_WatershedTest::~CV_WatershedTest() {}\r
-\r
-void CV_WatershedTest::run( int /* start_from */)\r
-{ \r
- string exp_path = string(ts->get_data_path()) + "watershed/wshed_exp.png"; \r
- Mat exp = imread(exp_path, 0);\r
- Mat orig = imread(string(ts->get_data_path()) + "inpaint/orig.jpg");\r
- FileStorage fs(string(ts->get_data_path()) + "watershed/comp.xml", FileStorage::READ);\r
- \r
- if (orig.empty() || !fs.isOpened())\r
- {\r
- ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA );\r
- return;\r
- }\r
- \r
- CvSeq* cnts = (CvSeq*)fs["contours"].readObj();\r
-\r
- Mat markers(orig.size(), CV_32SC1);\r
- markers = Scalar(0);\r
- IplImage iplmrks = markers; \r
-\r
- vector<unsigned char> colors(1);\r
- for(int i = 0; cnts != 0; cnts = cnts->h_next, ++i )\r
- {\r
- cvDrawContours( &iplmrks, cnts, Scalar::all(i + 1), Scalar::all(i + 1), -1, CV_FILLED);\r
- Point* p = (Point*)cvGetSeqElem(cnts, 0);\r
-\r
- //expected image was added with 1 in order to save to png\r
- //so now we substract 1 to get real color\r
- if(exp.data)\r
- colors.push_back(exp.ptr(p->y)[p->x] - 1);\r
- }\r
- fs.release();\r
- const int compNum = (int)(colors.size() - 1);\r
-\r
- watershed(orig, markers);\r
-\r
- for(int j = 0; j < markers.rows; ++j)\r
- {\r
- int* line = markers.ptr<int>(j);\r
- for(int i = 0; i < markers.cols; ++i)\r
- {\r
- int& pixel = line[i];\r
-\r
- if (pixel == -1) // border\r
- continue;\r
-\r
- if (pixel <= 0 || pixel > compNum)\r
- continue; // bad result, doing nothing and going to get error latter;\r
- \r
- // repaint in saved color to compare with expected;\r
- if(exp.data)\r
- pixel = colors[pixel]; \r
- }\r
- } \r
-\r
- Mat markers8U;\r
- markers.convertTo(markers8U, CV_8U, 1, 1);\r
- \r
- if( exp.empty() || orig.size() != exp.size() )\r
- {\r
- imwrite(exp_path, markers8U);\r
- exp = markers8U;\r
- }\r
- \r
- if (0 != norm(markers8U, exp, NORM_INF))\r
- { \r
- ts->set_failed_test_info( CvTS::FAIL_MISMATCH ); \r
- return;\r
- }\r
- ts->set_failed_test_info(CvTS::OK);\r
-}\r
-\r
-CV_WatershedTest watershed_test;\r
+++ /dev/null
-# ----------------------------------------------------------------------------
-# CMake file for cxcoretest. See root CMakeLists.txt
-#
-# ----------------------------------------------------------------------------
-project(opencv_test_core)
-
-file(GLOB test_srcs "src/*.cpp")
-source_group("Src" FILES ${test_srcs})
-file(GLOB test_hdrs "src/*.h*")
-source_group("Include" FILES ${test_hdrs})
-
-include_directories("${CMAKE_SOURCE_DIR}/include/opencv"
- "${CMAKE_SOURCE_DIR}/modules/core/include"
- "${CMAKE_CURRENT_SOURCE_DIR}/src"
- "${CMAKE_CURRENT_BINARY_DIR}")
-
-include_directories(../cxts)
-
-set(the_target "opencv_test_core")
-
-add_executable(${the_target} ${test_srcs} ${test_hdrs})
-
-if(PCHSupport_FOUND)
- set(pch_header ${CMAKE_SOURCE_DIR}/tests/cxcore/src/cxcoretest.h)
- if(${CMAKE_GENERATOR} MATCHES "Visual*" OR ${CMAKE_GENERATOR} MATCHES "Xcode*")
- if(${CMAKE_GENERATOR} MATCHES "Visual*")
- set(${the_target}_pch "src/precomp.cpp")
- endif()
- add_native_precompiled_header(${the_target} ${pch_header})
- elseif(CMAKE_COMPILER_IS_GNUCXX AND ${CMAKE_GENERATOR} MATCHES ".*Makefiles")
- add_precompiled_header(${the_target} ${pch_header})
- endif()
-endif()
-
-# Additional target properties
-set_target_properties(${the_target} PROPERTIES
- DEBUG_POSTFIX "${OPENCV_DEBUG_POSTFIX}"
- RUNTIME_OUTPUT_DIRECTORY "${CMAKE_BINARY_DIR}/bin/"
- )
-
-
-add_dependencies(${the_target} opencv_ts opencv_core)
-
-# Add the required libraries for linking:
-target_link_libraries(${the_target} ${OPENCV_LINKER_LIBS} opencv_ts opencv_core)
-
-enable_testing()
-get_target_property(LOC ${the_target} LOCATION)
-add_test(${the_target} "${LOC}")
-
-if(WIN32)
-install(TARGETS ${the_target} RUNTIME DESTINATION bin COMPONENT main)
-endif()
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-//////////////////////////////////////////////////////////////////////////////////////////
-////////////////// tests for arithmetic, logic and statistical functions /////////////////
-//////////////////////////////////////////////////////////////////////////////////////////
-
-#include "cxcoretest.h"
-#include <float.h>
-
-static const CvSize arithm_sizes[] = {{10,10}, {100,100}, {720,480}, {-1,-1}};
-static const CvSize arithm_whole_sizes[] = {{10,10}, {720,480}, {720,480}, {-1,-1}};
-static const int arithm_depths[] = { CV_8U, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F, -1 };
-static const int arithm_channels[] = { 1, 2, 3, 4, -1 };
-static const char* arithm_mask_param_names[] = { "size", "channels", "depth", "use_mask", 0 };
-static const char* arithm_param_names[] = { "size", "channels", "depth", 0 };
-static const char* minmax_param_names[] = { "size", "depth", 0 };
-
-class CxCore_ArithmTestImpl : public CvArrTest
-{
-public:
- CxCore_ArithmTestImpl( const char* test_name, const char* test_funcs,
- int _generate_scalars=0, bool _allow_mask=true, bool _calc_abs=false );
-protected:
- void prepare_to_validation( int test_case_idx );
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void get_timing_test_array_types_and_sizes( int /*test_case_idx*/,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images );
- void generate_scalars( int depth );
- void finalize_scalar( CvScalar& s );
- CvScalar alpha, beta, gamma;
- int gen_scalars;
- bool calc_abs;
- bool test_nd;
-};
-
-
-CxCore_ArithmTestImpl::CxCore_ArithmTestImpl( const char* test_name, const char* test_funcs,
- int _generate_scalars, bool _allow_mask, bool _calc_abs )
- : CvArrTest( test_name, test_funcs, "" ),
- gen_scalars(_generate_scalars), calc_abs(_calc_abs)
-{
- test_array[INPUT].push(NULL);
- test_array[INPUT].push(NULL);
- optional_mask = _allow_mask;
-
- if( optional_mask )
- {
- test_array[INPUT_OUTPUT].push(NULL);
- test_array[REF_INPUT_OUTPUT].push(NULL);
- test_array[TEMP].push(NULL);
- test_array[MASK].push(NULL);
- }
- else
- {
- test_array[OUTPUT].push(NULL);
- test_array[REF_OUTPUT].push(NULL);
- }
- alpha = beta = gamma = cvScalarAll(0);
-
- size_list = arithm_sizes;
- whole_size_list = arithm_whole_sizes;
- depth_list = arithm_depths;
- cn_list = arithm_channels;
- test_nd = false;
-}
-
-
-void CxCore_ArithmTestImpl::generate_scalars( int depth )
-{
- bool is_timing = ts->get_testing_mode() == CvTS::TIMING_MODE;
- double ab_min_val = -1.;
- double ab_max_val = 1.;
- double gamma_min_val = depth == CV_8U ? -100 : depth < CV_32F ? -10000 : -1e6;
- double gamma_max_val = depth == CV_8U ? 100 : depth < CV_32F ? 10000 : 1e6;
-
- if( gen_scalars )
- {
- CvRNG* rng = ts->get_rng();
- int i;
- double m = 3.;
- for( i = 0; i < 4; i++ )
- {
- if( gen_scalars & 1 )
- {
- alpha.val[i] = exp((cvTsRandReal(rng)-0.5)*m*2*CV_LOG2);
- alpha.val[i] *= (cvTsRandInt(rng) & 1) ? 1 : -1;
- if( is_timing )
- {
- alpha.val[i] = MAX( alpha.val[i], ab_min_val );
- alpha.val[i] = MIN( alpha.val[i], ab_max_val );
- }
- }
- if( gen_scalars & 2 )
- {
- beta.val[i] = exp((cvTsRandReal(rng)-0.5)*m*2*CV_LOG2);
- beta.val[i] *= (cvTsRandInt(rng) & 1) ? 1 : -1;
- if( is_timing )
- {
- beta.val[i] = MAX( beta.val[i], ab_min_val );
- beta.val[i] = MIN( beta.val[i], ab_max_val );
- }
- }
- if( gen_scalars & 4 )
- {
- gamma.val[i] = exp((cvTsRandReal(rng)-0.5)*m*2*CV_LOG2);
- gamma.val[i] *= (cvTsRandInt(rng) & 1) ? 1 : -1;
- if( is_timing )
- {
- gamma.val[i] = MAX( gamma.val[i], gamma_min_val );
- gamma.val[i] = MIN( gamma.val[i], gamma_max_val );
- }
- }
- }
- }
-
- if( depth == CV_32F )
- {
- CvMat fl = cvMat( 1, 4, CV_32F, buf );
- CvMat db = cvMat( 1, 4, CV_64F, 0 );
-
- db.data.db = alpha.val;
- cvTsConvert( &db, &fl );
- cvTsConvert( &fl, &db );
-
- db.data.db = beta.val;
- cvTsConvert( &db, &fl );
- cvTsConvert( &fl, &db );
-
- db.data.db = gamma.val;
- cvTsConvert( &db, &fl );
- cvTsConvert( &fl, &db );
- }
-}
-
-void CxCore_ArithmTestImpl::finalize_scalar( CvScalar& s )
-{
- int depth = CV_MAT_DEPTH(test_mat[INPUT][0].type);
- if( depth < CV_32F )
- s = cvScalar(cvRound(s.val[0]), cvRound(s.val[1]), cvRound(s.val[2]), cvRound(s.val[3]));
-}
-
-void CxCore_ArithmTestImpl::get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- int depth = cvTsRandInt(rng)%(CV_64F+1);
- int cn = cvTsRandInt(rng) % 4 + 1;
- int i, j;
- depth += depth == CV_8S;
- CvArrTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- generate_scalars( depth );
-
- for( i = 0; i < max_arr; i++ )
- {
- int count = test_array[i].size();
- int type = i != MASK ? CV_MAKETYPE(depth, cn) : CV_8UC1;
- for( j = 0; j < count; j++ )
- {
- types[i][j] = type;
- }
- }
- test_nd = cvTsRandInt(rng)%3 == 0;
-}
-
-
-void CxCore_ArithmTestImpl::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images )
-{
- CvArrTest::get_timing_test_array_types_and_sizes( test_case_idx, sizes, types,
- whole_sizes, are_images );
- generate_scalars( types[INPUT][0] );
- test_nd = false;
-}
-
-
-void CxCore_ArithmTestImpl::prepare_to_validation( int /*test_case_idx*/ )
-{
- const CvMat* mask = test_array[MASK].size() > 0 && test_array[MASK][0] ? &test_mat[MASK][0] : 0;
- CvMat* output = test_array[REF_INPUT_OUTPUT].size() > 0 ?
- &test_mat[REF_INPUT_OUTPUT][0] : &test_mat[REF_OUTPUT][0];
- CvMat* temp_dst = mask ? &test_mat[TEMP][0] : output;
- cvTsAdd( &test_mat[INPUT][0], alpha,
- test_array[INPUT].size() > 1 ? &test_mat[INPUT][1] : 0, beta,
- gamma, temp_dst, calc_abs );
- if( mask )
- cvTsCopy( temp_dst, output, mask );
-}
-
-
-CxCore_ArithmTestImpl arithm( "arithm", "", 0, false );
-
-
-class CxCore_ArithmTest : public CxCore_ArithmTestImpl
-{
-public:
- CxCore_ArithmTest( const char* test_name, const char* test_funcs,
- int _generate_scalars=0, bool _allow_mask=true, bool _calc_abs=false );
-};
-
-
-CxCore_ArithmTest::CxCore_ArithmTest( const char* test_name, const char* test_funcs,
- int _generate_scalars, bool _allow_mask, bool _calc_abs ) :
- CxCore_ArithmTestImpl( test_name, test_funcs, _generate_scalars, _allow_mask, _calc_abs )
-{
- default_timing_param_names = optional_mask ? arithm_mask_param_names : arithm_param_names;
-
- // inherit the default parameters from arithmetical test
- size_list = 0;
- whole_size_list = 0;
- depth_list = 0;
- cn_list = 0;
-}
-
-
-////////////////////////////// add /////////////////////////////
-
-class CxCore_AddTest : public CxCore_ArithmTest
-{
-public:
- CxCore_AddTest();
-protected:
- void run_func();
-};
-
-CxCore_AddTest::CxCore_AddTest()
- : CxCore_ArithmTest( "arithm-add", "cvAdd", 0, true )
-{
- alpha = beta = cvScalarAll(1.);
-}
-
-void CxCore_AddTest::run_func()
-{
- if(!test_nd)
- {
- cvAdd( test_array[INPUT][0], test_array[INPUT][1],
- test_array[INPUT_OUTPUT][0], test_array[MASK][0] );
- }
- else
- {
- cv::MatND a = cv::cvarrToMatND(test_array[INPUT][0]);
- cv::MatND b = cv::cvarrToMatND(test_array[INPUT][1]);
- cv::MatND c = cv::cvarrToMatND(test_array[INPUT_OUTPUT][0]);
- if( !test_array[MASK][0] )
- cv::add(a, b, c);
- else
- cv::add(a, b, c, cv::cvarrToMatND(test_array[MASK][0]));
- }
-}
-
-CxCore_AddTest add_test;
-
-////////////////////////////// sub /////////////////////////////
-
-class CxCore_SubTest : public CxCore_ArithmTest
-{
-public:
- CxCore_SubTest();
-protected:
- void run_func();
-};
-
-CxCore_SubTest::CxCore_SubTest()
- : CxCore_ArithmTest( "arithm-sub", "cvSub", 0, true )
-{
- alpha = cvScalarAll(1.);
- beta = cvScalarAll(-1.);
-}
-
-void CxCore_SubTest::run_func()
-{
- if(!test_nd)
- {
- cvSub( test_array[INPUT][0], test_array[INPUT][1],
- test_array[INPUT_OUTPUT][0], test_array[MASK][0] );
- }
- else
- {
- cv::MatND a = cv::cvarrToMatND(test_array[INPUT][0]);
- cv::MatND b = cv::cvarrToMatND(test_array[INPUT][1]);
- cv::MatND c = cv::cvarrToMatND(test_array[INPUT_OUTPUT][0]);
- if( !test_array[MASK][0] )
- cv::subtract(a, b, c);
- else
- cv::subtract(a, b, c, cv::cvarrToMatND(test_array[MASK][0]));
- }
-}
-
-CxCore_SubTest sub_test;
-
-
-////////////////////////////// adds /////////////////////////////
-
-class CxCore_AddSTest : public CxCore_ArithmTest
-{
-public:
- CxCore_AddSTest();
-protected:
- void run_func();
-};
-
-CxCore_AddSTest::CxCore_AddSTest()
- : CxCore_ArithmTest( "arithm-adds", "cvAddS", 4, true )
-{
- test_array[INPUT].pop();
- alpha = cvScalarAll(1.);
-}
-
-void CxCore_AddSTest::run_func()
-{
- finalize_scalar(gamma);
- if(!test_nd)
- {
- if( test_mat[INPUT][0].cols % 2 == 0 )
- cvAddS( test_array[INPUT][0], gamma,
- test_array[INPUT_OUTPUT][0], test_array[MASK][0] );
- else
- {
- cv::Mat a = cv::cvarrToMat(test_array[INPUT][0]),
- c = cv::cvarrToMat(test_array[INPUT_OUTPUT][0]);
- cv::subtract(a, -cv::Scalar(gamma), c, test_array[MASK][0] ?
- cv::cvarrToMat(test_array[MASK][0]) : cv::Mat());
- }
- }
- else
- {
- cv::MatND c = cv::cvarrToMatND(test_array[INPUT_OUTPUT][0]);
- cv::add( cv::cvarrToMatND(test_array[INPUT][0]),
- gamma, c, test_array[MASK][0] ?
- cv::cvarrToMatND(test_array[MASK][0]) : cv::MatND());
- }
-}
-
-CxCore_AddSTest adds_test;
-
-////////////////////////////// subrs /////////////////////////////
-
-class CxCore_SubRSTest : public CxCore_ArithmTest
-{
-public:
- CxCore_SubRSTest();
-protected:
- void run_func();
-};
-
-CxCore_SubRSTest::CxCore_SubRSTest()
- : CxCore_ArithmTest( "arithm-subrs", "cvSubRS", 4, true )
-{
- test_array[INPUT].pop();
- alpha = cvScalarAll(-1.);
-}
-
-void CxCore_SubRSTest::run_func()
-{
- finalize_scalar(gamma);
- if(!test_nd)
- {
- cvSubRS( test_array[INPUT][0], gamma,
- test_array[INPUT_OUTPUT][0], test_array[MASK][0] );
- }
- else
- {
- cv::MatND c = cv::cvarrToMatND(test_array[INPUT_OUTPUT][0]);
- cv::subtract( gamma,
- cv::cvarrToMatND(test_array[INPUT][0]),
- c, test_array[MASK][0] ?
- cv::cvarrToMatND(test_array[MASK][0]) : cv::MatND());
- }
-}
-
-CxCore_SubRSTest subrs_test;
-
-////////////////////////////// addweighted /////////////////////////////
-
-class CxCore_AddWeightedTest : public CxCore_ArithmTest
-{
-public:
- CxCore_AddWeightedTest();
-protected:
- void get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types );
- double get_success_error_level( int test_case_idx, int i, int j );
- void run_func();
-};
-
-CxCore_AddWeightedTest::CxCore_AddWeightedTest()
- : CxCore_ArithmTest( "arithm-addweighted", "cvAddWeighted", 7, false )
-{
-}
-
-void CxCore_AddWeightedTest::get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types )
-{
- CxCore_ArithmTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- alpha = cvScalarAll(alpha.val[0]);
- beta = cvScalarAll(beta.val[0]);
- gamma = cvScalarAll(gamma.val[0]);
-}
-
-
-double CxCore_AddWeightedTest::get_success_error_level( int test_case_idx, int i, int j )
-{
- int type = cvGetElemType(test_array[i][j]), depth = CV_MAT_DEPTH(type);
- if( depth <= CV_32S )
- return 2;
- if( depth == CV_32F )
- {
- CvScalar low=cvScalarAll(0), high=low;
- get_minmax_bounds(i,j,type, &low, &high);
- double a = (fabs(alpha.val[0])+fabs(beta.val[0]))*(fabs(low.val[0])+fabs(high.val[0]));
- double b = fabs(gamma.val[0]);
- return (a+b)*500*FLT_EPSILON;
- }
- return CvArrTest::get_success_error_level( test_case_idx, i, j );
-}
-
-
-void CxCore_AddWeightedTest::run_func()
-{
- if(!test_nd)
- {
- cvAddWeighted( test_array[INPUT][0], alpha.val[0],
- test_array[INPUT][1], beta.val[0],
- gamma.val[0], test_array[OUTPUT][0] );
- }
- else
- {
- cv::MatND c = cv::cvarrToMatND(test_array[OUTPUT][0]);
- cv::addWeighted(cv::cvarrToMatND(test_array[INPUT][0]),
- alpha.val[0],
- cv::cvarrToMatND(test_array[INPUT][1]),
- beta.val[0], gamma.val[0], c);
- }
-}
-
-CxCore_AddWeightedTest addweighted_test;
-
-
-////////////////////////////// absdiff /////////////////////////////
-
-class CxCore_AbsDiffTest : public CxCore_ArithmTest
-{
-public:
- CxCore_AbsDiffTest();
-protected:
- void run_func();
-};
-
-CxCore_AbsDiffTest::CxCore_AbsDiffTest()
- : CxCore_ArithmTest( "arithm-absdiff", "cvAbsDiff", 0, false, true )
-{
- alpha = cvScalarAll(1.);
- beta = cvScalarAll(-1.);
-}
-
-void CxCore_AbsDiffTest::run_func()
-{
- if(!test_nd)
- {
- cvAbsDiff( test_array[INPUT][0], test_array[INPUT][1], test_array[OUTPUT][0] );
- }
- else
- {
- cv::MatND c = cv::cvarrToMatND(test_array[OUTPUT][0]);
- cv::absdiff(cv::cvarrToMatND(test_array[INPUT][0]),
- cv::cvarrToMatND(test_array[INPUT][1]),
- c );
- }
-}
-
-CxCore_AbsDiffTest absdiff_test;
-
-////////////////////////////// absdiffs /////////////////////////////
-
-class CxCore_AbsDiffSTest : public CxCore_ArithmTest
-{
-public:
- CxCore_AbsDiffSTest();
-protected:
- void run_func();
-};
-
-CxCore_AbsDiffSTest::CxCore_AbsDiffSTest()
- : CxCore_ArithmTest( "arithm-absdiffs", "cvAbsDiffS", 4, false, true )
-{
- alpha = cvScalarAll(-1.);
- test_array[INPUT].pop();
-}
-
-void CxCore_AbsDiffSTest::run_func()
-{
- finalize_scalar(gamma);
- if(!test_nd)
- {
- cvAbsDiffS( test_array[INPUT][0], test_array[OUTPUT][0], gamma );
- }
- else
- {
- cv::MatND c = cv::cvarrToMatND(test_array[OUTPUT][0]);
- cv::absdiff(cv::cvarrToMatND(test_array[INPUT][0]),
- gamma, c);
- }
-}
-
-CxCore_AbsDiffSTest absdiffs_test;
-
-
-////////////////////////////// mul /////////////////////////////
-
-static const char* mul_param_names[] = { "size", "scale", "channels", "depth", 0 };
-static const char* mul_scale_flags[] = { "scale==1", "scale!=1", 0 };
-
-class CxCore_MulTest : public CxCore_ArithmTest
-{
-public:
- CxCore_MulTest();
-protected:
- void run_func();
- void get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types,
- CvSize** whole_sizes, bool* are_images );
- double get_success_error_level( int test_case_idx, int i, int j );
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
- void prepare_to_validation( int test_case_idx );
- int write_default_params( CvFileStorage* fs );
-};
-
-
-CxCore_MulTest::CxCore_MulTest()
- : CxCore_ArithmTest( "arithm-mul", "cvMul", 4, false, false )
-{
- default_timing_param_names = mul_param_names;
-}
-
-
-int CxCore_MulTest::write_default_params( CvFileStorage* fs )
-{
- int code = CxCore_ArithmTest::write_default_params(fs);
- if( code < 0 || ts->get_testing_mode() != CvTS::TIMING_MODE )
- return code;
- write_string_list( fs, "scale", mul_scale_flags );
- return code;
-}
-
-
-void CxCore_MulTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types,
- CvSize** whole_sizes, bool* are_images )
-{
- CxCore_ArithmTest::get_timing_test_array_types_and_sizes( test_case_idx,
- sizes, types, whole_sizes, are_images );
- const char* scale_flag_str = cvReadString( find_timing_param( "scale" ), "scale==1" );
- if( strstr( scale_flag_str, "==1" ) )
- alpha.val[0] = 1.;
- else
- {
- double val = alpha.val[0];
- int depth = CV_MAT_DEPTH(types[INPUT][0]);
- if( val == 1. )
- val = 1./CV_PI;
- if( depth == CV_16U || depth == CV_16S || depth == CV_32S )
- {
- double minmax = 1./cvTsMaxVal(depth);
- if( val < -minmax )
- val = -minmax;
- else if( val > minmax )
- val = minmax;
- if( depth == CV_16U && val < 0 )
- val = -val;
- }
- alpha.val[0] = val;
- ts->printf( CvTS::LOG, "alpha = %g\n", alpha.val[0] );
- }
-}
-
-
-void CxCore_MulTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- sprintf( ptr, "%s,", alpha.val[0] == 1. ? "scale==1" : "scale!=1" );
- ptr += strlen(ptr);
- params_left--;
- CxCore_ArithmTest::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-
-double CxCore_MulTest::get_success_error_level( int test_case_idx, int i, int j )
-{
- if( CV_MAT_DEPTH(cvGetElemType(test_array[i][j])) <= CV_32S )
- {
- return gamma.val[0] != cvRound(gamma.val[0]);
- }
- else
- return CvArrTest::get_success_error_level( test_case_idx, i, j );
-}
-
-
-void CxCore_MulTest::run_func()
-{
- if(!test_nd)
- {
- cvMul( test_array[INPUT][0], test_array[INPUT][1],
- test_array[OUTPUT][0], alpha.val[0] );
- }
- else
- {
- cv::MatND c = cv::cvarrToMatND(test_array[OUTPUT][0]);
- cv::multiply(cv::cvarrToMatND(test_array[INPUT][0]),
- cv::cvarrToMatND(test_array[INPUT][1]),
- c, alpha.val[0]);
- }
-}
-
-void CxCore_MulTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- cvTsMul( &test_mat[INPUT][0], &test_mat[INPUT][1],
- cvScalarAll(alpha.val[0]),
- &test_mat[REF_OUTPUT][0] );
-}
-
-CxCore_MulTest mul_test;
-
-////////////////////////////// div /////////////////////////////
-
-class CxCore_DivTest : public CxCore_ArithmTest
-{
-public:
- CxCore_DivTest();
-protected:
- void run_func();
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
- void prepare_to_validation( int /*test_case_idx*/ );
-};
-
-CxCore_DivTest::CxCore_DivTest()
- : CxCore_ArithmTest( "arithm-div", "cvDiv", 4, false, false )
-{
-}
-
-void CxCore_DivTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- sprintf( ptr, "s*A(i)/B(i)," );
- ptr += strlen(ptr);
- params_left--;
- CxCore_ArithmTest::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-void CxCore_DivTest::run_func()
-{
- if(!test_nd)
- {
- cvDiv( test_array[INPUT][0], test_array[INPUT][1],
- test_array[OUTPUT][0], alpha.val[0] );
- }
- else
- {
- cv::MatND b = cv::cvarrToMatND(test_array[INPUT][1]);
- cv::MatND c = cv::cvarrToMatND(test_array[OUTPUT][0]);
- cv::divide(cv::cvarrToMatND(test_array[INPUT][0]),
- b, c, alpha.val[0]);
- }
-}
-
-void CxCore_DivTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- cvTsDiv( &test_mat[INPUT][0], &test_mat[INPUT][1],
- cvScalarAll(alpha.val[0]),
- &test_mat[REF_OUTPUT][0] );
-}
-
-CxCore_DivTest div_test;
-
-////////////////////////////// recip /////////////////////////////
-
-class CxCore_RecipTest : public CxCore_ArithmTest
-{
-public:
- CxCore_RecipTest();
-protected:
- void run_func();
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
- void prepare_to_validation( int /*test_case_idx*/ );
-};
-
-CxCore_RecipTest::CxCore_RecipTest()
- : CxCore_ArithmTest( "arithm-recip", "cvDiv", 4, false, false )
-{
- test_array[INPUT].pop();
-}
-
-void CxCore_RecipTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- sprintf( ptr, "s/B(i)," );
- ptr += strlen(ptr);
- params_left--;
- CxCore_ArithmTest::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-void CxCore_RecipTest::run_func()
-{
- if(!test_nd)
- {
- cvDiv( 0, test_array[INPUT][0],
- test_array[OUTPUT][0], gamma.val[0] );
- }
- else
- {
- cv::MatND b = cv::cvarrToMatND(test_array[INPUT][0]);
- cv::MatND c = cv::cvarrToMatND(test_array[OUTPUT][0]);
- cv::divide(gamma.val[0], b, c);
- }
-}
-
-void CxCore_RecipTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- cvTsDiv( 0, &test_mat[INPUT][0],
- cvScalarAll(gamma.val[0]),
- &test_mat[REF_OUTPUT][0] );
-}
-
-CxCore_RecipTest recip_test;
-
-
-///////////////// matrix copy/initializing/permutations /////////////////////
-
-class CxCore_MemTestImpl : public CxCore_ArithmTestImpl
-{
-public:
- CxCore_MemTestImpl( const char* test_name, const char* test_funcs,
- int _generate_scalars=0, bool _allow_mask=true );
-protected:
- double get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ );
-};
-
-CxCore_MemTestImpl::CxCore_MemTestImpl( const char* test_name, const char* test_funcs,
- int _generate_scalars, bool _allow_mask ) :
- CxCore_ArithmTestImpl( test_name, test_funcs, _generate_scalars, _allow_mask, false )
-{
-}
-
-double CxCore_MemTestImpl::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- return 0;
-}
-
-CxCore_MemTestImpl mem_test( "mem", "", 0, false );
-
-
-class CxCore_MemTest : public CxCore_MemTestImpl
-{
-public:
- CxCore_MemTest( const char* test_name, const char* test_funcs,
- int _generate_scalars=0, bool _allow_mask=true );
-};
-
-CxCore_MemTest::CxCore_MemTest( const char* test_name, const char* test_funcs,
- int _generate_scalars, bool _allow_mask ) :
- CxCore_MemTestImpl( test_name, test_funcs, _generate_scalars, _allow_mask )
-{
- default_timing_param_names = optional_mask ? arithm_mask_param_names : arithm_param_names;
-
- // inherit the default parameters from arithmerical test
- size_list = 0;
- whole_size_list = 0;
- depth_list = 0;
- cn_list = 0;
-}
-
-
-///////////////// setidentity /////////////////////
-
-class CxCore_SetIdentityTest : public CxCore_MemTest
-{
-public:
- CxCore_SetIdentityTest();
-protected:
- void run_func();
- void prepare_to_validation( int test_case_idx );
-};
-
-
-CxCore_SetIdentityTest::CxCore_SetIdentityTest() :
- CxCore_MemTest( "mem-setidentity", "cvSetIdentity", 4, false )
-{
- test_array[INPUT].clear();
-}
-
-
-void CxCore_SetIdentityTest::run_func()
-{
- if(!test_nd)
- cvSetIdentity(test_array[OUTPUT][0], gamma);
- else
- {
- cv::Mat a = cv::cvarrToMat(test_array[OUTPUT][0]);
- cv::setIdentity(a, gamma);
- }
-}
-
-
-void CxCore_SetIdentityTest::prepare_to_validation( int )
-{
- cvTsSetIdentity( &test_mat[REF_OUTPUT][0], gamma );
-}
-
-CxCore_SetIdentityTest setidentity_test;
-
-
-///////////////// SetZero /////////////////////
-
-class CxCore_SetZeroTest : public CxCore_MemTest
-{
-public:
- CxCore_SetZeroTest();
-protected:
- void run_func();
- void prepare_to_validation( int test_case_idx );
-};
-
-
-CxCore_SetZeroTest::CxCore_SetZeroTest() :
- CxCore_MemTest( "mem-setzero", "cvSetZero", 0, false )
-{
- test_array[INPUT].clear();
-}
-
-
-void CxCore_SetZeroTest::run_func()
-{
- if(!test_nd)
- cvSetZero(test_array[OUTPUT][0]);
- else
- {
- cv::MatND a = cv::cvarrToMatND(test_array[OUTPUT][0]);
- a.setTo(cv::Scalar());
- }
-}
-
-
-void CxCore_SetZeroTest::prepare_to_validation( int )
-{
- cvTsZero( &test_mat[REF_OUTPUT][0] );
-}
-
-CxCore_SetZeroTest setzero_test;
-
-
-///////////////// Set /////////////////////
-
-class CxCore_FillTest : public CxCore_MemTest
-{
-public:
- CxCore_FillTest();
-protected:
- void run_func();
- void prepare_to_validation( int test_case_idx );
-};
-
-
-CxCore_FillTest::CxCore_FillTest() :
- CxCore_MemTest( "mem-fill", "cvSet", 4, true )
-{
- test_array[INPUT].clear();
-}
-
-
-void CxCore_FillTest::run_func()
-{
- const CvArr* mask = test_array[MASK][0];
- if(!test_nd)
- cvSet(test_array[INPUT_OUTPUT][0], gamma, mask);
- else
- {
- cv::MatND a = cv::cvarrToMatND(test_array[INPUT_OUTPUT][0]);
- a.setTo(gamma, mask ? cv::cvarrToMatND(mask) : cv::MatND());
- }
-}
-
-
-void CxCore_FillTest::prepare_to_validation( int )
-{
- if( test_array[MASK][0] )
- {
- cvTsAdd( 0, cvScalarAll(0.), 0, cvScalarAll(0.), gamma, &test_mat[TEMP][0], 0 );
- cvTsCopy( &test_mat[TEMP][0], &test_mat[REF_INPUT_OUTPUT][0], &test_mat[MASK][0] );
- }
- else
- {
- cvTsAdd( 0, cvScalarAll(0.), 0, cvScalarAll(0.), gamma, &test_mat[REF_INPUT_OUTPUT][0], 0 );
- }
-}
-
-CxCore_FillTest fill_test;
-
-
-///////////////// Copy /////////////////////
-
-class CxCore_CopyTest : public CxCore_MemTest
-{
-public:
- CxCore_CopyTest();
-protected:
- double get_success_error_level( int test_case_idx, int i, int j );
- void run_func();
- void prepare_to_validation( int test_case_idx );
-};
-
-
-CxCore_CopyTest::CxCore_CopyTest() :
- CxCore_MemTest( "mem-copy", "cvCopy", 0, true )
-{
- test_array[INPUT].pop();
-}
-
-
-double CxCore_CopyTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- return 0;
-}
-
-
-void CxCore_CopyTest::run_func()
-{
- const CvArr* mask = test_array[MASK][0];
- if(!test_nd)
- cvCopy(test_array[INPUT][0], test_array[INPUT_OUTPUT][0], mask);
- else
- {
- cv::MatND a = cv::cvarrToMatND(test_array[INPUT][0]);
- cv::MatND c = cv::cvarrToMatND(test_array[INPUT_OUTPUT][0]);
- if(!mask)
- a.copyTo(c);
- else
- a.copyTo(c, cv::cvarrToMatND(mask));
- }
-}
-
-
-void CxCore_CopyTest::prepare_to_validation( int )
-{
- cvTsCopy( &test_mat[INPUT][0], &test_mat[REF_INPUT_OUTPUT][0],
- test_array[MASK].size() > 0 && test_array[MASK][0] ? &test_mat[MASK][0] : 0 );
-}
-
-CxCore_CopyTest copy_test;
-
-///////////////// Transpose /////////////////////
-
-class CxCore_TransposeTest : public CxCore_MemTest
-{
-public:
- CxCore_TransposeTest();
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types,
- CvSize** whole_sizes, bool* are_images );
- int prepare_test_case( int test_case_idx );
- void run_func();
- void prepare_to_validation( int test_case_idx );
- bool inplace;
-};
-
-
-CxCore_TransposeTest::CxCore_TransposeTest() :
- CxCore_MemTest( "mem-transpose", "cvTranspose", 0, false ), inplace(false)
-{
- test_array[INPUT].pop();
-}
-
-
-void CxCore_TransposeTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- int bits = cvTsRandInt(ts->get_rng());
- CxCore_MemTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
-
- inplace = false;
- if( bits & 1 )
- {
- sizes[INPUT][0].height = sizes[INPUT][0].width;
- inplace = (bits & 2) != 0;
- }
-
- sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = cvSize(sizes[INPUT][0].height, sizes[INPUT][0].width );
-}
-
-
-void CxCore_TransposeTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool* are_images )
-{
- CxCore_MemTest::get_timing_test_array_types_and_sizes( test_case_idx,
- sizes, types, whole_sizes, are_images );
- CvSize size = sizes[INPUT][0];
- if( size.width != size.height )
- {
- sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] =
- whole_sizes[OUTPUT][0] = whole_sizes[REF_OUTPUT][0] = cvSize(size.height,size.width);
- }
-}
-
-
-int CxCore_TransposeTest::prepare_test_case( int test_case_idx )
-{
- int code = CxCore_MemTest::prepare_test_case( test_case_idx );
- if( inplace && code > 0 )
- cvTsCopy( &test_mat[INPUT][0], &test_mat[OUTPUT][0] );
- return code;
-}
-
-void CxCore_TransposeTest::run_func()
-{
- cvTranspose( inplace ? test_array[OUTPUT][0] : test_array[INPUT][0], test_array[OUTPUT][0]);
-}
-
-
-void CxCore_TransposeTest::prepare_to_validation( int )
-{
- cvTsTranspose( &test_mat[INPUT][0], &test_mat[REF_OUTPUT][0] );
-}
-
-CxCore_TransposeTest transpose_test;
-
-
-///////////////// Flip /////////////////////
-
-static const int flip_codes[] = { 0, 1, -1, INT_MIN };
-static const char* flip_strings[] = { "center", "vert", "horiz", 0 };
-static const char* flip_param_names[] = { "size", "flip_op", "channels", "depth", 0 };
-
-class CxCore_FlipTest : public CxCore_MemTest
-{
-public:
- CxCore_FlipTest();
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types,
- CvSize** whole_sizes, bool* are_images );
- int prepare_test_case( int test_case_idx );
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
- void run_func();
- void prepare_to_validation( int test_case_idx );
- int write_default_params( CvFileStorage* fs );
- int flip_type;
- bool inplace;
-};
-
-
-CxCore_FlipTest::CxCore_FlipTest() :
- CxCore_MemTest( "mem-flip", "cvFlip", 0, false ), flip_type(0), inplace(false)
-{
- test_array[INPUT].pop();
- default_timing_param_names = flip_param_names;
-}
-
-
-int CxCore_FlipTest::write_default_params( CvFileStorage* fs )
-{
- int i, code = CxCore_MemTest::write_default_params(fs);
- if( code < 0 || ts->get_testing_mode() != CvTS::TIMING_MODE )
- return code;
- start_write_param( fs );
- cvStartWriteStruct( fs, "flip_op", CV_NODE_SEQ + CV_NODE_FLOW );
- for( i = 0; flip_codes[i] != INT_MIN; i++ )
- cvWriteString( fs, 0, flip_strings[flip_codes[i]+1] );
- cvEndWriteStruct(fs);
- return code;
-}
-
-
-void CxCore_FlipTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- int bits = cvTsRandInt(ts->get_rng());
- CxCore_MemTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
-
- flip_type = (bits & 3) - 2;
- flip_type += flip_type == -2;
- inplace = (bits & 4) != 0;
-}
-
-
-void CxCore_FlipTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types,
- CvSize** whole_sizes, bool* are_images )
-{
- CxCore_MemTest::get_timing_test_array_types_and_sizes( test_case_idx,
- sizes, types, whole_sizes, are_images );
- const char* flip_op_str = cvReadString( find_timing_param( "flip_op" ), "center" );
- if( strcmp( flip_op_str, "vert" ) == 0 )
- flip_type = 0;
- else if( strcmp( flip_op_str, "horiz" ) == 0 )
- flip_type = 1;
- else
- flip_type = -1;
-}
-
-
-void CxCore_FlipTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- sprintf( ptr, "%s,", flip_type > 0 ? "horiz" : flip_type < 0 ? "center" : "vert" );
- ptr += strlen(ptr);
- params_left--;
- CxCore_MemTest::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-
-int CxCore_FlipTest::prepare_test_case( int test_case_idx )
-{
- int code = CxCore_MemTest::prepare_test_case( test_case_idx );
- if( inplace && code > 0 )
- cvTsCopy( &test_mat[INPUT][0], &test_mat[OUTPUT][0] );
- return code;
-}
-
-
-void CxCore_FlipTest::run_func()
-{
- cvFlip(inplace ? test_array[OUTPUT][0] : test_array[INPUT][0], test_array[OUTPUT][0], flip_type);
-}
-
-
-void CxCore_FlipTest::prepare_to_validation( int )
-{
- cvTsFlip( &test_mat[INPUT][0], &test_mat[REF_OUTPUT][0], flip_type );
-}
-
-CxCore_FlipTest flip_test;
-
-
-///////////////// Split/Merge /////////////////////
-
-static const char* split_merge_types[] = { "all", "single", 0 };
-static int split_merge_channels[] = { 2, 3, 4, -1 };
-static const char* split_merge_param_names[] = { "size", "planes", "channels", "depth", 0 };
-
-class CxCore_SplitMergeBaseTest : public CxCore_MemTest
-{
-public:
- CxCore_SplitMergeBaseTest( const char* test_name, const char* test_funcs, int _is_split );
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types,
- CvSize** whole_sizes, bool* are_images );
- int prepare_test_case( int test_case_idx );
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
- void prepare_to_validation( int test_case_idx );
- int write_default_params( CvFileStorage* fs );
- bool are_images;
- int is_split, coi;
- void* hdrs[4];
-};
-
-
-CxCore_SplitMergeBaseTest::CxCore_SplitMergeBaseTest( const char* test_name,
- const char* test_funcs, int _is_split )
- : CxCore_MemTest( test_name, test_funcs, 0, false ), are_images(false), is_split(_is_split), coi(0)
-{
- test_array[INPUT].pop();
- if( is_split )
- ;
- else
- {
- test_array[OUTPUT].clear();
- test_array[REF_OUTPUT].clear();
- test_array[INPUT_OUTPUT].push(NULL);
- test_array[REF_INPUT_OUTPUT].push(NULL);
- }
- memset( hdrs, 0, sizeof(hdrs) );
-
- default_timing_param_names = split_merge_param_names;
- cn_list = split_merge_channels;
-}
-
-
-int CxCore_SplitMergeBaseTest::write_default_params( CvFileStorage* fs )
-{
- int code = CxCore_MemTest::write_default_params(fs);
- if( code < 0 || ts->get_testing_mode() != CvTS::TIMING_MODE )
- return code;
- write_string_list( fs, "planes", split_merge_types );
- return code;
-}
-
-
-void CxCore_SplitMergeBaseTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- int cn, depth;
- CvRNG* rng = ts->get_rng();
- CxCore_MemTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- cn = cvTsRandInt(rng)%3 + 2;
- depth = CV_MAT_DEPTH(types[INPUT][0]);
-
- if( is_split )
- {
- types[INPUT][0] = CV_MAKETYPE(depth, cn);
- types[OUTPUT][0] = types[REF_OUTPUT][0] = depth;
- }
- else
- {
- types[INPUT][0] = depth;
- types[INPUT_OUTPUT][0] = types[REF_INPUT_OUTPUT][0] = CV_MAKETYPE(depth, cn);
- }
-
- if( (cvTsRandInt(rng) & 3) != 0 )
- {
- coi = cvTsRandInt(rng) % cn;
- }
- else
- {
- CvSize size = sizes[INPUT][0];
- size.height *= cn;
-
- if( is_split )
- sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = size;
- else
- sizes[INPUT][0] = size;
- coi = -1;
- }
-
- are_images = cvTsRandInt(rng)%2 != 0;
-}
-
-
-void CxCore_SplitMergeBaseTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool* _are_images )
-{
- CxCore_MemTest::get_timing_test_array_types_and_sizes( test_case_idx,
- sizes, types, whole_sizes, _are_images );
- const char* split_merge_type = cvReadString( find_timing_param( "planes" ), "all" );
- int type0 = types[INPUT][0];
- int depth = CV_MAT_DEPTH(type0);
- int cn = CV_MAT_CN(type0);
- CvSize size = sizes[INPUT][0];
-
- if( strcmp( split_merge_type, "single" ) == 0 )
- coi = cvTsRandInt(ts->get_rng()) % cn;
- else
- {
- coi = -1;
- size.height *= cn;
- }
-
- if( is_split )
- {
- types[OUTPUT][0] = types[REF_OUTPUT][0] = depth;
- sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = size;
-
- // planes are put into separate arrays, not ROI's
- whole_sizes[OUTPUT][0] = whole_sizes[REF_OUTPUT][0] = size;
- }
- else
- {
- types[INPUT][0] = depth;
- sizes[INPUT][0] = size;
-
- // planes are put into separate arrays, not ROI's
- whole_sizes[INPUT][0] = size;
- }
-
- are_images = false;
-}
-
-
-void CxCore_SplitMergeBaseTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- int i;
-
- sprintf( ptr, "%s,", coi >= 0 ? "single" : "all" );
- ptr += strlen(ptr);
- params_left--;
-
- // at once, delete the headers, though is not very good from structural point of view ...
- for( i = 0; i < 4; i++ )
- cvRelease( &hdrs[i] );
-
- CxCore_MemTest::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-
-int CxCore_SplitMergeBaseTest::prepare_test_case( int test_case_idx )
-{
- int code = CxCore_MemTest::prepare_test_case( test_case_idx );
- if( code > 0 )
- {
- CvMat* input = &test_mat[INPUT][0];
- CvMat* output = &test_mat[is_split ? OUTPUT : INPUT_OUTPUT][0];
- CvMat* merged = is_split ? input : output;
- CvMat* planes = is_split ? output : input;
- int depth = CV_MAT_DEPTH(merged->type);
- int i, cn = CV_MAT_CN(merged->type), y = 0;
- CvSize sz = cvGetMatSize(merged);
-
- for( i = 0; i < cn; i++ )
- {
- if( coi < 0 || coi == i )
- {
- if( are_images )
- hdrs[i] = cvCreateImageHeader( sz, cvIplDepth(depth), 1 );
- else
- hdrs[i] = cvCreateMatHeader( sz.height, sz.width, depth );
- cvSetData( hdrs[i], planes->data.ptr + planes->step*y, planes->step );
- y += sz.height;
- }
- }
- }
-
- return code;
-}
-
-
-void CxCore_SplitMergeBaseTest::prepare_to_validation( int )
-{
- CvMat* input = &test_mat[INPUT][0];
- CvMat* output = &test_mat[is_split ? REF_OUTPUT : REF_INPUT_OUTPUT][0];
- CvMat* merged = is_split ? input : output;
- CvMat* planes = is_split ? output : input;
- int i, cn = CV_MAT_CN(merged->type), y = 0;
- CvSize sz = cvGetSize(merged);
-
- for( i = 0; i < cn; i++ )
- {
- if( coi < 0 || coi == i )
- {
- CvMat stub, *h;
- cvSetData( hdrs[i], planes->data.ptr + planes->step*y, planes->step );
- h = cvGetMat( hdrs[i], &stub );
- if( is_split )
- cvTsExtract( input, h, i );
- else
- cvTsInsert( h, output, i );
- cvSetData( hdrs[i], 0, 0 );
- cvRelease( &hdrs[i] );
- y += sz.height;
- }
- }
-}
-
-
-class CxCore_SplitTest : public CxCore_SplitMergeBaseTest
-{
-public:
- CxCore_SplitTest();
-protected:
- void run_func();
-};
-
-
-CxCore_SplitTest::CxCore_SplitTest() :
- CxCore_SplitMergeBaseTest( "mem-split", "cvSplit", 1 )
-{
-}
-
-
-void CxCore_SplitTest::run_func()
-{
- int i, nz = (hdrs[0] != 0) + (hdrs[1] != 0) + (hdrs[2] != 0) + (hdrs[3] != 0);
-
- if(!test_nd || nz != CV_MAT_CN(test_mat[INPUT][0].type))
- cvSplit( test_array[INPUT][0], hdrs[0], hdrs[1], hdrs[2], hdrs[3] );
- else
- {
- cv::MatND _hdrs[4];
- for( i = 0; i < nz; i++ )
- _hdrs[i] = cv::cvarrToMatND(hdrs[i]);
- cv::split(cv::cvarrToMatND(test_array[INPUT][0]), _hdrs);
- }
-}
-
-CxCore_SplitTest split_test;
-
-class CxCore_MergeTest : public CxCore_SplitMergeBaseTest
-{
-public:
- CxCore_MergeTest();
-protected:
- void run_func();
-};
-
-
-CxCore_MergeTest::CxCore_MergeTest() :
- CxCore_SplitMergeBaseTest( "mem-merge", "cvMerge", 0 )
-{
-}
-
-
-void CxCore_MergeTest::run_func()
-{
- int i, nz = (hdrs[0] != 0) + (hdrs[1] != 0) + (hdrs[2] != 0) + (hdrs[3] != 0);
-
- if(!test_nd || nz != CV_MAT_CN(test_mat[INPUT_OUTPUT][0].type))
- cvMerge( hdrs[0], hdrs[1], hdrs[2], hdrs[3], test_array[INPUT_OUTPUT][0] );
- else
- {
- cv::MatND _hdrs[4], dst = cv::cvarrToMatND(test_array[INPUT_OUTPUT][0]);
- for( i = 0; i < nz; i++ )
- _hdrs[i] = cv::cvarrToMatND(hdrs[i]);
- cv::merge(_hdrs, nz, dst);
- }
-}
-
-CxCore_MergeTest merge_test;
-
-///////////////// CompleteSymm /////////////////////
-
-class CxCore_CompleteSymm : public CvArrTest
-{
-public:
- CxCore_CompleteSymm();
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- int prepare_test_case( int test_case_idx );
- void run_func();
- void prepare_to_validation( int test_case_idx );
- int LtoR; //flags
-};
-
-CxCore_CompleteSymm::CxCore_CompleteSymm() :
- CvArrTest("matrix-symm", "cvCompleteSymm", "Test of cvCompleteSymm function")
-{
- /*Generates 1 input and 1 outputs (by default we have 2 inputs and 1 output)*/
- test_array[INPUT].clear();
- test_array[INPUT].push(NULL);
- test_array[OUTPUT].clear();
- test_array[OUTPUT].push(NULL);
- test_array[REF_OUTPUT].clear();
- test_array[REF_OUTPUT].push(NULL);
-}
-
-
-void CxCore_CompleteSymm::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CvArrTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- sizes[INPUT][0] =sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = cvSize(sizes[INPUT][0].height, sizes[INPUT][0].height );
-
- /*Making input and output matrixes one-channel*/
- int type;
- switch (test_case_idx % 3)
- {
- case 0:
- type = CV_32FC1;
- break;
- case 1:
- type = CV_32SC1;
- break;
- default:
- type = CV_64FC1;
- }
- types[OUTPUT][0] = types[INPUT][0] = types[REF_OUTPUT][0] = type;
-}
-
-int CxCore_CompleteSymm::prepare_test_case( int test_case_idx )
-{
- int code = CvArrTest::prepare_test_case( test_case_idx );
- if (code)
- {
- CvRNG* rng = ts->get_rng();
- unsigned val = cvRandInt(rng);
- LtoR = val % 2;
- cvConvert(&test_mat[INPUT][0], &test_mat[OUTPUT][0]);
- }
- return code;
-}
-
-void CxCore_CompleteSymm::run_func()
-{
- cvCompleteSymm(&test_mat[OUTPUT][0],LtoR);
-}
-
-void CxCore_CompleteSymm::prepare_to_validation( int )
-{
- CvMat* ref_output = cvCreateMat(test_mat[OUTPUT][0].rows, test_mat[OUTPUT][0].cols, CV_64F);
- CvMat* input = cvCreateMat(test_mat[INPUT][0].rows, test_mat[INPUT][0].cols, CV_64F);
- cvConvert(&test_mat[INPUT][0], input);
-
- for (int i=0;i<input->rows;i++)
- {
- ref_output->data.db[i*input->cols+i]=input->data.db[i*input->cols+i];
- if (LtoR)
- {
- for (int j=0;j<i;j++)
- {
- ref_output->data.db[j*input->cols+i] = ref_output->data.db[i*input->cols+j]=input->data.db[i*input->cols+j];
- }
-
- }
- else
- {
- for (int j=0;j<i;j++)
- {
- ref_output->data.db[j*input->cols+i] = ref_output->data.db[i*input->cols+j]=input->data.db[j*input->cols+i];
- }
- }
- }
-
- cvConvert(ref_output, &test_mat[REF_OUTPUT][0]);
- cvReleaseMat(&input);
- cvReleaseMat(&ref_output);
-}
-
-CxCore_CompleteSymm complete_symm;
-
-
-////////////////////////////// Sort /////////////////////////////////
-
-class CxCore_SortTest : public CxCore_MemTest
-{
-public:
- CxCore_SortTest();
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- int prepare_test_case( int test_case_idx );
- void run_func();
- void prepare_to_validation( int test_case_idx );
- int flags; //flags for sorting
-private:
- static int compareIndexes (const void * a, const void * b); // comparing two elements of the matrix with pointers sorting
- static int compare(const void * a, const void * b); // comparing two elements of the matrix with pointers sorting
- bool useIndexMatrix;
- bool useInPlaceSort;
- CvMat* input;
-
-};
-
-CxCore_SortTest::CxCore_SortTest() :
- CxCore_MemTest( "matrix-sort", "cvSort", 0, false )
-{
- /*Generates 1 input and 2 outputs (by default we have 2 inputs and 1 output)*/
- test_array[INPUT].clear();
- test_array[INPUT].push(NULL);
- test_array[OUTPUT].push(NULL);
- test_array[REF_OUTPUT].push(NULL);
-}
-
-
-void CxCore_SortTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CxCore_MemTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- sizes[INPUT][0] = sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = sizes[OUTPUT][1] = sizes[REF_OUTPUT][1] = cvSize(sizes[INPUT][0].height, sizes[INPUT][0].width );
- types[OUTPUT][1] = types[REF_OUTPUT][1] = CV_32SC1;
-
- /*Making input and output matrixes one-channel*/
- types[OUTPUT][0] = types[INPUT][0] = CV_MAKETYPE(CV_MAT_DEPTH(types[INPUT][0]), 1);
- types[REF_OUTPUT][0] = CV_MAKETYPE(CV_MAT_DEPTH(types[REF_OUTPUT][0]), 1);
-}
-
-int CxCore_SortTest::prepare_test_case( int test_case_idx )
-{
- if (test_case_idx==0)
- {
- useIndexMatrix=true;
- useInPlaceSort=false;
- }
- int code = CxCore_MemTest::prepare_test_case( test_case_idx );
-
- if( code > 0 )
- {
- //Copying input data
- input = cvCreateMat(test_mat[INPUT][0].rows, test_mat[INPUT][0].cols, CV_64F);
- cvConvert(&test_mat[INPUT][0], input);
- CvRNG* rng = ts->get_rng();
- unsigned val = cvRandInt(rng);
- // Setting up flags
- switch (val%4)
- {
- case 0:
- flags = CV_SORT_EVERY_ROW + CV_SORT_DESCENDING;
- break;
- case 1:
- flags = CV_SORT_EVERY_ROW + CV_SORT_ASCENDING;
- break;
- case 2:
- flags = CV_SORT_EVERY_COLUMN + CV_SORT_DESCENDING;
- break;
- case 3:
- flags = CV_SORT_EVERY_COLUMN + CV_SORT_ASCENDING;
- break;
- }
- if (val%3)
- useIndexMatrix = !useIndexMatrix;
-
- if (val%5)
- useInPlaceSort = !useInPlaceSort;
-
- }
- return code;
-}
-
-void CxCore_SortTest::run_func()
-{
- //test_mat[OUTPUT][0] is sorted matrix
- //test_mat[OUTPUT][1] is index matrix
- if (useInPlaceSort)
- {
- cvConvert(&test_mat[INPUT][0], &test_mat[OUTPUT][0]);
- if (useIndexMatrix)
- cvSort(&(test_mat[OUTPUT][0]),&(test_mat[OUTPUT][0]),&(test_mat[OUTPUT][1]),flags);
- else
- {
- cvSort(&(test_mat[OUTPUT][0]),&(test_mat[OUTPUT][0]),0,flags);
- }
-
- }
- else
- {
- if (useIndexMatrix)
- cvSort(&(test_mat[INPUT][0]),&(test_mat[OUTPUT][0]),&(test_mat[OUTPUT][1]),flags);
- else
- {
- cvSort(&(test_mat[INPUT][0]),&(test_mat[OUTPUT][0]),0,flags);
- }
- }
-}
-
-int CxCore_SortTest::compareIndexes (const void * a, const void * b)
-{
- double zero = 1e-30;
- double res=(**((double**)a)-**((double**)b));
- return res<-zero?-1:(res>zero?1:0);
-}
-int CxCore_SortTest::compare (const void * a, const void * b)
-{
- return *((int*)a)-*((int*)b);
-}
-
-void CxCore_SortTest::prepare_to_validation(int)
-{
- /*Creating matrixes copies to work with*/
- CvMat* ref_indexes = cvCreateMat(test_mat[REF_OUTPUT][1].rows, test_mat[REF_OUTPUT][1].cols, CV_32SC1);
- CvMat* indexes = cvCreateMat(test_mat[OUTPUT][1].rows, test_mat[OUTPUT][1].cols, CV_32SC1);
- CvMat* ref_output = cvCreateMat(test_mat[OUTPUT][0].rows, test_mat[OUTPUT][0].cols,CV_64F);
-
- /*Copying data*/
- cvConvert(&test_mat[REF_OUTPUT][1], ref_indexes);
- cvConvert(&test_mat[OUTPUT][1], indexes);
-
- /*Following block generates REF_OUTPUT indexes matrix*/
- if ((flags == (CV_SORT_EVERY_ROW+CV_SORT_ASCENDING)) ||(flags == (CV_SORT_EVERY_ROW+CV_SORT_DESCENDING)))
- for (int i=0;i<test_mat[REF_OUTPUT][1].rows;i++)
- for (int j=0;j<test_mat[REF_OUTPUT][1].cols;j++)
- ref_indexes->data.i[ref_indexes->cols*i + j]=j;
- else
- for (int i=0;i<test_mat[REF_OUTPUT][1].rows;i++)
- for (int j=0;j<test_mat[REF_OUTPUT][1].cols;j++)
- ref_indexes->data.i[ref_indexes->cols*i + j]=i;
- cvConvert(ref_indexes, &test_mat[REF_OUTPUT][1]);
- /*End of block*/
-
- /* Matrix User's Sorting Algorithm */
- int order = -1; // order of sorting (ASCENDING or DESCENDING)
- //// Following to variables are for sorting rows or cols in one block without any conditions (if statements)
- short rowsSort=0;
- short colsSort=0;
- if ((flags == CV_SORT_EVERY_ROW+CV_SORT_ASCENDING)||(flags == CV_SORT_EVERY_COLUMN+CV_SORT_ASCENDING)) order=1;
- if ((flags == CV_SORT_EVERY_ROW+CV_SORT_ASCENDING)||(flags == CV_SORT_EVERY_ROW+CV_SORT_DESCENDING)) rowsSort=1;
- else colsSort=1;
- int i,j;
-
- // For accessing [i,j] element using index matrix we can use following formula
- // input->data.db[(input->cols*i+ref_indexes->cols*i+j)*rowsSort+(cols*(ref_indexes->cols*i+j)+j)*colsSort];
-
- if ((flags == CV_SORT_EVERY_ROW+CV_SORT_ASCENDING)||(flags == CV_SORT_EVERY_ROW+CV_SORT_DESCENDING))
- {
- double** row = new double*[input->cols];
- for (i=0;i<input->rows; i++)
- {
- for (int j=0;j<input->cols;j++)
- row[j]=&(input->data.db[(input->cols*i+j)]);
- qsort(row,input->cols,sizeof(row[0]),&CxCore_SortTest::compareIndexes);
- for (int j=0;j<ref_indexes->cols;j++)
- {
- if (order==1)
- ref_indexes->data.i[ref_indexes->cols*i+j]=(int)(row[j]-&(input->data.db[input->cols*i]));
- else
- ref_indexes->data.i[ref_indexes->cols*(i+1)-1-j]=(int)(row[j]-&(input->data.db[input->cols*i]));
- }
- }
- delete[] row;
- }
- else
- {
- double** col = new double*[input->rows];
- for (j=0;j<input->cols; j++)
- {
- for (int i=0;i<input->rows;i++)
- col[i]=&(input->data.db[(input->cols*i+j)]);
- qsort(col,input->rows,sizeof(col[0]),&CxCore_SortTest::compareIndexes);
- for (int i=0;i<ref_indexes->rows;i++)
- {
- if (order==1)
- ref_indexes->data.i[ref_indexes->cols*i+j]=(int)((col[i]-&(input->data.db[j]))/(ref_output->cols));
- else
- ref_indexes->data.i[ref_indexes->cols*(ref_indexes->rows-1-i)+j]=(int)(col[i]-&(input->data.db[j]))/(ref_output->cols);
- }
- }
- delete[] col;
- }
-
- /*End of Sort*/
-
- int n;
- for (i=0;i<input->rows;i++)
- for (j=0;j<input->cols;j++)
- {
- n=(input->cols*i+ref_indexes->data.i[ref_indexes->cols*i+j])*rowsSort+
- (input->cols*(ref_indexes->data.i[ref_indexes->cols*i+j])+j)*colsSort;
- ref_output->data.db[ref_output->cols*i+j] = input->data.db[n];
- }
-
- if (useIndexMatrix)
- {
- /* Comparing indexes matrixes */
- if ((flags == CV_SORT_EVERY_ROW+CV_SORT_ASCENDING)||(flags == CV_SORT_EVERY_ROW+CV_SORT_DESCENDING))
- {
- int begin=0,end=0;
- double temp;
- for (i=0;i<indexes->rows;i++)
- {
- for (j=0;j<indexes->cols-1;j++)
- if (ref_output->data.db[ref_output->cols*i+j]==ref_output->data.db[ref_output->cols*i+j+1])
- {
- temp=ref_output->data.db[ref_output->cols*i+j];
- begin=j++;
- while ((j<ref_output->cols)&&(temp==ref_output->data.db[ref_output->cols*i+j])) j++;
- end=--j;
- int* row = new int[end-begin+1];
- int* row1 = new int[end-begin+1];
-
- for (int k=0;k<=end-begin;k++)
- {
- row[k]=ref_indexes->data.i[ref_indexes->cols*i+k+begin];
- row1[k]=indexes->data.i[indexes->cols*i+k+begin];
- }
- qsort(row,end-begin+1,sizeof(row[0]),&CxCore_SortTest::compare);
- qsort(row1,end-begin+1,sizeof(row1[0]),&CxCore_SortTest::compare);
- for (int k=0;k<=end-begin;k++)
- {
- ref_indexes->data.i[ref_indexes->cols*i+k+begin]=row[k];
- indexes->data.i[indexes->cols*i+k+begin]=row1[k];
- }
- delete[] row;
- delete[] row1;
- }
- }
- }
- else
- {
- int begin=0,end=0;
- double temp;
- for (j=0;j<indexes->cols;j++)
- {
- for (i=0;i<indexes->rows-1;i++)
- if (ref_output->data.db[ref_output->cols*i+j]==ref_output->data.db[ref_output->cols*(i+1)+j])
- {
- temp=ref_output->data.db[ref_output->cols*i+j];
- begin=i++;
- while ((i<ref_output->rows)&&(temp==ref_output->data.db[ref_output->cols*i+j])) i++;
- end=--i;
-
- int* col = new int[end-begin+1];
- int* col1 = new int[end-begin+1];
-
- for (int k=0;k<=end-begin;k++)
- {
- col[k]=ref_indexes->data.i[ref_indexes->cols*(k+begin)+j];
- col1[k]=indexes->data.i[indexes->cols*(k+begin)+j];
- }
- qsort(col,end-begin+1,sizeof(col[0]),&CxCore_SortTest::compare);
- qsort(col1,end-begin+1,sizeof(col1[0]),&CxCore_SortTest::compare);
- for (int k=0;k<=end-begin;k++)
- {
- ref_indexes->data.i[ref_indexes->cols*(k+begin)+j]=col[k];
- indexes->data.i[indexes->cols*(k+begin)+j]=col1[k];
- }
- delete[] col;
- delete[] col1;
- }
- }
- }
- /* End of compare*/
- cvConvert(ref_indexes, &test_mat[REF_OUTPUT][1]);
- cvConvert(indexes, &test_mat[OUTPUT][1]);
- }
- else
- {
- cvConvert(ref_indexes, &test_mat[REF_OUTPUT][1]);
- cvConvert(ref_indexes, &test_mat[OUTPUT][1]);
- }
-
- cvConvert(ref_output, &test_mat[REF_OUTPUT][0]);
-
- /*releasing matrixes*/
- cvReleaseMat(&ref_output);
- cvReleaseMat(&input);
- cvReleaseMat(&indexes);
- cvReleaseMat(&ref_indexes);
-}
-
-CxCore_SortTest sort_test;
-
-////////////////////////////// min/max /////////////////////////////
-
-class CxCore_MinMaxBaseTest : public CxCore_ArithmTest
-{
-public:
- CxCore_MinMaxBaseTest( const char* test_name, const char* test_funcs,
- int _op_type, int _generate_scalars=0 );
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- double get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ );
- void prepare_to_validation( int /*test_case_idx*/ );
- int op_type;
-};
-
-CxCore_MinMaxBaseTest::CxCore_MinMaxBaseTest( const char* test_name, const char* test_funcs,
- int _op_type, int _generate_scalars )
- : CxCore_ArithmTest( test_name, test_funcs, _generate_scalars, false, false ), op_type(_op_type)
-{
- if( _generate_scalars )
- test_array[INPUT].pop();
- default_timing_param_names = minmax_param_names;
-}
-
-double CxCore_MinMaxBaseTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- return 0;
-}
-
-void CxCore_MinMaxBaseTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- int i, j;
- CxCore_ArithmTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- for( i = 0; i < max_arr; i++ )
- {
- int count = test_array[i].size();
- for( j = 0; j < count; j++ )
- {
- types[i][j] &= ~CV_MAT_CN_MASK;
- }
- }
-}
-
-void CxCore_MinMaxBaseTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- if( !gen_scalars )
- cvTsMinMax( &test_mat[INPUT][0], &test_mat[INPUT][1],
- &test_mat[REF_OUTPUT][0], op_type );
- else
- cvTsMinMaxS( &test_mat[INPUT][0], gamma.val[0],
- &test_mat[REF_OUTPUT][0], op_type );
-}
-
-
-class CxCore_MinTest : public CxCore_MinMaxBaseTest
-{
-public:
- CxCore_MinTest();
-protected:
- void run_func();
-};
-
-
-CxCore_MinTest::CxCore_MinTest()
- : CxCore_MinMaxBaseTest( "arithm-min", "cvMin", CV_TS_MIN, 0 )
-{
-}
-
-void CxCore_MinTest::run_func()
-{
- if(!test_nd)
- {
- cvMin( test_array[INPUT][0], test_array[INPUT][1], test_array[OUTPUT][0] );
- }
- else
- {
- cv::MatND c = cv::cvarrToMatND(test_array[OUTPUT][0]);
- cv::min(cv::cvarrToMatND(test_array[INPUT][0]),
- cv::cvarrToMatND(test_array[INPUT][1]), c);
- }
-}
-
-CxCore_MinTest min_test;
-
-
-////////////////////////////// max /////////////////////////////
-
-class CxCore_MaxTest : public CxCore_MinMaxBaseTest
-{
-public:
- CxCore_MaxTest();
-protected:
- void run_func();
-};
-
-CxCore_MaxTest::CxCore_MaxTest()
- : CxCore_MinMaxBaseTest( "arithm-max", "cvMax", CV_TS_MAX, 0 )
-{
-}
-
-void CxCore_MaxTest::run_func()
-{
- if(!test_nd)
- {
- cvMax( test_array[INPUT][0], test_array[INPUT][1], test_array[OUTPUT][0] );
- }
- else
- {
- cv::MatND c = cv::cvarrToMatND(test_array[OUTPUT][0]);
- cv::max(cv::cvarrToMatND(test_array[INPUT][0]),
- cv::cvarrToMatND(test_array[INPUT][1]), c);
- }
-}
-
-CxCore_MaxTest max_test;
-
-
-////////////////////////////// mins /////////////////////////////
-
-class CxCore_MinSTest : public CxCore_MinMaxBaseTest
-{
-public:
- CxCore_MinSTest();
-protected:
- void run_func();
-};
-
-CxCore_MinSTest::CxCore_MinSTest()
- : CxCore_MinMaxBaseTest( "arithm-mins", "cvMinS", CV_TS_MIN, 4 )
-{
-}
-
-void CxCore_MinSTest::run_func()
-{
- if(!test_nd)
- {
- cvMinS( test_array[INPUT][0], gamma.val[0], test_array[OUTPUT][0] );
- }
- else
- {
- cv::MatND c = cv::cvarrToMatND(test_array[OUTPUT][0]);
- cv::min(cv::cvarrToMatND(test_array[INPUT][0]),
- gamma.val[0], c);
- }
-}
-
-CxCore_MinSTest mins_test;
-
-////////////////////////////// maxs /////////////////////////////
-
-class CxCore_MaxSTest : public CxCore_MinMaxBaseTest
-{
-public:
- CxCore_MaxSTest();
-protected:
- void run_func();
-};
-
-CxCore_MaxSTest::CxCore_MaxSTest()
- : CxCore_MinMaxBaseTest( "arithm-maxs", "cvMaxS", CV_TS_MAX, 4 )
-{
-}
-
-void CxCore_MaxSTest::run_func()
-{
- if(!test_nd)
- {
- cvMaxS( test_array[INPUT][0], gamma.val[0], test_array[OUTPUT][0] );
- }
- else
- {
- cv::MatND c = cv::cvarrToMatND(test_array[OUTPUT][0]);
- cv::max(cv::cvarrToMatND(test_array[INPUT][0]),
- gamma.val[0], c);
- }
-}
-
-CxCore_MaxSTest maxs_test;
-
-
-//////////////////////////////// logic ///////////////////////////////////////
-
-class CxCore_LogicTestImpl : public CxCore_ArithmTestImpl
-{
-public:
- CxCore_LogicTestImpl( const char* test_name, const char* test_funcs, int _logic_op,
- int _generate_scalars=0, bool _allow_mask=true );
-protected:
- void prepare_to_validation( int test_case_idx );
- int logic_op;
-};
-
-CxCore_LogicTestImpl::CxCore_LogicTestImpl( const char* test_name, const char* test_funcs,
- int _logic_op, int _generate_scalars, bool _allow_mask )
- : CxCore_ArithmTestImpl( test_name, test_funcs, _generate_scalars, _allow_mask, false ),
- logic_op(_logic_op)
-{
- if( _generate_scalars )
- test_array[INPUT].pop();
-}
-
-void CxCore_LogicTestImpl::prepare_to_validation( int /*test_case_idx*/ )
-{
- int ref_output_idx = optional_mask ? REF_INPUT_OUTPUT : REF_OUTPUT;
- int output_idx = optional_mask ? INPUT_OUTPUT : OUTPUT;
- const CvMat* mask = test_array[MASK].size() > 0 && test_array[MASK][0] ? &test_mat[MASK][0] : 0;
- CvMat* dst = mask ? &test_mat[TEMP][0] : &test_mat[ref_output_idx][0];
- int i;
- if( test_array[INPUT].size() > 1 )
- {
- cvTsLogic( &test_mat[INPUT][0], &test_mat[INPUT][1], dst, logic_op );
- }
- else
- {
- cvTsLogicS( &test_mat[INPUT][0], gamma, dst, logic_op );
- }
- if( mask )
- cvTsCopy( dst, &test_mat[ref_output_idx][0], mask );
-
- for( i = 0; i < 2; i++ )
- {
- dst = i == 0 ? &test_mat[ref_output_idx][0] : &test_mat[output_idx][0];
-
- if( CV_IS_MAT(dst) )
- {
- CvMat* mat = (CvMat*)dst;
- mat->cols *= CV_ELEM_SIZE(mat->type);
- mat->type = (mat->type & ~CV_MAT_TYPE_MASK) | CV_8UC1;
- }
- else
- {
- IplImage* img = (IplImage*)dst;
- int elem_size;
-
- assert( CV_IS_IMAGE(dst) );
- elem_size = ((img->depth & 255)>>3)*img->nChannels;
- img->width *= elem_size;
-
- if( img->roi )
- {
- img->roi->xOffset *= elem_size;
- img->roi->width *= elem_size;
- }
- img->depth = IPL_DEPTH_8U;
- img->nChannels = 1;
- }
- }
-}
-
-CxCore_LogicTestImpl logic_test("logic", "", -1, 0, false );
-
-class CxCore_LogicTest : public CxCore_LogicTestImpl
-{
-public:
- CxCore_LogicTest( const char* test_name, const char* test_funcs, int _logic_op,
- int _generate_scalars=0, bool _allow_mask=true );
-};
-
-CxCore_LogicTest::CxCore_LogicTest( const char* test_name, const char* test_funcs,
- int _logic_op, int _generate_scalars, bool _allow_mask )
- : CxCore_LogicTestImpl( test_name, test_funcs, _logic_op, _generate_scalars, _allow_mask )
-{
- default_timing_param_names = optional_mask ? arithm_mask_param_names : arithm_param_names;
-
- // inherit the default parameters from arithmerical test
- size_list = 0;
- whole_size_list = 0;
- depth_list = 0;
- cn_list = 0;
-}
-
-
-///////////////////////// and //////////////////////////
-
-class CxCore_AndTest : public CxCore_LogicTest
-{
-public:
- CxCore_AndTest();
-protected:
- void run_func();
-};
-
-CxCore_AndTest::CxCore_AndTest()
- : CxCore_LogicTest( "logic-and", "cvAnd", CV_TS_LOGIC_AND )
-{
-}
-
-void CxCore_AndTest::run_func()
-{
- if(!test_nd)
- {
- cvAnd( test_array[INPUT][0], test_array[INPUT][1],
- test_array[INPUT_OUTPUT][0], test_array[MASK][0] );
- }
- else
- {
- cv::MatND c = cv::cvarrToMatND(test_array[INPUT_OUTPUT][0]);
- cv::bitwise_and(cv::cvarrToMatND(test_array[INPUT][0]),
- cv::cvarrToMatND(test_array[INPUT][1]),
- c, cv::cvarrToMatND(test_array[MASK][0]));
- }
-}
-
-CxCore_AndTest and_test;
-
-
-class CxCore_AndSTest : public CxCore_LogicTest
-{
-public:
- CxCore_AndSTest();
-protected:
- void run_func();
-};
-
-CxCore_AndSTest::CxCore_AndSTest()
- : CxCore_LogicTest( "logic-ands", "cvAndS", CV_TS_LOGIC_AND, 4 )
-{
-}
-
-void CxCore_AndSTest::run_func()
-{
- if(!test_nd)
- {
- cvAndS( test_array[INPUT][0], gamma,
- test_array[INPUT_OUTPUT][0], test_array[MASK][0] );
- }
- else
- {
- cv::MatND c = cv::cvarrToMatND(test_array[INPUT_OUTPUT][0]);
- cv::bitwise_and(cv::cvarrToMatND(test_array[INPUT][0]),
- gamma, c,
- cv::cvarrToMatND(test_array[MASK][0]));
- }
-}
-
-CxCore_AndSTest ands_test;
-
-
-///////////////////////// or /////////////////////////
-
-class CxCore_OrTest : public CxCore_LogicTest
-{
-public:
- CxCore_OrTest();
-protected:
- void run_func();
-};
-
-CxCore_OrTest::CxCore_OrTest()
- : CxCore_LogicTest( "logic-or", "cvOr", CV_TS_LOGIC_OR )
-{
-}
-
-void CxCore_OrTest::run_func()
-{
- if(!test_nd)
- {
- cvOr( test_array[INPUT][0], test_array[INPUT][1],
- test_array[INPUT_OUTPUT][0], test_array[MASK][0] );
- }
- else
- {
- cv::MatND c = cv::cvarrToMatND(test_array[INPUT_OUTPUT][0]);
- cv::bitwise_or(cv::cvarrToMatND(test_array[INPUT][0]),
- cv::cvarrToMatND(test_array[INPUT][1]),
- c, cv::cvarrToMatND(test_array[MASK][0]));
- }
-
-}
-
-CxCore_OrTest or_test;
-
-
-class CxCore_OrSTest : public CxCore_LogicTest
-{
-public:
- CxCore_OrSTest();
-protected:
- void run_func();
-};
-
-CxCore_OrSTest::CxCore_OrSTest()
- : CxCore_LogicTest( "logic-ors", "cvOrS", CV_TS_LOGIC_OR, 4 )
-{
-}
-
-void CxCore_OrSTest::run_func()
-{
- if(!test_nd)
- {
- cvOrS( test_array[INPUT][0], gamma,
- test_array[INPUT_OUTPUT][0], test_array[MASK][0] );
- }
- else
- {
- cv::MatND c = cv::cvarrToMatND(test_array[INPUT_OUTPUT][0]);
- cv::bitwise_or(cv::cvarrToMatND(test_array[INPUT][0]),
- gamma, c,
- cv::cvarrToMatND(test_array[MASK][0]));
- }
-}
-
-CxCore_OrSTest ors_test;
-
-
-////////////////////////// xor ////////////////////////////
-
-class CxCore_XorTest : public CxCore_LogicTest
-{
-public:
- CxCore_XorTest();
-protected:
- void run_func();
-};
-
-CxCore_XorTest::CxCore_XorTest()
- : CxCore_LogicTest( "logic-xor", "cvXor", CV_TS_LOGIC_XOR )
-{
-}
-
-void CxCore_XorTest::run_func()
-{
- if(!test_nd)
- {
- cvXor( test_array[INPUT][0], test_array[INPUT][1],
- test_array[INPUT_OUTPUT][0], test_array[MASK][0] );
- }
- else
- {
- cv::MatND c = cv::cvarrToMatND(test_array[INPUT_OUTPUT][0]);
- cv::bitwise_xor(cv::cvarrToMatND(test_array[INPUT][0]),
- cv::cvarrToMatND(test_array[INPUT][1]),
- c, cv::cvarrToMatND(test_array[MASK][0]));
- }
-
-}
-
-CxCore_XorTest xor_test;
-
-
-class CxCore_XorSTest : public CxCore_LogicTest
-{
-public:
- CxCore_XorSTest();
-protected:
- void run_func();
-};
-
-CxCore_XorSTest::CxCore_XorSTest()
- : CxCore_LogicTest( "logic-xors", "cvXorS", CV_TS_LOGIC_XOR, 4 )
-{
-}
-
-void CxCore_XorSTest::run_func()
-{
- if(!test_nd)
- {
- cvXorS( test_array[INPUT][0], gamma,
- test_array[INPUT_OUTPUT][0], test_array[MASK][0] );
- }
- else
- {
- cv::MatND c = cv::cvarrToMatND(test_array[INPUT_OUTPUT][0]);
- cv::bitwise_xor(cv::cvarrToMatND(test_array[INPUT][0]),
- gamma, c,
- cv::cvarrToMatND(test_array[MASK][0]));
- }
-}
-
-CxCore_XorSTest xors_test;
-
-
-////////////////////////// not ////////////////////////////
-
-class CxCore_NotTest : public CxCore_LogicTest
-{
-public:
- CxCore_NotTest();
-protected:
- void run_func();
-};
-
-CxCore_NotTest::CxCore_NotTest()
- : CxCore_LogicTest( "logic-not", "cvNot", CV_TS_LOGIC_NOT, 4, false )
-{
-}
-
-void CxCore_NotTest::run_func()
-{
- if(!test_nd)
- {
- cvNot( test_array[INPUT][0], test_array[OUTPUT][0] );
- }
- else
- {
- cv::MatND c = cv::cvarrToMatND(test_array[OUTPUT][0]);
- cv::bitwise_not(cv::cvarrToMatND(test_array[INPUT][0]), c);
- }
-}
-
-CxCore_NotTest nots_test;
-
-///////////////////////// cmp //////////////////////////////
-
-static int cmp_op_values[] = { CV_CMP_GE, CV_CMP_EQ, CV_CMP_NE, -1 };
-
-class CxCore_CmpBaseTestImpl : public CxCore_ArithmTestImpl
-{
-public:
- CxCore_CmpBaseTestImpl( const char* test_name, const char* test_funcs,
- int in_range, int _generate_scalars=0 );
-protected:
- double get_success_error_level( int test_case_idx, int i, int j );
- void get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types );
- void get_timing_test_array_types_and_sizes( int test_case_idx, CvSize** sizes,
- int** types, CvSize** whole_sizes, bool* are_images );
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
- void prepare_to_validation( int test_case_idx );
- int write_default_params( CvFileStorage* fs );
- int in_range;
- int cmp_op;
- enum { CMP_OP_COUNT=6 };
- const char* cmp_op_strings[CMP_OP_COUNT];
-};
-
-CxCore_CmpBaseTestImpl::CxCore_CmpBaseTestImpl( const char* test_name, const char* test_funcs,
- int _in_range, int _generate_scalars )
- : CxCore_ArithmTestImpl( test_name, test_funcs, _generate_scalars, 0, 0 ), in_range(_in_range)
-{
- static const char* cmp_param_names[] = { "size", "cmp_op", "depth", 0 };
- static const char* inrange_param_names[] = { "size", "channels", "depth", 0 };
-
- if( in_range )
- {
- test_array[INPUT].push(NULL);
- test_array[TEMP].push(NULL);
- test_array[TEMP].push(NULL);
- if( !gen_scalars )
- test_array[TEMP].push(NULL);
- }
- if( gen_scalars )
- test_array[INPUT].pop();
-
- default_timing_param_names = in_range == 1 ? inrange_param_names : cmp_param_names;
-
- cmp_op_strings[CV_CMP_EQ] = "eq";
- cmp_op_strings[CV_CMP_LT] = "lt";
- cmp_op_strings[CV_CMP_LE] = "le";
- cmp_op_strings[CV_CMP_GE] = "ge";
- cmp_op_strings[CV_CMP_GT] = "gt";
- cmp_op_strings[CV_CMP_NE] = "ne";
-
- cmp_op = -1;
-}
-
-double CxCore_CmpBaseTestImpl::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- return 0;
-}
-
-
-void CxCore_CmpBaseTestImpl::get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types )
-{
- int j, count;
- CxCore_ArithmTestImpl::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_8UC1;
- if( in_range == 0 )
- {
- // for cmp tests make all the input arrays single-channel
- count = test_array[INPUT].size();
- for( j = 0; j < count; j++ )
- types[INPUT][j] &= ~CV_MAT_CN_MASK;
-
- cmp_op = cvTsRandInt(ts->get_rng()) % 6; // == > >= < <= !=
- }
- else if( in_range == 1 )
- {
- types[TEMP][0] = CV_8UC1;
- types[TEMP][1] &= ~CV_MAT_CN_MASK;
- if( !gen_scalars )
- types[TEMP][2] &= ~CV_MAT_CN_MASK;
- }
-}
-
-
-int CxCore_CmpBaseTestImpl::write_default_params( CvFileStorage* fs )
-{
- int code = CxCore_ArithmTestImpl::write_default_params(fs);
- if( code < 0 || ts->get_testing_mode() != CvTS::TIMING_MODE )
- return code;
- if( in_range == 0 )
- {
- start_write_param( fs );
- int i;
- cvStartWriteStruct( fs, "cmp_op", CV_NODE_SEQ + CV_NODE_FLOW );
- for( i = 0; cmp_op_values[i] >= 0; i++ )
- cvWriteString( fs, 0, cmp_op_strings[cmp_op_values[i]] );
- cvEndWriteStruct(fs);
- }
- return code;
-}
-
-
-void CxCore_CmpBaseTestImpl::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types,
- CvSize** whole_sizes, bool* are_images )
-{
- CxCore_ArithmTestImpl::get_timing_test_array_types_and_sizes( test_case_idx,
- sizes, types, whole_sizes, are_images );
- types[OUTPUT][0] = CV_8UC1;
- if( in_range == 0 )
- {
- const char* cmp_op_str = cvReadString( find_timing_param( "cmp_op" ), "ge" );
- int i;
- cmp_op = CV_CMP_GE;
- for( i = 0; i < CMP_OP_COUNT; i++ )
- if( strcmp( cmp_op_str, cmp_op_strings[i] ) == 0 )
- {
- cmp_op = i;
- break;
- }
- }
-}
-
-
-void CxCore_CmpBaseTestImpl::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- if( in_range == 0 )
- {
- sprintf( ptr, "%s,", cmp_op_strings[cmp_op] );
- ptr += strlen(ptr);
- params_left--;
- }
- CxCore_ArithmTestImpl::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-
-void CxCore_CmpBaseTestImpl::prepare_to_validation( int /*test_case_idx*/ )
-{
- CvMat* dst = &test_mat[REF_OUTPUT][0];
- if( !in_range )
- {
- if( test_array[INPUT].size() > 1 )
- {
- cvTsCmp( &test_mat[INPUT][0], &test_mat[INPUT][1], dst, cmp_op );
- }
- else
- {
- cvTsCmpS( &test_mat[INPUT][0], gamma.val[0], dst, cmp_op );
- }
- }
- else
- {
- int el_type = CV_MAT_TYPE( test_mat[INPUT][0].type );
- int i, cn = CV_MAT_CN(el_type);
- CvMat* tdst = dst;
-
- for( i = 0; i < cn*2; i++ )
- {
- int coi = i / 2, is_lower = (i % 2) == 0;
- int cmp_op = is_lower ? CV_CMP_GE : CV_CMP_LT;
- const CvMat* src = &test_mat[INPUT][0];
- const CvMat* lu = gen_scalars ? 0 : &test_mat[INPUT][is_lower?1:2];
- double luS = is_lower ? alpha.val[coi] : gamma.val[coi];
-
- if( cn > 1 )
- {
- cvTsExtract( src, &test_mat[TEMP][1], coi );
- src = &test_mat[TEMP][1];
-
- if( !gen_scalars )
- {
- cvTsExtract( lu, &test_mat[TEMP][2], coi );
- lu = &test_mat[TEMP][2];
- }
- }
-
- if( !gen_scalars )
- cvTsCmp( src, lu, tdst, cmp_op );
- else
- cvTsCmpS( src, luS, tdst, cmp_op );
- if( i > 0 )
- cvTsLogic( tdst, dst, dst, CV_TS_LOGIC_AND );
- tdst = &test_mat[TEMP][0];
- }
- }
-}
-
-
-CxCore_CmpBaseTestImpl cmpbase_test( "cmp", "", -1 );
-
-
-class CxCore_CmpBaseTest : public CxCore_CmpBaseTestImpl
-{
-public:
- CxCore_CmpBaseTest( const char* test_name, const char* test_funcs,
- int in_range, int _generate_scalars=0 );
-};
-
-CxCore_CmpBaseTest::CxCore_CmpBaseTest( const char* test_name, const char* test_funcs,
- int _in_range, int _generate_scalars )
- : CxCore_CmpBaseTestImpl( test_name, test_funcs, _in_range, _generate_scalars )
-{
- // inherit the default parameters from arithmerical test
- size_list = 0;
- depth_list = 0;
- cn_list = 0;
-}
-
-
-class CxCore_CmpTest : public CxCore_CmpBaseTest
-{
-public:
- CxCore_CmpTest();
-protected:
- void run_func();
-};
-
-CxCore_CmpTest::CxCore_CmpTest()
- : CxCore_CmpBaseTest( "cmp-cmp", "cvCmp", 0, 0 )
-{
-}
-
-void CxCore_CmpTest::run_func()
-{
- if(!test_nd)
- {
- cvCmp( test_array[INPUT][0], test_array[INPUT][1],
- test_array[OUTPUT][0], cmp_op );
- }
- else
- {
- cv::MatND c = cv::cvarrToMatND(test_array[OUTPUT][0]);
- cv::compare(cv::cvarrToMatND(test_array[INPUT][0]),
- cv::cvarrToMatND(test_array[INPUT][1]),
- c, cmp_op);
- }
-}
-
-CxCore_CmpTest cmp_test;
-
-
-class CxCore_CmpSTest : public CxCore_CmpBaseTest
-{
-public:
- CxCore_CmpSTest();
-protected:
- void run_func();
-};
-
-CxCore_CmpSTest::CxCore_CmpSTest()
- : CxCore_CmpBaseTest( "cmp-cmps", "cvCmpS", 0, 4 )
-{
-}
-
-void CxCore_CmpSTest::run_func()
-{
- if(!test_nd)
- {
- cvCmpS( test_array[INPUT][0], gamma.val[0],
- test_array[OUTPUT][0], cmp_op );
- }
- else
- {
- cv::MatND c = cv::cvarrToMatND(test_array[OUTPUT][0]);
- cv::compare(cv::cvarrToMatND(test_array[INPUT][0]),
- gamma.val[0], c, cmp_op);
- }
-}
-
-CxCore_CmpSTest cmps_test;
-
-
-class CxCore_InRangeTest : public CxCore_CmpBaseTest
-{
-public:
- CxCore_InRangeTest();
-protected:
- void run_func();
-};
-
-CxCore_InRangeTest::CxCore_InRangeTest()
- : CxCore_CmpBaseTest( "cmp-inrange", "cvInRange", 1, 0 )
-{
-}
-
-void CxCore_InRangeTest::run_func()
-{
- if(!test_nd)
- {
- cvInRange( test_array[INPUT][0], test_array[INPUT][1],
- test_array[INPUT][2], test_array[OUTPUT][0] );
- }
- else
- {
- cv::MatND c = cv::cvarrToMatND(test_array[OUTPUT][0]);
- cv::inRange(cv::cvarrToMatND(test_array[INPUT][0]),
- cv::cvarrToMatND(test_array[INPUT][1]),
- cv::cvarrToMatND(test_array[INPUT][2]),
- c);
- }
-}
-
-CxCore_InRangeTest inrange_test;
-
-
-class CxCore_InRangeSTest : public CxCore_CmpBaseTest
-{
-public:
- CxCore_InRangeSTest();
-protected:
- void run_func();
-};
-
-CxCore_InRangeSTest::CxCore_InRangeSTest()
- : CxCore_CmpBaseTest( "cmp-inranges", "cvInRangeS", 1, 5 )
-{
-}
-
-void CxCore_InRangeSTest::run_func()
-{
- if(!test_nd)
- {
- cvInRangeS( test_array[INPUT][0], alpha, gamma, test_array[OUTPUT][0] );
- }
- else
- {
- cv::MatND c = cv::cvarrToMatND(test_array[OUTPUT][0]);
- cv::inRange(cv::cvarrToMatND(test_array[INPUT][0]), alpha, gamma, c);
- }
-}
-
-CxCore_InRangeSTest inranges_test;
-
-
-/////////////////////////// convertscale[abs] ////////////////////////////////////////
-
-static const char* cvt_param_names[] = { "size", "scale", "dst_depth", "depth", 0 };
-static const char* cvt_abs_param_names[] = { "size", "depth", 0 };
-static const int cvt_scale_flags[] = { 0, 1 };
-
-class CxCore_CvtBaseTestImpl : public CxCore_ArithmTestImpl
-{
-public:
- CxCore_CvtBaseTestImpl( const char* test_name, const char* test_funcs, bool calc_abs );
-protected:
- void get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types );
- void get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types,
- CvSize** whole_sizes, bool *are_images );
- double get_success_error_level( int test_case_idx, int i, int j );
-
- int prepare_test_case( int test_case_idx );
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
- int write_default_params( CvFileStorage* fs );
-
- void prepare_to_validation( int test_case_idx );
-};
-
-
-CxCore_CvtBaseTestImpl::CxCore_CvtBaseTestImpl( const char* test_name,
- const char* test_funcs,
- bool _calc_abs )
- : CxCore_ArithmTestImpl( test_name, test_funcs, 5, false, _calc_abs )
-{
- test_array[INPUT].pop();
- default_timing_param_names = 0;
- cn_list = 0;
-}
-
-
-// unlike many other arithmetic functions, conversion operations support 8s type,
-// also, for cvCvtScale output array depth may be arbitrary and
-// for cvCvtScaleAbs output depth = CV_8U
-void CxCore_CvtBaseTestImpl::get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types )
-{
- CxCore_ArithmTestImpl::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- CvRNG* rng = ts->get_rng();
- int depth = CV_8U, rbits;
- types[INPUT][0] = (types[INPUT][0] & ~CV_MAT_DEPTH_MASK)|
- cvTsRandInt(rng)%(CV_64F+1);
- if( !calc_abs )
- depth = cvTsRandInt(rng) % (CV_64F+1);
- types[OUTPUT][0] = types[REF_OUTPUT][0] = (types[INPUT][0] & ~CV_MAT_DEPTH_MASK)|depth;
-
- rbits = cvTsRandInt(rng);
- // check special cases: shift=0 and/or scale=1.
- if( (rbits & 3) == 0 )
- gamma.val[0] = 0;
- if( (rbits & 12) == 0 )
- alpha.val[0] = 1;
-}
-
-
-double CxCore_CvtBaseTestImpl::get_success_error_level( int, int, int )
-{
- if( CV_MAT_DEPTH(test_mat[OUTPUT][0].type) <= CV_32S )
- return alpha.val[0] != cvRound(alpha.val[0]) ||
- beta.val[0] != cvRound(beta.val[0]) ||
- gamma.val[0] != cvRound(gamma.val[0]);
-
- CvScalar l1, h1, l2, h2;
- int stype = CV_MAT_TYPE(test_mat[INPUT][0].type);
- int dtype = CV_MAT_TYPE(test_mat[OUTPUT][0].type);
- get_minmax_bounds( INPUT, 0, stype, &l1, &h1 );
- get_minmax_bounds( OUTPUT, 0, dtype, &l2, &h2 );
- double maxval = 0;
- for( int i = 0; i < 4; i++ )
- {
- maxval = MAX(maxval, fabs(l1.val[i]));
- maxval = MAX(maxval, fabs(h1.val[i]));
- maxval = MAX(maxval, fabs(l2.val[i]));
- maxval = MAX(maxval, fabs(h2.val[i]));
- }
- double max_err = (CV_MAT_DEPTH(stype) == CV_64F || CV_MAT_DEPTH(dtype) == CV_64F ?
- DBL_EPSILON : FLT_EPSILON)*maxval*MAX(fabs(alpha.val[0]), 1.)*100;
- return max_err;
-}
-
-
-void CxCore_CvtBaseTestImpl::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool* are_images )
-{
- CxCore_ArithmTestImpl::get_timing_test_array_types_and_sizes( test_case_idx,
- sizes, types, whole_sizes, are_images );
- bool scale = true;
- int dst_depth = CV_8U;
- int cn = CV_MAT_CN(types[INPUT][0]);
- if( !calc_abs )
- {
- scale = cvReadInt( find_timing_param( "scale" ), 1 ) != 0;
- dst_depth = cvTsTypeByName( cvReadString(find_timing_param( "dst_depth" ), "8u") );
- }
-
- types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_MAKETYPE(dst_depth, cn);
-
- if( scale )
- {
- alpha.val[0] = 2.1;
- gamma.val[0] = -100.;
- }
- else
- {
- alpha.val[0] = 1.;
- gamma.val[0] = 0.;
- }
-}
-
-
-int CxCore_CvtBaseTestImpl::prepare_test_case( int test_case_idx )
-{
- int code = CxCore_ArithmTestImpl::prepare_test_case( test_case_idx );
-
- if( code > 0 && ts->get_testing_mode() == CvTS::TIMING_MODE )
- {
- if( CV_ARE_TYPES_EQ( &test_mat[INPUT][0], &test_mat[OUTPUT][0] ) &&
- !calc_abs && alpha.val[0] == 1 && gamma.val[0] == 0 )
- code = 0; // skip the case when no any transformation is done
- }
-
- return code;
-}
-
-
-void CxCore_CvtBaseTestImpl::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- sprintf( ptr, "%s,", alpha.val[0] == 1. && gamma.val[0] == 0. ? "no_scale" : "scale" );
- ptr += strlen(ptr);
- params_left--;
- CxCore_ArithmTestImpl::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-
-int CxCore_CvtBaseTestImpl::write_default_params( CvFileStorage* fs )
-{
- int i, code = CxCore_ArithmTestImpl::write_default_params(fs);
- if( code < 0 || ts->get_testing_mode() != CvTS::TIMING_MODE )
- return code;
- if( !calc_abs )
- {
- start_write_param( fs );
- cvStartWriteStruct( fs, "dst_depth", CV_NODE_SEQ + CV_NODE_FLOW );
- for( i = 0; arithm_depths[i] >= 0; i++ )
- cvWriteString( fs, 0, cvTsGetTypeName(arithm_depths[i]) );
- cvEndWriteStruct(fs);
- write_int_list( fs, "scale", cvt_scale_flags, CV_DIM(cvt_scale_flags) );
- }
- return code;
-}
-
-
-void CxCore_CvtBaseTestImpl::prepare_to_validation( int /*test_case_idx*/ )
-{
- cvTsAdd( &test_mat[INPUT][0], cvScalarAll(alpha.val[0]), 0, beta,
- cvScalarAll(gamma.val[0]), &test_mat[REF_OUTPUT][0], calc_abs );
-}
-
-CxCore_CvtBaseTestImpl cvt_test( "cvt", "", true );
-
-
-class CxCore_CvtBaseTest : public CxCore_CvtBaseTestImpl
-{
-public:
- CxCore_CvtBaseTest( const char* test_name, const char* test_funcs, bool calc_abs );
-};
-
-
-CxCore_CvtBaseTest::CxCore_CvtBaseTest( const char* test_name, const char* test_funcs, bool _calc_abs )
- : CxCore_CvtBaseTestImpl( test_name, test_funcs, _calc_abs )
-{
- // inherit the default parameters from arithmerical test
- size_list = 0;
- whole_size_list = 0;
- depth_list = 0;
- cn_list = 0;
-}
-
-
-class CxCore_CvtScaleTest : public CxCore_CvtBaseTest
-{
-public:
- CxCore_CvtScaleTest();
-protected:
- void run_func();
-};
-
-CxCore_CvtScaleTest::CxCore_CvtScaleTest()
- : CxCore_CvtBaseTest( "cvt-scale", "cvCvtScale", false )
-{
- default_timing_param_names = cvt_param_names;
-}
-
-void CxCore_CvtScaleTest::run_func()
-{
- if(!test_nd)
- {
- cvConvertScale( test_array[INPUT][0], test_array[OUTPUT][0],
- alpha.val[0], gamma.val[0] );
- }
- else
- {
- cv::MatND c = cv::cvarrToMatND(test_array[OUTPUT][0]);
- cv::cvarrToMatND(test_array[INPUT][0]).convertTo(c,c.type(),alpha.val[0], gamma.val[0]);
- }
-}
-
-CxCore_CvtScaleTest cvtscale_test;
-
-
-class CxCore_CvtScaleAbsTest : public CxCore_CvtBaseTest
-{
-public:
- CxCore_CvtScaleAbsTest();
-protected:
- void run_func();
-};
-
-CxCore_CvtScaleAbsTest::CxCore_CvtScaleAbsTest()
- : CxCore_CvtBaseTest( "cvt-scaleabs", "cvCvtScaleAbs", true )
-{
- default_timing_param_names = cvt_abs_param_names;
-}
-
-void CxCore_CvtScaleAbsTest::run_func()
-{
- if(!test_nd)
- {
- cvConvertScaleAbs( test_array[INPUT][0], test_array[OUTPUT][0],
- alpha.val[0], gamma.val[0] );
- }
- else
- {
- cv::Mat c = cv::cvarrToMat(test_array[OUTPUT][0]);
- cv::convertScaleAbs(cv::cvarrToMat(test_array[INPUT][0]),c,alpha.val[0], gamma.val[0]);
- }
-}
-
-CxCore_CvtScaleAbsTest cvtscaleabs_test;
-
-
-/////////////////////////////// statistics //////////////////////////////////
-
-static const char* stat_param_names[] = { "size", "coi", "channels", "depth", 0 };
-static const char* stat_mask_param_names[] = { "size", "coi", "channels", "depth", "use_mask", 0 };
-static const char* stat_single_param_names[] = { "size", "channels", "depth", 0 };
-static const char* stat_single_mask_param_names[] = { "size", "channels", "depth", "use_mask", 0 };
-static const char* stat_coi_modes[] = { "all", "single", 0 };
-
-class CxCore_StatTestImpl : public CvArrTest
-{
-public:
- CxCore_StatTestImpl( const char* test_name, const char* test_funcs,
- int _output_count, bool _single_channel,
- bool _allow_mask=true, bool _is_binary=false );
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types,
- CvSize** whole_sizes, bool* are_images );
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
- int write_default_params( CvFileStorage* fs );
- int prepare_test_case( int test_case_idx );
- double get_success_error_level( int test_case_idx, int i, int j );
-
- int coi;
- int output_count;
- bool single_channel;
- bool is_binary;
- bool test_nd;
-};
-
-
-CxCore_StatTestImpl::CxCore_StatTestImpl( const char* test_name,
- const char* test_funcs, int _output_count,
- bool _single_channel, bool _allow_mask, bool _is_binary )
- : CvArrTest( test_name, test_funcs, "" ), output_count(_output_count),
- single_channel(_single_channel), is_binary(_is_binary)
-{
- test_array[INPUT].push(NULL);
- if( is_binary )
- test_array[INPUT].push(NULL);
- optional_mask = _allow_mask;
- if( optional_mask )
- test_array[MASK].push(NULL);
- test_array[OUTPUT].push(NULL);
- test_array[REF_OUTPUT].push(NULL);
- coi = 0;
-
- size_list = arithm_sizes;
- whole_size_list = arithm_whole_sizes;
- depth_list = arithm_depths;
- cn_list = arithm_channels;
- test_nd = false;
-}
-
-
-void CxCore_StatTestImpl::get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- int depth = cvTsRandInt(rng)%(CV_64F+1);
- int cn = cvTsRandInt(rng) % 4 + 1;
- int j, count = test_array[INPUT].size();
-
- CvArrTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- depth += depth == CV_8S;
-
- for( j = 0; j < count; j++ )
- types[INPUT][j] = CV_MAKETYPE(depth, cn);
-
- // regardless of the test case, the output is always a fixed-size tuple of numbers
- sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = cvSize( output_count, 1 );
- types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_64FC1;
-
- coi = 0;
- cvmat_allowed = true;
- if( cn > 1 && (single_channel || (cvTsRandInt(rng) & 3) == 0) )
- {
- coi = cvTsRandInt(rng) % cn + 1;
- cvmat_allowed = false;
- }
- test_nd = cvTsRandInt(rng) % 3 == 0;
-}
-
-
-void CxCore_StatTestImpl::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool* are_images )
-{
- CvArrTest::get_timing_test_array_types_and_sizes( test_case_idx, sizes, types,
- whole_sizes, are_images );
- const char* coi_mode_str = cvReadString(find_timing_param("coi"), single_channel ? "single" : "all");
-
- // regardless of the test case, the output is always a fixed-size tuple of numbers
- sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = cvSize( output_count, 1 );
- types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_64FC1;
-
- int cn = CV_MAT_CN(types[INPUT][0]);
- coi = 0;
- cvmat_allowed = true;
- if( strcmp( coi_mode_str, "single" ) == 0 )
- {
- CvRNG* rng = ts->get_rng();
- coi = cvTsRandInt(rng) % cn + 1;
- cvmat_allowed = false;
- *are_images = true;
- }
-}
-
-
-int CxCore_StatTestImpl::write_default_params( CvFileStorage* fs )
-{
- int code = CvArrTest::write_default_params(fs);
- if( code < 0 || ts->get_testing_mode() != CvTS::TIMING_MODE )
- return code;
- if( !single_channel )
- write_string_list( fs, "coi", stat_coi_modes );
- return code;
-}
-
-
-int CxCore_StatTestImpl::prepare_test_case( int test_case_idx )
-{
- int code = CvArrTest::prepare_test_case( test_case_idx );
-
- if( coi && code > 0 )
- {
- int j, count = test_array[INPUT].size();
-
- if( ts->get_testing_mode() == CvTS::TIMING_MODE && CV_MAT_CN(test_mat[INPUT][0].type) == 1 )
- return 0;
-
- for( j = 0; j < count; j++ )
- {
- IplImage* img = (IplImage*)test_array[INPUT][j];
- if( img )
- cvSetImageCOI( img, coi );
- }
- }
-
- return code;
-}
-
-
-void CxCore_StatTestImpl::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- sprintf( ptr, "%s,", coi > 0 || CV_MAT_CN(test_mat[INPUT][0].type) == 1 ? "single" : "all" );
- ptr += strlen(ptr);
- params_left--;
- CvArrTest::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-
-double CxCore_StatTestImpl::get_success_error_level( int test_case_idx, int i, int j )
-{
- int depth = CV_MAT_DEPTH(cvGetElemType(test_array[INPUT][0]));
- if( depth == CV_32F )
- return FLT_EPSILON*1000;
- if( depth == CV_64F )
- return DBL_EPSILON*100000;
- else
- return CvArrTest::get_success_error_level( test_case_idx, i, j );
-}
-
-CxCore_StatTestImpl stat_test( "stat", "", 0, true, false );
-
-
-class CxCore_StatTest : public CxCore_StatTestImpl
-{
-public:
- CxCore_StatTest( const char* test_name, const char* test_funcs,
- int _output_count, bool _single_channel,
- bool _allow_mask=1, bool _is_binary=0 );
-};
-
-CxCore_StatTest::CxCore_StatTest( const char* test_name, const char* test_funcs,
- int _output_count, bool _single_channel,
- bool _allow_mask, bool _is_binary )
- : CxCore_StatTestImpl( test_name, test_funcs, _output_count, _single_channel, _allow_mask, _is_binary )
-{
- if( !single_channel )
- default_timing_param_names = optional_mask ? stat_single_mask_param_names : stat_single_param_names;
- else
- default_timing_param_names = optional_mask ? stat_mask_param_names : stat_param_names;
-
- // inherit the default parameters from arithmerical test
- size_list = 0;
- whole_size_list = 0;
- depth_list = 0;
- cn_list = 0;
-}
-
-////////////////// sum /////////////////
-class CxCore_SumTest : public CxCore_StatTest
-{
-public:
- CxCore_SumTest();
-protected:
- void run_func();
- void prepare_to_validation( int test_case_idx );
- double get_success_error_level( int test_case_idx, int i, int j );
-};
-
-
-CxCore_SumTest::CxCore_SumTest()
- : CxCore_StatTest( "stat-sum", "cvSum", 4 /* CvScalar */, false, false, false )
-{
-}
-
-double CxCore_SumTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- int depth = CV_MAT_DEPTH(cvGetElemType(test_array[INPUT][0]));
- if( depth == CV_32F )
- return FLT_EPSILON*1000;
- return DBL_EPSILON*100000;
-}
-
-
-void CxCore_SumTest::run_func()
-{
- if(!test_nd || coi)
- {
- *(CvScalar*)(test_mat[OUTPUT][0].data.db) = cvSum(test_array[INPUT][0]);
- }
- else
- {
- *(cv::Scalar*)(test_mat[OUTPUT][0].data.db) = cv::sum(cv::cvarrToMatND(test_array[INPUT][0]));
- }
-}
-
-void CxCore_SumTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- CvScalar mean;
- int nonzero = cvTsMeanStdDevNonZero( &test_mat[INPUT][0], 0, &mean, 0, coi );
-
- *(CvScalar*)(test_mat[REF_OUTPUT][0].data.db) = mean;
- mean = *(CvScalar*)(test_mat[OUTPUT][0].data.db);
-
- mean.val[0] /= nonzero;
- mean.val[1] /= nonzero;
- mean.val[2] /= nonzero;
- mean.val[3] /= nonzero;
- *(CvScalar*)(test_mat[OUTPUT][0].data.db) = mean;
-}
-
-CxCore_SumTest sum_test;
-
-
-////////////////// nonzero /////////////////
-class CxCore_NonZeroTest : public CxCore_StatTest
-{
-public:
- CxCore_NonZeroTest();
-protected:
- void run_func();
- void prepare_to_validation( int test_case_idx );
- void get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types );
-};
-
-
-CxCore_NonZeroTest::CxCore_NonZeroTest()
- : CxCore_StatTest( "stat-nonzero", "cvCountNonZero", 1 /* int */, true, false, false )
-{
- test_array[TEMP].push(NULL);
- test_array[TEMP].push(NULL);
-}
-
-void CxCore_NonZeroTest::run_func()
-{
- if(!test_nd || coi)
- {
- test_mat[OUTPUT][0].data.db[0] = cvCountNonZero(test_array[INPUT][0]);
- }
- else
- {
- test_mat[OUTPUT][0].data.db[0] = cv::countNonZero(cv::cvarrToMatND(test_array[INPUT][0]));
- }
-}
-
-void CxCore_NonZeroTest::get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types )
-{
- CxCore_StatTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- types[TEMP][0] = CV_8UC1;
- if( CV_MAT_CN(types[INPUT][0]) > 1 )
- types[TEMP][1] = types[INPUT][0] & ~CV_MAT_CN_MASK;
- else
- sizes[TEMP][1] = cvSize(0,0);
-}
-
-
-void CxCore_NonZeroTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- CvMat* plane = &test_mat[INPUT][0];
- if( CV_MAT_CN(plane->type) > 1 )
- {
- plane = &test_mat[TEMP][1];
- assert( coi > 0 );
- cvTsExtract( &test_mat[INPUT][0], plane, coi-1 );
- }
- cvTsCmpS( plane, 0, &test_mat[TEMP][0], CV_CMP_NE );
- int nonzero = cvTsMeanStdDevNonZero( &test_mat[INPUT][0], &test_mat[TEMP][0], 0, 0, coi );
- test_mat[REF_OUTPUT][0].data.db[0] = nonzero;
-}
-
-
-CxCore_NonZeroTest nonzero_test;
-
-
-/////////////////// mean //////////////////////
-class CxCore_MeanTest : public CxCore_StatTest
-{
-public:
- CxCore_MeanTest();
-protected:
- void run_func();
- void prepare_to_validation( int test_case_idx );
-};
-
-
-CxCore_MeanTest::CxCore_MeanTest()
- : CxCore_StatTest( "stat-mean", "cvAvg", 4 /* CvScalar */, false, true, false )
-{
-}
-
-void CxCore_MeanTest::run_func()
-{
- if(!test_nd || coi)
- {
- *(CvScalar*)(test_mat[OUTPUT][0].data.db) =
- cvAvg(test_array[INPUT][0], test_array[MASK][0]);
- }
- else
- {
- *(cv::Scalar*)(test_mat[OUTPUT][0].data.db) = cv::mean(
- cv::cvarrToMatND(test_array[INPUT][0]),
- cv::cvarrToMatND(test_array[MASK][0]));
- }
-}
-
-void CxCore_MeanTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- CvScalar mean;
- cvTsMeanStdDevNonZero( &test_mat[INPUT][0],
- test_array[MASK][0] ? &test_mat[MASK][0] : 0,
- &mean, 0, coi );
- *(CvScalar*)(test_mat[REF_OUTPUT][0].data.db) = mean;
-}
-
-CxCore_MeanTest mean_test;
-
-
-/////////////////// mean_stddev //////////////////////
-class CxCore_MeanStdDevTest : public CxCore_StatTest
-{
-public:
- CxCore_MeanStdDevTest();
-protected:
- void run_func();
- void prepare_to_validation( int test_case_idx );
- double get_success_error_level( int test_case_idx, int i, int j );
-};
-
-
-CxCore_MeanStdDevTest::CxCore_MeanStdDevTest()
- : CxCore_StatTest( "stat-mean_stddev", "cvAvgSdv", 8 /* CvScalar x 2 */, false, true, false )
-{
-}
-
-void CxCore_MeanStdDevTest::run_func()
-{
- if(!test_nd || coi)
- {
- cvAvgSdv( test_array[INPUT][0],
- &((CvScalar*)(test_mat[OUTPUT][0].data.db))[0],
- &((CvScalar*)(test_mat[OUTPUT][0].data.db))[1],
- test_array[MASK][0] );
- }
- else
- {
- cv::meanStdDev(cv::cvarrToMatND(test_array[INPUT][0]),
- ((cv::Scalar*)(test_mat[OUTPUT][0].data.db))[0],
- ((cv::Scalar*)(test_mat[OUTPUT][0].data.db))[1],
- cv::cvarrToMatND(test_array[MASK][0]) );
- }
-}
-
-double CxCore_MeanStdDevTest::get_success_error_level( int test_case_idx, int i, int j )
-{
- int depth = CV_MAT_DEPTH(cvGetElemType(test_array[INPUT][0]));
- if( depth < CV_64F && depth != CV_32S )
- return CxCore_StatTest::get_success_error_level( test_case_idx, i, j );
- return DBL_EPSILON*1e6;
-}
-
-void CxCore_MeanStdDevTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- CvScalar mean, stddev;
- int i;
- CvMat* output = &test_mat[OUTPUT][0];
- CvMat* ref_output = &test_mat[REF_OUTPUT][0];
- cvTsMeanStdDevNonZero( &test_mat[INPUT][0],
- test_array[MASK][0] ? &test_mat[MASK][0] : 0,
- &mean, &stddev, coi );
- ((CvScalar*)(ref_output->data.db))[0] = mean;
- ((CvScalar*)(ref_output->data.db))[1] = stddev;
- for( i = 0; i < 4; i++ )
- {
- output->data.db[i] *= output->data.db[i];
- output->data.db[i+4] = output->data.db[i+4]*output->data.db[i+4] + 1000;
- ref_output->data.db[i] *= ref_output->data.db[i];
- ref_output->data.db[i+4] = ref_output->data.db[i+4]*ref_output->data.db[i+4] + 1000;
- }
-}
-
-CxCore_MeanStdDevTest mean_stddev_test;
-
-
-/////////////////// minmaxloc //////////////////////
-class CxCore_MinMaxLocTest : public CxCore_StatTest
-{
-public:
- CxCore_MinMaxLocTest();
-protected:
- void run_func();
- void prepare_to_validation( int test_case_idx );
-};
-
-
-CxCore_MinMaxLocTest::CxCore_MinMaxLocTest()
- : CxCore_StatTest( "stat-minmaxloc", "cvMinMaxLoc", 6 /* double x 2 + CvPoint x 2 */, true, true, false )
-{
-}
-
-void CxCore_MinMaxLocTest::run_func()
-{
- CvPoint minloc = {0,0}, maxloc = {0,0};
- double* output = test_mat[OUTPUT][0].data.db;
-
- cvMinMaxLoc( test_array[INPUT][0],
- output, output+1, &minloc, &maxloc,
- test_array[MASK][0] );
- output[2] = minloc.x;
- output[3] = minloc.y;
- output[4] = maxloc.x;
- output[5] = maxloc.y;
-}
-
-void CxCore_MinMaxLocTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- double minval = 0, maxval = 0;
- CvPoint minloc = {0,0}, maxloc = {0,0};
- double* ref_output = test_mat[REF_OUTPUT][0].data.db;
- cvTsMinMaxLoc( &test_mat[INPUT][0], test_array[MASK][0] ?
- &test_mat[MASK][0] : 0, &minval, &maxval, &minloc, &maxloc, coi );
- ref_output[0] = minval;
- ref_output[1] = maxval;
- ref_output[2] = minloc.x;
- ref_output[3] = minloc.y;
- ref_output[4] = maxloc.x;
- ref_output[5] = maxloc.y;
-}
-
-CxCore_MinMaxLocTest minmaxloc_test;
-
-
-/////////////////// norm //////////////////////
-
-static const char* stat_norm_param_names[] = { "size", "coi", "norm_type", "channels", "depth", "use_mask", 0 };
-static const char* stat_norm_type_names[] = { "Inf", "L1", "L2", "diff_Inf", "diff_L1", "diff_L2", 0 };
-
-class CxCore_NormTest : public CxCore_StatTest
-{
-public:
- CxCore_NormTest();
-protected:
- void run_func();
- void prepare_to_validation( int test_case_idx );
- void get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types );
- void get_timing_test_array_types_and_sizes( int /*test_case_idx*/,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images );
- int prepare_test_case( int test_case_idx );
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
- int write_default_params( CvFileStorage* fs );
- double get_success_error_level( int test_case_idx, int i, int j );
- int norm_type;
-};
-
-
-CxCore_NormTest::CxCore_NormTest()
- : CxCore_StatTest( "stat-norm", "cvNorm", 1 /* double */, false, true, true )
-{
- test_array[TEMP].push(NULL);
- default_timing_param_names = stat_norm_param_names;
-}
-
-
-double CxCore_NormTest::get_success_error_level( int test_case_idx, int i, int j )
-{
- int depth = CV_MAT_DEPTH(cvGetElemType(test_array[INPUT][0]));
- if( (depth == CV_16U || depth == CV_16S) /*&& (norm_type&3) != CV_C*/ )
- return 1e-4;
- else
- return CxCore_StatTest::get_success_error_level( test_case_idx, i, j );
-}
-
-
-void CxCore_NormTest::get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types )
-{
- int intype;
- int norm_kind;
- CxCore_StatTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- norm_type = cvTsRandInt(ts->get_rng()) % 3; // CV_C, CV_L1 or CV_L2
- norm_kind = cvTsRandInt(ts->get_rng()) % 3; // simple, difference or relative difference
- if( norm_kind == 0 )
- sizes[INPUT][1] = cvSize(0,0);
- norm_type = (1 << norm_type) | (norm_kind*8);
- intype = types[INPUT][0];
- if( CV_MAT_CN(intype) > 1 && coi == 0 )
- sizes[MASK][0] = cvSize(0,0);
- sizes[TEMP][0] = cvSize(0,0);
- if( (norm_type & (CV_DIFF|CV_RELATIVE)) && CV_MAT_DEPTH(intype) <= CV_32F )
- {
- sizes[TEMP][0] = sizes[INPUT][0];
- types[TEMP][0] = (intype & ~CV_MAT_DEPTH_MASK)|
- (CV_MAT_DEPTH(intype) < CV_32F ? CV_32S : CV_64F);
- }
-}
-
-
-void CxCore_NormTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types,
- CvSize** whole_sizes, bool* are_images )
-{
- CxCore_StatTest::get_timing_test_array_types_and_sizes( test_case_idx,
- sizes, types, whole_sizes, are_images );
- const char* norm_type_str = cvReadString( find_timing_param( "norm_type" ), "L2" );
- bool diff = false;
- if( strncmp( norm_type_str, "diff_", 5 ) == 0 )
- {
- diff = true;
- norm_type_str += 5;
- }
-
- if( strcmp( norm_type_str, "L1" ) == 0 )
- norm_type = CV_L1;
- else if( strcmp( norm_type_str, "L2" ) == 0 )
- norm_type = CV_L2;
- else
- norm_type = CV_C;
-
- if( diff )
- norm_type += CV_DIFF;
- else
- sizes[INPUT][1] = cvSize(0,0);
-}
-
-
-int CxCore_NormTest::prepare_test_case( int test_case_idx )
-{
- int code = CxCore_StatTest::prepare_test_case( test_case_idx );
- if( code > 0 && ts->get_testing_mode() == CvTS::TIMING_MODE )
- {
- // currently it is not supported
- if( test_array[MASK][0] && CV_MAT_CN(test_mat[INPUT][0].type) > 1 && coi == 0 )
- return 0;
- }
- return code;
-}
-
-
-int CxCore_NormTest::write_default_params( CvFileStorage* fs )
-{
- int code = CxCore_StatTest::write_default_params(fs);
- if( code < 0 || ts->get_testing_mode() != CvTS::TIMING_MODE )
- return code;
- write_string_list( fs, "norm_type", stat_norm_type_names );
- return code;
-}
-
-
-void CxCore_NormTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- int nt = norm_type & CV_NORM_MASK;
- sprintf( ptr, "%s%s,", norm_type & CV_DIFF ? "diff_" : "",
- nt == CV_C ? "Inf" : nt == CV_L1 ? "L1" : "L2" );
- ptr += strlen(ptr);
- params_left--;
- CxCore_StatTest::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-
-void CxCore_NormTest::run_func()
-{
- if(!test_nd || coi)
- {
- test_mat[OUTPUT][0].data.db[0] = cvNorm( test_array[INPUT][0],
- test_array[INPUT][1], norm_type, test_array[MASK][0] );
- }
- else
- {
- cv::MatND a = cv::cvarrToMatND(test_array[INPUT][0]);
- cv::MatND b = cv::cvarrToMatND(test_array[INPUT][1]);
- cv::MatND mask = cv::cvarrToMatND(test_array[MASK][0]);
- test_mat[OUTPUT][0].data.db[0] = b.data ?
- cv::norm( a, b, norm_type, mask ) :
- cv::norm( a, norm_type, mask );
- }
-}
-
-void CxCore_NormTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- double a_norm = 0, b_norm = 0;
- CvMat* a = &test_mat[INPUT][0];
- CvMat* b = &test_mat[INPUT][1];
- CvMat* mask = test_array[MASK][0] ? &test_mat[MASK][0] : 0;
- CvMat* diff = a;
-
- if( norm_type & (CV_DIFF|CV_RELATIVE) )
- {
- diff = test_array[TEMP][0] ? &test_mat[TEMP][0] : a;
- cvTsAdd( a, cvScalarAll(1.), b, cvScalarAll(-1.),
- cvScalarAll(0.), diff, 0 );
- }
- a_norm = cvTsNorm( diff, mask, norm_type & CV_NORM_MASK, coi );
- if( norm_type & CV_RELATIVE )
- {
- b_norm = cvTsNorm( b, mask, norm_type & CV_NORM_MASK, coi );
- a_norm /= (b_norm + DBL_EPSILON );
- }
- test_mat[REF_OUTPUT][0].data.db[0] = a_norm;
-}
-
-CxCore_NormTest norm_test;
-
-// TODO: repeat(?), reshape(?), lut
-
-/* End of file. */
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-//////////////////////////////////////////////////////////////////////////////////////////
-////////////////// tests for arithmetic, logic and statistical functions /////////////////
-//////////////////////////////////////////////////////////////////////////////////////////
-
-#include "cxcoretest.h"
-#include <map>
-#include <vector>
-
-using namespace cv;
-using namespace std;
-
-class CV_ArrayOpTest : public CvTest
-{
-public:
- CV_ArrayOpTest();
- ~CV_ArrayOpTest();
-protected:
- void run(int);
-};
-
-
-CV_ArrayOpTest::CV_ArrayOpTest() : CvTest( "nd-array-ops", "?" )
-{
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;
-}
-CV_ArrayOpTest::~CV_ArrayOpTest() {}
-
-static string idx2string(const int* idx, int dims)
-{
- char buf[256];
- char* ptr = buf;
- for( int k = 0; k < dims; k++ )
- {
- sprintf(ptr, "%4d ", idx[k]);
- ptr += strlen(ptr);
- }
- ptr[-1] = '\0';
- return string(buf);
-}
-
-static const int* string2idx(const string& s, int* idx, int dims)
-{
- const char* ptr = s.c_str();
- for( int k = 0; k < dims; k++ )
- {
- int n = 0;
- sscanf(ptr, "%d%n", idx + k, &n);
- ptr += n;
- }
- return idx;
-}
-
-static double getValue(SparseMat& M, const int* idx, RNG& rng)
-{
- int d = M.dims();
- size_t hv = 0, *phv = 0;
- if( (unsigned)rng % 2 )
- {
- hv = d == 2 ? M.hash(idx[0], idx[1]) :
- d == 3 ? M.hash(idx[0], idx[1], idx[2]) : M.hash(idx);
- phv = &hv;
- }
-
- const uchar* ptr = d == 2 ? M.ptr(idx[0], idx[1], false, phv) :
- d == 3 ? M.ptr(idx[0], idx[1], idx[2], false, phv) :
- M.ptr(idx, false, phv);
- return !ptr ? 0 : M.type() == CV_32F ? *(float*)ptr : M.type() == CV_64F ? *(double*)ptr : 0;
-}
-
-static double getValue(const CvSparseMat* M, const int* idx)
-{
- int type = 0;
- const uchar* ptr = cvPtrND(M, idx, &type, 0);
- return !ptr ? 0 : type == CV_32F ? *(float*)ptr : type == CV_64F ? *(double*)ptr : 0;
-}
-
-static void eraseValue(SparseMat& M, const int* idx, RNG& rng)
-{
- int d = M.dims();
- size_t hv = 0, *phv = 0;
- if( (unsigned)rng % 2 )
- {
- hv = d == 2 ? M.hash(idx[0], idx[1]) :
- d == 3 ? M.hash(idx[0], idx[1], idx[2]) : M.hash(idx);
- phv = &hv;
- }
-
- if( d == 2 )
- M.erase(idx[0], idx[1], phv);
- else if( d == 3 )
- M.erase(idx[0], idx[1], idx[2], phv);
- else
- M.erase(idx, phv);
-}
-
-static void eraseValue(CvSparseMat* M, const int* idx)
-{
- cvClearND(M, idx);
-}
-
-static void setValue(SparseMat& M, const int* idx, double value, RNG& rng)
-{
- int d = M.dims();
- size_t hv = 0, *phv = 0;
- if( (unsigned)rng % 2 )
- {
- hv = d == 2 ? M.hash(idx[0], idx[1]) :
- d == 3 ? M.hash(idx[0], idx[1], idx[2]) : M.hash(idx);
- phv = &hv;
- }
-
- uchar* ptr = d == 2 ? M.ptr(idx[0], idx[1], true, phv) :
- d == 3 ? M.ptr(idx[0], idx[1], idx[2], true, phv) :
- M.ptr(idx, true, phv);
- if( M.type() == CV_32F )
- *(float*)ptr = (float)value;
- else if( M.type() == CV_64F )
- *(double*)ptr = value;
- else
- CV_Error(CV_StsUnsupportedFormat, "");
-}
-
-void CV_ArrayOpTest::run( int /* start_from */)
-{
- int errcount = 0;
-
- // dense matrix operations
- {
- int sz3[] = {5, 10, 15};
- MatND A(3, sz3, CV_32F), B(3, sz3, CV_16SC4);
- CvMatND matA = A, matB = B;
- RNG rng;
- rng.fill(A, CV_RAND_UNI, Scalar::all(-10), Scalar::all(10));
- rng.fill(B, CV_RAND_UNI, Scalar::all(-10), Scalar::all(10));
-
- int idx0[] = {3,4,5}, idx1[] = {0, 9, 7};
- float val0 = 130;
- Scalar val1(-1000, 30, 3, 8);
- cvSetRealND(&matA, idx0, val0);
- cvSetReal3D(&matA, idx1[0], idx1[1], idx1[2], -val0);
- cvSetND(&matB, idx0, val1);
- cvSet3D(&matB, idx1[0], idx1[1], idx1[2], -val1);
- Ptr<CvMatND> matC = cvCloneMatND(&matB);
-
- if( A.at<float>(idx0[0], idx0[1], idx0[2]) != val0 ||
- A.at<float>(idx1[0], idx1[1], idx1[2]) != -val0 ||
- cvGetReal3D(&matA, idx0[0], idx0[1], idx0[2]) != val0 ||
- cvGetRealND(&matA, idx1) != -val0 ||
-
- Scalar(B.at<Vec4s>(idx0[0], idx0[1], idx0[2])) != val1 ||
- Scalar(B.at<Vec4s>(idx1[0], idx1[1], idx1[2])) != -val1 ||
- Scalar(cvGet3D(matC, idx0[0], idx0[1], idx0[2])) != val1 ||
- Scalar(cvGetND(matC, idx1)) != -val1 )
- {
- ts->printf(CvTS::LOG, "one of cvSetReal3D, cvSetRealND, cvSet3D, cvSetND "
- "or the corresponding *Get* functions is not correct\n");
- errcount++;
- }
- }
-
- RNG rng;
- const int MAX_DIM = 5, MAX_DIM_SZ = 10;
- // sparse matrix operations
- for( int si = 0; si < 10; si++ )
- {
- int depth = (unsigned)rng % 2 == 0 ? CV_32F : CV_64F;
- int dims = ((unsigned)rng % MAX_DIM) + 1;
- int i, k, size[MAX_DIM]={0}, idx[MAX_DIM]={0};
- vector<string> all_idxs;
- vector<double> all_vals;
- vector<double> all_vals2;
- string sidx, min_sidx, max_sidx;
- double min_val=0, max_val=0;
-
- int p = 1;
- for( k = 0; k < dims; k++ )
- {
- size[k] = ((unsigned)rng % MAX_DIM_SZ) + 1;
- p *= size[k];
- }
- SparseMat M( dims, size, depth );
- map<string, double> M0;
-
- int nz0 = (unsigned)rng % max(p/5,10);
- nz0 = min(max(nz0, 1), p);
- all_vals.resize(nz0);
- all_vals2.resize(nz0);
- Mat_<double> _all_vals(all_vals), _all_vals2(all_vals2);
- rng.fill(_all_vals, CV_RAND_UNI, Scalar(-1000), Scalar(1000));
- if( depth == CV_32F )
- {
- Mat _all_vals_f;
- _all_vals.convertTo(_all_vals_f, CV_32F);
- _all_vals_f.convertTo(_all_vals, CV_64F);
- }
- _all_vals.convertTo(_all_vals2, _all_vals2.type(), 2);
- if( depth == CV_32F )
- {
- Mat _all_vals2_f;
- _all_vals2.convertTo(_all_vals2_f, CV_32F);
- _all_vals2_f.convertTo(_all_vals2, CV_64F);
- }
-
- minMaxLoc(_all_vals, &min_val, &max_val);
- double _norm0 = norm(_all_vals, CV_C);
- double _norm1 = norm(_all_vals, CV_L1);
- double _norm2 = norm(_all_vals, CV_L2);
-
- for( i = 0; i < nz0; i++ )
- {
- for(;;)
- {
- for( k = 0; k < dims; k++ )
- idx[k] = (unsigned)rng % size[k];
- sidx = idx2string(idx, dims);
- if( M0.count(sidx) == 0 )
- break;
- }
- all_idxs.push_back(sidx);
- M0[sidx] = all_vals[i];
- if( all_vals[i] == min_val )
- min_sidx = sidx;
- if( all_vals[i] == max_val )
- max_sidx = sidx;
- setValue(M, idx, all_vals[i], rng);
- double v = getValue(M, idx, rng);
- if( v != all_vals[i] )
- {
- ts->printf(CvTS::LOG, "%d. immediately after SparseMat[%s]=%.20g the current value is %.20g\n",
- i, sidx.c_str(), all_vals[i], v);
- errcount++;
- break;
- }
- }
-
- Ptr<CvSparseMat> M2 = (CvSparseMat*)M;
- MatND Md;
- M.copyTo(Md);
- SparseMat M3; SparseMat(Md).convertTo(M3, Md.type(), 2);
-
- int nz1 = (int)M.nzcount(), nz2 = (int)M3.nzcount();
- double norm0 = norm(M, CV_C);
- double norm1 = norm(M, CV_L1);
- double norm2 = norm(M, CV_L2);
- double eps = depth == CV_32F ? FLT_EPSILON*100 : DBL_EPSILON*1000;
-
- if( nz1 != nz0 || nz2 != nz0)
- {
- errcount++;
- ts->printf(CvTS::LOG, "%d: The number of non-zero elements before/after converting to/from dense matrix is not correct: %d/%d (while it should be %d)\n",
- si, nz1, nz2, nz0 );
- break;
- }
-
- if( fabs(norm0 - _norm0) > fabs(_norm0)*eps ||
- fabs(norm1 - _norm1) > fabs(_norm1)*eps ||
- fabs(norm2 - _norm2) > fabs(_norm2)*eps )
- {
- errcount++;
- ts->printf(CvTS::LOG, "%d: The norms are different: %.20g/%.20g/%.20g vs %.20g/%.20g/%.20g\n",
- si, norm0, norm1, norm2, _norm0, _norm1, _norm2 );
- break;
- }
-
- int n = (unsigned)rng % max(p/5,10);
- n = min(max(n, 1), p) + nz0;
-
- for( i = 0; i < n; i++ )
- {
- double val1, val2, val3, val0;
- if(i < nz0)
- {
- sidx = all_idxs[i];
- string2idx(sidx, idx, dims);
- val0 = all_vals[i];
- }
- else
- {
- for( k = 0; k < dims; k++ )
- idx[k] = (unsigned)rng % size[k];
- sidx = idx2string(idx, dims);
- val0 = M0[sidx];
- }
- val1 = getValue(M, idx, rng);
- val2 = getValue(M2, idx);
- val3 = getValue(M3, idx, rng);
-
- if( val1 != val0 || val2 != val0 || fabs(val3 - val0*2) > fabs(val0*2)*FLT_EPSILON )
- {
- errcount++;
- ts->printf(CvTS::LOG, "SparseMat M[%s] = %g/%g/%g (while it should be %g)\n", sidx.c_str(), val1, val2, val3, val0 );
- break;
- }
- }
-
- for( i = 0; i < n; i++ )
- {
- double val1, val2;
- if(i < nz0)
- {
- sidx = all_idxs[i];
- string2idx(sidx, idx, dims);
- }
- else
- {
- for( k = 0; k < dims; k++ )
- idx[k] = (unsigned)rng % size[k];
- sidx = idx2string(idx, dims);
- }
- eraseValue(M, idx, rng);
- eraseValue(M2, idx);
- val1 = getValue(M, idx, rng);
- val2 = getValue(M2, idx);
- if( val1 != 0 || val2 != 0 )
- {
- errcount++;
- ts->printf(CvTS::LOG, "SparseMat: after deleting M[%s], it is =%g/%g (while it should be 0)\n", sidx.c_str(), val1, val2 );
- break;
- }
- }
-
- int nz = (int)M.nzcount();
- if( nz != 0 )
- {
- errcount++;
- ts->printf(CvTS::LOG, "The number of non-zero elements after removing all the elements = %d (while it should be 0)\n", nz );
- break;
- }
-
- int idx1[MAX_DIM], idx2[MAX_DIM];
- double val1 = 0, val2 = 0;
- M3 = SparseMat(Md);
- minMaxLoc(M3, &val1, &val2, idx1, idx2);
- string s1 = idx2string(idx1, dims), s2 = idx2string(idx2, dims);
- if( val1 != min_val || val2 != max_val || s1 != min_sidx || s2 != max_sidx )
- {
- errcount++;
- ts->printf(CvTS::LOG, "%d. Sparse: The value and positions of minimum/maximum elements are different from the reference values and positions:\n\t"
- "(%g, %g, %s, %s) vs (%g, %g, %s, %s)\n", si, val1, val2, s1.c_str(), s2.c_str(),
- min_val, max_val, min_sidx.c_str(), max_sidx.c_str());
- break;
- }
-
- minMaxLoc(Md, &val1, &val2, idx1, idx2);
- s1 = idx2string(idx1, dims), s2 = idx2string(idx2, dims);
- if( (min_val < 0 && (val1 != min_val || s1 != min_sidx)) ||
- (max_val > 0 && (val2 != max_val || s2 != max_sidx)) )
- {
- errcount++;
- ts->printf(CvTS::LOG, "%d. Dense: The value and positions of minimum/maximum elements are different from the reference values and positions:\n\t"
- "(%g, %g, %s, %s) vs (%g, %g, %s, %s)\n", si, val1, val2, s1.c_str(), s2.c_str(),
- min_val, max_val, min_sidx.c_str(), max_sidx.c_str());
- break;
- }
- }
-
- ts->set_failed_test_info(errcount == 0 ? CvTS::OK : CvTS::FAIL_INVALID_OUTPUT);
-}
-
-CV_ArrayOpTest cv_ArrayOp_test;
-
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-//////////////////////////////////////////////////////////////////////////////////////////
-//////////////////// tests for operations on dynamic data structures /////////////////////
-//////////////////////////////////////////////////////////////////////////////////////////
-
-#include "cxcoretest.h"
-
-/****************************************************************************************\
-* simple sequence implementation *
-\****************************************************************************************/
-
-typedef struct CvTsSimpleSeq
-{
- schar* array;
- int count;
- int max_count;
- int elem_size;
-}
-CvTsSimpleSeq;
-
-
-static CvTsSimpleSeq* cvTsCreateSimpleSeq( int max_count, int elem_size )
-{
- CvTsSimpleSeq* seq = (CvTsSimpleSeq*)cvAlloc( sizeof(*seq) + max_count * elem_size );
- seq->elem_size = elem_size;
- seq->max_count = max_count;
- seq->count = 0;
- seq->array = (schar*)(seq + 1);
- return seq;
-}
-
-
-static void cvTsReleaseSimpleSeq( CvTsSimpleSeq** seq )
-{
- cvFree( seq );
-}
-
-
-static schar* cvTsSimpleSeqElem( CvTsSimpleSeq* seq, int index )
-{
- assert( 0 <= index && index < seq->count );
- return seq->array + index * seq->elem_size;
-}
-
-
-static void cvTsClearSimpleSeq( CvTsSimpleSeq* seq )
-{
- seq->count = 0;
-}
-
-
-static void cvTsSimpleSeqShiftAndCopy( CvTsSimpleSeq* seq, int from_idx, int to_idx, void* elem=0 )
-{
- int elem_size = seq->elem_size;
-
- if( from_idx == to_idx )
- return;
- assert( (from_idx > to_idx && !elem) || (from_idx < to_idx && elem) );
-
- if( from_idx < seq->count )
- {
- memmove( seq->array + to_idx*elem_size, seq->array + from_idx*elem_size,
- (seq->count - from_idx)*elem_size );
- }
- seq->count += to_idx - from_idx;
- if( elem && to_idx > from_idx )
- memcpy( seq->array + from_idx*elem_size, elem, (to_idx - from_idx)*elem_size );
-}
-
-static void cvTsSimpleSeqInvert( CvTsSimpleSeq* seq )
-{
- int i, k, len = seq->count, elem_size = seq->elem_size;
- schar *data = seq->array, t;
-
- for( i = 0; i < len/2; i++ )
- {
- schar* a = data + i*elem_size;
- schar* b = data + (len - i - 1)*elem_size;
- for( k = 0; k < elem_size; k++ )
- CV_SWAP( a[k], b[k], t );
- }
-}
-
-/****************************************************************************************\
-* simple cvset implementation *
-\****************************************************************************************/
-
-typedef struct CvTsSimpleSet
-{
- schar* array;
- int count, max_count;
- int elem_size;
- int* free_stack;
- int free_count;
-}
-CvTsSimpleSet;
-
-
-static void cvTsClearSimpleSet( CvTsSimpleSet* set_header )
-{
- int i;
- int elem_size = set_header->elem_size;
-
- for( i = 0; i < set_header->max_count; i++ )
- {
- set_header->array[i*elem_size] = 0;
- set_header->free_stack[i] = set_header->max_count - i - 1;
- }
- set_header->free_count = set_header->max_count;
- set_header->count = 0;
-}
-
-
-static CvTsSimpleSet* cvTsCreateSimpleSet( int max_count, int elem_size )
-{
- CvTsSimpleSet* set_header = (CvTsSimpleSet*)cvAlloc( sizeof(*set_header) + max_count *
- (elem_size + 1 + sizeof(int)));
- set_header->elem_size = elem_size + 1;
- set_header->max_count = max_count;
- set_header->free_stack = (int*)(set_header + 1);
- set_header->array = (schar*)(set_header->free_stack + max_count);
-
- cvTsClearSimpleSet( set_header );
- return set_header;
-}
-
-
-static void cvTsReleaseSimpleSet( CvTsSimpleSet** set_header )
-{
- cvFree( set_header );
-}
-
-
-static schar* cvTsSimpleSetFind( CvTsSimpleSet* set_header, int index )
-{
- int idx = index * set_header->elem_size;
- assert( 0 <= index && index < set_header->max_count );
- return set_header->array[idx] ? set_header->array + idx + 1 : 0;
-}
-
-
-static int cvTsSimpleSetAdd( CvTsSimpleSet* set_header, void* elem )
-{
- int idx, idx2;
- assert( set_header->free_count > 0 );
-
- idx = set_header->free_stack[--set_header->free_count];
- idx2 = idx * set_header->elem_size;
- assert( set_header->array[idx2] == 0 );
- set_header->array[idx2] = 1;
- if( set_header->elem_size > 1 )
- memcpy( set_header->array + idx2 + 1, elem, set_header->elem_size - 1 );
- set_header->count = MAX( set_header->count, idx + 1 );
-
- return idx;
-}
-
-
-static void cvTsSimpleSetRemove( CvTsSimpleSet* set_header, int index )
-{
- assert( set_header->free_count < set_header->max_count &&
- 0 <= index && index < set_header->max_count );
- assert( set_header->array[index * set_header->elem_size] == 1 );
-
- set_header->free_stack[set_header->free_count++] = index;
- set_header->array[index * set_header->elem_size] = 0;
-}
-
-
-/****************************************************************************************\
-* simple graph implementation *
-\****************************************************************************************/
-
-typedef struct CvTsSimpleGraph
-{
- char* matrix;
- int edge_size;
- int oriented;
- CvTsSimpleSet* vtx;
-}
-CvTsSimpleGraph;
-
-
-static void cvTsClearSimpleGraph( CvTsSimpleGraph* graph )
-{
- int max_vtx_count = graph->vtx->max_count;
- cvTsClearSimpleSet( graph->vtx );
- memset( graph->matrix, 0, max_vtx_count * max_vtx_count * graph->edge_size );
-}
-
-
-static CvTsSimpleGraph* cvTsCreateSimpleGraph( int max_vtx_count, int vtx_size,
- int edge_size, int oriented )
-{
- CvTsSimpleGraph* graph;
-
- assert( max_vtx_count > 1 && vtx_size >= 0 && edge_size >= 0 );
- graph = (CvTsSimpleGraph*)cvAlloc( sizeof(*graph) +
- max_vtx_count * max_vtx_count * (edge_size + 1));
- graph->vtx = cvTsCreateSimpleSet( max_vtx_count, vtx_size );
- graph->edge_size = edge_size + 1;
- graph->matrix = (char*)(graph + 1);
- graph->oriented = oriented;
-
- cvTsClearSimpleGraph( graph );
- return graph;
-}
-
-
-static void cvTsReleaseSimpleGraph( CvTsSimpleGraph** graph )
-{
- if( *graph )
- {
- cvTsReleaseSimpleSet( &(graph[0]->vtx) );
- cvFree( graph );
- }
-}
-
-
-static int cvTsSimpleGraphAddVertex( CvTsSimpleGraph* graph, void* vertex )
-{
- return cvTsSimpleSetAdd( graph->vtx, vertex );
-}
-
-
-static void cvTsSimpleGraphRemoveVertex( CvTsSimpleGraph* graph, int index )
-{
- int i, max_vtx_count = graph->vtx->max_count;
- int edge_size = graph->edge_size;
- cvTsSimpleSetRemove( graph->vtx, index );
-
- /* remove all the corresponding edges */
- for( i = 0; i < max_vtx_count; i++ )
- {
- graph->matrix[(i*max_vtx_count + index)*edge_size] =
- graph->matrix[(index*max_vtx_count + i)*edge_size] = 0;
- }
-}
-
-
-static void cvTsSimpleGraphAddEdge( CvTsSimpleGraph* graph, int idx1, int idx2, void* edge )
-{
- int i, t, n = graph->oriented ? 1 : 2;
-
- assert( cvTsSimpleSetFind( graph->vtx, idx1 ) &&
- cvTsSimpleSetFind( graph->vtx, idx2 ));
-
- for( i = 0; i < n; i++ )
- {
- int ofs = (idx1*graph->vtx->max_count + idx2)*graph->edge_size;
- assert( graph->matrix[ofs] == 0 );
- graph->matrix[ofs] = 1;
- if( graph->edge_size > 1 )
- memcpy( graph->matrix + ofs + 1, edge, graph->edge_size - 1 );
-
- CV_SWAP( idx1, idx2, t );
- }
-}
-
-
-static void cvTsSimpleGraphRemoveEdge( CvTsSimpleGraph* graph, int idx1, int idx2 )
-{
- int i, t, n = graph->oriented ? 1 : 2;
-
- assert( cvTsSimpleSetFind( graph->vtx, idx1 ) &&
- cvTsSimpleSetFind( graph->vtx, idx2 ));
-
- for( i = 0; i < n; i++ )
- {
- int ofs = (idx1*graph->vtx->max_count + idx2)*graph->edge_size;
- assert( graph->matrix[ofs] == 1 );
- graph->matrix[ofs] = 0;
- CV_SWAP( idx1, idx2, t );
- }
-}
-
-
-static schar* cvTsSimpleGraphFindVertex( CvTsSimpleGraph* graph, int index )
-{
- return cvTsSimpleSetFind( graph->vtx, index );
-}
-
-
-static char* cvTsSimpleGraphFindEdge( CvTsSimpleGraph* graph, int idx1, int idx2 )
-{
- if( cvTsSimpleGraphFindVertex( graph, idx1 ) &&
- cvTsSimpleGraphFindVertex( graph, idx2 ))
- {
- char* edge = graph->matrix + (idx1 * graph->vtx->max_count + idx2)*graph->edge_size;
- if( edge[0] ) return edge + 1;
- }
- return 0;
-}
-
-
-static int cvTsSimpleGraphVertexDegree( CvTsSimpleGraph* graph, int index )
-{
- int i, count = 0;
- int edge_size = graph->edge_size;
- int max_vtx_count = graph->vtx->max_count;
- assert( cvTsSimpleGraphFindVertex( graph, index ) != 0 );
-
- for( i = 0; i < max_vtx_count; i++ )
- {
- count += graph->matrix[(i*max_vtx_count + index)*edge_size] +
- graph->matrix[(index*max_vtx_count + i)*edge_size];
- }
-
- if( !graph->oriented )
- {
- assert( count % 2 == 0 );
- count /= 2;
- }
- return count;
-}
-
-
-///////////////////////////////////// the tests //////////////////////////////////
-
-#define CV_TS_SEQ_CHECK_CONDITION( expr, err_msg ) \
- if( !(expr) ) \
- { \
- set_error_context( #expr, err_msg, cvFuncName ); \
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT ); \
- EXIT; \
- }
-
-class CxCore_DynStructBaseTest : public CvTest
-{
-public:
- CxCore_DynStructBaseTest( const char* test_name, const char* test_funcs );
- virtual ~CxCore_DynStructBaseTest();
- int write_default_params(CvFileStorage* fs);
- bool can_do_fast_forward();
- void clear();
-
-protected:
- int read_params( CvFileStorage* fs );
- void run_func(void);
- void set_error_context( const char* condition,
- const char* err_msg,
- const char* func_name );
- int test_seq_block_consistence( int _struct_idx, CvSeq* seq, int total );
- void update_progressbar();
-
- int struct_count, max_struct_size, iterations, generations;
- int min_log_storage_block_size, max_log_storage_block_size;
- int min_log_elem_size, max_log_elem_size;
- int gen, struct_idx, iter;
- int test_progress;
- int64 start_time;
- double cpu_freq;
- void** cxcore_struct;
- void** simple_struct;
- CvMemStorage* storage;
-};
-
-
-CxCore_DynStructBaseTest::CxCore_DynStructBaseTest( const char* test_name, const char* test_funcs ):
- CvTest( test_name, test_funcs )
-{
- struct_count = 2;
- max_struct_size = 2000;
- min_log_storage_block_size = 7;
- max_log_storage_block_size = 12;
- min_log_elem_size = 0;
- max_log_elem_size = 8;
- generations = 10;
- iterations = max_struct_size*2;
- gen = struct_idx = iter = -1;
- test_progress = -1;
-
- storage = 0;
- cxcore_struct = 0;
- simple_struct = 0;
-}
-
-
-CxCore_DynStructBaseTest::~CxCore_DynStructBaseTest()
-{
- clear();
-}
-
-
-void CxCore_DynStructBaseTest::run_func()
-{
-}
-
-bool CxCore_DynStructBaseTest::can_do_fast_forward()
-{
- return false;
-}
-
-
-void CxCore_DynStructBaseTest::clear()
-{
- CvTest::clear();
- cvReleaseMemStorage( &storage );
- cvFree( &cxcore_struct );
- cvFree( &simple_struct );
-}
-
-
-int CxCore_DynStructBaseTest::write_default_params( CvFileStorage* fs )
-{
- write_param( fs, "struct_count", struct_count );
- write_param( fs, "max_struct_size", max_struct_size );
- write_param( fs, "generations", generations );
- write_param( fs, "iterations", iterations );
- write_param( fs, "min_log_storage_block_size", min_log_storage_block_size );
- write_param( fs, "max_log_storage_block_size", max_log_storage_block_size );
- write_param( fs, "min_log_elem_size", min_log_elem_size );
- write_param( fs, "max_log_elem_size", max_log_elem_size );
- return 0;
-}
-
-
-int CxCore_DynStructBaseTest::read_params( CvFileStorage* fs )
-{
- int code = CvTest::read_params( fs );
- double sqrt_scale = sqrt(ts->get_test_case_count_scale());
- if( code < 0 )
- return code;
-
- struct_count = cvReadInt( find_param( fs, "struct_count" ), struct_count );
- max_struct_size = cvReadInt( find_param( fs, "max_struct_size" ), max_struct_size );
- generations = cvReadInt( find_param( fs, "generations" ), generations );
- iterations = cvReadInt( find_param( fs, "iterations" ), iterations );
- generations = cvRound(generations*sqrt_scale);
- iterations = cvRound(iterations*sqrt_scale);
-
- min_log_storage_block_size = cvReadInt( find_param( fs, "min_log_storage_block_size" ),
- min_log_storage_block_size );
- max_log_storage_block_size = cvReadInt( find_param( fs, "max_log_storage_block_size" ),
- max_log_storage_block_size );
- min_log_elem_size = cvReadInt( find_param( fs, "min_log_elem_size" ), min_log_elem_size );
- max_log_elem_size = cvReadInt( find_param( fs, "max_log_elem_size" ), max_log_elem_size );
-
- struct_count = cvTsClipInt( struct_count, 1, 100 );
- max_struct_size = cvTsClipInt( max_struct_size, 1, 1<<20 );
- generations = cvTsClipInt( generations, 1, 100 );
- iterations = cvTsClipInt( iterations, 100, 1<<20 );
-
- min_log_storage_block_size = cvTsClipInt( min_log_storage_block_size, 7, 20 );
- max_log_storage_block_size = cvTsClipInt( max_log_storage_block_size,
- min_log_storage_block_size, 20 );
-
- min_log_elem_size = cvTsClipInt( min_log_elem_size, 0, 8 );
- max_log_elem_size = cvTsClipInt( max_log_elem_size, min_log_elem_size, 10 );
-
- return 0;
-}
-
-
-void CxCore_DynStructBaseTest::update_progressbar()
-{
- int64 t;
-
- if( test_progress < 0 )
- {
- test_progress = 0;
- cpu_freq = cv::getTickFrequency();
- start_time = cv::getTickCount();
- }
-
- t = cv::getTickCount();
- test_progress = update_progress( test_progress, 0, 0, (double)(t - start_time)/cpu_freq );
-}
-
-
-void CxCore_DynStructBaseTest::set_error_context( const char* condition,
- const char* err_msg,
- const char* func_name )
-{
- ts->printf( CvTS::LOG, "%s: %s\n(\"%s\" failed).\n"
- "generation = %d, struct_idx = %d, iter = %d\n",
- func_name, err_msg, condition, gen, struct_idx, iter );
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
-}
-
-
-int CxCore_DynStructBaseTest::test_seq_block_consistence( int _struct_idx, CvSeq* seq, int total )
-{
- int sum = 0, code = -1;
- CV_FUNCNAME( "CxCore_DynStructBaseTest::test_seq_block_consistence" );
-
- struct_idx = _struct_idx;
-
- __BEGIN__;
-
- CV_TS_SEQ_CHECK_CONDITION( seq != 0, "Null sequence pointer" );
-
- if( seq->first )
- {
- CvSeqBlock* block = seq->first;
- CvSeqBlock* prev_block = block->prev;
-
- int delta_idx = seq->first->start_index;
-
- for( ;; )
- {
- CV_TS_SEQ_CHECK_CONDITION( sum == block->start_index - delta_idx &&
- block->count > 0 && block->prev == prev_block &&
- prev_block->next == block,
- "sequence blocks are inconsistent" );
- sum += block->count;
- prev_block = block;
- block = block->next;
- if( block == seq->first ) break;
- }
-
- CV_TS_SEQ_CHECK_CONDITION( block->prev->count * seq->elem_size +
- block->prev->data <= seq->block_max,
- "block->data or block_max pointer are incorrect" );
- }
-
- CV_TS_SEQ_CHECK_CONDITION( seq->total == sum && sum == total,
- "total number of elements is incorrect" );
-
- code = 0;
-
- __END__;
-
- return code;
-}
-
-
-CxCore_DynStructBaseTest ds_test( "ds", "" );
-
-/////////////////////////////////// sequence tests ////////////////////////////////////
-
-class CxCore_SeqBaseTest : public CxCore_DynStructBaseTest
-{
-public:
- CxCore_SeqBaseTest( const char* test_name, const char* test_funcs );
- void clear();
- void run( int );
-
-protected:
- int test_multi_create();
- int test_get_seq_elem( int _struct_idx, int iters );
- int test_get_seq_reading( int _struct_idx, int iters );
- int test_seq_ops( int iters );
-};
-
-
-CxCore_SeqBaseTest::CxCore_SeqBaseTest( const char* test_name, const char* test_funcs ) :
- CxCore_DynStructBaseTest( test_name, test_funcs )
-{
-}
-
-
-void CxCore_SeqBaseTest::clear()
-{
- int i;
- if( simple_struct )
- {
- for( i = 0; i < struct_count; i++ )
- cvTsReleaseSimpleSeq( (CvTsSimpleSeq**)&simple_struct[i] );
- }
- CxCore_DynStructBaseTest::clear();
-}
-
-
-int CxCore_SeqBaseTest::test_multi_create()
-{
- CvSeqWriter* writer = (CvSeqWriter*)cvStackAlloc( struct_count*sizeof(writer[0]) );
- int* pos = (int*)cvStackAlloc( struct_count*sizeof(pos[0]) );
- int* index = (int*)cvStackAlloc( struct_count*sizeof(index[0]) );
- int i, cur_count, elem_size;
- int code = -1;
- CvRNG* rng = ts->get_rng();
-
- CV_FUNCNAME( "CxCore_SeqBaseTest::test_multi_create" );
-
- __BEGIN__;
-
- for( i = 0; i < struct_count; i++ )
- {
- double t;
- CvMat m;
- CvTsSimpleSeq* sseq;
-
- pos[i] = -1;
- index[i] = i;
-
- t = cvTsRandReal(rng)*(max_log_elem_size - min_log_elem_size) + min_log_elem_size;
- elem_size = cvRound( exp(t * CV_LOG2) );
- elem_size = MIN( elem_size, (int)(storage->block_size - sizeof(void*) -
- sizeof(CvSeqBlock) - sizeof(CvMemBlock)) );
-
- cvTsReleaseSimpleSeq( (CvTsSimpleSeq**)&simple_struct[i] );
- simple_struct[i] = sseq = cvTsCreateSimpleSeq( max_struct_size, elem_size );
- cxcore_struct[i] = 0;
- sseq->count = cvTsRandInt( rng ) % max_struct_size;
- m = cvMat( 1, MAX(sseq->count,1)*elem_size, CV_8UC1, sseq->array );
- cvRandArr( rng, &m, CV_RAND_UNI, cvScalarAll(0), cvScalarAll(256) );
- }
-
- for( cur_count = struct_count; cur_count > 0; cur_count-- )
- {
- for(;;)
- {
- int k = cvTsRandInt( rng ) % cur_count;
- struct_idx = index[k];
- CvTsSimpleSeq* sseq = (CvTsSimpleSeq*)simple_struct[struct_idx];
-
- if( pos[struct_idx] < 0 )
- {
- int hdr_size = (cvTsRandInt(rng) % 10)*4 + sizeof(CvSeq);
- hdr_size = MIN( hdr_size, (int)(storage->block_size - sizeof(CvMemBlock)) );
- elem_size = sseq->elem_size;
-
- if( cvTsRandInt(rng) % 2 )
- {
- CV_CALL( cvStartWriteSeq( 0, hdr_size, elem_size, storage, writer + struct_idx ));
- }
- else
- {
- CvSeq* s;
- CV_CALL( s = cvCreateSeq( 0, hdr_size, elem_size, storage ));
- CV_CALL( cvStartAppendToSeq( s, writer + struct_idx ));
- }
-
- CV_CALL( cvSetSeqBlockSize( writer[struct_idx].seq, cvTsRandInt( rng ) % 10000 ));
- pos[struct_idx] = 0;
- }
-
- update_progressbar();
- if( pos[struct_idx] == sseq->count )
- {
- CV_CALL( cxcore_struct[struct_idx] = cvEndWriteSeq( writer + struct_idx ));
- /* del index */
- for( ; k < cur_count-1; k++ )
- index[k] = index[k+1];
- break;
- }
-
- {
- schar* el = cvTsSimpleSeqElem( sseq, pos[struct_idx] );
- CV_WRITE_SEQ_ELEM_VAR( el, writer[struct_idx] );
- }
- pos[struct_idx]++;
- }
- }
-
- code = 0;
-
- __END__;
-
- return code;
-}
-
-
-int CxCore_SeqBaseTest::test_get_seq_elem( int _struct_idx, int iters )
-{
- int i, code = -1;
- CvRNG* rng = ts->get_rng();
-
- CV_FUNCNAME( "CxCore_SeqBaseTest::test_get_seq_elem" );
-
- __BEGIN__;
-
- CvSeq* seq = (CvSeq*)cxcore_struct[_struct_idx];
- CvTsSimpleSeq* sseq = (CvTsSimpleSeq*)simple_struct[_struct_idx];
- struct_idx = _struct_idx;
-
- assert( seq->total == sseq->count );
-
- if( sseq->count == 0 )
- return 0;
-
- for( i = 0; i < iters; i++ )
- {
- int idx = cvTsRandInt(rng) % (sseq->count*3) - sseq->count*3/2;
- int idx0 = (unsigned)idx < (unsigned)(sseq->count) ? idx : idx < 0 ?
- idx + sseq->count : idx - sseq->count;
- int bad_range = (unsigned)idx0 >= (unsigned)(sseq->count);
- schar* elem;
- CV_CALL( elem = cvGetSeqElem( seq, idx ));
-
- if( bad_range )
- {
- CV_TS_SEQ_CHECK_CONDITION( elem == 0,
- "cvGetSeqElem doesn't "
- "handle \"out of range\" properly" );
- }
- else
- {
- CV_TS_SEQ_CHECK_CONDITION( elem != 0 &&
- !memcmp( elem, cvTsSimpleSeqElem(sseq, idx0), sseq->elem_size ),
- "cvGetSeqElem returns wrong element" );
-
- CV_CALL( idx = cvSeqElemIdx(seq, elem ));
- CV_TS_SEQ_CHECK_CONDITION( idx >= 0 && idx == idx0,
- "cvSeqElemIdx is incorrect" );
- }
- }
-
- code = 0;
-
- __END__;
-
- return code;
-}
-
-
-int CxCore_SeqBaseTest::test_get_seq_reading( int _struct_idx, int iters )
-{
- const int max_val = 3*5 + 2;
- int code = -1, pos;
- CvSeq* seq = (CvSeq*)cxcore_struct[_struct_idx];
- CvTsSimpleSeq* sseq = (CvTsSimpleSeq*)simple_struct[_struct_idx];
- int total = seq->total;
- CvRNG* rng = ts->get_rng();
- CvSeqReader reader;
- schar* elem;
-
- CV_FUNCNAME( "CxCore_SeqBaseTest::test_get_seq_reading" );
-
- __BEGIN__;
-
- assert( total == sseq->count );
- this->struct_idx = _struct_idx;
- elem = (schar*)alloca( sseq->elem_size );
-
- pos = cvTsRandInt(rng) % 2;
- CV_CALL( cvStartReadSeq( seq, &reader, pos ));
-
- if( total == 0 )
- {
- CV_TS_SEQ_CHECK_CONDITION( reader.ptr == 0, "Empty sequence reader pointer is not NULL" );
- code = 0;
- EXIT;
- }
-
- pos = pos ? seq->total - 1 : 0;
-
- CV_TS_SEQ_CHECK_CONDITION( pos == cvGetSeqReaderPos(&reader),
- "initial reader position is wrong" );
-
- for( iter = 0; iter < iters; iter++ )
- {
- int op = cvTsRandInt(rng) % max_val;
-
- if( op >= max_val - 2 )
- {
- int new_pos, new_pos0;
- int bad_range;
- int is_relative = op == max_val - 1;
-
- new_pos = cvTsRandInt(rng) % (total*2) - total;
- new_pos0 = new_pos + (is_relative ? pos : 0 );
-
- if( new_pos0 < 0 ) new_pos0 += total;
- if( new_pos0 >= total ) new_pos0 -= total;
-
- bad_range = (unsigned)new_pos0 >= (unsigned)total;
- CV_CALL( cvSetSeqReaderPos( &reader, new_pos, is_relative ));
-
- if( !bad_range )
- {
- CV_TS_SEQ_CHECK_CONDITION( new_pos0 == cvGetSeqReaderPos( &reader ),
- "cvset reader position doesn't work" );
- pos = new_pos0;
- }
- else
- {
- CV_TS_SEQ_CHECK_CONDITION( pos == cvGetSeqReaderPos( &reader ),
- "reader doesn't stay at the current position after wrong positioning" );
- }
- }
- else
- {
- int direction = (op % 3) - 1;
- memcpy( elem, reader.ptr, sseq->elem_size );
-
- if( direction > 0 )
- {
- CV_NEXT_SEQ_ELEM( sseq->elem_size, reader );
- }
- else if( direction < 0 )
- {
- CV_PREV_SEQ_ELEM( sseq->elem_size, reader );
- }
-
- CV_TS_SEQ_CHECK_CONDITION( memcmp(elem, cvTsSimpleSeqElem(sseq, pos),
- sseq->elem_size) == 0, "reading is incorrect" );
- pos += direction;
- if( pos < 0 ) pos += total;
- if( pos >= total ) pos -= total;
-
- CV_TS_SEQ_CHECK_CONDITION( pos == cvGetSeqReaderPos( &reader ),
- "reader doesn't move correctly after reading" );
- }
- }
-
- code = 0;
-
- __END__;
-
- return code;
-}
-
-
-int CxCore_SeqBaseTest::test_seq_ops( int iters )
-{
- const int max_op = 14;
- int i, code = -1;
- int max_elem_size = 0;
- schar *elem = 0, *elem2 = 0;
- CvMat* elem_mat = 0;
- CvRNG* rng = ts->get_rng();
-
- CV_FUNCNAME( "CxCore_SeqBaseTest::test_seq_ops" );
-
- __BEGIN__;
-
- for( i = 0; i < struct_count; i++ )
- max_elem_size = MAX( max_elem_size, ((CvSeq*)cxcore_struct[i])->elem_size );
-
- CV_CALL( elem_mat = cvCreateMat( 1, max_struct_size*max_elem_size, CV_8UC1 ));
- elem = (schar*)elem_mat->data.ptr;
-
- for( iter = 0; iter < iters; iter++ )
- {
- struct_idx = cvTsRandInt(rng) % struct_count;
- int op = cvTsRandInt(rng) % max_op;
- CvSeq* seq = (CvSeq*)cxcore_struct[struct_idx];
- CvTsSimpleSeq* sseq = (CvTsSimpleSeq*)simple_struct[struct_idx];
- int elem_size = sseq->elem_size;
- int whence = 0, pos = 0, count = 0;
-
- switch( op )
- {
- case 0:
- case 1:
- case 2: // push/pushfront/insert
- if( sseq->count == sseq->max_count )
- break;
-
- elem_mat->cols = elem_size;
- cvRandArr( rng, elem_mat, CV_RAND_UNI, cvScalarAll(0), cvScalarAll(255) );
-
- whence = op - 1;
- if( whence < 0 )
- {
- pos = 0;
- CV_CALL(cvSeqPushFront( seq, elem ));
- }
- else if( whence > 0 )
- {
- pos = sseq->count;
- CV_CALL(cvSeqPush( seq, elem ));
- }
- else
- {
- pos = cvTsRandInt(rng) % (sseq->count + 1);
- CV_CALL(cvSeqInsert( seq, pos, elem ));
- }
-
- cvTsSimpleSeqShiftAndCopy( sseq, pos, pos + 1, elem );
- elem2 = cvGetSeqElem( seq, pos );
- CV_TS_SEQ_CHECK_CONDITION( elem2 != 0, "The inserted element could not be retrieved" );
- CV_TS_SEQ_CHECK_CONDITION( seq->total == sseq->count &&
- memcmp(elem2, cvTsSimpleSeqElem(sseq,pos), elem_size) == 0,
- "The inserted sequence element is wrong" );
- break;
-
- case 3:
- case 4:
- case 5: // pop/popfront/remove
- if( sseq->count == 0 )
- break;
-
- whence = op - 4;
- if( whence < 0 )
- {
- pos = 0;
- CV_CALL( cvSeqPopFront( seq, elem ));
- }
- else if( whence > 0 )
- {
- pos = sseq->count-1;
- CV_CALL( cvSeqPop( seq, elem ));
- }
- else
- {
- pos = cvTsRandInt(rng) % sseq->count;
- CV_CALL( cvSeqRemove( seq, pos ));
- }
-
- if( whence != 0 )
- CV_TS_SEQ_CHECK_CONDITION( seq->total == sseq->count - 1 &&
- memcmp( elem, cvTsSimpleSeqElem(sseq,pos), elem_size) == 0,
- "The popped sequence element isn't correct" );
-
- cvTsSimpleSeqShiftAndCopy( sseq, pos + 1, pos );
-
- if( sseq->count > 0 )
- {
- CV_CALL( elem2 = cvGetSeqElem( seq, pos < sseq->count ? pos : -1 ));
- CV_TS_SEQ_CHECK_CONDITION( elem2 != 0, "GetSeqElem fails after removing the element" );
-
- CV_TS_SEQ_CHECK_CONDITION( memcmp( elem2,
- cvTsSimpleSeqElem(sseq, pos - (pos == sseq->count)), elem_size) == 0,
- "The first shifted element is not correct after removing another element" );
- }
- else
- {
- CV_TS_SEQ_CHECK_CONDITION( seq->first == 0,
- "The sequence doesn't become empty after the final remove" );
- }
- break;
-
- case 6:
- case 7:
- case 8: // push [front] multi/insert slice
- if( sseq->count == sseq->max_count )
- break;
-
- count = cvTsRandInt( rng ) % (sseq->max_count - sseq->count + 1);
- elem_mat->cols = MAX(count,1) * elem_size;
- cvRandArr( rng, elem_mat, CV_RAND_UNI, cvScalarAll(0), cvScalarAll(255) );
-
- whence = op - 7;
- pos = whence < 0 ? 0 : whence > 0 ? sseq->count : cvTsRandInt(rng) % (sseq->count+1);
- if( whence != 0 )
- {
- CV_CALL( cvSeqPushMulti( seq, elem, count, whence < 0 ));
- }
- else
- {
- CvSeq header;
- CvSeqBlock block;
- CV_CALL( cvMakeSeqHeaderForArray( CV_SEQ_KIND_GENERIC, sizeof(CvSeq),
- sseq->elem_size,
- elem_mat->data.ptr, count,
- &header, &block ));
-
- CV_CALL( cvSeqInsertSlice( seq, pos, &header ));
- }
- cvTsSimpleSeqShiftAndCopy( sseq, pos, pos + count, elem );
-
- if( sseq->count > 0 )
- {
- // choose the random element among the added
- pos = count > 0 ? cvTsRandInt(rng) % count + pos : MAX(pos-1,0);
- CV_CALL( elem2 = cvGetSeqElem( seq, pos ));
- CV_TS_SEQ_CHECK_CONDITION( elem2 != 0, "multi push operation doesn't add elements" );
- CV_TS_SEQ_CHECK_CONDITION( seq->total == sseq->count &&
- memcmp( elem2, cvTsSimpleSeqElem(sseq,pos), elem_size) == 0,
- "One of the added elements is wrong" );
- }
- else
- {
- CV_TS_SEQ_CHECK_CONDITION( seq->total == 0 && seq->first == 0,
- "Adding no elements to empty sequence fails" );
- }
- break;
-
- case 9:
- case 10:
- case 11: // pop [front] multi
- if( sseq->count == 0 )
- break;
-
- count = cvTsRandInt(rng) % (sseq->count+1);
- whence = op - 10;
- pos = whence < 0 ? 0 : whence > 0 ? sseq->count - count :
- cvTsRandInt(rng) % (sseq->count - count + 1);
-
- if( whence != 0 )
- {
- CV_CALL( cvSeqPopMulti( seq, elem, count, whence < 0 ));
-
- if( count > 0 )
- {
- CV_TS_SEQ_CHECK_CONDITION( memcmp(elem,
- cvTsSimpleSeqElem(sseq,pos), elem_size) == 0,
- "The first (in the sequence order) removed element is wrong after popmulti" );
- }
- }
- else
- {
- CV_CALL( cvSeqRemoveSlice( seq, cvSlice(pos, pos + count) ));
- }
-
- CV_TS_SEQ_CHECK_CONDITION( seq->total == sseq->count - count,
- "The popmulti left a wrong number of elements in the sequence" );
-
- cvTsSimpleSeqShiftAndCopy( sseq, pos + count, pos, 0 );
- if( sseq->count > 0 )
- {
- pos = whence < 0 ? 0 : MIN( pos, sseq->count - 1 );
- elem2 = cvGetSeqElem( seq, pos );
- CV_TS_SEQ_CHECK_CONDITION( elem2 &&
- memcmp( elem2, cvTsSimpleSeqElem(sseq,pos), elem_size) == 0,
- "The last sequence element is wrong after POP" );
- }
- else
- {
- CV_TS_SEQ_CHECK_CONDITION( seq->total == 0 && seq->first == 0,
- "The sequence doesn't become empty after final POP" );
- }
- break;
- case 12: // seqslice
- {
- CvMemStoragePos storage_pos;
- cvSaveMemStoragePos( storage, &storage_pos );
-
- int copy_data = cvTsRandInt(rng) % 2;
- count = cvTsRandInt(rng) % (seq->total + 1);
- pos = cvTsRandInt(rng) % (seq->total - count + 1);
- CvSeq* seq_slice = cvSeqSlice( seq, cvSlice(pos, pos + count), storage, copy_data );
-
- CV_TS_SEQ_CHECK_CONDITION( seq_slice && seq_slice->total == count,
- "cvSeqSlice returned incorrect slice" );
-
- if( count > 0 )
- {
- int test_idx = cvTsRandInt(rng) % count;
- elem2 = cvGetSeqElem( seq_slice, test_idx );
- schar* elem3 = cvGetSeqElem( seq, pos + test_idx );
- CV_TS_SEQ_CHECK_CONDITION( elem2 &&
- memcmp( elem2, cvTsSimpleSeqElem(sseq,pos + test_idx), elem_size) == 0,
- "The extracted slice elements are not correct" );
- CV_TS_SEQ_CHECK_CONDITION( (elem2 == elem3) ^ copy_data,
- "copy_data flag is handled incorrectly" );
- }
-
- cvRestoreMemStoragePos( storage, &storage_pos );
- }
- break;
- case 13: // clear
- cvTsClearSimpleSeq( sseq );
- cvClearSeq( seq );
- CV_TS_SEQ_CHECK_CONDITION( seq->total == 0 && seq->first == 0,
- "The sequence doesn't become empty after clear" );
- break;
- default:
- assert(0);
- EXIT;
- }
-
- if( test_seq_block_consistence(struct_idx, seq, sseq->count) < 0 )
- EXIT;
-
- if( test_get_seq_elem(struct_idx, 7) < 0 )
- EXIT;
-
- update_progressbar();
- }
-
- code = 0;
-
- __END__;
-
- if( elem_mat )
- elem_mat->cols = 1; // just to skip a consistency check
- cvReleaseMat( &elem_mat );
-
- return code;
-}
-
-
-void CxCore_SeqBaseTest::run( int )
-{
- CvRNG* rng = ts->get_rng();
- int i;
- double t;
-
- //CV_FUNCNAME( "CxCore_SeqBaseTest::run" );
-
- __BEGIN__;
-
- clear();
- test_progress = -1;
-
- simple_struct = (void**)cvAlloc( struct_count * sizeof(simple_struct[0]) );
- memset( simple_struct, 0, struct_count * sizeof(simple_struct[0]) );
- cxcore_struct = (void**)cvAlloc( struct_count * sizeof(cxcore_struct[0]) );
- memset( cxcore_struct, 0, struct_count * sizeof(cxcore_struct[0]) );
-
- for( gen = 0; gen < generations; gen++ )
- {
- struct_idx = iter = -1;
-
- if( !storage )
- {
- t = cvTsRandReal(rng)*(max_log_storage_block_size - min_log_storage_block_size)
- + min_log_storage_block_size;
- storage = cvCreateMemStorage( cvRound( exp(t * CV_LOG2) ) );
- }
-
- iter = struct_idx = -1;
- test_multi_create();
-
- for( i = 0; i < struct_count; i++ )
- {
- if( test_seq_block_consistence(i, (CvSeq*)cxcore_struct[i],
- ((CvTsSimpleSeq*)simple_struct[i])->count) < 0 )
- EXIT;
-
- if( test_get_seq_elem( i, MAX(iterations/3,7) ) < 0 )
- EXIT;
-
- if( test_get_seq_reading( i, MAX(iterations/3,7) ) < 0 )
- EXIT;
- update_progressbar();
- }
-
- if( test_seq_ops( iterations ) < 0 )
- EXIT;
-
- if( cvTsRandInt(rng) % 2 )
- cvReleaseMemStorage( &storage );
- else
- cvClearMemStorage( storage );
- }
-
- __END__;
-}
-
-CxCore_SeqBaseTest seqbase_test( "ds-seq-base", "cvCreateSeq, cvClearSeq, cvSeqSlice, "
- "cvStartAppendToSeq, cvStartWriteSeq, cvEndWriteSeq, CV_WRITE_SEQ_ELEM_VAR, "
- "cvGetSeqElem, cvSeqElemIdx, cvStartReadSeq, CV_NEXT_SEQ_ELEM, CV_PREV_SEQ_ELEM, "
- "cvSetSeqReaderPos, cvGetSeqReaderPos, cvSeqPush, cvSeqPushFront, cvSeqPop, "
- "cvSeqPopFront, cvSeqPushMulti, cvSeqPopMulti, cvSeqInsert, cvSeqRemove, "
- "cvSeqInsertSlice, cvSeqRemoveSlice, cvMakeSeqHeaderForArray" );
-
-////////////////////////////// more sequence tests //////////////////////////////////////
-
-class CxCore_SeqSortInvTest : public CxCore_SeqBaseTest
-{
-public:
- CxCore_SeqSortInvTest( const char* test_name, const char* test_funcs );
- void run( int );
-
-protected:
-};
-
-
-CxCore_SeqSortInvTest::CxCore_SeqSortInvTest( const char* test_name, const char* test_funcs ) :
- CxCore_SeqBaseTest( test_name, test_funcs )
-{
-}
-
-
-static int icvCmpSeqElems( const void* a, const void* b, void* userdata )
-{
- return memcmp( a, b, ((CvSeq*)userdata)->elem_size );
-}
-
-static int icvCmpSeqElems2_elem_size = 0;
-static int icvCmpSeqElems2( const void* a, const void* b )
-{
- return memcmp( a, b, icvCmpSeqElems2_elem_size );
-}
-
-
-void CxCore_SeqSortInvTest::run( int )
-{
- CvRNG* rng = ts->get_rng();
- int i, k;
- double t;
- schar *elem0, *elem, *elem2;
- CvMat* buffer = 0;
-
- CV_FUNCNAME( "CxCore_SeqSortInvTest::run" );
-
- __BEGIN__;
-
- clear();
- test_progress = -1;
-
- simple_struct = (void**)cvAlloc( struct_count * sizeof(simple_struct[0]) );
- memset( simple_struct, 0, struct_count * sizeof(simple_struct[0]) );
- cxcore_struct = (void**)cvAlloc( struct_count * sizeof(cxcore_struct[0]) );
- memset( cxcore_struct, 0, struct_count * sizeof(cxcore_struct[0]) );
-
- for( gen = 0; gen < generations; gen++ )
- {
- struct_idx = iter = -1;
-
- if( !storage )
- {
- t = cvTsRandReal(rng)*(max_log_storage_block_size - min_log_storage_block_size)
- + min_log_storage_block_size;
- storage = cvCreateMemStorage( cvRound( exp(t * CV_LOG2) ) );
- }
-
- for( iter = 0; iter < iterations/10; iter++ )
- {
- int max_size = 0;
- test_multi_create();
-
- for( i = 0; i < struct_count; i++ )
- {
- CvTsSimpleSeq* sseq = (CvTsSimpleSeq*)simple_struct[i];
- max_size = MAX( max_size, sseq->count*sseq->elem_size );
- }
-
- if( !buffer || buffer->cols < max_size )
- {
- cvReleaseMat( &buffer );
- CV_CALL( buffer = cvCreateMat( 1, max_size, CV_8UC1 ));
- }
-
- for( i = 0; i < struct_count; i++ )
- {
- CvSeq* seq = (CvSeq*)cxcore_struct[i];
- CvTsSimpleSeq* sseq = (CvTsSimpleSeq*)simple_struct[i];
- CvSlice slice = CV_WHOLE_SEQ;
-
- //printf("%d. %d. %d-th size = %d\n", gen, iter, i, sseq->count );
-
- CV_CALL( cvSeqInvert( seq ));
- cvTsSimpleSeqInvert( sseq );
-
- if( test_seq_block_consistence( i, seq, sseq->count ) < 0 )
- EXIT;
-
- if( sseq->count > 0 && cvTsRandInt(rng) % 2 == 0 )
- {
- slice.end_index = cvTsRandInt(rng) % sseq->count + 1;
- slice.start_index = cvTsRandInt(rng) % (sseq->count - slice.end_index + 1);
- slice.end_index += slice.start_index;
- }
-
- CV_CALL( cvCvtSeqToArray( seq, buffer->data.ptr, slice ));
-
- slice.end_index = MIN( slice.end_index, sseq->count );
- CV_TS_SEQ_CHECK_CONDITION( sseq->count == 0 || memcmp( buffer->data.ptr,
- sseq->array + slice.start_index*sseq->elem_size,
- (slice.end_index - slice.start_index)*sseq->elem_size ) == 0,
- "cvSeqInvert returned wrong result" );
-
- for( k = 0; k < (sseq->count > 0 ? 10 : 0); k++ )
- {
- int idx0 = cvTsRandInt(rng) % sseq->count, idx = 0;
- CV_CALL( elem0 = cvTsSimpleSeqElem( sseq, idx0 ));
- CV_CALL( elem = cvGetSeqElem( seq, idx0 ));
- elem2 = cvSeqSearch( seq, elem0, k % 2 ? icvCmpSeqElems : 0, 0, &idx, seq );
-
- CV_TS_SEQ_CHECK_CONDITION( elem != 0 &&
- memcmp( elem0, elem, seq->elem_size ) == 0,
- "cvSeqInvert gives incorrect result" );
- CV_TS_SEQ_CHECK_CONDITION( elem2 != 0 &&
- memcmp( elem0, elem2, seq->elem_size ) == 0 &&
- elem2 == cvGetSeqElem( seq, idx ),
- "cvSeqSearch failed (linear search)" );
- }
-
- CV_CALL( cvSeqSort( seq, icvCmpSeqElems, seq ));
-
- if( test_seq_block_consistence( i, seq, sseq->count ) < 0 )
- EXIT;
-
- if( sseq->count > 0 )
- {
- // !!! This is not thread-safe !!!
- icvCmpSeqElems2_elem_size = sseq->elem_size;
- qsort( sseq->array, sseq->count, sseq->elem_size, icvCmpSeqElems2 );
-
- if( cvTsRandInt(rng) % 2 == 0 )
- {
- slice.end_index = cvTsRandInt(rng) % sseq->count + 1;
- slice.start_index = cvTsRandInt(rng) % (sseq->count - slice.end_index + 1);
- slice.end_index += slice.start_index;
- }
- }
-
- CV_CALL( cvCvtSeqToArray( seq, buffer->data.ptr, slice ));
- CV_TS_SEQ_CHECK_CONDITION( sseq->count == 0 || memcmp( buffer->data.ptr,
- sseq->array + slice.start_index*sseq->elem_size,
- (slice.end_index - slice.start_index)*sseq->elem_size ) == 0,
- "cvSeqSort returned wrong result" );
-
- for( k = 0; k < (sseq->count > 0 ? 10 : 0); k++ )
- {
- int idx0 = cvTsRandInt(rng) % sseq->count, idx = 0;
- CV_CALL( elem0 = cvTsSimpleSeqElem( sseq, idx0 ));
- CV_CALL( elem = cvGetSeqElem( seq, idx0 ));
- elem2 = cvSeqSearch( seq, elem0, icvCmpSeqElems, 1, &idx, seq );
-
- CV_TS_SEQ_CHECK_CONDITION( elem != 0 &&
- memcmp( elem0, elem, seq->elem_size ) == 0,
- "cvSeqSort gives incorrect result" );
- CV_TS_SEQ_CHECK_CONDITION( elem2 != 0 &&
- memcmp( elem0, elem2, seq->elem_size ) == 0 &&
- elem2 == cvGetSeqElem( seq, idx ),
- "cvSeqSearch failed (binary search)" );
- }
- }
-
- cvClearMemStorage( storage );
- }
-
- cvReleaseMemStorage( &storage );
- }
-
- __END__;
-
- cvReleaseMat( &buffer );
-}
-
-
-CxCore_SeqSortInvTest seqsortinv_test( "ds-seq-sortinv",
- "cvCreateSeq, cvStartAppendToSeq, cvStartWriteSeq, "
- "cvEndWriteSeq, CV_WRITE_SEQ_ELEM_VAR, "
- "cvSeqSort, cvSeqSearch, cvSeqInvert, "
- "cvCvtSeqToArray, cvGetSeqElem" );
-
-/////////////////////////////////////// set tests ///////////////////////////////////////
-
-class CxCore_SetTest : public CxCore_DynStructBaseTest
-{
-public:
- CxCore_SetTest();
- void clear();
- void run( int );
-
-protected:
- //int test_seq_block_consistence( int struct_idx );
- int test_set_ops( int iters );
-};
-
-
-CxCore_SetTest::CxCore_SetTest():
- CxCore_DynStructBaseTest( "ds-set", "cvCreateSet, cvClearSet, "
- "cvSetAdd, cvSetRemove, cvSetNew, cvSetRemoveByPtr, cvGetSetElem" )
-{
-}
-
-
-void CxCore_SetTest::clear()
-{
- int i;
- if( simple_struct )
- for( i = 0; i < struct_count; i++ )
- cvTsReleaseSimpleSet( (CvTsSimpleSet**)&simple_struct[i] );
- CxCore_DynStructBaseTest::clear();
-}
-
-
-int CxCore_SetTest::test_set_ops( int iters )
-{
- const int max_op = 4;
- int i, code = -1;
- int max_elem_size = 0;
- int idx, idx0;
- CvSetElem *elem = 0, *elem2 = 0, *elem3 = 0;
- schar* elem_data = 0;
- CvMat* elem_mat = 0;
- CvRNG* rng = ts->get_rng();
- //int max_active_count = 0, mean_active_count = 0;
-
- CV_FUNCNAME( "CxCore_SetTest::test_set_ops" );
-
- __BEGIN__;
-
- for( i = 0; i < struct_count; i++ )
- max_elem_size = MAX( max_elem_size, ((CvSeq*)cxcore_struct[i])->elem_size );
-
- CV_CALL( elem_mat = cvCreateMat( 1, max_elem_size, CV_8UC1 ));
-
- for( iter = 0; iter < iters; iter++ )
- {
- struct_idx = cvTsRandInt(rng) % struct_count;
-
- CvSet* cvset = (CvSet*)cxcore_struct[struct_idx];
- CvTsSimpleSet* sset = (CvTsSimpleSet*)simple_struct[struct_idx];
- int pure_elem_size = sset->elem_size - 1;
- int prev_total = cvset->total, prev_count = cvset->active_count;
- int op = cvTsRandInt(rng) % (iter <= iters/10 ? 2 : max_op);
- int by_ptr = op % 2 == 0;
- CvSetElem* first_free = cvset->free_elems;
- CvSetElem* next_free = first_free ? first_free->next_free : 0;
- int pass_data = 0;
-
- if( iter > iters/10 && cvTsRandInt(rng)%200 == 0 ) // clear set
- {
- int prev_count = cvset->total;
- cvClearSet( cvset );
- cvTsClearSimpleSet( sset );
-
- CV_TS_SEQ_CHECK_CONDITION( cvset->active_count == 0 && cvset->total == 0 &&
- cvset->first == 0 && cvset->free_elems == 0 &&
- (cvset->free_blocks != 0 || prev_count == 0),
- "cvClearSet doesn't remove all the elements" );
- continue;
- }
- else if( op == 0 || op == 1 ) // add element
- {
- if( sset->free_count == 0 )
- continue;
-
- elem_mat->cols = cvset->elem_size;
- cvRandArr( rng, elem_mat, CV_RAND_UNI, cvScalarAll(0), cvScalarAll(255) );
- elem = (CvSetElem*)elem_mat->data.ptr;
-
- if( by_ptr )
- {
- CV_CALL( elem2 = cvSetNew( cvset ));
- CV_TS_SEQ_CHECK_CONDITION( elem2 != 0, "cvSetNew returned NULL pointer" );
- }
- else
- {
- pass_data = cvTsRandInt(rng) % 2;
- CV_CALL( idx = cvSetAdd( cvset, pass_data ? elem : 0, &elem2 ));
- CV_TS_SEQ_CHECK_CONDITION( elem2 != 0 && elem2->flags == idx,
- "cvSetAdd returned NULL pointer or a wrong index" );
- }
-
- elem_data = (schar*)elem + sizeof(int);
-
- if( !pass_data )
- memcpy( (schar*)elem2 + sizeof(int), elem_data, pure_elem_size );
-
- idx = elem2->flags;
- idx0 = cvTsSimpleSetAdd( sset, elem_data );
- CV_CALL( elem3 = cvGetSetElem( cvset, idx ));
-
- CV_TS_SEQ_CHECK_CONDITION( CV_IS_SET_ELEM(elem3) &&
- idx == idx0 && elem3 == elem2 && (!pass_data ||
- memcmp( (char*)elem3 + sizeof(int), elem_data, pure_elem_size) == 0),
- "The added element is not correct" );
-
- CV_TS_SEQ_CHECK_CONDITION( (!first_free || elem3 == first_free) &&
- (!next_free || cvset->free_elems == next_free) &&
- cvset->active_count == prev_count + 1,
- "The free node list is modified incorrectly" );
- }
- else if( op == 2 || op == 3 ) // remove element
- {
- idx = cvTsRandInt(rng) % sset->max_count;
-
- if( sset->free_count == sset->max_count || idx >= sset->count )
- continue;
-
- elem_data = cvTsSimpleSetFind(sset, idx);
- if( elem_data == 0 )
- continue;
-
- CV_CALL( elem = cvGetSetElem( cvset, idx ));
- CV_TS_SEQ_CHECK_CONDITION( CV_IS_SET_ELEM(elem) && elem->flags == idx &&
- memcmp((char*)elem + sizeof(int), elem_data, pure_elem_size) == 0,
- "cvGetSetElem returned wrong element" );
-
- if( by_ptr )
- {
- CV_CALL( cvSetRemoveByPtr( cvset, elem ));
- }
- else
- {
- CV_CALL( cvSetRemove( cvset, idx ));
- }
-
- cvTsSimpleSetRemove( sset, idx );
-
- CV_TS_SEQ_CHECK_CONDITION( !CV_IS_SET_ELEM(elem) && !cvGetSetElem(cvset, idx) &&
- (elem->flags & CV_SET_ELEM_IDX_MASK) == idx,
- "cvSetRemove[ByPtr] didn't release the element properly" );
-
- CV_TS_SEQ_CHECK_CONDITION( elem->next_free == first_free &&
- cvset->free_elems == elem &&
- cvset->active_count == prev_count - 1,
- "The free node list has not been updated properly" );
- }
-
- //max_active_count = MAX( max_active_count, cvset->active_count );
- //mean_active_count += cvset->active_count;
- CV_TS_SEQ_CHECK_CONDITION( cvset->active_count == sset->max_count - sset->free_count &&
- cvset->total >= cvset->active_count &&
- (cvset->total == 0 || cvset->total >= prev_total),
- "The total number of cvset elements is not correct" );
-
- // CvSet and simple set do not neccessary have the same "total" (active & free) number,
- // so pass "set->total" to skip that check
- test_seq_block_consistence( struct_idx, (CvSeq*)cvset, cvset->total );
- update_progressbar();
- }
-
- code = 0;
- //ts->printf( CvTS::LOG, "\ngeneration %d. max_active_count = %d,\n\tmean_active_count = %d\n",
- // gen, max_active_count, mean_active_count/iters );
-
- __END__;
-
- if( elem_mat )
- elem_mat->cols = 1; // just to skip a consistency check
- cvReleaseMat( &elem_mat );
-
- return code;
-}
-
-
-void CxCore_SetTest::run( int )
-{
- CvRNG* rng = ts->get_rng();
- int i;
- double t;
-
- CV_FUNCNAME( "CxCore_SetTest::run" );
-
- __BEGIN__;
-
- clear();
- test_progress = -1;
-
- simple_struct = (void**)cvAlloc( struct_count * sizeof(simple_struct[0]) );
- memset( simple_struct, 0, struct_count * sizeof(simple_struct[0]) );
- cxcore_struct = (void**)cvAlloc( struct_count * sizeof(cxcore_struct[0]) );
- memset( cxcore_struct, 0, struct_count * sizeof(cxcore_struct[0]) );
-
- for( gen = 0; gen < generations; gen++ )
- {
- struct_idx = iter = -1;
- t = cvTsRandReal(rng)*(max_log_storage_block_size - min_log_storage_block_size) + min_log_storage_block_size;
- storage = cvCreateMemStorage( cvRound( exp(t * CV_LOG2) ) );
-
- for( i = 0; i < struct_count; i++ )
- {
- t = cvTsRandReal(rng)*(max_log_elem_size - min_log_elem_size) + min_log_elem_size;
- int pure_elem_size = cvRound( exp(t * CV_LOG2) );
- int elem_size = pure_elem_size + sizeof(int);
- elem_size = (elem_size + sizeof(size_t) - 1) & ~(sizeof(size_t)-1);
- elem_size = MAX( elem_size, (int)sizeof(CvSetElem) );
- elem_size = MIN( elem_size, (int)(storage->block_size - sizeof(void*) - sizeof(CvMemBlock) - sizeof(CvSeqBlock)) );
- pure_elem_size = MIN( pure_elem_size, elem_size-(int)sizeof(CvSetElem) );
-
- cvTsReleaseSimpleSet( (CvTsSimpleSet**)&simple_struct[i] );
- simple_struct[i] = cvTsCreateSimpleSet( max_struct_size, pure_elem_size );
- CV_CALL( cxcore_struct[i] = cvCreateSet( 0, sizeof(CvSet), elem_size, storage ));
- }
-
- if( test_set_ops( iterations*100 ) < 0 )
- EXIT;
-
- cvReleaseMemStorage( &storage );
- }
-
- __END__;
-}
-
-CxCore_SetTest set_test;
-
-
-/////////////////////////////////////// graph tests //////////////////////////////////
-
-class CxCore_GraphTest : public CxCore_DynStructBaseTest
-{
-public:
- CxCore_GraphTest();
- void clear();
- void run( int );
-
-protected:
- //int test_seq_block_consistence( int struct_idx );
- int test_graph_ops( int iters );
-};
-
-
-CxCore_GraphTest::CxCore_GraphTest():
- CxCore_DynStructBaseTest( "ds-graph", "cvCreateGraph, cvClearGraph, "
- "cvGraphAddVtx, cvGraphRemoveVtx, cvGraphRemoveVtxByPtr, "
- "cvGraphAddEdge, cvGraphAddEdgeByPtr, "
- "cvGraphRemoveEdge, cvGraphRemoveEdgeByPtr, "
- "cvGraphVtxDegree, cvGraphVtxDegreeByPtr, "
- "cvGetGraphVtx, cvFindGraphEdge, cvFindGraphEdgeByPtr " )
-{
-}
-
-
-void CxCore_GraphTest::clear()
-{
- int i;
- if( simple_struct )
- for( i = 0; i < struct_count; i++ )
- cvTsReleaseSimpleGraph( (CvTsSimpleGraph**)&simple_struct[i] );
- CxCore_DynStructBaseTest::clear();
-}
-
-
-int CxCore_GraphTest::test_graph_ops( int iters )
-{
- const int max_op = 4;
- int i, k, code = -1;
- int max_elem_size = 0;
- int idx, idx0;
- CvGraphVtx *vtx = 0, *vtx2 = 0, *vtx3 = 0;
- CvGraphEdge* edge = 0, *edge2 = 0;
- CvMat* elem_mat = 0;
- CvRNG* rng = ts->get_rng();
- //int max_active_count = 0, mean_active_count = 0;
-
- CV_FUNCNAME( "CxCore_GraphTest::test_graph_ops" );
-
- __BEGIN__;
-
- for( i = 0; i < struct_count; i++ )
- {
- CvGraph* graph = (CvGraph*)cxcore_struct[i];
- max_elem_size = MAX( max_elem_size, graph->elem_size );
- max_elem_size = MAX( max_elem_size, graph->edges->elem_size );
- }
-
- CV_CALL( elem_mat = cvCreateMat( 1, max_elem_size, CV_8UC1 ));
-
- for( iter = 0; iter < iters; iter++ )
- {
- struct_idx = cvTsRandInt(rng) % struct_count;
- CvGraph* graph = (CvGraph*)cxcore_struct[struct_idx];
- CvTsSimpleGraph* sgraph = (CvTsSimpleGraph*)simple_struct[struct_idx];
- CvSet* edges = graph->edges;
- schar *vtx_data;
- char *edge_data;
- int pure_vtx_size = sgraph->vtx->elem_size - 1,
- pure_edge_size = sgraph->edge_size - 1;
- int prev_vtx_total = graph->total,
- prev_edge_total = graph->edges->total,
- prev_vtx_count = graph->active_count,
- prev_edge_count = graph->edges->active_count;
- int op = cvTsRandInt(rng) % max_op;
- int pass_data = 0, vtx_degree0 = 0, vtx_degree = 0;
- CvSetElem *first_free, *next_free;
-
- if( cvTsRandInt(rng) % 200 == 0 ) // clear graph
- {
- int prev_vtx_count = graph->total, prev_edge_count = graph->edges->total;
-
- cvClearGraph( graph );
- cvTsClearSimpleGraph( sgraph );
-
- CV_TS_SEQ_CHECK_CONDITION( graph->active_count == 0 && graph->total == 0 &&
- graph->first == 0 && graph->free_elems == 0 &&
- (graph->free_blocks != 0 || prev_vtx_count == 0),
- "The graph is not empty after clearing" );
-
- CV_TS_SEQ_CHECK_CONDITION( edges->active_count == 0 && edges->total == 0 &&
- edges->first == 0 && edges->free_elems == 0 &&
- (edges->free_blocks != 0 || prev_edge_count == 0),
- "The graph is not empty after clearing" );
- }
- else if( op == 0 ) // add vertex
- {
- if( sgraph->vtx->free_count == 0 )
- continue;
-
- first_free = graph->free_elems;
- next_free = first_free ? first_free->next_free : 0;
-
- if( pure_vtx_size )
- {
- elem_mat->cols = graph->elem_size;
- cvRandArr( rng, elem_mat, CV_RAND_UNI, cvScalarAll(0), cvScalarAll(255) );
- }
-
- vtx = (CvGraphVtx*)elem_mat->data.ptr;
- idx0 = cvTsSimpleGraphAddVertex( sgraph, vtx + 1 );
-
- pass_data = cvTsRandInt(rng) % 2;
- CV_CALL( idx = cvGraphAddVtx( graph, pass_data ? vtx : 0, &vtx2 ));
-
- if( !pass_data && pure_vtx_size > 0 )
- memcpy( vtx2 + 1, vtx + 1, pure_vtx_size );
-
- vtx3 = cvGetGraphVtx( graph, idx );
-
- CV_TS_SEQ_CHECK_CONDITION( (CV_IS_SET_ELEM(vtx3) && vtx3->flags == idx &&
- vtx3->first == 0) || (idx == idx0 && vtx3 == vtx2 &&
- (!pass_data || pure_vtx_size == 0 ||
- memcmp(vtx3 + 1, vtx + 1, pure_vtx_size) == 0)),
- "The added element is not correct" );
-
- CV_TS_SEQ_CHECK_CONDITION( (!first_free || first_free == (CvSetElem*)vtx3) &&
- (!next_free || graph->free_elems == next_free) &&
- graph->active_count == prev_vtx_count + 1,
- "The free node list is modified incorrectly" );
- }
- else if( op == 1 ) // remove vertex
- {
- idx = cvTsRandInt(rng) % sgraph->vtx->max_count;
- if( sgraph->vtx->free_count == sgraph->vtx->max_count || idx >= sgraph->vtx->count )
- continue;
-
- vtx_data = cvTsSimpleGraphFindVertex(sgraph, idx);
- if( vtx_data == 0 )
- continue;
-
- vtx_degree0 = cvTsSimpleGraphVertexDegree( sgraph, idx );
- first_free = graph->free_elems;
-
- CV_CALL( vtx = cvGetGraphVtx( graph, idx ));
- CV_TS_SEQ_CHECK_CONDITION( CV_IS_SET_ELEM(vtx) && vtx->flags == idx &&
- (pure_vtx_size == 0 || memcmp( vtx + 1, vtx_data, pure_vtx_size) == 0),
- "cvGetGraphVtx returned wrong element" );
-
- if( cvTsRandInt(rng) % 2 )
- {
- CV_CALL( vtx_degree = cvGraphVtxDegreeByPtr( graph, vtx ));
- CV_CALL( cvGraphRemoveVtxByPtr( graph, vtx ));
- }
- else
- {
- CV_CALL( vtx_degree = cvGraphVtxDegree( graph, idx ));
- CV_CALL( cvGraphRemoveVtx( graph, idx ));
- }
-
- cvTsSimpleGraphRemoveVertex( sgraph, idx );
-
- CV_TS_SEQ_CHECK_CONDITION( vtx_degree == vtx_degree0,
- "Number of incident edges is different in two graph representations" );
-
- CV_TS_SEQ_CHECK_CONDITION( !CV_IS_SET_ELEM(vtx) && !cvGetGraphVtx(graph, idx) &&
- (vtx->flags & CV_SET_ELEM_IDX_MASK) == idx,
- "cvGraphRemoveVtx[ByPtr] didn't release the vertex properly" );
-
- CV_TS_SEQ_CHECK_CONDITION( graph->edges->active_count == prev_edge_count - vtx_degree,
- "cvGraphRemoveVtx[ByPtr] didn't remove all the incident edges "
- "(or removed some extra)" );
-
- CV_TS_SEQ_CHECK_CONDITION( ((CvSetElem*)vtx)->next_free == first_free &&
- graph->free_elems == (CvSetElem*)vtx &&
- graph->active_count == prev_vtx_count - 1,
- "The free node list has not been updated properly" );
- }
- else if( op == 2 ) // add edge
- {
- int v_idx[2] = {0,0}, res = 0;
- int v_prev_degree[2] = {0,0}, v_degree[2] = {0,0};
-
- if( sgraph->vtx->free_count >= sgraph->vtx->max_count-1 )
- continue;
-
- for( i = 0, k = 0; i < 10; i++ )
- {
- int j = cvTsRandInt(rng) % sgraph->vtx->count;
- vtx_data = cvTsSimpleGraphFindVertex( sgraph, j );
- if( vtx_data )
- {
- v_idx[k] = j;
- if( k == 0 )
- k++;
- else if( v_idx[0] != v_idx[1] &&
- cvTsSimpleGraphFindEdge( sgraph, v_idx[0], v_idx[1] ) == 0 )
- {
- k++;
- break;
- }
- }
- }
-
- if( k < 2 )
- continue;
-
- first_free = graph->edges->free_elems;
- next_free = first_free ? first_free->next_free : 0;
-
- CV_CALL( edge = cvFindGraphEdge( graph, v_idx[0], v_idx[1] ));
- CV_TS_SEQ_CHECK_CONDITION( edge == 0, "Extra edge appeared in the graph" );
-
- if( pure_edge_size > 0 )
- {
- elem_mat->cols = graph->edges->elem_size;
- cvRandArr( rng, elem_mat, CV_RAND_UNI, cvScalarAll(0), cvScalarAll(255) );
- }
- edge = (CvGraphEdge*)elem_mat->data.ptr;
-
- // assign some default weight that is easy to check for
- // consistensy, 'cause an edge weight is not stored
- // in the simple graph
- edge->weight = (float)(v_idx[0] + v_idx[1]);
- pass_data = cvTsRandInt(rng) % 2;
-
- CV_CALL( vtx = cvGetGraphVtx( graph, v_idx[0] ));
- CV_CALL( vtx2 = cvGetGraphVtx( graph, v_idx[1] ));
- CV_TS_SEQ_CHECK_CONDITION( vtx != 0 && vtx2 != 0 && vtx->flags == v_idx[0] &&
- vtx2->flags == v_idx[1], "Some of the vertices are missing" );
-
- if( cvTsRandInt(rng) % 2 )
- {
- CV_CALL( v_prev_degree[0] = cvGraphVtxDegreeByPtr( graph, vtx ));
- CV_CALL( v_prev_degree[1] = cvGraphVtxDegreeByPtr( graph, vtx2 ));
- CV_CALL( res = cvGraphAddEdgeByPtr(graph, vtx, vtx2, pass_data ? edge : 0, &edge2));
- CV_CALL( v_degree[0] = cvGraphVtxDegreeByPtr( graph, vtx ));
- CV_CALL( v_degree[1] = cvGraphVtxDegreeByPtr( graph, vtx2 ));
- }
- else
- {
- CV_CALL( v_prev_degree[0] = cvGraphVtxDegree( graph, v_idx[0] ));
- CV_CALL( v_prev_degree[1] = cvGraphVtxDegree( graph, v_idx[1] ));
- CV_CALL( res = cvGraphAddEdge(graph, v_idx[0], v_idx[1], pass_data ? edge : 0, &edge2));
- CV_CALL( v_degree[0] = cvGraphVtxDegree( graph, v_idx[0] ));
- CV_CALL( v_degree[1] = cvGraphVtxDegree( graph, v_idx[1] ));
- }
-
- //edge3 = (CvGraphEdge*)cvGetSetElem( graph->edges, idx );
- CV_TS_SEQ_CHECK_CONDITION( res == 1 && edge2 != 0 && CV_IS_SET_ELEM(edge2) &&
- ((edge2->vtx[0] == vtx && edge2->vtx[1] == vtx2) ||
- (!CV_IS_GRAPH_ORIENTED(graph) && edge2->vtx[0] == vtx2 && edge2->vtx[1] == vtx)) &&
- (!pass_data || pure_edge_size == 0 || memcmp( edge2 + 1, edge + 1, pure_edge_size ) == 0),
- "The edge has been added incorrectly" );
-
- if( !pass_data )
- {
- if( pure_edge_size > 0 )
- memcpy( edge2 + 1, edge + 1, pure_edge_size );
- edge2->weight = edge->weight;
- }
-
- CV_TS_SEQ_CHECK_CONDITION( v_degree[0] == v_prev_degree[0] + 1 &&
- v_degree[1] == v_prev_degree[1] + 1,
- "The vertices lists have not been updated properly" );
-
- cvTsSimpleGraphAddEdge( sgraph, v_idx[0], v_idx[1], edge + 1 );
-
- CV_TS_SEQ_CHECK_CONDITION( (!first_free || first_free == (CvSetElem*)edge2) &&
- (!next_free || graph->edges->free_elems == next_free) &&
- graph->edges->active_count == prev_edge_count + 1,
- "The free node list is modified incorrectly" );
- }
- else if( op == 3 ) // find & remove edge
- {
- int v_idx[2] = {0,0}, by_ptr;
- int v_prev_degree[2] = {0,0}, v_degree[2] = {0,0};
-
- if( sgraph->vtx->free_count >= sgraph->vtx->max_count-1 )
- continue;
-
- edge_data = 0;
- for( i = 0, k = 0; i < 10; i++ )
- {
- int j = cvTsRandInt(rng) % sgraph->vtx->count;
- vtx_data = cvTsSimpleGraphFindVertex( sgraph, j );
- if( vtx_data )
- {
- v_idx[k] = j;
- if( k == 0 )
- k++;
- else
- {
- edge_data = cvTsSimpleGraphFindEdge( sgraph, v_idx[0], v_idx[1] );
- if( edge_data )
- {
- k++;
- break;
- }
- }
- }
- }
-
- if( k < 2 )
- continue;
-
- by_ptr = cvTsRandInt(rng) % 2;
- first_free = graph->edges->free_elems;
-
- CV_CALL( vtx = cvGetGraphVtx( graph, v_idx[0] ));
- CV_CALL( vtx2 = cvGetGraphVtx( graph, v_idx[1] ));
- CV_TS_SEQ_CHECK_CONDITION( vtx != 0 && vtx2 != 0 && vtx->flags == v_idx[0] &&
- vtx2->flags == v_idx[1], "Some of the vertices are missing" );
-
- if( by_ptr )
- {
- CV_CALL( edge = cvFindGraphEdgeByPtr( graph, vtx, vtx2 ));
- CV_CALL( v_prev_degree[0] = cvGraphVtxDegreeByPtr( graph, vtx ));
- CV_CALL( v_prev_degree[1] = cvGraphVtxDegreeByPtr( graph, vtx2 ));
- }
- else
- {
- CV_CALL( edge = cvFindGraphEdge( graph, v_idx[0], v_idx[1] ));
- CV_CALL( v_prev_degree[0] = cvGraphVtxDegree( graph, v_idx[0] ));
- CV_CALL( v_prev_degree[1] = cvGraphVtxDegree( graph, v_idx[1] ));
- }
-
- idx = edge->flags;
-
- CV_TS_SEQ_CHECK_CONDITION( edge != 0 && edge->weight == v_idx[0] + v_idx[1] &&
- ((edge->vtx[0] == vtx && edge->vtx[1] == vtx2) ||
- (!CV_IS_GRAPH_ORIENTED(graph) && edge->vtx[1] == vtx && edge->vtx[0] == vtx2)) &&
- (pure_edge_size == 0 || memcmp(edge + 1, edge_data, pure_edge_size) == 0),
- "An edge is missing or incorrect" );
-
- if( by_ptr )
- {
- CV_CALL( cvGraphRemoveEdgeByPtr( graph, vtx, vtx2 ));
- CV_CALL( edge2 = cvFindGraphEdgeByPtr( graph, vtx, vtx2 ));
- CV_CALL( v_degree[0] = cvGraphVtxDegreeByPtr( graph, vtx ));
- CV_CALL( v_degree[1] = cvGraphVtxDegreeByPtr( graph, vtx2 ));
- }
- else
- {
- CV_CALL( cvGraphRemoveEdge(graph, v_idx[0], v_idx[1] ));
- CV_CALL( edge2 = cvFindGraphEdge( graph, v_idx[0], v_idx[1] ));
- CV_CALL( v_degree[0] = cvGraphVtxDegree( graph, v_idx[0] ));
- CV_CALL( v_degree[1] = cvGraphVtxDegree( graph, v_idx[1] ));
- }
-
- CV_TS_SEQ_CHECK_CONDITION( !edge2 && !CV_IS_SET_ELEM(edge),
- "The edge has not been removed from the edge set" );
-
- CV_TS_SEQ_CHECK_CONDITION( v_degree[0] == v_prev_degree[0] - 1 &&
- v_degree[1] == v_prev_degree[1] - 1,
- "The vertices lists have not been updated properly" );
-
- cvTsSimpleGraphRemoveEdge( sgraph, v_idx[0], v_idx[1] );
-
- CV_TS_SEQ_CHECK_CONDITION( graph->edges->free_elems == (CvSetElem*)edge &&
- graph->edges->free_elems->next_free == first_free &&
- graph->edges->active_count == prev_edge_count - 1,
- "The free edge list has not been modified properly" );
- }
-
- //max_active_count = MAX( max_active_count, graph->active_count );
- //mean_active_count += graph->active_count;
-
- CV_TS_SEQ_CHECK_CONDITION( graph->active_count == sgraph->vtx->max_count - sgraph->vtx->free_count &&
- graph->total >= graph->active_count &&
- (graph->total == 0 || graph->total >= prev_vtx_total),
- "The total number of graph vertices is not correct" );
-
- CV_TS_SEQ_CHECK_CONDITION( graph->edges->total >= graph->edges->active_count &&
- (graph->edges->total == 0 || graph->edges->total >= prev_edge_total),
- "The total number of graph vertices is not correct" );
-
- // CvGraph and simple graph do not neccessary have the same "total" (active & free) number,
- // so pass "graph->total" (or "graph->edges->total") to skip that check
- test_seq_block_consistence( struct_idx, (CvSeq*)graph, graph->total );
- test_seq_block_consistence( struct_idx, (CvSeq*)graph->edges, graph->edges->total );
- update_progressbar();
- }
-
- code = 0;
- //ts->printf( CvTS::LOG, "\ngeneration %d. max_active_count = %d,\n\tmean_active_count = %d\n",
- // gen, max_active_count, mean_active_count/iters );
-
- __END__;
-
- if( elem_mat )
- elem_mat->cols = 1; // just to skip a consistency check
- cvReleaseMat( &elem_mat );
-
- return code;
-}
-
-
-void CxCore_GraphTest::run( int )
-{
- CvRNG* rng = ts->get_rng();
- int i, k;
- double t;
-
- CV_FUNCNAME( "CxCore_GraphTest::run" );
-
- __BEGIN__;
-
- clear();
- test_progress = -1;
-
- simple_struct = (void**)cvAlloc( struct_count * sizeof(simple_struct[0]) );
- memset( simple_struct, 0, struct_count * sizeof(simple_struct[0]) );
- cxcore_struct = (void**)cvAlloc( struct_count * sizeof(cxcore_struct[0]) );
- memset( cxcore_struct, 0, struct_count * sizeof(cxcore_struct[0]) );
-
- for( gen = 0; gen < generations; gen++ )
- {
- struct_idx = iter = -1;
- t = cvTsRandReal(rng)*(max_log_storage_block_size - min_log_storage_block_size) + min_log_storage_block_size;
- int block_size = cvRound( exp(t * CV_LOG2) );
- block_size = MAX(block_size, (int)(sizeof(CvGraph) + sizeof(CvMemBlock) + sizeof(CvSeqBlock)));
-
- storage = cvCreateMemStorage(block_size);
-
- for( i = 0; i < struct_count; i++ )
- {
- int pure_elem_size[2], elem_size[2];
- int is_oriented = (gen + i) % 2;
- for( k = 0; k < 2; k++ )
- {
- t = cvTsRandReal(rng)*(max_log_elem_size - min_log_elem_size) + min_log_elem_size;
- int pe = cvRound( exp(t * CV_LOG2) ) - 1; // pure_elem_size==0 does also make sense
- int delta = k == 0 ? sizeof(CvGraphVtx) : sizeof(CvGraphEdge);
- int e = pe + delta;
- e = (e + sizeof(size_t) - 1) & ~(sizeof(size_t)-1);
- e = MIN( e, (int)(storage->block_size - sizeof(CvMemBlock) -
- sizeof(CvSeqBlock) - sizeof(void*)) );
- pe = MIN(pe, e - delta);
- pure_elem_size[k] = pe;
- elem_size[k] = e;
- }
-
- cvTsReleaseSimpleGraph( (CvTsSimpleGraph**)&simple_struct[i] );
- simple_struct[i] = cvTsCreateSimpleGraph( max_struct_size/4, pure_elem_size[0],
- pure_elem_size[1], is_oriented );
- CV_CALL( cxcore_struct[i] = cvCreateGraph( is_oriented ? CV_ORIENTED_GRAPH : CV_GRAPH,
- sizeof(CvGraph), elem_size[0], elem_size[1],
- storage ));
- }
-
- if( test_graph_ops( iterations*10 ) < 0 )
- EXIT;
-
- cvReleaseMemStorage( &storage );
- }
-
- __END__;
-}
-
-CxCore_GraphTest graph_test;
-
-
-
-//////////// graph scan test //////////////
-
-class CxCore_GraphScanTest : public CxCore_DynStructBaseTest
-{
-public:
- CxCore_GraphScanTest();
- void run( int );
-
-protected:
- //int test_seq_block_consistence( int struct_idx );
- int create_random_graph( int );
-};
-
-
-CxCore_GraphScanTest::CxCore_GraphScanTest():
- CxCore_DynStructBaseTest( "ds-graphscan", "cvCreateGraph, "
- "cvGraphAddVtx, cvGraphAddEdge, cvNextGraphItem, "
- "cvCreateGraphScanner, cvReleaseGraphScanner" )
-{
- iterations = 100;
- struct_count = 1;
-}
-
-
-int CxCore_GraphScanTest::create_random_graph( int _struct_idx )
-{
- CvRNG* rng = ts->get_rng();
- int is_oriented = cvTsRandInt(rng) % 2;
- int i, vtx_count = cvTsRandInt(rng) % max_struct_size;
- int edge_count = cvTsRandInt(rng) % MAX(vtx_count*20, 1);
- CvGraph* graph;
-
- CV_FUNCNAME( "CxCore_GraphScanTest::create_random_graph" );
-
- __BEGIN__;
-
- struct_idx = _struct_idx;
-
- CV_CALL( cxcore_struct[_struct_idx] = graph = cvCreateGraph(
- is_oriented ? CV_ORIENTED_GRAPH : CV_GRAPH,
- sizeof(CvGraph), sizeof(CvGraphVtx), sizeof(CvGraphEdge), storage ));
-
- for( i = 0; i < vtx_count; i++ )
- CV_CALL( cvGraphAddVtx( graph ));
-
- assert( graph->active_count == vtx_count );
-
- for( i = 0; i < edge_count; i++ )
- {
- int j = cvTsRandInt(rng) % vtx_count;
- int k = cvTsRandInt(rng) % vtx_count;
-
- if( j != k )
- CV_CALL( cvGraphAddEdge( graph, j, k ));
- }
-
- assert( graph->active_count == vtx_count && graph->edges->active_count <= edge_count );
-
- __END__;
-
- return 0;
-}
-
-
-void CxCore_GraphScanTest::run( int )
-{
- CvRNG* rng = ts->get_rng();
- CvGraphScanner* scanner = 0;
- CvMat* vtx_mask = 0, *edge_mask = 0;
- double t;
- int i;
-
- CV_FUNCNAME( "CxCore_GraphTest::run" );
-
- __BEGIN__;
-
- clear();
- test_progress = -1;
-
- cxcore_struct = (void**)cvAlloc( struct_count * sizeof(cxcore_struct[0]) );
- memset( cxcore_struct, 0, struct_count * sizeof(cxcore_struct[0]) );
-
- for( gen = 0; gen < generations; gen++ )
- {
- struct_idx = iter = -1;
- t = cvTsRandReal(rng)*(max_log_storage_block_size - min_log_storage_block_size) + min_log_storage_block_size;
- int storage_blocksize = cvRound( exp(t * CV_LOG2) );
- storage_blocksize = MAX(storage_blocksize, (int)(sizeof(CvGraph) + sizeof(CvMemBlock) + sizeof(CvSeqBlock)));
- storage_blocksize = MAX(storage_blocksize, (int)(sizeof(CvGraphEdge) + sizeof(CvMemBlock) + sizeof(CvSeqBlock)));
- storage_blocksize = MAX(storage_blocksize, (int)(sizeof(CvGraphVtx) + sizeof(CvMemBlock) + sizeof(CvSeqBlock)));
- storage = cvCreateMemStorage(storage_blocksize);
-
- if( gen == 0 )
- {
- // special regression test for one sample graph.
- // !!! ATTENTION !!! The test relies on the particular order of the inserted edges
- // (LIFO: the edge inserted last goes first in the list of incident edges).
- // if it is changed, the test will have to be modified.
-
- int vtx_count = -1, edge_count = 0, edges[][3] =
- {
- {0,4,'f'}, {0,1,'t'}, {1,4,'t'}, {1,2,'t'}, {2,3,'t'}, {4,3,'c'}, {3,1,'b'},
- {5,7,'t'}, {7,5,'b'}, {5,6,'t'}, {6,0,'c'}, {7,6,'c'}, {6,4,'c'}, {-1,-1,0}
- };
-
- CvGraph* graph;
- CV_CALL( graph = cvCreateGraph( CV_ORIENTED_GRAPH, sizeof(CvGraph),
- sizeof(CvGraphVtx), sizeof(CvGraphEdge), storage ));
-
- for( i = 0; edges[i][0] >= 0; i++ )
- {
- vtx_count = MAX( vtx_count, edges[i][0] );
- vtx_count = MAX( vtx_count, edges[i][1] );
- }
- vtx_count++;
-
- for( i = 0; i < vtx_count; i++ )
- CV_CALL( cvGraphAddVtx( graph ));
-
- for( i = 0; edges[i][0] >= 0; i++ )
- {
- CvGraphEdge* edge;
- CV_CALL( cvGraphAddEdge( graph, edges[i][0], edges[i][1], 0, &edge ));
- edge->weight = (float)edges[i][2];
- }
-
- edge_count = i;
- CV_CALL( scanner = cvCreateGraphScanner( graph, 0, CV_GRAPH_ALL_ITEMS ));
-
- for(;;)
- {
- int code, a = -1, b = -1;
- const char* event = "";
- CV_CALL( code = cvNextGraphItem( scanner ));
-
- switch( code )
- {
- case CV_GRAPH_VERTEX:
- event = "Vertex";
- vtx_count--;
- a = cvGraphVtxIdx( graph, scanner->vtx );
- break;
- case CV_GRAPH_TREE_EDGE:
- event = "Tree Edge";
- edge_count--;
- CV_TS_SEQ_CHECK_CONDITION( scanner->edge->weight == (float)'t',
- "Invalid edge type" );
- a = cvGraphVtxIdx( graph, scanner->vtx );
- b = cvGraphVtxIdx( graph, scanner->dst );
- break;
- case CV_GRAPH_BACK_EDGE:
- event = "Back Edge";
- edge_count--;
- CV_TS_SEQ_CHECK_CONDITION( scanner->edge->weight == (float)'b',
- "Invalid edge type" );
- a = cvGraphVtxIdx( graph, scanner->vtx );
- b = cvGraphVtxIdx( graph, scanner->dst );
- break;
- case CV_GRAPH_CROSS_EDGE:
- event = "Cross Edge";
- edge_count--;
- CV_TS_SEQ_CHECK_CONDITION( scanner->edge->weight == (float)'c',
- "Invalid edge type" );
- a = cvGraphVtxIdx( graph, scanner->vtx );
- b = cvGraphVtxIdx( graph, scanner->dst );
- break;
- case CV_GRAPH_FORWARD_EDGE:
- event = "Forward Edge";
- edge_count--;
- CV_TS_SEQ_CHECK_CONDITION( scanner->edge->weight == (float)'f',
- "Invalid edge type" );
- a = cvGraphVtxIdx( graph, scanner->vtx );
- b = cvGraphVtxIdx( graph, scanner->dst );
- break;
- case CV_GRAPH_BACKTRACKING:
- event = "Backtracking";
- a = cvGraphVtxIdx( graph, scanner->vtx );
- break;
- case CV_GRAPH_NEW_TREE:
- event = "New search tree";
- break;
- case CV_GRAPH_OVER:
- event = "End of procedure";
- break;
- default:
- CV_TS_SEQ_CHECK_CONDITION( 0, "Invalid code appeared during graph scan" );
- }
-
- ts->printf( CvTS::LOG, "%s", event );
- if( a >= 0 )
- {
- if( b >= 0 )
- ts->printf( CvTS::LOG, ": (%d,%d)", a, b );
- else
- ts->printf( CvTS::LOG, ": %d", a );
- }
-
- ts->printf( CvTS::LOG, "\n" );
-
- if( code < 0 )
- break;
- }
-
- CV_TS_SEQ_CHECK_CONDITION( vtx_count == 0 && edge_count == 0,
- "Not every vertex/edge has been visited" );
- update_progressbar();
- }
-
- // for a random graph the test just checks that every graph vertex and
- // every edge is vitisted during the scan
- for( iter = 0; iter < iterations; iter++ )
- {
- create_random_graph(0);
- CvGraph* graph = (CvGraph*)cxcore_struct[0];
-
- // iterate twice to check that scanner doesn't damage the graph
- for( i = 0; i < 2; i++ )
- {
- CvGraphVtx* start_vtx = cvTsRandInt(rng) % 2 || graph->active_count == 0 ? 0 :
- cvGetGraphVtx( graph, cvTsRandInt(rng) % graph->active_count );
-
- CV_CALL( scanner = cvCreateGraphScanner( graph, start_vtx, CV_GRAPH_ALL_ITEMS ));
-
- if( !vtx_mask || vtx_mask->cols < graph->active_count )
- {
- cvReleaseMat( &vtx_mask );
- CV_CALL( vtx_mask = cvCreateMat( 1, MAX(graph->active_count, 1), CV_8UC1 ));
- }
-
- if( !edge_mask || edge_mask->cols < graph->edges->active_count )
- {
- cvReleaseMat( &edge_mask );
- CV_CALL( edge_mask = cvCreateMat( 1, MAX(graph->edges->active_count, 1), CV_8UC1 ));
- }
-
- cvZero( vtx_mask );
- cvZero( edge_mask );
-
- for(;;)
- {
- int code;
- CV_CALL( code = cvNextGraphItem( scanner ));
-
- if( code == CV_GRAPH_OVER )
- break;
- else if( code & CV_GRAPH_ANY_EDGE )
- {
- int edge_idx = scanner->edge->flags & CV_SET_ELEM_IDX_MASK;
-
- CV_TS_SEQ_CHECK_CONDITION( edge_idx < graph->edges->active_count &&
- edge_mask->data.ptr[edge_idx] == 0,
- "The edge is not found or visited for the second time" );
- edge_mask->data.ptr[edge_idx] = 1;
- }
- else if( code & CV_GRAPH_VERTEX )
- {
- int vtx_idx = scanner->vtx->flags & CV_SET_ELEM_IDX_MASK;
-
- CV_TS_SEQ_CHECK_CONDITION( vtx_idx < graph->active_count &&
- vtx_mask->data.ptr[vtx_idx] == 0,
- "The vtx is not found or visited for the second time" );
- vtx_mask->data.ptr[vtx_idx] = 1;
- }
- }
-
- cvReleaseGraphScanner( &scanner );
-
- CV_TS_SEQ_CHECK_CONDITION( cvNorm(vtx_mask,0,CV_L1) == graph->active_count &&
- cvNorm(edge_mask,0,CV_L1) == graph->edges->active_count,
- "Some vertices or edges have not been visited" );
- update_progressbar();
- }
- cvClearMemStorage( storage );
- }
-
- cvReleaseMemStorage( &storage );
- }
-
- __END__;
-
- cvReleaseGraphScanner( &scanner );
- cvReleaseMat( &vtx_mask );
- cvReleaseMat( &edge_mask );
-}
-
-CxCore_GraphScanTest graphscan_test;
-
-/* End of file. */
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-//////////////////////////////////////////////////////////////////////////////////////////
-////////////////// tests for discrete linear transforms (FFT, DCT ...) ///////////////////
-//////////////////////////////////////////////////////////////////////////////////////////
-
-#include "cxcoretest.h"
-#include <float.h>
-
-typedef struct CvTsComplex32f
-{
- float re, im;
-}
-CvTsComplex32f;
-
-typedef struct CvTsComplex64f
-{
- double re, im;
-}
-CvTsComplex64f;
-
-static CvMat* cvTsInitDFTWave( int n, int inv )
-{
- int i;
- double angle = (inv ? 1 : -1)*CV_PI*2/n;
- CvTsComplex64f wi, w1;
- CvMat* wave = cvCreateMat( 1, n, CV_64FC2 );
- CvTsComplex64f* w = (CvTsComplex64f*)wave->data.db;
-
- w1.re = cos(angle);
- w1.im = sin(angle);
- w[0].re = wi.re = 1.;
- w[0].im = wi.im = 0.;
-
- for( i = 1; i < n; i++ )
- {
- double t = wi.re*w1.re - wi.im*w1.im;
- wi.im = wi.re*w1.im + wi.im*w1.re;
- wi.re = t;
- w[i] = wi;
- }
-
- return wave;
-}
-
-
-static void cvTsDFT_1D( const CvMat* _src, CvMat* _dst, int flags, CvMat* wave=0 )
-{
- int i, j, k, n = _dst->cols + _dst->rows - 1;
- const CvMat* wave0 = wave;
- double scale = (flags & CV_DXT_SCALE) ? 1./n : 1.;
- assert( _src->cols + _src->rows - 1 == n );
- int src_step = 1, dst_step = 1;
- CvTsComplex64f* w;
-
- assert( CV_ARE_TYPES_EQ(_src,_dst) && _src->rows*_src->cols == _dst->rows*_dst->cols );
-
- if( !wave )
- wave = cvTsInitDFTWave( n, flags & CV_DXT_INVERSE );
-
- w = (CvTsComplex64f*)wave->data.db;
- if( !CV_IS_MAT_CONT(_src->type) )
- src_step = _src->step/CV_ELEM_SIZE(_src->type);
- if( !CV_IS_MAT_CONT(_dst->type) )
- dst_step = _dst->step/CV_ELEM_SIZE(_dst->type);
-
- if( CV_MAT_TYPE(_src->type) == CV_32FC2 )
- {
- CvTsComplex32f* dst = (CvTsComplex32f*)_dst->data.fl;
- for( i = 0; i < n; i++, dst += dst_step )
- {
- CvTsComplex32f* src = (CvTsComplex32f*)_src->data.fl;
- CvTsComplex64f sum = {0,0};
- int delta = i;
- k = 0;
-
- for( j = 0; j < n; j++, src += src_step )
- {
- sum.re += src->re*w[k].re - src->im*w[k].im;
- sum.im += src->re*w[k].im + src->im*w[k].re;
- k += delta;
- k -= (k >= n ? n : 0);
- }
-
- dst->re = (float)(sum.re*scale);
- dst->im = (float)(sum.im*scale);
- }
- }
- else if( CV_MAT_TYPE(_src->type) == CV_64FC2 )
- {
- CvTsComplex64f* dst = (CvTsComplex64f*)_dst->data.db;
- for( i = 0; i < n; i++, dst += dst_step )
- {
- CvTsComplex64f* src = (CvTsComplex64f*)_src->data.db;
- CvTsComplex64f sum = {0,0};
- int delta = i;
- k = 0;
-
- for( j = 0; j < n; j++, src += src_step )
- {
- sum.re += src->re*w[k].re - src->im*w[k].im;
- sum.im += src->re*w[k].im + src->im*w[k].re;
- k += delta;
- k -= (k >= n ? n : 0);
- }
-
- dst->re = sum.re*scale;
- dst->im = sum.im*scale;
- }
- }
- else
- assert(0);
-
- if( !wave0 )
- cvReleaseMat( &wave );
-}
-
-
-static void cvTsDFT_2D( const CvMat* src, CvMat* dst, int flags )
-{
- int i;
- CvMat* tmp = cvCreateMat( dst->cols, dst->rows, dst->type );
- CvMat* wave = cvTsInitDFTWave( dst->cols, flags & CV_DXT_INVERSE );
-
- // 1. row-wise transform
- for( i = 0; i < dst->rows; i++ )
- {
- CvMat src_row, dst_row;
- cvGetRow( src, &src_row, i );
- cvGetCol( tmp, &dst_row, i );
- cvTsDFT_1D( &src_row, &dst_row, flags, wave );
- }
-
- if( !(flags & CV_DXT_ROWS) )
- {
- if( dst->cols != dst->rows )
- {
- cvReleaseMat( &wave );
- wave = cvTsInitDFTWave( dst->rows, flags & CV_DXT_INVERSE );
- }
-
- // 2. column-wise transform
- for( i = 0; i < dst->cols; i++ )
- {
- CvMat src_row, dst_row;
- cvGetRow( tmp, &src_row, i );
- cvGetCol( dst, &dst_row, i );
- cvTsDFT_1D( &src_row, &dst_row, flags, wave );
- }
- }
- else
- cvTsTranspose( tmp, dst );
-
- cvReleaseMat( &wave );
- cvReleaseMat( &tmp );
-}
-
-
-static CvMat* cvTsInitDCTWave( int n, int inv )
-{
- int i, k;
- double angle = CV_PI*0.5/n;
- CvMat* wave = cvCreateMat( n, n, CV_64FC1 );
-
- double scale = sqrt(1./n);
- for( k = 0; k < n; k++ )
- wave->data.db[k] = scale;
- scale *= sqrt(2.);
- for( i = 1; i < n; i++ )
- for( k = 0; k < n; k++ )
- wave->data.db[i*n + k] = scale*cos( angle*i*(2*k + 1) );
-
- if( inv )
- cvTsTranspose( wave, wave );
-
- return wave;
-}
-
-
-static void cvTsDCT_1D( const CvMat* _src, CvMat* _dst, int flags, CvMat* wave=0 )
-{
- int i, j, n = _dst->cols + _dst->rows - 1;
- const CvMat* wave0 = wave;
- assert( _src->cols + _src->rows - 1 == n);
- int src_step = 1, dst_step = 1;
- double* w;
-
- assert( CV_ARE_TYPES_EQ(_src,_dst) && _src->rows*_src->cols == _dst->rows*_dst->cols );
-
- if( !wave )
- wave = cvTsInitDCTWave( n, flags & CV_DXT_INVERSE );
- w = wave->data.db;
-
- if( !CV_IS_MAT_CONT(_src->type) )
- src_step = _src->step/CV_ELEM_SIZE(_src->type);
- if( !CV_IS_MAT_CONT(_dst->type) )
- dst_step = _dst->step/CV_ELEM_SIZE(_dst->type);
-
- if( CV_MAT_TYPE(_src->type) == CV_32FC1 )
- {
- float *dst = _dst->data.fl;
-
- for( i = 0; i < n; i++, dst += dst_step )
- {
- const float* src = _src->data.fl;
- double sum = 0;
-
- for( j = 0; j < n; j++, src += src_step )
- sum += src[0]*w[j];
- w += n;
- dst[0] = (float)sum;
- }
- }
- else if( CV_MAT_TYPE(_src->type) == CV_64FC1 )
- {
- double *dst = _dst->data.db;
-
- for( i = 0; i < n; i++, dst += dst_step )
- {
- const double* src = _src->data.db;
- double sum = 0;
-
- for( j = 0; j < n; j++, src += src_step )
- sum += src[0]*w[j];
- w += n;
- dst[0] = sum;
- }
- }
- else
- assert(0);
-
- if( !wave0 )
- cvReleaseMat( &wave );
-}
-
-
-static void cvTsDCT_2D( const CvMat* src, CvMat* dst, int flags )
-{
- int i;
- CvMat* tmp = cvCreateMat( dst->cols, dst->rows, dst->type );
- CvMat* wave = cvTsInitDCTWave( dst->cols, flags & CV_DXT_INVERSE );
-
- // 1. row-wise transform
- for( i = 0; i < dst->rows; i++ )
- {
- CvMat src_row, dst_row;
- cvGetRow( src, &src_row, i );
- cvGetCol( tmp, &dst_row, i );
- cvTsDCT_1D( &src_row, &dst_row, flags, wave );
- }
-
- if( !(flags & CV_DXT_ROWS) )
- {
- if( dst->cols != dst->rows )
- {
- cvReleaseMat( &wave );
- wave = cvTsInitDCTWave( dst->rows, flags & CV_DXT_INVERSE );
- }
-
- // 2. column-wise transform
- for( i = 0; i < dst->cols; i++ )
- {
- CvMat src_row, dst_row;
- cvGetRow( tmp, &src_row, i );
- cvGetCol( dst, &dst_row, i );
- cvTsDCT_1D( &src_row, &dst_row, flags, wave );
- }
- }
- else
- {
- cvTranspose( tmp, dst );
- }
-
- cvReleaseMat( &wave );
- cvReleaseMat( &tmp );
-}
-
-
-static void cvTsConvertFromCCS( const CvMat* _src0, const CvMat* _src1,
- CvMat* _dst, int flags )
-{
- if( _dst->rows > 1 && (_dst->cols > 1 || (flags & CV_DXT_ROWS)) )
- {
- int i, count = _dst->rows, len = _dst->cols;
- int is_2d = (flags & CV_DXT_ROWS) == 0;
- CvMat src0_row, src1_row, dst_row;
- for( i = 0; i < count; i++ )
- {
- int j = !is_2d || i == 0 ? i : count - i;
- cvGetRow( _src0, &src0_row, i );
- cvGetRow( _src1, &src1_row, j );
- cvGetRow( _dst, &dst_row, i );
- cvTsConvertFromCCS( &src0_row, &src1_row, &dst_row, 0 );
- }
-
- if( is_2d )
- {
- cvGetCol( _src0, &src0_row, 0 );
- cvGetCol( _dst, &dst_row, 0 );
- cvTsConvertFromCCS( &src0_row, &src0_row, &dst_row, 0 );
- if( (len & 1) == 0 )
- {
- cvGetCol( _src0, &src0_row, _src0->cols - 1 );
- cvGetCol( _dst, &dst_row, len/2 );
- cvTsConvertFromCCS( &src0_row, &src0_row, &dst_row, 0 );
- }
- }
- }
- else
- {
- int i, n = _dst->cols + _dst->rows - 1, n2 = (n+1) >> 1;
- int cn = CV_MAT_CN(_src0->type);
- int src_step = cn, dst_step = 1;
-
- if( !CV_IS_MAT_CONT(_dst->type) )
- dst_step = _dst->step/CV_ELEM_SIZE(_dst->type);
-
- if( !CV_IS_MAT_CONT(_src0->type) )
- src_step = _src0->step/CV_ELEM_SIZE(_src0->type & CV_MAT_DEPTH_MASK);
-
- if( CV_MAT_DEPTH(_dst->type) == CV_32F )
- {
- CvTsComplex32f* dst = (CvTsComplex32f*)_dst->data.fl;
- const float* src0 = _src0->data.fl;
- const float* src1 = _src1->data.fl;
- int delta0, delta1;
-
- dst->re = src0[0];
- dst->im = 0;
-
- if( (n & 1) == 0 )
- {
- dst[n2*dst_step].re = src0[(cn == 1 ? n-1 : n2)*src_step];
- dst[n2*dst_step].im = 0;
- }
-
- delta0 = src_step;
- delta1 = delta0 + (cn == 1 ? src_step : 1);
- if( cn == 1 )
- src_step *= 2;
-
- for( i = 1; i < n2; i++, delta0 += src_step, delta1 += src_step )
- {
- float t0 = src0[delta0];
- float t1 = src0[delta1];
-
- dst[i*dst_step].re = t0;
- dst[i*dst_step].im = t1;
-
- t0 = src1[delta0];
- t1 = -src1[delta1];
-
- dst[(n-i)*dst_step].re = t0;
- dst[(n-i)*dst_step].im = t1;
- }
- }
- else
- {
- CvTsComplex64f* dst = (CvTsComplex64f*)_dst->data.db;
- const double* src0 = _src0->data.db;
- const double* src1 = _src1->data.db;
- int delta0, delta1;
-
- dst->re = src0[0];
- dst->im = 0;
-
- if( (n & 1) == 0 )
- {
- dst[n2*dst_step].re = src0[(cn == 1 ? n-1 : n2)*src_step];
- dst[n2*dst_step].im = 0;
- }
-
- delta0 = src_step;
- delta1 = delta0 + (cn == 1 ? src_step : 1);
- if( cn == 1 )
- src_step *= 2;
-
- for( i = 1; i < n2; i++, delta0 += src_step, delta1 += src_step )
- {
- double t0 = src0[delta0];
- double t1 = src0[delta1];
-
- dst[i*dst_step].re = t0;
- dst[i*dst_step].im = t1;
-
- t0 = src1[delta0];
- t1 = -src1[delta1];
-
- dst[(n-i)*dst_step].re = t0;
- dst[(n-i)*dst_step].im = t1;
- }
- }
- }
-}
-
-
-static void cvTsFixCCS( CvMat* mat, int cols, int flags )
-{
- int i, rows = mat->rows;
- int rows2 = flags & CV_DXT_ROWS ? rows : rows/2 + 1, cols2 = cols/2 + 1;
-
- assert( cols2 == mat->cols );
-
- if( CV_MAT_TYPE(mat->type) == CV_32FC2 )
- {
- for( i = 0; i < rows2; i++ )
- {
- CvTsComplex32f* row = (CvTsComplex32f*)(mat->data.ptr + mat->step*i);
- if( (flags & CV_DXT_ROWS) || i == 0 || (i == rows2 - 1 && rows % 2 == 0) )
- {
- row[0].im = 0;
- if( cols % 2 == 0 )
- row[cols2-1].im = 0;
- }
- else
- {
- CvTsComplex32f* row2 = (CvTsComplex32f*)(mat->data.ptr + mat->step*(rows-i));
- row2[0].re = row[0].re;
- row2[0].im = -row[0].im;
-
- if( cols % 2 == 0 )
- {
- row2[cols2-1].re = row[cols2-1].re;
- row2[cols2-1].im = -row[cols2-1].im;
- }
- }
- }
- }
- else if( CV_MAT_TYPE(mat->type) == CV_64FC2 )
- {
- for( i = 0; i < rows2; i++ )
- {
- CvTsComplex64f* row = (CvTsComplex64f*)(mat->data.ptr + mat->step*i);
- if( (flags & CV_DXT_ROWS) || i == 0 || (i == rows2 - 1 && rows % 2 == 0) )
- {
- row[0].im = 0;
- if( cols % 2 == 0 )
- row[cols2-1].im = 0;
- }
- else
- {
- CvTsComplex64f* row2 = (CvTsComplex64f*)(mat->data.ptr + mat->step*(rows-i));
- row2[0].re = row[0].re;
- row2[0].im = -row[0].im;
-
- if( cols % 2 == 0 )
- {
- row2[cols2-1].re = row[cols2-1].re;
- row2[cols2-1].im = -row[cols2-1].im;
- }
- }
- }
- }
-}
-
-
-static const CvSize dxt_sizes[] = {{16,1}, {256,1}, {1024,1}, {65536,1},
- {10,1}, {100,1}, {1000,1}, {100000,1}, {256, 256}, {1024,1024}, {-1,-1}};
-static const int dxt_depths[] = { CV_32F, CV_64F, -1 };
-static const char* dxt_param_names[] = { "size", "depth", "transform_type", 0 };
-static const char* dft_transforms[] = { "Fwd_CToC", "Inv_CToC", "Fwd_RToPack", "Inv_PackToR", 0 };
-static const char* mulsp_transforms[] = { "Fwd_CToC", "Fwd_RToPack", 0 };
-static const char* dct_transforms[] = { "Fwd", "Inv", 0 };
-
-class CxCore_DXTBaseTestImpl : public CvArrTest
-{
-public:
- CxCore_DXTBaseTestImpl( const char* test_name, const char* test_funcs,
- bool _allow_complex=false, bool _allow_odd=false,
- bool _spectrum_mode=false );
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- int prepare_test_case( int test_case_idx );
- double get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ );
- void get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types,
- CvSize** whole_sizes, bool* are_images );
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
- int write_default_params( CvFileStorage* fs );
- int flags; // transformation flags
- bool allow_complex, // whether input/output may be complex or not:
- // true for DFT and MulSpectrums, false for DCT
- allow_odd, // whether input/output may be have odd (!=1) dimensions:
- // true for DFT and MulSpectrums, false for DCT
- spectrum_mode, // (2 complex/ccs inputs, 1 complex/ccs output):
- // true for MulSpectrums, false for DFT and DCT
- inplace, // inplace operation (set for each individual test case)
- temp_dst; // use temporary destination (for real->ccs DFT and ccs MulSpectrums)
- const char** transform_type_list;
-};
-
-
-CxCore_DXTBaseTestImpl::CxCore_DXTBaseTestImpl( const char* test_name, const char* test_funcs,
- bool _allow_complex, bool _allow_odd, bool _spectrum_mode )
- : CvArrTest( test_name, test_funcs, "" ),
- flags(0), allow_complex(_allow_complex), allow_odd(_allow_odd),
- spectrum_mode(_spectrum_mode), inplace(false), temp_dst(false)
-{
- test_array[INPUT].push(NULL);
- if( spectrum_mode )
- test_array[INPUT].push(NULL);
- test_array[OUTPUT].push(NULL);
- test_array[REF_OUTPUT].push(NULL);
- test_array[TEMP].push(NULL);
- test_array[TEMP].push(NULL);
-
- max_log_array_size = 9;
- element_wise_relative_error = spectrum_mode;
-
- size_list = (CvSize*)dxt_sizes;
- whole_size_list = 0;
- depth_list = (int*)dxt_depths;
- cn_list = 0;
- transform_type_list = 0;
-}
-
-
-void CxCore_DXTBaseTestImpl::get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- int bits = cvTsRandInt(rng);
- int depth = cvTsRandInt(rng)%2 + CV_32F;
- int cn = !allow_complex || !(bits & 256) ? 1 : 2;
- CvSize size;
- CvArrTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
-
- flags = bits & (CV_DXT_INVERSE | CV_DXT_SCALE | CV_DXT_ROWS | CV_DXT_MUL_CONJ);
- if( spectrum_mode )
- flags &= ~CV_DXT_INVERSE;
- types[TEMP][0] = types[TEMP][1] = types[INPUT][0] =
- types[OUTPUT][0] = CV_MAKETYPE(depth, cn);
- size = sizes[INPUT][0];
-
- //size.width = size.width % 10 + 1;
- //size.height = size.width % 10 + 1;
- //size.width = 1;
- //flags &= ~CV_DXT_ROWS;
- temp_dst = false;
-
- if( flags & CV_DXT_ROWS && (bits&1024) )
- {
- if( bits&16 )
- size.width = 1;
- else
- size.height = 1;
- flags &= ~CV_DXT_ROWS;
- }
-
- const int P2_MIN_SIZE = 32;
- if( ((bits >> 10) & 1) == 0 )
- {
- size.width = (size.width / P2_MIN_SIZE)*P2_MIN_SIZE;
- size.width = MAX(size.width, 1);
- size.height = (size.height / P2_MIN_SIZE)*P2_MIN_SIZE;
- size.height = MAX(size.height, 1);
- }
-
- if( !allow_odd )
- {
- if( size.width > 1 && (size.width&1) != 0 )
- size.width = (size.width + 1) & -2;
-
- if( size.height > 1 && (size.height&1) != 0 && !(flags & CV_DXT_ROWS) )
- size.height = (size.height + 1) & -2;
- }
-
- sizes[INPUT][0] = sizes[OUTPUT][0] = size;
- sizes[TEMP][0] = sizes[TEMP][1] = cvSize(0,0);
-
- if( spectrum_mode )
- {
- if( cn == 1 )
- {
- types[OUTPUT][0] = depth + 8;
- sizes[TEMP][0] = size;
- }
- sizes[INPUT][0] = sizes[INPUT][1] = size;
- types[INPUT][1] = types[INPUT][0];
- }
- else if( /*(cn == 2 && (bits&32)) ||*/ (cn == 1 && allow_complex) )
- {
- types[TEMP][0] = depth + 8; // CV_??FC2
- sizes[TEMP][0] = size;
- size = cvSize(size.width/2+1, size.height);
-
- if( flags & CV_DXT_INVERSE )
- {
- if( cn == 2 )
- {
- types[OUTPUT][0] = depth;
- sizes[INPUT][0] = size;
- }
- types[TEMP][1] = types[TEMP][0];
- sizes[TEMP][1] = sizes[TEMP][0];
- }
- else
- {
- if( allow_complex )
- types[OUTPUT][0] = depth + 8;
-
- if( cn == 2 )
- {
- types[INPUT][0] = depth;
- types[TEMP][1] = types[TEMP][0];
- sizes[TEMP][1] = size;
- }
- else
- {
- types[TEMP][1] = depth;
- sizes[TEMP][1] = sizes[TEMP][0];
- }
- temp_dst = true;
- }
- }
-
- inplace = false;
- if( spectrum_mode ||
- (!temp_dst && types[INPUT][0] == types[OUTPUT][0]) ||
- (temp_dst && types[INPUT][0] == types[TEMP][1]) )
- inplace = (bits & 64) != 0;
-
- types[REF_OUTPUT][0] = types[OUTPUT][0];
- sizes[REF_OUTPUT][0] = sizes[OUTPUT][0];
-}
-
-
-void CxCore_DXTBaseTestImpl::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types,
- CvSize** whole_sizes, bool* are_images )
-{
- CvArrTest::get_timing_test_array_types_and_sizes( test_case_idx,
- sizes, types, whole_sizes, are_images );
- const char* transform_type = cvReadString( find_timing_param( "transform_type" ), "" );
- int depth = CV_MAT_DEPTH(types[INPUT][0]);
- int in_type = depth, out_type = depth;
-
- if( strcmp( transform_type, "Fwd_CToC" ) == 0 || strcmp( transform_type, "Inv_CToC" ) == 0 )
- in_type = out_type = CV_MAKETYPE(depth,2);
-
- if( strncmp( transform_type, "Fwd", 3 ) == 0 )
- flags = CV_DXT_FORWARD;
- else
- flags = CV_DXT_INV_SCALE;
-
- types[INPUT][0] = in_type;
- if( spectrum_mode )
- types[INPUT][1] = in_type;
- types[OUTPUT][0] = types[REF_OUTPUT][0] = out_type;
- sizes[TEMP][0] = cvSize(0,0);
-
- inplace = false;
-}
-
-
-int CxCore_DXTBaseTestImpl::write_default_params( CvFileStorage* fs )
-{
- int code = CvArrTest::write_default_params(fs);
- if( code < 0 || ts->get_testing_mode() != CvTS::TIMING_MODE )
- return code;
- write_string_list( fs, "transform_type", transform_type_list );
- return code;
-}
-
-
-void CxCore_DXTBaseTestImpl::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- sprintf( ptr, "%s,", cvReadString( find_timing_param("transform_type"), "" ) );
- ptr += strlen(ptr);
- params_left--;
- CvArrTest::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-
-double CxCore_DXTBaseTestImpl::get_success_error_level( int test_case_idx, int i, int j )
-{
- return CvArrTest::get_success_error_level( test_case_idx, i, j );
-}
-
-
-int CxCore_DXTBaseTestImpl::prepare_test_case( int test_case_idx )
-{
- int code = CvArrTest::prepare_test_case( test_case_idx );
- if( code > 0 && ts->get_testing_mode() == CvTS::CORRECTNESS_CHECK_MODE )
- {
- int in_type = CV_MAT_TYPE(test_mat[INPUT][0].type);
- int out_type = CV_MAT_TYPE(test_mat[OUTPUT][0].type);
-
- if( CV_MAT_CN(in_type) == 2 && CV_MAT_CN(out_type) == 1 )
- cvTsFixCCS( &test_mat[INPUT][0], test_mat[OUTPUT][0].cols, flags );
-
- if( inplace )
- cvTsCopy( &test_mat[INPUT][test_case_idx & (int)spectrum_mode],
- temp_dst ? &test_mat[TEMP][1] :
- in_type == out_type ? &test_mat[OUTPUT][0] :
- &test_mat[TEMP][0] );
- }
-
- return code;
-}
-
-CxCore_DXTBaseTestImpl dxt_test( "dxt", "" );
-
-
-class CxCore_DXTBaseTest : public CxCore_DXTBaseTestImpl
-{
-public:
- CxCore_DXTBaseTest( const char* test_name, const char* test_funcs,
- bool _allow_complex=false, bool _allow_odd=false,
- bool _spectrum_mode=false );
-};
-
-CxCore_DXTBaseTest::CxCore_DXTBaseTest( const char* test_name, const char* test_funcs,
- bool _allow_complex, bool _allow_odd, bool _spectrum_mode )
- : CxCore_DXTBaseTestImpl( test_name, test_funcs, _allow_complex, _allow_odd, _spectrum_mode )
-{
- size_list = 0;
- depth_list = 0;
- default_timing_param_names = dxt_param_names;
- transform_type_list = dft_transforms;
-}
-
-
-////////////////////// FFT ////////////////////////
-class CxCore_DFTTest : public CxCore_DXTBaseTest
-{
-public:
- CxCore_DFTTest();
-protected:
- void run_func();
- void prepare_to_validation( int test_case_idx );
-};
-
-
-CxCore_DFTTest::CxCore_DFTTest() : CxCore_DXTBaseTest( "dxt-dft", "cvDFT", true, true, false )
-{
-}
-
-
-void CxCore_DFTTest::run_func()
-{
- CvArr* dst = temp_dst ? test_array[TEMP][1] : test_array[OUTPUT][0];
- CvArr* src = inplace ? dst : test_array[INPUT][0];
-
- if(!(flags & CV_DXT_INVERSE))
- cvDFT( src, dst, flags );
- else
- {
- cv::Mat _src = cv::cvarrToMat(src), _dst = cv::cvarrToMat(dst);
- idft(_src, _dst, flags & ~CV_DXT_INVERSE);
- }
-}
-
-
-void CxCore_DFTTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- CvMat* src = &test_mat[INPUT][0];
- CvMat* dst = &test_mat[REF_OUTPUT][0];
- CvMat* tmp_src = src;
- CvMat* tmp_dst = dst;
- int src_cn = CV_MAT_CN( src->type );
- int dst_cn = CV_MAT_CN( dst->type );
-
- if( src_cn != 2 || dst_cn != 2 )
- {
- tmp_src = &test_mat[TEMP][0];
-
- if( !(flags & CV_DXT_INVERSE ) )
- {
- CvMat* cvdft_dst = &test_mat[TEMP][1];
- cvTsConvertFromCCS( cvdft_dst, cvdft_dst,
- &test_mat[OUTPUT][0], flags );
- cvTsZero( tmp_src );
- cvTsInsert( src, tmp_src, 0 );
- }
- else
- {
- cvTsConvertFromCCS( src, src, tmp_src, flags );
- tmp_dst = &test_mat[TEMP][1];
- }
- }
-
- if( src->rows == 1 || (src->cols == 1 && !(flags & CV_DXT_ROWS)) )
- cvTsDFT_1D( tmp_src, tmp_dst, flags );
- else
- cvTsDFT_2D( tmp_src, tmp_dst, flags );
-
- if( tmp_dst != dst )
- cvTsExtract( tmp_dst, dst, 0 );
-}
-
-
-CxCore_DFTTest dft_test;
-
-
-////////////////////// DCT ////////////////////////
-class CxCore_DCTTest : public CxCore_DXTBaseTest
-{
-public:
- CxCore_DCTTest();
-protected:
- void run_func();
- void prepare_to_validation( int test_case_idx );
-};
-
-
-CxCore_DCTTest::CxCore_DCTTest() : CxCore_DXTBaseTest( "dxt-dct", "cvDCT", false, false, false )
-{
- transform_type_list = dct_transforms;
-}
-
-
-void CxCore_DCTTest::run_func()
-{
- CvArr* dst = test_array[OUTPUT][0];
- CvArr* src = inplace ? dst : test_array[INPUT][0];
-
- if(!(flags & CV_DXT_INVERSE))
- cvDCT( src, dst, flags );
- else
- {
- cv::Mat _src = cv::cvarrToMat(src), _dst = cv::cvarrToMat(dst);
- idct(_src, _dst, flags & ~CV_DXT_INVERSE);
- }
-}
-
-
-void CxCore_DCTTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- CvMat* src = &test_mat[INPUT][0];
- CvMat* dst = &test_mat[REF_OUTPUT][0];
-
- if( src->rows == 1 || (src->cols == 1 && !(flags & CV_DXT_ROWS)) )
- cvTsDCT_1D( src, dst, flags );
- else
- cvTsDCT_2D( src, dst, flags );
-}
-
-
-CxCore_DCTTest dct_test;
-
-
-////////////////////// MulSpectrums ////////////////////////
-class CxCore_MulSpectrumsTest : public CxCore_DXTBaseTest
-{
-public:
- CxCore_MulSpectrumsTest();
-protected:
- void run_func();
- void prepare_to_validation( int test_case_idx );
-};
-
-
-CxCore_MulSpectrumsTest::CxCore_MulSpectrumsTest() :
- CxCore_DXTBaseTest( "dxt-mulspectrums", "cvMulSpectrums", true, true, true )
-{
- transform_type_list = mulsp_transforms;
-}
-
-
-void CxCore_MulSpectrumsTest::run_func()
-{
- CvArr* dst = test_array[TEMP].size() > 0 && test_array[TEMP][0] ?
- test_array[TEMP][0] : test_array[OUTPUT][0];
- CvArr *src1 = test_array[INPUT][0], *src2 = test_array[INPUT][1];
-
- if( inplace )
- {
- if( ts->get_current_test_info()->test_case_idx & 1 )
- src2 = dst;
- else
- src1 = dst;
- }
-
- cvMulSpectrums( src1, src2, dst, flags );
-}
-
-
-static void cvTsMulComplex( const CvMat* A, const CvMat* B, CvMat* C, int flags )
-{
- int i, j, depth = CV_MAT_DEPTH(A->type), cols = A->cols*2;
-
- assert( CV_ARE_SIZES_EQ(A,B) && CV_ARE_SIZES_EQ(B,C) &&
- CV_ARE_TYPES_EQ(A,B) && CV_ARE_TYPES_EQ(B,C) &&
- CV_MAT_CN(A->type) == 2 && CV_MAT_DEPTH(A->type) >= CV_32F );
-
- for( i = 0; i < C->rows; i++ )
- {
- if( depth == CV_32F )
- {
- const float* a = (float*)(A->data.ptr + A->step*i);
- const float* b = (float*)(B->data.ptr + B->step*i);
- float* c = (float*)(C->data.ptr + C->step*i);
-
- if( !(flags & CV_DXT_MUL_CONJ) )
- for( j = 0; j < cols; j += 2 )
- {
- double re = (double)a[j]*b[j] - (double)a[j+1]*b[j+1];
- double im = (double)a[j+1]*b[j] + (double)a[j]*b[j+1];
-
- c[j] = (float)re;
- c[j+1] = (float)im;
- }
- else
- for( j = 0; j < cols; j += 2 )
- {
- double re = (double)a[j]*b[j] + (double)a[j+1]*b[j+1];
- double im = (double)a[j+1]*b[j] - (double)a[j]*b[j+1];
-
- c[j] = (float)re;
- c[j+1] = (float)im;
- }
- }
- else
- {
- const double* a = (double*)(A->data.ptr + A->step*i);
- const double* b = (double*)(B->data.ptr + B->step*i);
- double* c = (double*)(C->data.ptr + C->step*i);
-
- if( !(flags & CV_DXT_MUL_CONJ) )
- for( j = 0; j < cols; j += 2 )
- {
- double re = a[j]*b[j] - a[j+1]*b[j+1];
- double im = a[j+1]*b[j] + a[j]*b[j+1];
-
- c[j] = re;
- c[j+1] = im;
- }
- else
- for( j = 0; j < cols; j += 2 )
- {
- double re = a[j]*b[j] + a[j+1]*b[j+1];
- double im = a[j+1]*b[j] - a[j]*b[j+1];
-
- c[j] = re;
- c[j+1] = im;
- }
- }
- }
-}
-
-
-void CxCore_MulSpectrumsTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- CvMat* src1 = &test_mat[INPUT][0];
- CvMat* src2 = &test_mat[INPUT][1];
- CvMat* dst = &test_mat[OUTPUT][0];
- CvMat* dst0 = &test_mat[REF_OUTPUT][0];
- CvMat* temp = test_array[TEMP].size() > 0 && test_array[TEMP][0] ? &test_mat[TEMP][0] : 0;
- int cn = CV_MAT_CN(src1->type);
-
- if( cn == 1 )
- {
- cvTsConvertFromCCS( src1, src1, dst, flags );
- cvTsConvertFromCCS( src2, src2, dst0, flags );
- src1 = dst;
- src2 = dst0;
- }
-
- cvTsMulComplex( src1, src2, dst0, flags );
- if( cn == 1 )
- {
- assert( temp != 0 );
- cvTsConvertFromCCS( temp, temp, dst, flags );
- }
-}
-
-
-CxCore_MulSpectrumsTest mulspectrums_test;
-
-
-/* End of file. */
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cxcoretest.h"
-#include <stdio.h>
-
-using namespace cv;
-
-class CV_IOTest : public CvTest
-{
-public:
- CV_IOTest();
-protected:
- void run(int);
-};
-
-
-CV_IOTest::CV_IOTest():
-CvTest( "io", "cvOpenFileStorage, cvReleaseFileStorage, cvRead*, cvWrite*, cvStartWriteStruct, cvEndWriteStruct" )
-{
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;
-}
-
-
-static SparseMat cvTsGetRandomSparseMat(int dims, const int* sz, int type,
- int nzcount, double a, double b, CvRNG* rng)
-{
- SparseMat m(dims, sz, type);
- int i, j;
- CV_Assert(CV_MAT_CN(type) == 1);
- for( i = 0; i < nzcount; i++ )
- {
- int idx[CV_MAX_DIM];
- for( j = 0; j < dims; j++ )
- idx[j] = cvTsRandInt(rng) % sz[j];
- double val = cvTsRandReal(rng)*(b - a) + a;
- uchar* ptr = m.ptr(idx, true, 0);
- if( type == CV_8U )
- *(uchar*)ptr = saturate_cast<uchar>(val);
- else if( type == CV_8S )
- *(schar*)ptr = saturate_cast<schar>(val);
- else if( type == CV_16U )
- *(ushort*)ptr = saturate_cast<ushort>(val);
- else if( type == CV_16S )
- *(short*)ptr = saturate_cast<short>(val);
- else if( type == CV_32S )
- *(int*)ptr = saturate_cast<int>(val);
- else if( type == CV_32F )
- *(float*)ptr = saturate_cast<float>(val);
- else
- *(double*)ptr = saturate_cast<double>(val);
- }
-
- return m;
-}
-
-static bool cvTsCheckSparse(const CvSparseMat* m1, const CvSparseMat* m2, double eps)
-{
- CvSparseMatIterator it1;
- CvSparseNode* node1;
- int depth = CV_MAT_DEPTH(m1->type);
-
- if( m1->heap->active_count != m2->heap->active_count ||
- m1->dims != m2->dims || CV_MAT_TYPE(m1->type) != CV_MAT_TYPE(m2->type) )
- return false;
-
- for( node1 = cvInitSparseMatIterator( m1, &it1 );
- node1 != 0; node1 = cvGetNextSparseNode( &it1 ))
- {
- uchar* v1 = (uchar*)CV_NODE_VAL(m1,node1);
- uchar* v2 = cvPtrND( m2, CV_NODE_IDX(m1,node1), 0, 0, &node1->hashval );
- if( !v2 )
- return false;
- if( depth == CV_8U || depth == CV_8S )
- {
- if( *v1 != *v2 )
- return false;
- }
- else if( depth == CV_16U || depth == CV_16S )
- {
- if( *(ushort*)v1 != *(ushort*)v2 )
- return false;
- }
- else if( depth == CV_32S )
- {
- if( *(int*)v1 != *(int*)v2 )
- return false;
- }
- else if( depth == CV_32F )
- {
- if( fabs(*(float*)v1 - *(float*)v2) > eps*(fabs(*(float*)v2) + 1) )
- return false;
- }
- else if( fabs(*(double*)v1 - *(double*)v2) > eps*(fabs(*(double*)v2) + 1) )
- return false;
- }
-
- return true;
-}
-
-void CV_IOTest::run( int )
-{
- double ranges[][2] = {{0, 256}, {-128, 128}, {0, 65536}, {-32768, 32768},
- {-1000000, 1000000}, {-10, 10}, {-10, 10}};
- CvRNG* rng = ts->get_rng();
- RNG rng0;
- test_case_count = 2;
- int progress = 0;
- MemStorage storage(cvCreateMemStorage(0));
-
- for( int idx = 0; idx < test_case_count; idx++ )
- {
- ts->update_context( this, idx, false );
- progress = update_progress( progress, idx, test_case_count, 0 );
-
- cvClearMemStorage(storage);
-
- char buf[L_tmpnam+16];
- char* filename = tmpnam(buf);
- strcat(filename, idx % 2 ? ".yml" : ".xml");
- if(filename[0] == '\\')
- filename++;
-
- FileStorage fs(filename, FileStorage::WRITE);
-
- int test_int = (int)cvTsRandInt(rng);
- double test_real = (cvTsRandInt(rng)%2?1:-1)*exp(cvTsRandReal(rng)*18-9);
- string test_string = "vw wv23424rt\"&<>&'@#$@$%$%&%IJUKYILFD@#$@%$&*&() ";
-
- int depth = cvTsRandInt(rng) % (CV_64F+1);
- int cn = cvTsRandInt(rng) % 4 + 1;
- Mat test_mat(cvTsRandInt(rng)%30+1, cvTsRandInt(rng)%30+1, CV_MAKETYPE(depth, cn));
-
- rng0.fill(test_mat, CV_RAND_UNI, Scalar::all(ranges[depth][0]), Scalar::all(ranges[depth][1]));
- if( depth >= CV_32F )
- {
- exp(test_mat, test_mat);
- Mat test_mat_scale(test_mat.size(), test_mat.type());
- rng0.fill(test_mat_scale, CV_RAND_UNI, Scalar::all(-1), Scalar::all(1));
- multiply(test_mat, test_mat_scale, test_mat);
- }
-
- CvSeq* seq = cvCreateSeq(test_mat.type(), (int)sizeof(CvSeq),
- (int)test_mat.elemSize(), storage);
- cvSeqPushMulti(seq, test_mat.data, test_mat.cols*test_mat.rows);
-
- CvGraph* graph = cvCreateGraph( CV_ORIENTED_GRAPH,
- sizeof(CvGraph), sizeof(CvGraphVtx),
- sizeof(CvGraphEdge), storage );
- int edges[][2] = {{0,1},{1,2},{2,0},{0,3},{3,4},{4,1}};
- int i, vcount = 5, ecount = 6;
- for( i = 0; i < vcount; i++ )
- cvGraphAddVtx(graph);
- for( i = 0; i < ecount; i++ )
- {
- CvGraphEdge* edge;
- cvGraphAddEdge(graph, edges[i][0], edges[i][1], 0, &edge);
- edge->weight = (float)(i+1);
- }
-
- depth = cvTsRandInt(rng) % (CV_64F+1);
- cn = cvTsRandInt(rng) % 4 + 1;
- int sz[] = {cvTsRandInt(rng)%10+1, cvTsRandInt(rng)%10+1, cvTsRandInt(rng)%10+1};
- MatND test_mat_nd(3, sz, CV_MAKETYPE(depth, cn));
-
- rng0.fill(test_mat_nd, CV_RAND_UNI, Scalar::all(ranges[depth][0]), Scalar::all(ranges[depth][1]));
- if( depth >= CV_32F )
- {
- exp(test_mat_nd, test_mat_nd);
- MatND test_mat_scale(test_mat_nd.dims, test_mat_nd.size, test_mat_nd.type());
- rng0.fill(test_mat_scale, CV_RAND_UNI, Scalar::all(-1), Scalar::all(1));
- multiply(test_mat_nd, test_mat_scale, test_mat_nd);
- }
-
- int ssz[] = {cvTsRandInt(rng)%10+1, cvTsRandInt(rng)%10+1,
- cvTsRandInt(rng)%10+1,cvTsRandInt(rng)%10+1};
- SparseMat test_sparse_mat = cvTsGetRandomSparseMat(4, ssz, cvTsRandInt(rng)%(CV_64F+1),
- cvTsRandInt(rng) % 10000, 0, 100, rng);
-
- fs << "test_int" << test_int << "test_real" << test_real << "test_string" << test_string;
- fs << "test_mat" << test_mat;
- fs << "test_mat_nd" << test_mat_nd;
- fs << "test_sparse_mat" << test_sparse_mat;
-
- fs << "test_list" << "[" << 0.0000000000001 << 2 << CV_PI << -3435345 << "2-502 2-029 3egegeg" <<
- "{:" << "month" << 12 << "day" << 31 << "year" << 1969 << "}" << "]";
- fs << "test_map" << "{" << "x" << 1 << "y" << 2 << "width" << 100 << "height" << 200 << "lbp" << "[:";
-
- const uchar arr[] = {0, 1, 1, 0, 1, 1, 0, 1};
- fs.writeRaw("u", arr, (int)(sizeof(arr)/sizeof(arr[0])));
-
- fs << "]" << "}";
- cvWriteComment(*fs, "test comment", 0);
-
- fs.writeObj("test_seq", seq);
- fs.writeObj("test_graph",graph);
- CvGraph* graph2 = (CvGraph*)cvClone(graph);
-
- fs.release();
-
- if(!fs.open(filename, FileStorage::READ))
- {
- ts->printf( CvTS::LOG, "filename %s can not be read\n", filename );
- ts->set_failed_test_info( CvTS::FAIL_MISSING_TEST_DATA );
- return;
- }
-
- int real_int = (int)fs["test_int"];
- double real_real = (double)fs["test_real"];
- string real_string = (string)fs["test_string"];
-
- if( real_int != test_int ||
- fabs(real_real - test_real) > DBL_EPSILON*(fabs(test_real)+1) ||
- real_string != test_string )
- {
- ts->printf( CvTS::LOG, "the read scalars are not correct\n" );
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- return;
- }
-
- CvMat* m = (CvMat*)fs["test_mat"].readObj();
- CvMat _test_mat = test_mat;
- double max_diff = 0;
- CvMat stub1, _test_stub1;
- cvReshape(m, &stub1, 1, 0);
- cvReshape(&_test_mat, &_test_stub1, 1, 0);
- CvPoint pt = {0,0};
-
- if( !m || !CV_IS_MAT(m) || m->rows != test_mat.rows || m->cols != test_mat.cols ||
- cvTsCmpEps( &stub1, &_test_stub1, &max_diff, 0, &pt, true) < 0 )
- {
- ts->printf( CvTS::LOG, "the read matrix is not correct: (%.20g vs %.20g) at (%d,%d)\n",
- cvGetReal2D(&stub1, pt.y, pt.x), cvGetReal2D(&_test_stub1, pt.y, pt.x),
- pt.y, pt.x );
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- return;
- }
- if( m && CV_IS_MAT(m))
- cvReleaseMat(&m);
-
- CvMatND* m_nd = (CvMatND*)fs["test_mat_nd"].readObj();
- CvMatND _test_mat_nd = test_mat_nd;
-
- if( !m_nd || !CV_IS_MATND(m_nd) )
- {
- ts->printf( CvTS::LOG, "the read nd-matrix is not correct\n" );
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- return;
- }
-
- CvMat stub, _test_stub;
- cvGetMat(m_nd, &stub, 0, 1);
- cvGetMat(&_test_mat_nd, &_test_stub, 0, 1);
- cvReshape(&stub, &stub1, 1, 0);
- cvReshape(&_test_stub, &_test_stub1, 1, 0);
-
- if( !CV_ARE_TYPES_EQ(&stub, &_test_stub) ||
- !CV_ARE_SIZES_EQ(&stub, &_test_stub) ||
- //cvNorm(&stub, &_test_stub, CV_L2) != 0 )
- cvTsCmpEps( &stub1, &_test_stub1, &max_diff, 0, &pt, true) < 0 )
- {
- ts->printf( CvTS::LOG, "readObj method: the read nd matrix is not correct: (%.20g vs %.20g) vs at (%d,%d)\n",
- cvGetReal2D(&stub1, pt.y, pt.x), cvGetReal2D(&_test_stub1, pt.y, pt.x),
- pt.y, pt.x );
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- return;
- }
-
- MatND mat_nd2;
- fs["test_mat_nd"] >> mat_nd2;
- CvMatND m_nd2 = mat_nd2;
- cvGetMat(&m_nd2, &stub, 0, 1);
- cvReshape(&stub, &stub1, 1, 0);
-
- if( !CV_ARE_TYPES_EQ(&stub, &_test_stub) ||
- !CV_ARE_SIZES_EQ(&stub, &_test_stub) ||
- //cvNorm(&stub, &_test_stub, CV_L2) != 0 )
- cvTsCmpEps( &stub1, &_test_stub1, &max_diff, 0, &pt, true) < 0 )
- {
- ts->printf( CvTS::LOG, "C++ method: the read nd matrix is not correct: (%.20g vs %.20g) vs at (%d,%d)\n",
- cvGetReal2D(&stub1, pt.y, pt.x), cvGetReal2D(&_test_stub1, pt.y, pt.x),
- pt.y, pt.x );
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- return;
- }
-
- cvRelease((void**)&m_nd);
-
- Ptr<CvSparseMat> m_s = (CvSparseMat*)fs["test_sparse_mat"].readObj();
- Ptr<CvSparseMat> _test_sparse_ = (CvSparseMat*)test_sparse_mat;
- Ptr<CvSparseMat> _test_sparse = (CvSparseMat*)cvClone(_test_sparse_);
- SparseMat m_s2;
- fs["test_sparse_mat"] >> m_s2;
- Ptr<CvSparseMat> _m_s2 = (CvSparseMat*)m_s2;
-
- if( !m_s || !CV_IS_SPARSE_MAT(m_s) ||
- !cvTsCheckSparse(m_s, _test_sparse,0) ||
- !cvTsCheckSparse(_m_s2, _test_sparse,0))
- {
- ts->printf( CvTS::LOG, "the read sparse matrix is not correct\n" );
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- return;
- }
-
- FileNode tl = fs["test_list"];
- if( tl.type() != FileNode::SEQ || tl.size() != 6 ||
- fabs((double)tl[0] - 0.0000000000001) >= DBL_EPSILON ||
- (int)tl[1] != 2 ||
- fabs((double)tl[2] - CV_PI) >= DBL_EPSILON ||
- (int)tl[3] != -3435345 ||
- (string)tl[4] != "2-502 2-029 3egegeg" ||
- tl[5].type() != FileNode::MAP || tl[5].size() != 3 ||
- (int)tl[5]["month"] != 12 ||
- (int)tl[5]["day"] != 31 ||
- (int)tl[5]["year"] != 1969 )
- {
- ts->printf( CvTS::LOG, "the test list is incorrect\n" );
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- return;
- }
-
- FileNode tm = fs["test_map"];
- FileNode tm_lbp = tm["lbp"];
-
- int real_x = (int)tm["x"];
- int real_y = (int)tm["y"];
- int real_width = (int)tm["width"];
- int real_height = (int)tm["height"];
-
-
- int real_lbp_val = 0;
- FileNodeIterator it;
- it = tm_lbp.begin();
- real_lbp_val |= (int)*it << 0;
- ++it;
- real_lbp_val |= (int)*it << 1;
- it++;
- real_lbp_val |= (int)*it << 2;
- it += 1;
- real_lbp_val |= (int)*it << 3;
- FileNodeIterator it2(it);
- it2 += 4;
- real_lbp_val |= (int)*it2 << 7;
- --it2;
- real_lbp_val |= (int)*it2 << 6;
- it2--;
- real_lbp_val |= (int)*it2 << 5;
- it2 -= 1;
- real_lbp_val |= (int)*it2 << 4;
- it2 += -1;
- CV_Assert( it == it2 );
-
- if( tm.type() != FileNode::MAP || tm.size() != 5 ||
- real_x != 1 ||
- real_y != 2 ||
- real_width != 100 ||
- real_height != 200 ||
- tm_lbp.type() != FileNode::SEQ ||
- tm_lbp.size() != 8 ||
- real_lbp_val != 0xb6 )
- {
- ts->printf( CvTS::LOG, "the test map is incorrect\n" );
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- return;
- }
-
- CvGraph* graph3 = (CvGraph*)fs["test_graph"].readObj();
- if(graph2->active_count != vcount || graph3->active_count != vcount ||
- graph2->edges->active_count != ecount || graph3->edges->active_count != ecount)
- {
- ts->printf( CvTS::LOG, "the cloned or read graph have wrong number of vertices or edges\n" );
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- return;
- }
-
- for( i = 0; i < ecount; i++ )
- {
- CvGraphEdge* edge2 = cvFindGraphEdge(graph2, edges[i][0], edges[i][1]);
- CvGraphEdge* edge3 = cvFindGraphEdge(graph3, edges[i][0], edges[i][1]);
- if( !edge2 || edge2->weight != (float)(i+1) ||
- !edge3 || edge3->weight != (float)(i+1) )
- {
- ts->printf( CvTS::LOG, "the cloned or read graph do not have the edge (%d, %d)\n", edges[i][0], edges[i][1] );
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- return;
- }
- }
-
- fs.release();
- remove(filename);
- }
-}
-
-CV_IOTest opencv_io_test;
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-//////////////////////////////////////////////////////////////////////////////////////////
-/////////////////// tests for matrix operations and math functions ///////////////////////
-//////////////////////////////////////////////////////////////////////////////////////////
-
-#include "cxcoretest.h"
-#include <float.h>
-#include <math.h>
-
-/// !!! NOTE !!! These tests happily avoid overflow cases & out-of-range arguments
-/// so that output arrays contain neigher Inf's nor Nan's.
-/// Handling such cases would require special modification of check function
-/// (validate_test_results) => TBD.
-/// Also, need some logarithmic-scale generation of input data. Right now it is done (in some tests)
-/// by generating min/max boundaries for random data in logarimithic scale, but
-/// within the same test case all the input array elements are of the same order.
-
-static const CvSize math_sizes[] = {{10,1}, {100,1}, {10000,1}, {-1,-1}};
-static const int math_depths[] = { CV_32F, CV_64F, -1 };
-static const char* math_param_names[] = { "size", "depth", 0 };
-
-static const CvSize matrix_sizes[] = {{3,3}, {4,4}, {10,10}, {30,30}, {100,100}, {500,500}, {-1,-1}};
-
-class CxCore_MathTestImpl : public CvArrTest
-{
-public:
- CxCore_MathTestImpl( const char* test_name, const char* test_funcs );
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- double get_success_error_level( int /*test_case_idx*/, int i, int j );
- bool test_nd;
-};
-
-
-CxCore_MathTestImpl::CxCore_MathTestImpl( const char* test_name, const char* test_funcs )
- : CvArrTest( test_name, test_funcs, "" )
-{
- optional_mask = false;
-
- test_array[INPUT].push(NULL);
- test_array[OUTPUT].push(NULL);
- test_array[REF_OUTPUT].push(NULL);
-
- default_timing_param_names = math_param_names;
-
- size_list = math_sizes;
- whole_size_list = 0;
- depth_list = math_depths;
- cn_list = 0;
- test_nd = false;
-}
-
-
-double CxCore_MathTestImpl::get_success_error_level( int /*test_case_idx*/, int i, int j )
-{
- return CV_MAT_DEPTH(test_mat[i][j].type) == CV_32F ? FLT_EPSILON*128 : DBL_EPSILON*1024;
-}
-
-
-void CxCore_MathTestImpl::get_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- int depth = cvTsRandInt(rng)%2 + CV_32F;
- int cn = cvTsRandInt(rng) % 4 + 1, type = CV_MAKETYPE(depth, cn);
- int i, j;
- CvArrTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
-
- for( i = 0; i < max_arr; i++ )
- {
- int count = test_array[i].size();
- for( j = 0; j < count; j++ )
- types[i][j] = type;
- }
- test_nd = cvTsRandInt(rng)%3 == 0;
-}
-
-CxCore_MathTestImpl math_test( "math", "" );
-
-
-class CxCore_MathTest : public CxCore_MathTestImpl
-{
-public:
- CxCore_MathTest( const char* test_name, const char* test_funcs );
-};
-
-
-CxCore_MathTest::CxCore_MathTest( const char* test_name, const char* test_funcs )
- : CxCore_MathTestImpl( test_name, test_funcs )
-{
- size_list = 0;
- depth_list = 0;
-}
-
-
-////////// exp /////////////
-class CxCore_ExpTest : public CxCore_MathTest
-{
-public:
- CxCore_ExpTest();
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void get_minmax_bounds( int i, int j, int type, CvScalar* low, CvScalar* high );
- double get_success_error_level( int /*test_case_idx*/, int i, int j );
- int prepare_test_case( int test_case );
- void run_func();
- void prepare_to_validation( int test_case_idx );
- int out_type;
-};
-
-
-CxCore_ExpTest::CxCore_ExpTest()
- : CxCore_MathTest( "math-exp", "cvExp" )
-{
- out_type = 0;
-}
-
-
-double CxCore_ExpTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- int in_depth = CV_MAT_DEPTH(test_mat[INPUT][0].type);
- int out_depth = CV_MAT_DEPTH(test_mat[OUTPUT][0].type);
- int min_depth = MIN(in_depth, out_depth);
- return min_depth == CV_32F ? 1e-5 : 1e-8;
-}
-
-
-void CxCore_ExpTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CxCore_MathTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- out_type = types[OUTPUT][0];
- /*if( CV_MAT_DEPTH(types[INPUT][0]) == CV_32F && (cvRandInt(ts->get_rng()) & 3) == 0 )
- types[OUTPUT][0] = types[REF_OUTPUT][0] =
- out_type = (types[INPUT][0] & ~CV_MAT_DEPTH_MASK)|CV_64F;*/
-}
-
-void CxCore_ExpTest::get_minmax_bounds( int /*i*/, int /*j*/, int /*type*/, CvScalar* low, CvScalar* high )
-{
- double l = cvTsRandReal(ts->get_rng())*10+1;
- double u = cvTsRandReal(ts->get_rng())*10+1;
- l *= -l;
- u *= u;
- *low = cvScalarAll(l);
- *high = cvScalarAll(CV_MAT_DEPTH(out_type)==CV_64F? u : u*0.5);
-}
-
-int CxCore_ExpTest::prepare_test_case( int test_case )
-{
- int code = CxCore_MathTest::prepare_test_case(test_case);
- if( code < 0 )
- return code;
-
- CvRNG* rng = ts->get_rng();
-
- int i, j, k, count = cvTsRandInt(rng) % 10;
- CvMat* src = &test_mat[INPUT][0];
- int depth = CV_MAT_DEPTH(src->type);
-
- // add some extremal values
- for( k = 0; k < count; k++ )
- {
- i = cvTsRandInt(rng) % src->rows;
- j = cvTsRandInt(rng) % (src->cols*CV_MAT_CN(src->type));
- int sign = cvTsRandInt(rng) % 2 ? 1 : -1;
- if( depth == CV_32F )
- ((float*)(src->data.ptr + src->step*i))[j] = FLT_MAX*sign;
- else
- ((double*)(src->data.ptr + src->step*i))[j] = DBL_MAX*sign;
- }
-
- return code;
-}
-
-
-void CxCore_ExpTest::run_func()
-{
- if(!test_nd)
- cvExp( test_array[INPUT][0], test_array[OUTPUT][0] );
- else
- {
- cv::MatND a = cv::cvarrToMatND(test_array[INPUT][0]);
- cv::MatND b = cv::cvarrToMatND(test_array[OUTPUT][0]);
- cv::exp(a, b);
- }
-}
-
-
-void CxCore_ExpTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- CvMat* a = &test_mat[INPUT][0];
- CvMat* b = &test_mat[REF_OUTPUT][0];
-
- int a_depth = CV_MAT_DEPTH(a->type);
- int b_depth = CV_MAT_DEPTH(b->type);
- int ncols = test_mat[INPUT][0].cols*CV_MAT_CN(a->type);
- int i, j;
-
- for( i = 0; i < a->rows; i++ )
- {
- uchar* a_data = a->data.ptr + i*a->step;
- uchar* b_data = b->data.ptr + i*b->step;
-
- if( a_depth == CV_32F && b_depth == CV_32F )
- {
- for( j = 0; j < ncols; j++ )
- ((float*)b_data)[j] = (float)exp((double)((float*)a_data)[j]);
- }
- else if( a_depth == CV_32F && b_depth == CV_64F )
- {
- for( j = 0; j < ncols; j++ )
- ((double*)b_data)[j] = exp((double)((float*)a_data)[j]);
- }
- else
- {
- assert( a_depth == CV_64F && b_depth == CV_64F );
- for( j = 0; j < ncols; j++ )
- ((double*)b_data)[j] = exp(((double*)a_data)[j]);
- }
- }
-}
-
-CxCore_ExpTest exp_test;
-
-
-////////// log /////////////
-class CxCore_LogTest : public CxCore_MathTest
-{
-public:
- CxCore_LogTest();
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void get_minmax_bounds( int i, int j, int type, CvScalar* low, CvScalar* high );
- void run_func();
- void prepare_to_validation( int test_case_idx );
-};
-
-
-CxCore_LogTest::CxCore_LogTest()
- : CxCore_MathTest( "math-log", "cvLog" )
-{
-}
-
-
-void CxCore_LogTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CxCore_MathTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- /*if( CV_MAT_DEPTH(types[INPUT][0]) == CV_32F && (cvRandInt(ts->get_rng()) & 3) == 0 )
- types[INPUT][0] = (types[INPUT][0] & ~CV_MAT_DEPTH_MASK)|CV_64F;*/
-}
-
-
-void CxCore_LogTest::get_minmax_bounds( int /*i*/, int /*j*/, int /*type*/, CvScalar* low, CvScalar* high )
-{
- double l = cvTsRandReal(ts->get_rng())*15-5;
- double u = cvTsRandReal(ts->get_rng())*15-5;
- double t;
- l = exp(l);
- u = exp(u);
- if( l > u )
- CV_SWAP( l, u, t );
- *low = cvScalarAll(l);
- *high = cvScalarAll(u);
-}
-
-
-void CxCore_LogTest::run_func()
-{
- if(!test_nd)
- cvLog( test_array[INPUT][0], test_array[OUTPUT][0] );
- else
- {
- cv::MatND a = cv::cvarrToMatND(test_array[INPUT][0]);
- cv::MatND b = cv::cvarrToMatND(test_array[OUTPUT][0]);
- cv::log(a, b);
- }
-}
-
-
-void CxCore_LogTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- CvMat* a = &test_mat[INPUT][0];
- CvMat* b = &test_mat[REF_OUTPUT][0];
-
- int a_depth = CV_MAT_DEPTH(a->type);
- int b_depth = CV_MAT_DEPTH(b->type);
- int ncols = test_mat[INPUT][0].cols*CV_MAT_CN(a->type);
- int i, j;
-
- for( i = 0; i < a->rows; i++ )
- {
- uchar* a_data = a->data.ptr + i*a->step;
- uchar* b_data = b->data.ptr + i*b->step;
-
- if( a_depth == CV_32F && b_depth == CV_32F )
- {
- for( j = 0; j < ncols; j++ )
- ((float*)b_data)[j] = (float)log((double)((float*)a_data)[j]);
- }
- else if( a_depth == CV_64F && b_depth == CV_32F )
- {
- for( j = 0; j < ncols; j++ )
- ((float*)b_data)[j] = (float)log(((double*)a_data)[j]);
- }
- else
- {
- assert( a_depth == CV_64F && b_depth == CV_64F );
- for( j = 0; j < ncols; j++ )
- ((double*)b_data)[j] = log(((double*)a_data)[j]);
- }
- }
-}
-
-CxCore_LogTest log_test;
-
-
-////////// pow /////////////
-
-static const double math_pow_values[] = { 2., 5., 0.5, -0.5, 1./3, -1./3, CV_PI };
-static const char* math_pow_param_names[] = { "size", "power", "depth", 0 };
-static const int math_pow_depths[] = { CV_8U, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F, -1 };
-
-class CxCore_PowTest : public CxCore_MathTest
-{
-public:
- CxCore_PowTest();
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void get_minmax_bounds( int i, int j, int type, CvScalar* low, CvScalar* high );
- void get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types,
- CvSize** whole_sizes, bool* are_images );
- int write_default_params( CvFileStorage* fs );
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
- void run_func();
- int prepare_test_case( int test_case_idx );
- void prepare_to_validation( int test_case_idx );
- double get_success_error_level( int test_case_idx, int i, int j );
- double power;
-};
-
-
-CxCore_PowTest::CxCore_PowTest()
- : CxCore_MathTest( "math-pow", "cvPow" )
-{
- power = 0;
- default_timing_param_names = math_pow_param_names;
- depth_list = math_pow_depths;
-}
-
-
-void CxCore_PowTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- int depth = cvTsRandInt(rng) % (CV_64F+1);
- int cn = cvTsRandInt(rng) % 4 + 1;
- int i, j;
- CvArrTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- depth += depth == CV_8S;
-
- if( depth < CV_32F || cvTsRandInt(rng)%8 == 0 )
- // integer power
- power = (int)(cvTsRandInt(rng)%21 - 10);
- else
- {
- i = cvTsRandInt(rng)%17;
- power = i == 16 ? 1./3 : i == 15 ? 0.5 : i == 14 ? -0.5 : cvTsRandReal(rng)*10 - 5;
- }
-
- for( i = 0; i < max_arr; i++ )
- {
- int count = test_array[i].size();
- int type = CV_MAKETYPE(depth, cn);
- for( j = 0; j < count; j++ )
- types[i][j] = type;
- }
- test_nd = cvTsRandInt(rng)%3 == 0;
-}
-
-
-void CxCore_PowTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types,
- CvSize** whole_sizes, bool* are_images )
-{
- CxCore_MathTest::get_timing_test_array_types_and_sizes( test_case_idx,
- sizes, types, whole_sizes, are_images );
- power = cvReadReal( find_timing_param( "power" ), 0.2 );
-}
-
-
-int CxCore_PowTest::write_default_params( CvFileStorage* fs )
-{
- int i, code = CxCore_MathTest::write_default_params(fs);
- if( code < 0 || ts->get_testing_mode() != CvTS::TIMING_MODE )
- return code;
- start_write_param( fs );
- cvStartWriteStruct( fs, "power", CV_NODE_SEQ + CV_NODE_FLOW );
- for( i = 0; i < CV_DIM(math_pow_values); i++ )
- cvWriteReal( fs, 0, math_pow_values[i] );
- cvEndWriteStruct(fs);
- return code;
-}
-
-
-int CxCore_PowTest::prepare_test_case( int test_case_idx )
-{
- int code = CxCore_MathTest::prepare_test_case( test_case_idx );
- if( code > 0 && ts->get_testing_mode() == CvTS::TIMING_MODE )
- {
- if( cvRound(power) != power && CV_MAT_DEPTH(test_mat[INPUT][0].type) < CV_32F )
- return 0;
- }
- return code;
-}
-
-
-void CxCore_PowTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- sprintf( ptr, "%g,", power );
- ptr += strlen(ptr);
- params_left--;
- CxCore_MathTest::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-
-double CxCore_PowTest::get_success_error_level( int test_case_idx, int i, int j )
-{
- int type = cvGetElemType( test_array[i][j] );
- if( CV_MAT_DEPTH(type) < CV_32F )
- return power == cvRound(power) && power >= 0 ? 0 : 1;
- else
- return CxCore_MathTest::get_success_error_level( test_case_idx, i, j );
-}
-
-
-void CxCore_PowTest::get_minmax_bounds( int /*i*/, int /*j*/, int type, CvScalar* low, CvScalar* high )
-{
- double l, u = cvTsRandInt(ts->get_rng())%1000 + 1;
- if( power > 0 )
- {
- double mval = cvTsMaxVal(type);
- double u1 = pow(mval,1./power)*2;
- u = MIN(u,u1);
- }
-
- l = power == cvRound(power) ? -u : FLT_EPSILON;
- *low = cvScalarAll(l);
- *high = cvScalarAll(u);
-}
-
-
-void CxCore_PowTest::run_func()
-{
- if(!test_nd)
- {
- if( fabs(power-1./3) <= DBL_EPSILON && CV_MAT_DEPTH(test_mat[INPUT][0].type) == CV_32F )
- {
- cv::Mat a(&test_mat[INPUT][0]), b(&test_mat[OUTPUT][0]);
-
- a = a.reshape(1);
- b = b.reshape(1);
- for( int i = 0; i < a.rows; i++ )
- {
- b.at<float>(i,0) = (float)fabs(cvCbrt(a.at<float>(i,0)));
- for( int j = 1; j < a.cols; j++ )
- b.at<float>(i,j) = (float)fabs(cv::cubeRoot(a.at<float>(i,j)));
- }
- }
- else
- cvPow( test_array[INPUT][0], test_array[OUTPUT][0], power );
- }
- else
- {
- cv::MatND a = cv::cvarrToMatND(test_array[INPUT][0]);
- cv::MatND b = cv::cvarrToMatND(test_array[OUTPUT][0]);
- if(power == 0.5)
- cv::sqrt(a, b);
- else
- cv::pow(a, power, b);
- }
-}
-
-
-inline static int ipow( int a, int power )
-{
- int b = 1;
- while( power > 0 )
- {
- if( power&1 )
- b *= a, power--;
- else
- a *= a, power >>= 1;
- }
- return b;
-}
-
-
-inline static double ipow( double a, int power )
-{
- double b = 1.;
- while( power > 0 )
- {
- if( power&1 )
- b *= a, power--;
- else
- a *= a, power >>= 1;
- }
- return b;
-}
-
-
-void CxCore_PowTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- CvMat* a = &test_mat[INPUT][0];
- CvMat* b = &test_mat[REF_OUTPUT][0];
-
- int depth = CV_MAT_DEPTH(a->type);
- int ncols = test_mat[INPUT][0].cols*CV_MAT_CN(a->type);
- int ipower = cvRound(power), apower = abs(ipower);
- int i, j;
-
- for( i = 0; i < a->rows; i++ )
- {
- uchar* a_data = a->data.ptr + i*a->step;
- uchar* b_data = b->data.ptr + i*b->step;
-
- switch( depth )
- {
- case CV_8U:
- if( ipower < 0 )
- for( j = 0; j < ncols; j++ )
- {
- int val = ((uchar*)a_data)[j];
- ((uchar*)b_data)[j] = (uchar)(val <= 1 ? val :
- val == 2 && ipower == -1 ? 1 : 0);
- }
- else
- for( j = 0; j < ncols; j++ )
- {
- int val = ((uchar*)a_data)[j];
- val = ipow( val, ipower );
- ((uchar*)b_data)[j] = CV_CAST_8U(val);
- }
- break;
- case CV_8S:
- if( ipower < 0 )
- for( j = 0; j < ncols; j++ )
- {
- int val = ((char*)a_data)[j];
- ((char*)b_data)[j] = (char)((val&~1)==0 ? val :
- val ==-1 ? 1-2*(ipower&1) :
- val == 2 && ipower == -1 ? 1 : 0);
- }
- else
- for( j = 0; j < ncols; j++ )
- {
- int val = ((char*)a_data)[j];
- val = ipow( val, ipower );
- ((char*)b_data)[j] = CV_CAST_8S(val);
- }
- break;
- case CV_16U:
- if( ipower < 0 )
- for( j = 0; j < ncols; j++ )
- {
- int val = ((ushort*)a_data)[j];
- ((ushort*)b_data)[j] = (ushort)((val&~1)==0 ? val :
- val ==-1 ? 1-2*(ipower&1) :
- val == 2 && ipower == -1 ? 1 : 0);
- }
- else
- for( j = 0; j < ncols; j++ )
- {
- int val = ((ushort*)a_data)[j];
- val = ipow( val, ipower );
- ((ushort*)b_data)[j] = CV_CAST_16U(val);
- }
- break;
- case CV_16S:
- if( ipower < 0 )
- for( j = 0; j < ncols; j++ )
- {
- int val = ((short*)a_data)[j];
- ((short*)b_data)[j] = (short)((val&~1)==0 ? val :
- val ==-1 ? 1-2*(ipower&1) :
- val == 2 && ipower == -1 ? 1 : 0);
- }
- else
- for( j = 0; j < ncols; j++ )
- {
- int val = ((short*)a_data)[j];
- val = ipow( val, ipower );
- ((short*)b_data)[j] = CV_CAST_16S(val);
- }
- break;
- case CV_32S:
- if( ipower < 0 )
- for( j = 0; j < ncols; j++ )
- {
- int val = ((int*)a_data)[j];
- ((int*)b_data)[j] = (val&~1)==0 ? val :
- val ==-1 ? 1-2*(ipower&1) :
- val == 2 && ipower == -1 ? 1 : 0;
- }
- else
- for( j = 0; j < ncols; j++ )
- {
- int val = ((int*)a_data)[j];
- val = ipow( val, ipower );
- ((int*)b_data)[j] = val;
- }
- break;
- case CV_32F:
- if( power != ipower )
- for( j = 0; j < ncols; j++ )
- {
- double val = ((float*)a_data)[j];
- val = pow( fabs(val), power );
- ((float*)b_data)[j] = CV_CAST_32F(val);
- }
- else
- for( j = 0; j < ncols; j++ )
- {
- double val = ((float*)a_data)[j];
- if( ipower < 0 )
- val = 1./val;
- val = ipow( val, apower );
- ((float*)b_data)[j] = (float)val;
- }
- break;
- case CV_64F:
- if( power != ipower )
- for( j = 0; j < ncols; j++ )
- {
- double val = ((double*)a_data)[j];
- val = pow( fabs(val), power );
- ((double*)b_data)[j] = CV_CAST_64F(val);
- }
- else
- for( j = 0; j < ncols; j++ )
- {
- double val = ((double*)a_data)[j];
- if( ipower < 0 )
- val = 1./val;
- val = ipow( val, apower );
- ((double*)b_data)[j] = (double)val;
- }
- break;
- }
- }
-}
-
-CxCore_PowTest pow_test;
-
-
-
-////////// cart2polar /////////////
-class CxCore_CartToPolarTest : public CxCore_MathTest
-{
-public:
- CxCore_CartToPolarTest();
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- double get_success_error_level( int test_case_idx, int i, int j );
- void run_func();
- void prepare_to_validation( int test_case_idx );
- int use_degrees;
-};
-
-
-CxCore_CartToPolarTest::CxCore_CartToPolarTest()
- : CxCore_MathTest( "math-cart2polar", "cvCartToPolar" )
-{
- use_degrees = 0;
- test_array[INPUT].push(NULL);
- test_array[OUTPUT].push(NULL);
- test_array[REF_OUTPUT].push(NULL);
-}
-
-
-void CxCore_CartToPolarTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- CxCore_MathTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
-
- use_degrees = cvTsRandInt(rng) & 1;
- if( cvTsRandInt(rng) % 4 == 0 ) // check missing magnitude/angle cases
- {
- int idx = cvTsRandInt(rng) & 1;
- sizes[OUTPUT][idx] = sizes[REF_OUTPUT][idx] = cvSize(0,0);
- }
-}
-
-
-void CxCore_CartToPolarTest::run_func()
-{
- if(!test_nd)
- {
- cvCartToPolar( test_array[INPUT][0], test_array[INPUT][1],
- test_array[OUTPUT][0], test_array[OUTPUT][1], use_degrees );
- }
- else
- {
- cv::Mat X = cv::cvarrToMat(test_array[INPUT][0]);
- cv::Mat Y = cv::cvarrToMat(test_array[INPUT][1]);
- cv::Mat mag = test_array[OUTPUT][0] ? cv::cvarrToMat(test_array[OUTPUT][0]) : cv::Mat();
- cv::Mat ph = test_array[OUTPUT][1] ? cv::cvarrToMat(test_array[OUTPUT][1]) : cv::Mat();
- if(!mag.data)
- cv::phase(X, Y, ph, use_degrees != 0);
- else if(!ph.data)
- cv::magnitude(X, Y, mag);
- else
- cv::cartToPolar(X, Y, mag, ph, use_degrees != 0);
- }
-}
-
-
-double CxCore_CartToPolarTest::get_success_error_level( int test_case_idx, int i, int j )
-{
- return j == 1 ? 0.5*(use_degrees ? 1 : CV_PI/180.) :
- CxCore_MathTest::get_success_error_level( test_case_idx, i, j );
-}
-
-
-void CxCore_CartToPolarTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- CvMat* x = &test_mat[INPUT][0];
- CvMat* y = &test_mat[INPUT][1];
- CvMat* mag = test_array[REF_OUTPUT][0] ? &test_mat[REF_OUTPUT][0] : 0;
- CvMat* angle = test_array[REF_OUTPUT][1] ? &test_mat[REF_OUTPUT][1] : 0;
- double C = use_degrees ? 180./CV_PI : 1.;
-
- int depth = CV_MAT_DEPTH(x->type);
- int ncols = x->cols*CV_MAT_CN(x->type);
- int i, j;
-
- for( i = 0; i < x->rows; i++ )
- {
- uchar* x_data = x->data.ptr + i*x->step;
- uchar* y_data = y->data.ptr + i*y->step;
- uchar* mag_data = mag ? mag->data.ptr + i*mag->step : 0;
- uchar* angle_data = angle ? angle->data.ptr + i*angle->step : 0;
-
- if( depth == CV_32F )
- {
- for( j = 0; j < ncols; j++ )
- {
- double xval = ((float*)x_data)[j];
- double yval = ((float*)y_data)[j];
-
- if( mag_data )
- ((float*)mag_data)[j] = (float)sqrt(xval*xval + yval*yval);
- if( angle_data )
- {
- double a = atan2( yval, xval );
- if( a < 0 )
- a += CV_PI*2;
- a *= C;
- ((float*)angle_data)[j] = (float)a;
- }
- }
- }
- else
- {
- assert( depth == CV_64F );
- for( j = 0; j < ncols; j++ )
- {
- double xval = ((double*)x_data)[j];
- double yval = ((double*)y_data)[j];
-
- if( mag_data )
- ((double*)mag_data)[j] = sqrt(xval*xval + yval*yval);
- if( angle_data )
- {
- double a = atan2( yval, xval );
- if( a < 0 )
- a += CV_PI*2;
- a *= C;
- ((double*)angle_data)[j] = a;
- }
- }
- }
- }
-
- if( angle )
- {
- // hack: increase angle value by 1 (so that alpha becomes 1+alpha)
- // to hide large relative errors in case of very small angles
- cvTsAdd( &test_mat[OUTPUT][1], cvScalarAll(1.), 0, cvScalarAll(0.),
- cvScalarAll(1.), &test_mat[OUTPUT][1], 0 );
- cvTsAdd( &test_mat[REF_OUTPUT][1], cvScalarAll(1.), 0, cvScalarAll(0.),
- cvScalarAll(1.), &test_mat[REF_OUTPUT][1], 0 );
- }
-}
-
-CxCore_CartToPolarTest cart2polar_test;
-
-
-
-////////// polar2cart /////////////
-class CxCore_PolarToCartTest : public CxCore_MathTest
-{
-public:
- CxCore_PolarToCartTest();
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- double get_success_error_level( int test_case_idx, int i, int j );
- void run_func();
- void prepare_to_validation( int test_case_idx );
- int use_degrees;
-};
-
-
-CxCore_PolarToCartTest::CxCore_PolarToCartTest()
- : CxCore_MathTest( "math-polar2cart", "cvPolarToCart" )
-{
- use_degrees = 0;
- test_array[INPUT].push(NULL);
- test_array[OUTPUT].push(NULL);
- test_array[REF_OUTPUT].push(NULL);
-}
-
-
-void CxCore_PolarToCartTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- CxCore_MathTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
-
- use_degrees = cvTsRandInt(rng) & 1;
- if( cvTsRandInt(rng) % 4 == 0 ) // check missing magnitude case
- sizes[INPUT][1] = cvSize(0,0);
-
- if( cvTsRandInt(rng) % 4 == 0 ) // check missing x/y cases
- {
- int idx = cvTsRandInt(rng) & 1;
- sizes[OUTPUT][idx] = sizes[REF_OUTPUT][idx] = cvSize(0,0);
- }
-}
-
-
-void CxCore_PolarToCartTest::run_func()
-{
- if(!test_nd)
- {
- cvPolarToCart( test_array[INPUT][1], test_array[INPUT][0],
- test_array[OUTPUT][0], test_array[OUTPUT][1], use_degrees );
- }
- else
- {
- cv::Mat X = test_array[OUTPUT][0] ? cv::cvarrToMat(test_array[OUTPUT][0]) : cv::Mat();
- cv::Mat Y = test_array[OUTPUT][1] ? cv::cvarrToMat(test_array[OUTPUT][1]) : cv::Mat();
- cv::Mat mag = test_array[INPUT][1] ? cv::cvarrToMat(test_array[INPUT][1]) : cv::Mat();
- cv::Mat ph = test_array[INPUT][0] ? cv::cvarrToMat(test_array[INPUT][0]) : cv::Mat();
- cv::polarToCart(mag, ph, X, Y, use_degrees != 0);
- }
-}
-
-
-double CxCore_PolarToCartTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- return FLT_EPSILON*100;
-}
-
-
-void CxCore_PolarToCartTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- CvMat* x = test_array[REF_OUTPUT][0] ? &test_mat[REF_OUTPUT][0] : 0;
- CvMat* y = test_array[REF_OUTPUT][1] ? &test_mat[REF_OUTPUT][1] : 0;
- CvMat* angle = &test_mat[INPUT][0];
- CvMat* mag = test_array[INPUT][1] ? &test_mat[INPUT][1] : 0;
- double C = use_degrees ? CV_PI/180. : 1.;
-
- int depth = CV_MAT_DEPTH(angle->type);
- int ncols = angle->cols*CV_MAT_CN(angle->type);
- int i, j;
-
- for( i = 0; i < angle->rows; i++ )
- {
- uchar* x_data = x ? x->data.ptr + i*x->step : 0;
- uchar* y_data = y ? y->data.ptr + i*y->step : 0;
- uchar* mag_data = mag ? mag->data.ptr + i*mag->step : 0;
- uchar* angle_data = angle->data.ptr + i*angle->step;
-
- if( depth == CV_32F )
- {
- for( j = 0; j < ncols; j++ )
- {
- double a = ((float*)angle_data)[j]*C;
- double m = mag_data ? ((float*)mag_data)[j] : 1.;
-
- if( x_data )
- ((float*)x_data)[j] = (float)(m*cos(a));
- if( y_data )
- ((float*)y_data)[j] = (float)(m*sin(a));
- }
- }
- else
- {
- assert( depth == CV_64F );
- for( j = 0; j < ncols; j++ )
- {
- double a = ((double*)angle_data)[j]*C;
- double m = mag_data ? ((double*)mag_data)[j] : 1.;
-
- if( x_data )
- ((double*)x_data)[j] = m*cos(a);
- if( y_data )
- ((double*)y_data)[j] = m*sin(a);
- }
- }
- }
-}
-
-CxCore_PolarToCartTest polar2cart_test;
-
-///////////////////////////////////////// matrix tests ////////////////////////////////////////////
-
-static const int matrix_all_depths[] = { CV_8U, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F, -1 };
-
-class CxCore_MatrixTestImpl : public CvArrTest
-{
-public:
- CxCore_MatrixTestImpl( const char* test_name, const char* test_funcs, int in_count, int out_count,
- bool allow_int, bool scalar_output, int max_cn );
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types,
- CvSize** whole_sizes, bool* are_images );
- double get_success_error_level( int test_case_idx, int i, int j );
- bool allow_int;
- bool scalar_output;
- int max_cn;
-};
-
-
-CxCore_MatrixTestImpl::CxCore_MatrixTestImpl( const char* test_name, const char* test_funcs,
- int in_count, int out_count,
- bool _allow_int, bool _scalar_output, int _max_cn )
- : CvArrTest( test_name, test_funcs, "" ),
- allow_int(_allow_int), scalar_output(_scalar_output), max_cn(_max_cn)
-{
- int i;
- for( i = 0; i < in_count; i++ )
- test_array[INPUT].push(NULL);
-
- for( i = 0; i < out_count; i++ )
- {
- test_array[OUTPUT].push(NULL);
- test_array[REF_OUTPUT].push(NULL);
- }
-
- element_wise_relative_error = false;
-
- default_timing_param_names = math_param_names;
-
- size_list = (CvSize*)matrix_sizes;
- whole_size_list = 0;
- depth_list = (int*)math_depths;
- cn_list = 0;
-}
-
-
-void CxCore_MatrixTestImpl::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- int depth = cvTsRandInt(rng) % (allow_int ? CV_64F+1 : 2);
- int cn = cvTsRandInt(rng) % max_cn + 1;
- int i, j;
-
- if( allow_int )
- depth += depth == CV_8S;
- else
- depth += CV_32F;
-
- CvArrTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
-
- for( i = 0; i < max_arr; i++ )
- {
- int count = test_array[i].size();
- int flag = (i == OUTPUT || i == REF_OUTPUT) && scalar_output;
- int type = !flag ? CV_MAKETYPE(depth, cn) : CV_64FC1;
-
- for( j = 0; j < count; j++ )
- {
- types[i][j] = type;
- if( flag )
- sizes[i][j] = cvSize( 4, 1 );
- }
- }
-}
-
-
-void CxCore_MatrixTestImpl::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool* are_images )
-{
- CvArrTest::get_timing_test_array_types_and_sizes( test_case_idx,
- sizes, types, whole_sizes, are_images );
- if( scalar_output )
- {
- types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_64FC1;
- sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = cvSize( 4, 1 );
- whole_sizes[OUTPUT][0] = whole_sizes[REF_OUTPUT][0] = cvSize( 4, 1 );
- }
-}
-
-
-double CxCore_MatrixTestImpl::get_success_error_level( int test_case_idx, int i, int j )
-{
- int input_depth = CV_MAT_DEPTH(cvGetElemType( test_array[INPUT][0] ));
- double input_precision = input_depth < CV_32F ? 0 : input_depth == CV_32F ?
- 5e-5 : 5e-10;
- double output_precision = CvArrTest::get_success_error_level( test_case_idx, i, j );
- return MAX(input_precision, output_precision);
-}
-
-CxCore_MatrixTestImpl matrix_test( "matrix", "", 0, 0, false, false, 0 );
-
-
-class CxCore_MatrixTest : public CxCore_MatrixTestImpl
-{
-public:
- CxCore_MatrixTest( const char* test_name, const char* test_funcs, int in_count, int out_count,
- bool allow_int, bool scalar_output, int max_cn );
-};
-
-
-CxCore_MatrixTest::CxCore_MatrixTest( const char* test_name, const char* test_funcs,
- int in_count, int out_count, bool _allow_int,
- bool _scalar_output, int _max_cn )
- : CxCore_MatrixTestImpl( test_name, test_funcs, in_count, out_count,
- _allow_int, _scalar_output, _max_cn )
-{
- size_list = 0;
- depth_list = 0;
-}
-
-
-///////////////// Trace /////////////////////
-
-class CxCore_TraceTest : public CxCore_MatrixTest
-{
-public:
- CxCore_TraceTest();
-protected:
- void run_func();
- void prepare_to_validation( int test_case_idx );
-};
-
-
-CxCore_TraceTest::CxCore_TraceTest() :
- CxCore_MatrixTest( "matrix-trace", "cvTrace", 1, 1, true, true, 4 )
-{
-}
-
-
-void CxCore_TraceTest::run_func()
-{
- *((CvScalar*)(test_mat[OUTPUT][0].data.db)) = cvTrace(test_array[INPUT][0]);
-}
-
-
-void CxCore_TraceTest::prepare_to_validation( int )
-{
- CvMat* mat = &test_mat[INPUT][0];
- int i, j, count = MIN( mat->rows, mat->cols );
- CvScalar trace = {{0,0,0,0}};
-
- for( i = 0; i < count; i++ )
- {
- CvScalar el = cvGet2D( mat, i, i );
- for( j = 0; j < 4; j++ )
- trace.val[j] += el.val[j];
- }
-
- *((CvScalar*)(test_mat[REF_OUTPUT][0].data.db)) = trace;
-}
-
-CxCore_TraceTest trace_test;
-
-
-///////// dotproduct //////////
-
-class CxCore_DotProductTest : public CxCore_MatrixTest
-{
-public:
- CxCore_DotProductTest();
-protected:
- void run_func();
- void prepare_to_validation( int test_case_idx );
-};
-
-
-CxCore_DotProductTest::CxCore_DotProductTest() :
- CxCore_MatrixTest( "matrix-dotproduct", "cvDotProduct", 2, 1, true, true, 4 )
-{
- depth_list = matrix_all_depths;
-}
-
-
-void CxCore_DotProductTest::run_func()
-{
- *((CvScalar*)(test_mat[OUTPUT][0].data.ptr)) =
- cvRealScalar(cvDotProduct( test_array[INPUT][0], test_array[INPUT][1] ));
-}
-
-
-void CxCore_DotProductTest::prepare_to_validation( int )
-{
- *((CvScalar*)(test_mat[REF_OUTPUT][0].data.ptr)) =
- cvRealScalar(cvTsCrossCorr( &test_mat[INPUT][0], &test_mat[INPUT][1] ));
-}
-
-CxCore_DotProductTest dotproduct_test;
-
-
-///////// crossproduct //////////
-
-static const CvSize cross_product_sizes[] = {{3,1}, {-1,-1}};
-
-class CxCore_CrossProductTest : public CxCore_MatrixTest
-{
-public:
- CxCore_CrossProductTest();
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void run_func();
- void prepare_to_validation( int test_case_idx );
-};
-
-
-CxCore_CrossProductTest::CxCore_CrossProductTest() :
- CxCore_MatrixTest( "matrix-crossproduct", "cvCrossProduct", 2, 1, false, false, 1 )
-{
- size_list = cross_product_sizes;
-}
-
-
-void CxCore_CrossProductTest::get_test_array_types_and_sizes( int /*test_case_idx*/, CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- int depth = cvTsRandInt(rng) % 2 + CV_32F;
- int cn = cvTsRandInt(rng) & 1 ? 3 : 1, type = CV_MAKETYPE(depth, cn);
- CvSize sz;
-
- types[INPUT][0] = types[INPUT][1] = types[OUTPUT][0] = types[REF_OUTPUT][0] = type;
-
- if( cn == 3 )
- sz = cvSize(1,1);
- else if( cvTsRandInt(rng) & 1 )
- sz = cvSize(3,1);
- else
- sz = cvSize(1,3);
-
- sizes[INPUT][0] = sizes[INPUT][1] = sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = sz;
-}
-
-
-void CxCore_CrossProductTest::run_func()
-{
- cvCrossProduct( test_array[INPUT][0], test_array[INPUT][1], test_array[OUTPUT][0] );
-}
-
-
-void CxCore_CrossProductTest::prepare_to_validation( int )
-{
- CvScalar a = {{0,0,0,0}}, b = {{0,0,0,0}}, c = {{0,0,0,0}};
-
- if( test_mat[INPUT][0].rows > 1 )
- {
- a.val[0] = cvGetReal2D( &test_mat[INPUT][0], 0, 0 );
- a.val[1] = cvGetReal2D( &test_mat[INPUT][0], 1, 0 );
- a.val[2] = cvGetReal2D( &test_mat[INPUT][0], 2, 0 );
-
- b.val[0] = cvGetReal2D( &test_mat[INPUT][1], 0, 0 );
- b.val[1] = cvGetReal2D( &test_mat[INPUT][1], 1, 0 );
- b.val[2] = cvGetReal2D( &test_mat[INPUT][1], 2, 0 );
- }
- else if( test_mat[INPUT][0].cols > 1 )
- {
- a.val[0] = cvGetReal1D( &test_mat[INPUT][0], 0 );
- a.val[1] = cvGetReal1D( &test_mat[INPUT][0], 1 );
- a.val[2] = cvGetReal1D( &test_mat[INPUT][0], 2 );
-
- b.val[0] = cvGetReal1D( &test_mat[INPUT][1], 0 );
- b.val[1] = cvGetReal1D( &test_mat[INPUT][1], 1 );
- b.val[2] = cvGetReal1D( &test_mat[INPUT][1], 2 );
- }
- else
- {
- a = cvGet1D( &test_mat[INPUT][0], 0 );
- b = cvGet1D( &test_mat[INPUT][1], 0 );
- }
-
- c.val[2] = a.val[0]*b.val[1] - a.val[1]*b.val[0];
- c.val[1] = -a.val[0]*b.val[2] + a.val[2]*b.val[0];
- c.val[0] = a.val[1]*b.val[2] - a.val[2]*b.val[1];
-
- if( test_mat[REF_OUTPUT][0].rows > 1 )
- {
- cvSetReal2D( &test_mat[REF_OUTPUT][0], 0, 0, c.val[0] );
- cvSetReal2D( &test_mat[REF_OUTPUT][0], 1, 0, c.val[1] );
- cvSetReal2D( &test_mat[REF_OUTPUT][0], 2, 0, c.val[2] );
- }
- else if( test_mat[REF_OUTPUT][0].cols > 1 )
- {
- cvSetReal1D( &test_mat[REF_OUTPUT][0], 0, c.val[0] );
- cvSetReal1D( &test_mat[REF_OUTPUT][0], 1, c.val[1] );
- cvSetReal1D( &test_mat[REF_OUTPUT][0], 2, c.val[2] );
- }
- else
- {
- cvSet1D( &test_mat[REF_OUTPUT][0], 0, c );
- }
-}
-
-CxCore_CrossProductTest crossproduct_test;
-
-
-///////////////// scaleadd /////////////////////
-
-class CxCore_ScaleAddTest : public CxCore_MatrixTest
-{
-public:
- CxCore_ScaleAddTest();
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types,
- CvSize** whole_sizes, bool* are_images );
- int prepare_test_case( int test_case_idx );
- void run_func();
- void prepare_to_validation( int test_case_idx );
- CvScalar alpha;
- bool test_nd;
-};
-
-CxCore_ScaleAddTest::CxCore_ScaleAddTest() :
- CxCore_MatrixTest( "matrix-scaleadd", "cvScaleAdd", 3, 1, false, false, 4 )
-{
- alpha = cvScalarAll(0);
- test_nd = false;
-}
-
-
-void CxCore_ScaleAddTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CxCore_MatrixTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- sizes[INPUT][2] = cvSize(1,1);
- types[INPUT][2] &= CV_MAT_DEPTH_MASK;
- test_nd = cvTsRandInt(ts->get_rng()) % 2 != 0;
-}
-
-
-void CxCore_ScaleAddTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types,
- CvSize** whole_sizes, bool* are_images )
-{
- CxCore_MatrixTest::get_timing_test_array_types_and_sizes( test_case_idx, sizes, types,
- whole_sizes, are_images );
- sizes[INPUT][2] = cvSize(1,1);
- types[INPUT][2] &= CV_MAT_DEPTH_MASK;
-}
-
-
-int CxCore_ScaleAddTest::prepare_test_case( int test_case_idx )
-{
- int code = CxCore_MatrixTest::prepare_test_case( test_case_idx );
- if( code > 0 )
- alpha = cvGet1D( &test_mat[INPUT][2], 0 );
- if( test_nd )
- alpha.val[1] = 0;
- return code;
-}
-
-
-void CxCore_ScaleAddTest::run_func()
-{
- if(!test_nd)
- cvScaleAdd( test_array[INPUT][0], alpha, test_array[INPUT][1], test_array[OUTPUT][0] );
- else
- {
- cv::MatND c = cv::cvarrToMatND(test_array[OUTPUT][0]);
- cv::scaleAdd( cv::cvarrToMatND(test_array[INPUT][0]), alpha.val[0],
- cv::cvarrToMatND(test_array[INPUT][1]), c);
- }
-}
-
-
-void CxCore_ScaleAddTest::prepare_to_validation( int )
-{
- cvTsAdd( &test_mat[INPUT][0], cvScalarAll(alpha.val[0]),
- &test_mat[INPUT][1], cvScalarAll(1.),
- cvScalarAll(0.), &test_mat[REF_OUTPUT][0], 0 );
-}
-
-CxCore_ScaleAddTest scaleadd_test;
-
-
-///////////////// gemm /////////////////////
-
-static const char* matrix_gemm_param_names[] = { "size", "add_c", "mul_type", "depth", 0 };
-static const char* matrix_gemm_mul_types[] = { "AB", "AtB", "ABt", "AtBt", 0 };
-static const int matrix_gemm_add_c_flags[] = { 0, 1 };
-
-class CxCore_GEMMTest : public CxCore_MatrixTest
-{
-public:
- CxCore_GEMMTest();
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void get_minmax_bounds( int /*i*/, int /*j*/, int /*type*/, CvScalar* low, CvScalar* high );
- void get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types,
- CvSize** whole_sizes, bool* are_images );
- int write_default_params( CvFileStorage* fs );
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
- int prepare_test_case( int test_case_idx );
- void run_func();
- void prepare_to_validation( int test_case_idx );
- int tabc_flag;
- double alpha, beta;
-};
-
-CxCore_GEMMTest::CxCore_GEMMTest() :
- CxCore_MatrixTest( "matrix-gemm", "cvGEMM", 5, 1, false, false, 2 )
-{
- test_case_count = 100;
- max_log_array_size = 10;
- default_timing_param_names = matrix_gemm_param_names;
- alpha = beta = 0;
-}
-
-
-void CxCore_GEMMTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- CvSize sizeA;
- CxCore_MatrixTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- sizeA = sizes[INPUT][0];
- CxCore_MatrixTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- sizes[INPUT][0] = sizeA;
- sizes[INPUT][2] = sizes[INPUT][3] = cvSize(1,1);
- types[INPUT][2] = types[INPUT][3] &= ~CV_MAT_CN_MASK;
-
- tabc_flag = cvTsRandInt(rng) & 7;
-
- switch( tabc_flag & (CV_GEMM_A_T|CV_GEMM_B_T) )
- {
- case 0:
- sizes[INPUT][1].height = sizes[INPUT][0].width;
- sizes[OUTPUT][0].height = sizes[INPUT][0].height;
- sizes[OUTPUT][0].width = sizes[INPUT][1].width;
- break;
- case CV_GEMM_B_T:
- sizes[INPUT][1].width = sizes[INPUT][0].width;
- sizes[OUTPUT][0].height = sizes[INPUT][0].height;
- sizes[OUTPUT][0].width = sizes[INPUT][1].height;
- break;
- case CV_GEMM_A_T:
- sizes[INPUT][1].height = sizes[INPUT][0].height;
- sizes[OUTPUT][0].height = sizes[INPUT][0].width;
- sizes[OUTPUT][0].width = sizes[INPUT][1].width;
- break;
- case CV_GEMM_A_T | CV_GEMM_B_T:
- sizes[INPUT][1].width = sizes[INPUT][0].height;
- sizes[OUTPUT][0].height = sizes[INPUT][0].width;
- sizes[OUTPUT][0].width = sizes[INPUT][1].height;
- break;
- }
-
- sizes[REF_OUTPUT][0] = sizes[OUTPUT][0];
-
- if( cvTsRandInt(rng) & 1 )
- sizes[INPUT][4] = cvSize(0,0);
- else if( !(tabc_flag & CV_GEMM_C_T) )
- sizes[INPUT][4] = sizes[OUTPUT][0];
- else
- {
- sizes[INPUT][4].width = sizes[OUTPUT][0].height;
- sizes[INPUT][4].height = sizes[OUTPUT][0].width;
- }
-}
-
-
-void CxCore_GEMMTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types,
- CvSize** whole_sizes, bool* are_images )
-{
- CxCore_MatrixTest::get_timing_test_array_types_and_sizes( test_case_idx,
- sizes, types, whole_sizes, are_images );
- const char* mul_type = cvReadString( find_timing_param("mul_type"), "AB" );
- if( strcmp( mul_type, "AtB" ) == 0 )
- tabc_flag = CV_GEMM_A_T;
- else if( strcmp( mul_type, "ABt" ) == 0 )
- tabc_flag = CV_GEMM_B_T;
- else if( strcmp( mul_type, "AtBt" ) == 0 )
- tabc_flag = CV_GEMM_A_T + CV_GEMM_B_T;
- else
- tabc_flag = 0;
-
- if( cvReadInt( find_timing_param( "add_c" ), 0 ) == 0 )
- sizes[INPUT][4] = cvSize(0,0);
-}
-
-
-int CxCore_GEMMTest::write_default_params( CvFileStorage* fs )
-{
- int code = CxCore_MatrixTest::write_default_params(fs);
- if( code < 0 || ts->get_testing_mode() != CvTS::TIMING_MODE )
- return code;
- write_string_list( fs, "mul_type", matrix_gemm_mul_types );
- write_int_list( fs, "add_c", matrix_gemm_add_c_flags, CV_DIM(matrix_gemm_add_c_flags) );
- return code;
-}
-
-
-void CxCore_GEMMTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- sprintf( ptr, "%s%s,%s,",
- tabc_flag & CV_GEMM_A_T ? "At" : "A",
- tabc_flag & CV_GEMM_B_T ? "Bt" : "B",
- test_array[INPUT][4] ? "plusC" : "" );
- ptr += strlen(ptr);
- params_left -= 2;
- CxCore_MatrixTest::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-
-int CxCore_GEMMTest::prepare_test_case( int test_case_idx )
-{
- int code = CxCore_MatrixTest::prepare_test_case( test_case_idx );
- if( code > 0 )
- {
- alpha = cvmGet( &test_mat[INPUT][2], 0, 0 );
- beta = cvmGet( &test_mat[INPUT][3], 0, 0 );
- }
- return code;
-}
-
-
-void CxCore_GEMMTest::get_minmax_bounds( int /*i*/, int /*j*/, int /*type*/, CvScalar* low, CvScalar* high )
-{
- *low = cvScalarAll(-10.);
- *high = cvScalarAll(10.);
-}
-
-
-void CxCore_GEMMTest::run_func()
-{
- cvGEMM( test_array[INPUT][0], test_array[INPUT][1], alpha,
- test_array[INPUT][4], beta, test_array[OUTPUT][0], tabc_flag );
-}
-
-
-void CxCore_GEMMTest::prepare_to_validation( int )
-{
- cvTsGEMM( &test_mat[INPUT][0], &test_mat[INPUT][1], alpha,
- test_array[INPUT][4] ? &test_mat[INPUT][4] : 0,
- beta, &test_mat[REF_OUTPUT][0], tabc_flag );
-}
-
-CxCore_GEMMTest gemm_test;
-
-
-///////////////// multransposed /////////////////////
-
-static const char* matrix_multrans_param_names[] = { "size", "use_delta", "mul_type", "depth", 0 };
-static const int matrix_multrans_use_delta_flags[] = { 0, 1 };
-static const char* matrix_multrans_mul_types[] = { "AAt", "AtA", 0 };
-
-class CxCore_MulTransposedTest : public CxCore_MatrixTest
-{
-public:
- CxCore_MulTransposedTest();
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types,
- CvSize** whole_sizes, bool* are_images );
- int write_default_params( CvFileStorage* fs );
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
- void get_minmax_bounds( int /*i*/, int /*j*/, int /*type*/, CvScalar* low, CvScalar* high );
- void run_func();
- void prepare_to_validation( int test_case_idx );
- int order;
-};
-
-
-CxCore_MulTransposedTest::CxCore_MulTransposedTest() :
- CxCore_MatrixTest( "matrix-multransposed", "cvMulTransposed, cvRepeat", 2, 1, false, false, 1 )
-{
- test_case_count = 100;
- order = 0;
- test_array[TEMP].push(NULL);
- default_timing_param_names = matrix_multrans_param_names;
-}
-
-
-void CxCore_MulTransposedTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- int bits = cvTsRandInt(rng);
- int src_type = cvTsRandInt(rng) % 5;
- int dst_type = cvTsRandInt(rng) % 2;
-
- src_type = src_type == 0 ? CV_8U : src_type == 1 ? CV_16U : src_type == 2 ? CV_16S :
- src_type == 3 ? CV_32F : CV_64F;
- dst_type = dst_type == 0 ? CV_32F : CV_64F;
- dst_type = MAX( dst_type, src_type );
-
- CxCore_MatrixTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
-
- if( bits & 1 )
- sizes[INPUT][1] = cvSize(0,0);
- else
- {
- sizes[INPUT][1] = sizes[INPUT][0];
- if( bits & 2 )
- sizes[INPUT][1].height = 1;
- if( bits & 4 )
- sizes[INPUT][1].width = 1;
- }
-
- sizes[TEMP][0] = sizes[INPUT][0];
- types[INPUT][0] = src_type;
- types[OUTPUT][0] = types[REF_OUTPUT][0] = types[INPUT][1] = types[TEMP][0] = dst_type;
-
- order = (bits & 8) != 0;
- sizes[OUTPUT][0].width = sizes[OUTPUT][0].height = order == 0 ?
- sizes[INPUT][0].height : sizes[INPUT][0].width;
- sizes[REF_OUTPUT][0] = sizes[OUTPUT][0];
-}
-
-
-void CxCore_MulTransposedTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types,
- CvSize** whole_sizes, bool* are_images )
-{
- CxCore_MatrixTest::get_timing_test_array_types_and_sizes( test_case_idx,
- sizes, types, whole_sizes, are_images );
- const char* mul_type = cvReadString( find_timing_param("mul_type"), "AAt" );
- order = strcmp( mul_type, "AtA" ) == 0;
-
- if( cvReadInt( find_timing_param( "use_delta" ), 0 ) == 0 )
- sizes[INPUT][1] = cvSize(0,0);
-}
-
-
-int CxCore_MulTransposedTest::write_default_params( CvFileStorage* fs )
-{
- int code = CxCore_MatrixTest::write_default_params(fs);
- if( code < 0 || ts->get_testing_mode() != CvTS::TIMING_MODE )
- return code;
- write_string_list( fs, "mul_type", matrix_multrans_mul_types );
- write_int_list( fs, "use_delta", matrix_multrans_use_delta_flags,
- CV_DIM(matrix_multrans_use_delta_flags) );
- return code;
-}
-
-
-void CxCore_MulTransposedTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- sprintf( ptr, "%s,%s,", order == 0 ? "AAt" : "AtA", test_array[INPUT][1] ? "delta" : "" );
- ptr += strlen(ptr);
- params_left -= 2;
- CxCore_MatrixTest::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-
-void CxCore_MulTransposedTest::get_minmax_bounds( int /*i*/, int /*j*/, int /*type*/, CvScalar* low, CvScalar* high )
-{
- *low = cvScalarAll(-10.);
- *high = cvScalarAll(10.);
-}
-
-
-void CxCore_MulTransposedTest::run_func()
-{
- cvMulTransposed( test_array[INPUT][0], test_array[OUTPUT][0],
- order, test_array[INPUT][1] );
-}
-
-
-void CxCore_MulTransposedTest::prepare_to_validation( int )
-{
- CvMat* delta = test_array[INPUT][1] ? &test_mat[INPUT][1] : 0;
- if( delta )
- {
- if( test_mat[INPUT][1].rows < test_mat[INPUT][0].rows ||
- test_mat[INPUT][1].cols < test_mat[INPUT][0].cols )
- {
- cvRepeat( delta, &test_mat[TEMP][0] );
- delta = &test_mat[TEMP][0];
- }
- cvTsAdd( &test_mat[INPUT][0], cvScalarAll(1.), delta, cvScalarAll(-1.),
- cvScalarAll(0.), &test_mat[TEMP][0], 0 );
- }
- else
- cvTsConvert( &test_mat[INPUT][0], &test_mat[TEMP][0] );
- delta = &test_mat[TEMP][0];
-
- cvTsGEMM( delta, delta, 1., 0, 0, &test_mat[REF_OUTPUT][0], order == 0 ? CV_GEMM_B_T : CV_GEMM_A_T );
-}
-
-CxCore_MulTransposedTest multransposed_test;
-
-
-///////////////// Transform /////////////////////
-
-static const CvSize matrix_transform_sizes[] = {{10,10}, {100,100}, {720,480}, {-1,-1}};
-static const CvSize matrix_transform_whole_sizes[] = {{10,10}, {720,480}, {720,480}, {-1,-1}};
-static const int matrix_transform_channels[] = { 2, 3, 4, -1 };
-static const char* matrix_transform_param_names[] = { "size", "channels", "depth", 0 };
-
-class CxCore_TransformTest : public CxCore_MatrixTest
-{
-public:
- CxCore_TransformTest();
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- double get_success_error_level( int test_case_idx, int i, int j );
- void get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types,
- CvSize** whole_sizes, bool* are_images );
- int prepare_test_case( int test_case_idx );
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
- void run_func();
- void prepare_to_validation( int test_case_idx );
-
- double scale;
- bool diagMtx;
-};
-
-
-CxCore_TransformTest::CxCore_TransformTest() :
- CxCore_MatrixTest( "matrix-transform", "cvTransform", 3, 1, true, false, 4 )
-{
- default_timing_param_names = matrix_transform_param_names;
- cn_list = matrix_transform_channels;
- depth_list = matrix_all_depths;
- size_list = matrix_transform_sizes;
- whole_size_list = matrix_transform_whole_sizes;
-}
-
-
-void CxCore_TransformTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- int bits = cvTsRandInt(rng);
- int depth, dst_cn, mat_cols, mattype;
- CxCore_MatrixTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
-
- mat_cols = CV_MAT_CN(types[INPUT][0]);
- depth = CV_MAT_DEPTH(types[INPUT][0]);
- dst_cn = cvTsRandInt(rng) % 4 + 1;
- types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_MAKETYPE(depth, dst_cn);
-
- mattype = depth < CV_32S ? CV_32F : depth == CV_64F ? CV_64F : bits & 1 ? CV_32F : CV_64F;
- types[INPUT][1] = mattype;
- types[INPUT][2] = CV_MAKETYPE(mattype, dst_cn);
-
- scale = 1./((cvTsRandInt(rng)%4)*50+1);
-
- if( bits & 2 )
- {
- sizes[INPUT][2] = cvSize(0,0);
- mat_cols += (bits & 4) != 0;
- }
- else if( bits & 4 )
- sizes[INPUT][2] = cvSize(1,1);
- else
- {
- if( bits & 8 )
- sizes[INPUT][2] = cvSize(dst_cn,1);
- else
- sizes[INPUT][2] = cvSize(1,dst_cn);
- types[INPUT][2] &= ~CV_MAT_CN_MASK;
- }
- diagMtx = (bits & 16) != 0;
-
- sizes[INPUT][1] = cvSize(mat_cols,dst_cn);
-}
-
-
-void CxCore_TransformTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool* are_images )
-{
- CxCore_MatrixTest::get_timing_test_array_types_and_sizes( test_case_idx,
- sizes, types, whole_sizes, are_images );
- int cn = CV_MAT_CN(types[INPUT][0]);
- sizes[INPUT][1] = cvSize(cn + (cn < 4), cn);
- sizes[INPUT][2] = cvSize(0,0);
- types[INPUT][1] = types[INPUT][2] = CV_64FC1;
- scale = 1./1000;
-}
-
-int CxCore_TransformTest::prepare_test_case( int test_case_idx )
-{
- int code = CxCore_MatrixTest::prepare_test_case( test_case_idx );
- if( code > 0 )
- {
- cvTsAdd(&test_mat[INPUT][1], cvScalarAll(scale), &test_mat[INPUT][1],
- cvScalarAll(0), cvScalarAll(0), &test_mat[INPUT][1], 0 );
- if(diagMtx)
- {
- CvMat* w = cvCloneMat(&test_mat[INPUT][1]);
- cvSetIdentity(w, cvScalarAll(1));
- cvMul(w, &test_mat[INPUT][1], &test_mat[INPUT][1]);
- cvReleaseMat(&w);
- }
- }
- return code;
-}
-
-void CxCore_TransformTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- CvSize size = cvGetMatSize(&test_mat[INPUT][1]);
- sprintf( ptr, "matrix=%dx%d,", size.height, size.width );
- ptr += strlen(ptr);
- params_left--;
- CxCore_MatrixTest::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-
-double CxCore_TransformTest::get_success_error_level( int test_case_idx, int i, int j )
-{
- int depth = CV_MAT_DEPTH(test_mat[INPUT][0].type);
- return depth <= CV_8S ? 1 : depth <= CV_32S ? 9 :
- CxCore_MatrixTest::get_success_error_level( test_case_idx, i, j );
-}
-
-void CxCore_TransformTest::run_func()
-{
- cvTransform( test_array[INPUT][0], test_array[OUTPUT][0], &test_mat[INPUT][1],
- test_array[INPUT][2] ? &test_mat[INPUT][2] : 0);
-}
-
-
-void CxCore_TransformTest::prepare_to_validation( int )
-{
- CvMat* transmat = &test_mat[INPUT][1];
- CvMat* shift = test_array[INPUT][2] ? &test_mat[INPUT][2] : 0;
-
- cvTsTransform( &test_mat[INPUT][0], &test_mat[REF_OUTPUT][0], transmat, shift );
-}
-
-CxCore_TransformTest transform_test;
-
-
-///////////////// PerspectiveTransform /////////////////////
-
-static const int matrix_perspective_transform_channels[] = { 2, 3, -1 };
-
-class CxCore_PerspectiveTransformTest : public CxCore_MatrixTest
-{
-public:
- CxCore_PerspectiveTransformTest();
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- double get_success_error_level( int test_case_idx, int i, int j );
- void get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types,
- CvSize** whole_sizes, bool* are_images );
- void run_func();
- void prepare_to_validation( int test_case_idx );
-};
-
-
-CxCore_PerspectiveTransformTest::CxCore_PerspectiveTransformTest() :
- CxCore_MatrixTest( "matrix-perspective", "cvPerspectiveTransform", 2, 1, false, false, 2 )
-{
- default_timing_param_names = matrix_transform_param_names;
- cn_list = matrix_perspective_transform_channels;
- size_list = matrix_transform_sizes;
- whole_size_list = matrix_transform_whole_sizes;
-}
-
-
-void CxCore_PerspectiveTransformTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- int bits = cvTsRandInt(rng);
- int depth, cn, mattype;
- CxCore_MatrixTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
-
- cn = CV_MAT_CN(types[INPUT][0]) + 1;
- depth = CV_MAT_DEPTH(types[INPUT][0]);
- types[INPUT][0] = types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_MAKETYPE(depth, cn);
-
- mattype = depth == CV_64F ? CV_64F : bits & 1 ? CV_32F : CV_64F;
- types[INPUT][1] = mattype;
- sizes[INPUT][1] = cvSize(cn + 1, cn + 1);
-}
-
-
-double CxCore_PerspectiveTransformTest::get_success_error_level( int test_case_idx, int i, int j )
-{
- int depth = CV_MAT_DEPTH(test_mat[INPUT][0].type);
- return depth == CV_32F ? 1e-4 : depth == CV_64F ? 1e-8 :
- CxCore_MatrixTest::get_success_error_level(test_case_idx, i, j);
-}
-
-
-void CxCore_PerspectiveTransformTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool* are_images )
-{
- CxCore_MatrixTest::get_timing_test_array_types_and_sizes( test_case_idx,
- sizes, types, whole_sizes, are_images );
- int cn = CV_MAT_CN(types[INPUT][0]);
- sizes[INPUT][1] = cvSize(cn + 1, cn + 1);
- types[INPUT][1] = CV_64FC1;
-}
-
-
-void CxCore_PerspectiveTransformTest::run_func()
-{
- cvPerspectiveTransform( test_array[INPUT][0], test_array[OUTPUT][0], &test_mat[INPUT][1] );
-}
-
-
-static void cvTsPerspectiveTransform( const CvArr* _src, CvArr* _dst, const CvMat* transmat )
-{
- int i, j, cols;
- int cn, depth, mat_depth;
- CvMat astub, bstub, *a, *b;
- double mat[16], *buf;
-
- a = cvGetMat( _src, &astub, 0, 0 );
- b = cvGetMat( _dst, &bstub, 0, 0 );
-
- cn = CV_MAT_CN(a->type);
- depth = CV_MAT_DEPTH(a->type);
- mat_depth = CV_MAT_DEPTH(transmat->type);
- cols = transmat->cols;
-
- // prepare cn x (cn + 1) transform matrix
- if( mat_depth == CV_32F )
- {
- for( i = 0; i < transmat->rows; i++ )
- for( j = 0; j < cols; j++ )
- mat[i*cols + j] = ((float*)(transmat->data.ptr + transmat->step*i))[j];
- }
- else
- {
- assert( mat_depth == CV_64F );
- for( i = 0; i < transmat->rows; i++ )
- for( j = 0; j < cols; j++ )
- mat[i*cols + j] = ((double*)(transmat->data.ptr + transmat->step*i))[j];
- }
-
- // transform data
- cols = a->cols * cn;
- buf = (double*)cvStackAlloc( cols * sizeof(double) );
-
- for( i = 0; i < a->rows; i++ )
- {
- uchar* src = a->data.ptr + i*a->step;
- uchar* dst = b->data.ptr + i*b->step;
-
- switch( depth )
- {
- case CV_32F:
- for( j = 0; j < cols; j++ )
- buf[j] = ((float*)src)[j];
- break;
- case CV_64F:
- for( j = 0; j < cols; j++ )
- buf[j] = ((double*)src)[j];
- break;
- default:
- assert(0);
- }
-
- switch( cn )
- {
- case 2:
- for( j = 0; j < cols; j += 2 )
- {
- double t0 = buf[j]*mat[0] + buf[j+1]*mat[1] + mat[2];
- double t1 = buf[j]*mat[3] + buf[j+1]*mat[4] + mat[5];
- double w = buf[j]*mat[6] + buf[j+1]*mat[7] + mat[8];
- w = w ? 1./w : 0;
- buf[j] = t0*w;
- buf[j+1] = t1*w;
- }
- break;
- case 3:
- for( j = 0; j < cols; j += 3 )
- {
- double t0 = buf[j]*mat[0] + buf[j+1]*mat[1] + buf[j+2]*mat[2] + mat[3];
- double t1 = buf[j]*mat[4] + buf[j+1]*mat[5] + buf[j+2]*mat[6] + mat[7];
- double t2 = buf[j]*mat[8] + buf[j+1]*mat[9] + buf[j+2]*mat[10] + mat[11];
- double w = buf[j]*mat[12] + buf[j+1]*mat[13] + buf[j+2]*mat[14] + mat[15];
- w = w ? 1./w : 0;
- buf[j] = t0*w;
- buf[j+1] = t1*w;
- buf[j+2] = t2*w;
- }
- break;
- default:
- assert(0);
- }
-
- switch( depth )
- {
- case CV_32F:
- for( j = 0; j < cols; j++ )
- ((float*)dst)[j] = (float)buf[j];
- break;
- case CV_64F:
- for( j = 0; j < cols; j++ )
- ((double*)dst)[j] = buf[j];
- break;
- default:
- assert(0);
- }
- }
-}
-
-
-void CxCore_PerspectiveTransformTest::prepare_to_validation( int )
-{
- CvMat* transmat = &test_mat[INPUT][1];
- cvTsPerspectiveTransform( test_array[INPUT][0], test_array[REF_OUTPUT][0], transmat );
-}
-
-CxCore_PerspectiveTransformTest perspective_test;
-
-
-///////////////// Mahalanobis /////////////////////
-
-class CxCore_MahalanobisTest : public CxCore_MatrixTest
-{
-public:
- CxCore_MahalanobisTest();
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types,
- CvSize** whole_sizes, bool* are_images );
- int prepare_test_case( int test_case_idx );
- void run_func();
- void prepare_to_validation( int test_case_idx );
-};
-
-
-CxCore_MahalanobisTest::CxCore_MahalanobisTest() :
- CxCore_MatrixTest( "matrix-mahalanobis", "cvMahalanobis", 3, 1, false, true, 1 )
-{
- test_case_count = 100;
- test_array[TEMP].push(NULL);
- test_array[TEMP].push(NULL);
- test_array[TEMP].push(NULL);
-}
-
-
-void CxCore_MahalanobisTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- CxCore_MatrixTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
-
- if( cvTsRandInt(rng) & 1 )
- sizes[INPUT][0].width = sizes[INPUT][1].width = 1;
- else
- sizes[INPUT][0].height = sizes[INPUT][1].height = 1;
-
- sizes[TEMP][0] = sizes[TEMP][1] = sizes[INPUT][0];
- sizes[INPUT][2].width = sizes[INPUT][2].height = sizes[INPUT][0].width + sizes[INPUT][0].height - 1;
- sizes[TEMP][2] = sizes[INPUT][2];
- types[TEMP][0] = types[TEMP][1] = types[TEMP][2] = types[INPUT][0];
-}
-
-
-void CxCore_MahalanobisTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types, CvSize** whole_sizes, bool* are_images )
-{
- CxCore_MatrixTest::get_timing_test_array_types_and_sizes( test_case_idx,
- sizes, types, whole_sizes, are_images );
- sizes[INPUT][0].height = sizes[INPUT][1].height = 1;
-}
-
-
-int CxCore_MahalanobisTest::prepare_test_case( int test_case_idx )
-{
- int code = CxCore_MatrixTest::prepare_test_case( test_case_idx );
- if( code > 0 && ts->get_testing_mode() == CvTS::CORRECTNESS_CHECK_MODE )
- {
- // make sure that the inverted "covariation" matrix is symmetrix and positively defined.
- cvTsGEMM( &test_mat[INPUT][2], &test_mat[INPUT][2], 1., 0, 0., &test_mat[TEMP][2], CV_GEMM_B_T );
- cvTsCopy( &test_mat[TEMP][2], &test_mat[INPUT][2] );
- }
-
- return code;
-}
-
-
-void CxCore_MahalanobisTest::run_func()
-{
- *((CvScalar*)(test_mat[OUTPUT][0].data.db)) =
- cvRealScalar(cvMahalanobis(test_array[INPUT][0], test_array[INPUT][1], test_array[INPUT][2]));
-}
-
-void CxCore_MahalanobisTest::prepare_to_validation( int )
-{
- cvTsAdd( &test_mat[INPUT][0], cvScalarAll(1.),
- &test_mat[INPUT][1], cvScalarAll(-1.),
- cvScalarAll(0.), &test_mat[TEMP][0], 0 );
- if( test_mat[INPUT][0].rows == 1 )
- cvTsGEMM( &test_mat[TEMP][0], &test_mat[INPUT][2], 1.,
- 0, 0., &test_mat[TEMP][1], 0 );
- else
- cvTsGEMM( &test_mat[INPUT][2], &test_mat[TEMP][0], 1.,
- 0, 0., &test_mat[TEMP][1], 0 );
-
- *((CvScalar*)(test_mat[REF_OUTPUT][0].data.db)) =
- cvRealScalar(sqrt(cvTsCrossCorr(&test_mat[TEMP][0], &test_mat[TEMP][1])));
-}
-
-CxCore_MahalanobisTest mahalanobis_test;
-
-
-///////////////// covarmatrix /////////////////////
-
-class CxCore_CovarMatrixTest : public CxCore_MatrixTest
-{
-public:
- CxCore_CovarMatrixTest();
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- int prepare_test_case( int test_case_idx );
- void run_func();
- void prepare_to_validation( int test_case_idx );
- CvTestPtrVec temp_hdrs;
- uchar* hdr_data;
- int flags, t_flag, len, count;
- bool are_images;
-};
-
-
-CxCore_CovarMatrixTest::CxCore_CovarMatrixTest() :
- CxCore_MatrixTest( "matrix-covar", "cvCalcCovarMatrix", 1, 1, true, false, 1 ),
- flags(0), t_flag(0), are_images(false)
-{
- test_case_count = 100;
- test_array[INPUT_OUTPUT].push(NULL);
- test_array[REF_INPUT_OUTPUT].push(NULL);
- test_array[TEMP].push(NULL);
- test_array[TEMP].push(NULL);
-
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;
-}
-
-
-void CxCore_CovarMatrixTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- int bits = cvTsRandInt(rng);
- int i, single_matrix;
- CxCore_MatrixTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
-
- flags = bits & (CV_COVAR_NORMAL | CV_COVAR_USE_AVG | CV_COVAR_SCALE | CV_COVAR_ROWS );
- single_matrix = flags & CV_COVAR_ROWS;
- t_flag = (bits & 256) != 0;
-
- const int min_count = 2;
-
- if( !t_flag )
- {
- len = sizes[INPUT][0].width;
- count = sizes[INPUT][0].height;
- count = MAX(count, min_count);
- sizes[INPUT][0] = cvSize(len, count);
- }
- else
- {
- len = sizes[INPUT][0].height;
- count = sizes[INPUT][0].width;
- count = MAX(count, min_count);
- sizes[INPUT][0] = cvSize(count, len);
- }
-
- if( single_matrix && t_flag )
- flags = (flags & ~CV_COVAR_ROWS) | CV_COVAR_COLS;
-
- if( CV_MAT_DEPTH(types[INPUT][0]) == CV_32S )
- types[INPUT][0] = (types[INPUT][0] & ~CV_MAT_DEPTH_MASK) | CV_32F;
-
- sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = flags & CV_COVAR_NORMAL ? cvSize(len,len) : cvSize(count,count);
- sizes[INPUT_OUTPUT][0] = sizes[REF_INPUT_OUTPUT][0] = !t_flag ? cvSize(len,1) : cvSize(1,len);
- sizes[TEMP][0] = sizes[INPUT][0];
-
- types[INPUT_OUTPUT][0] = types[REF_INPUT_OUTPUT][0] =
- types[OUTPUT][0] = types[REF_OUTPUT][0] = types[TEMP][0] =
- CV_MAT_DEPTH(types[INPUT][0]) == CV_64F || (bits & 512) ? CV_64F : CV_32F;
-
- are_images = (bits & 1024) != 0;
- for( i = 0; i < (single_matrix ? 1 : count); i++ )
- temp_hdrs.push(NULL);
-}
-
-
-int CxCore_CovarMatrixTest::prepare_test_case( int test_case_idx )
-{
- int code = CxCore_MatrixTest::prepare_test_case( test_case_idx );
- if( code > 0 )
- {
- int i;
- int single_matrix = flags & (CV_COVAR_ROWS|CV_COVAR_COLS);
- int hdr_size = are_images ? sizeof(IplImage) : sizeof(CvMat);
-
- hdr_data = (uchar*)cvAlloc( count*hdr_size );
- if( single_matrix )
- {
- if( !are_images )
- *((CvMat*)hdr_data) = test_mat[INPUT][0];
- else
- cvGetImage( &test_mat[INPUT][0], (IplImage*)hdr_data );
- temp_hdrs[0] = hdr_data;
- }
- else
- for( i = 0; i < count; i++ )
- {
- CvMat part;
- void* ptr = hdr_data + i*hdr_size;
-
- if( !t_flag )
- cvGetRow( &test_mat[INPUT][0], &part, i );
- else
- cvGetCol( &test_mat[INPUT][0], &part, i );
-
- if( !are_images )
- *((CvMat*)ptr) = part;
- else
- cvGetImage( &part, (IplImage*)ptr );
-
- temp_hdrs[i] = ptr;
- }
- }
-
- return code;
-}
-
-
-void CxCore_CovarMatrixTest::run_func()
-{
- cvCalcCovarMatrix( (const void**)&temp_hdrs[0], count,
- test_array[OUTPUT][0], test_array[INPUT_OUTPUT][0], flags );
-}
-
-
-void CxCore_CovarMatrixTest::prepare_to_validation( int )
-{
- CvMat* avg = &test_mat[REF_INPUT_OUTPUT][0];
- double scale = 1.;
-
- if( !(flags & CV_COVAR_USE_AVG) )
- {
- int i;
- cvTsZero( avg );
-
- for( i = 0; i < count; i++ )
- {
- CvMat stub, *vec = 0;
- if( flags & CV_COVAR_ROWS )
- vec = cvGetRow( temp_hdrs[0], &stub, i );
- else if( flags & CV_COVAR_COLS )
- vec = cvGetCol( temp_hdrs[0], &stub, i );
- else
- vec = cvGetMat( temp_hdrs[i], &stub );
-
- cvTsAdd( avg, cvScalarAll(1.), vec,
- cvScalarAll(1.), cvScalarAll(0.), avg, 0 );
- }
-
- cvTsAdd( avg, cvScalarAll(1./count), 0,
- cvScalarAll(0.), cvScalarAll(0.), avg, 0 );
- }
-
- if( flags & CV_COVAR_SCALE )
- {
- scale = 1./count;
- }
-
- cvRepeat( avg, &test_mat[TEMP][0] );
- cvTsAdd( &test_mat[INPUT][0], cvScalarAll(1.),
- &test_mat[TEMP][0], cvScalarAll(-1.),
- cvScalarAll(0.), &test_mat[TEMP][0], 0 );
-
- cvTsGEMM( &test_mat[TEMP][0], &test_mat[TEMP][0],
- scale, 0, 0., &test_mat[REF_OUTPUT][0],
- t_flag ^ ((flags & CV_COVAR_NORMAL) != 0) ?
- CV_GEMM_A_T : CV_GEMM_B_T );
-
- cvFree( &hdr_data );
- temp_hdrs.clear();
-}
-
-CxCore_CovarMatrixTest covarmatrix_test;
-
-
-static void cvTsFloodWithZeros( CvMat* mat, CvRNG* rng )
-{
- int k, total = mat->rows*mat->cols;
- int zero_total = cvTsRandInt(rng) % total;
- assert( CV_MAT_TYPE(mat->type) == CV_32FC1 ||
- CV_MAT_TYPE(mat->type) == CV_64FC1 );
-
- for( k = 0; k < zero_total; k++ )
- {
- int i = cvTsRandInt(rng) % mat->rows;
- int j = cvTsRandInt(rng) % mat->cols;
- uchar* row = mat->data.ptr + mat->step*i;
-
- if( CV_MAT_DEPTH(mat->type) == CV_32FC1 )
- ((float*)row)[j] = 0.f;
- else
- ((double*)row)[j] = 0.;
- }
-}
-
-
-///////////////// determinant /////////////////////
-
-class CxCore_DetTest : public CxCore_MatrixTest
-{
-public:
- CxCore_DetTest();
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- double get_success_error_level( int test_case_idx, int i, int j );
- void get_minmax_bounds( int /*i*/, int /*j*/, int /*type*/, CvScalar* low, CvScalar* high );
- int prepare_test_case( int test_case_idx );
- void run_func();
- void prepare_to_validation( int test_case_idx );
-};
-
-
-CxCore_DetTest::CxCore_DetTest() :
- CxCore_MatrixTest( "matrix-det", "cvDet", 1, 1, false, true, 1 )
-{
- test_case_count = 100;
- max_log_array_size = 7;
- test_array[TEMP].push(NULL);
-}
-
-
-void CxCore_DetTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CxCore_MatrixTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
-
- sizes[INPUT][0].width = sizes[INPUT][0].height = sizes[INPUT][0].height;
- sizes[TEMP][0] = sizes[INPUT][0];
- types[TEMP][0] = CV_64FC1;
-}
-
-
-void CxCore_DetTest::get_minmax_bounds( int /*i*/, int /*j*/, int /*type*/, CvScalar* low, CvScalar* high )
-{
- *low = cvScalarAll(-2.);
- *high = cvScalarAll(2.);
-}
-
-
-double CxCore_DetTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- return CV_MAT_DEPTH(cvGetElemType(test_array[INPUT][0])) == CV_32F ? 1e-2 : 1e-5;
-}
-
-
-int CxCore_DetTest::prepare_test_case( int test_case_idx )
-{
- int code = CxCore_MatrixTest::prepare_test_case( test_case_idx );
- if( code > 0 )
- cvTsFloodWithZeros( &test_mat[INPUT][0], ts->get_rng() );
-
- return code;
-}
-
-
-void CxCore_DetTest::run_func()
-{
- *((CvScalar*)(test_mat[OUTPUT][0].data.db)) = cvRealScalar(cvDet(test_array[INPUT][0]));
-}
-
-
-// LU method that chooses the optimal in a column pivot element
-static double cvTsLU( CvMat* a, CvMat* b=NULL, CvMat* x=NULL, int* rank=0 )
-{
- int i, j, k, N = a->rows, N1 = a->cols, Nm = MIN(N, N1), step = a->step/sizeof(double);
- int M = b ? b->cols : 0, b_step = b ? b->step/sizeof(double) : 0;
- int x_step = x ? x->step/sizeof(double) : 0;
- double *a0 = a->data.db, *b0 = b ? b->data.db : 0;
- double *x0 = x ? x->data.db : 0;
- double t, det = 1.;
- assert( CV_MAT_TYPE(a->type) == CV_64FC1 &&
- (!b || CV_ARE_TYPES_EQ(a,b)) && (!x || CV_ARE_TYPES_EQ(a,x)));
-
- for( i = 0; i < Nm; i++ )
- {
- double max_val = fabs(a0[i*step + i]);
- double *a1, *a2, *b1 = 0, *b2 = 0;
- k = i;
-
- for( j = i+1; j < N; j++ )
- {
- t = fabs(a0[j*step + i]);
- if( max_val < t )
- {
- max_val = t;
- k = j;
- }
- }
-
- if( k != i )
- {
- for( j = i; j < N1; j++ )
- CV_SWAP( a0[i*step + j], a0[k*step + j], t );
-
- for( j = 0; j < M; j++ )
- CV_SWAP( b0[i*b_step + j], b0[k*b_step + j], t );
- det = -det;
- }
-
- if( max_val == 0 )
- {
- if( rank )
- *rank = i;
- return 0.;
- }
-
- a1 = a0 + i*step;
- a2 = a1 + step;
- b1 = b0 + i*b_step;
- b2 = b1 + b_step;
-
- for( j = i+1; j < N; j++, a2 += step, b2 += b_step )
- {
- t = a2[i]/a1[i];
- for( k = i+1; k < N1; k++ )
- a2[k] -= t*a1[k];
-
- for( k = 0; k < M; k++ )
- b2[k] -= t*b1[k];
- }
-
- det *= a1[i];
- }
-
- if( x )
- {
- assert( b );
-
- for( i = N-1; i >= 0; i-- )
- {
- double* a1 = a0 + i*step;
- double* b1 = b0 + i*b_step;
- for( j = 0; j < M; j++ )
- {
- t = b1[j];
- for( k = i+1; k < N1; k++ )
- t -= a1[k]*x0[k*x_step + j];
- x0[i*x_step + j] = t/a1[i];
- }
- }
- }
-
- if( rank )
- *rank = i;
- return det;
-}
-
-
-void CxCore_DetTest::prepare_to_validation( int )
-{
- if( !CV_ARE_TYPES_EQ( &test_mat[INPUT][0], &test_mat[TEMP][0] ))
- cvTsConvert( &test_mat[INPUT][0], &test_mat[TEMP][0] );
- else
- cvTsCopy( &test_mat[INPUT][0], &test_mat[TEMP][0], 0 );
-
- *((CvScalar*)(test_mat[REF_OUTPUT][0].data.db)) = cvRealScalar(cvTsLU(&test_mat[TEMP][0], 0, 0));
-}
-
-CxCore_DetTest det_test;
-
-
-
-///////////////// invert /////////////////////
-
-static const char* matrix_solve_invert_param_names[] = { "size", "method", "depth", 0 };
-static const char* matrix_solve_invert_methods[] = { "LU", "SVD", 0 };
-
-class CxCore_InvertTest : public CxCore_MatrixTest
-{
-public:
- CxCore_InvertTest();
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types,
- CvSize** whole_sizes, bool* are_images );
- int write_default_params( CvFileStorage* fs );
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
- void get_minmax_bounds( int /*i*/, int /*j*/, int /*type*/, CvScalar* low, CvScalar* high );
- double get_success_error_level( int test_case_idx, int i, int j );
- int prepare_test_case( int test_case_idx );
- void run_func();
- void prepare_to_validation( int test_case_idx );
- int method, rank;
- double result;
-};
-
-
-CxCore_InvertTest::CxCore_InvertTest() :
- CxCore_MatrixTest( "matrix-invert", "cvInvert, cvSVD, cvSVBkSb", 1, 1, false, false, 1 ), method(0), rank(0), result(0.)
-{
- test_case_count = 100;
- max_log_array_size = 7;
- test_array[TEMP].push(NULL);
- test_array[TEMP].push(NULL);
-
- default_timing_param_names = matrix_solve_invert_param_names;
-}
-
-
-void CxCore_InvertTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- int bits = cvTsRandInt(rng);
- CxCore_MatrixTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- int min_size = MIN( sizes[INPUT][0].width, sizes[INPUT][0].height );
-
- if( (bits & 3) == 0 )
- {
- method = CV_SVD;
- if( bits & 4 )
- {
- sizes[INPUT][0] = cvSize(min_size, min_size);
- if( bits & 16 )
- method = CV_CHOLESKY;
- }
- }
- else
- {
- method = CV_LU;
- sizes[INPUT][0] = cvSize(min_size, min_size);
- }
-
- sizes[TEMP][0].width = sizes[INPUT][0].height;
- sizes[TEMP][0].height = sizes[INPUT][0].width;
- sizes[TEMP][1] = sizes[INPUT][0];
- types[TEMP][0] = types[INPUT][0];
- types[TEMP][1] = CV_64FC1;
- sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = cvSize(min_size, min_size);
-}
-
-
-void CxCore_InvertTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types,
- CvSize** whole_sizes, bool* are_images )
-{
- CxCore_MatrixTest::get_timing_test_array_types_and_sizes( test_case_idx,
- sizes, types, whole_sizes, are_images );
- const char* method_str = cvReadString( find_timing_param("method"), "LU" );
- method = strcmp( method_str, "LU" ) == 0 ? CV_LU : CV_SVD;
-}
-
-
-int CxCore_InvertTest::write_default_params( CvFileStorage* fs )
-{
- int code = CxCore_MatrixTest::write_default_params(fs);
- if( code < 0 || ts->get_testing_mode() != CvTS::TIMING_MODE )
- return code;
- write_string_list( fs, "method", matrix_solve_invert_methods );
- return code;
-}
-
-
-void CxCore_InvertTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- sprintf( ptr, "%s,", method == CV_LU ? "LU" : "SVD" );
- ptr += strlen(ptr);
- params_left--;
- CxCore_MatrixTest::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-
-double CxCore_InvertTest::get_success_error_level( int /*test_case_idx*/, int, int )
-{
- return CV_MAT_DEPTH(cvGetElemType(test_array[OUTPUT][0])) == CV_32F ? 1e-2 : 1e-6;
-}
-
-int CxCore_InvertTest::prepare_test_case( int test_case_idx )
-{
- int code = CxCore_MatrixTest::prepare_test_case( test_case_idx );
- if( code > 0 )
- {
- cvTsFloodWithZeros( &test_mat[INPUT][0], ts->get_rng() );
-
- if( method == CV_CHOLESKY )
- {
- cvTsGEMM( &test_mat[INPUT][0], &test_mat[INPUT][0], 1.,
- 0, 0., &test_mat[TEMP][0], CV_GEMM_B_T );
- cvTsCopy( &test_mat[TEMP][0], &test_mat[INPUT][0] );
- }
- }
-
- return code;
-}
-
-
-
-void CxCore_InvertTest::get_minmax_bounds( int /*i*/, int /*j*/, int /*type*/, CvScalar* low, CvScalar* high )
-{
- *low = cvScalarAll(-1.);
- *high = cvScalarAll(1.);
-}
-
-
-void CxCore_InvertTest::run_func()
-{
- result = cvInvert(test_array[INPUT][0], test_array[TEMP][0], method);
-}
-
-
-static double cvTsSVDet( CvMat* mat, double* ratio )
-{
- int type = CV_MAT_TYPE(mat->type);
- int i, nm = MIN( mat->rows, mat->cols );
- CvMat* w = cvCreateMat( nm, 1, type );
- double det = 1.;
-
- cvSVD( mat, w, 0, 0, 0 );
-
- if( type == CV_32FC1 )
- {
- for( i = 0; i < nm; i++ )
- det *= w->data.fl[i];
- *ratio = w->data.fl[nm-1] < FLT_EPSILON ? FLT_MAX : w->data.fl[nm-1]/w->data.fl[0];
- }
- else
- {
- for( i = 0; i < nm; i++ )
- det *= w->data.db[i];
- *ratio = w->data.db[nm-1] < FLT_EPSILON ? DBL_MAX : w->data.db[nm-1]/w->data.db[0];
- }
-
- cvReleaseMat( &w );
- return det;
-}
-
-void CxCore_InvertTest::prepare_to_validation( int )
-{
- CvMat* input = &test_mat[INPUT][0];
- double ratio = 0, det = cvTsSVDet( input, &ratio );
- double threshold = (CV_MAT_DEPTH(input->type) == CV_32F ? FLT_EPSILON : DBL_EPSILON)*1000;
-
- if( CV_MAT_TYPE(input->type) == CV_32FC1 )
- cvTsConvert( input, &test_mat[TEMP][1] );
- else
- cvTsCopy( input, &test_mat[TEMP][1], 0 );
-
- if( det < threshold ||
- ((method == CV_LU || method == CV_CHOLESKY) && (result == 0 || ratio < threshold)) ||
- ((method == CV_SVD || method == CV_SVD_SYM) && result < threshold) )
- {
- cvTsZero( &test_mat[OUTPUT][0] );
- cvTsZero( &test_mat[REF_OUTPUT][0] );
- //cvTsAdd( 0, cvScalarAll(0.), 0, cvScalarAll(0.), cvScalarAll(fabs(det)>1e-3),
- // &test_mat[REF_OUTPUT][0], 0 );
- return;
- }
-
- if( input->rows >= input->cols )
- cvTsGEMM( &test_mat[TEMP][0], input, 1., 0, 0., &test_mat[OUTPUT][0], 0 );
- else
- cvTsGEMM( input, &test_mat[TEMP][0], 1., 0, 0., &test_mat[OUTPUT][0], 0 );
-
- cvTsSetIdentity( &test_mat[REF_OUTPUT][0], cvScalarAll(1.) );
-}
-
-CxCore_InvertTest invert_test;
-
-
-///////////////// solve /////////////////////
-
-class CxCore_SolveTest : public CxCore_MatrixTest
-{
-public:
- CxCore_SolveTest();
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types,
- CvSize** whole_sizes, bool* are_images );
- int write_default_params( CvFileStorage* fs );
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
- void get_minmax_bounds( int /*i*/, int /*j*/, int /*type*/, CvScalar* low, CvScalar* high );
- double get_success_error_level( int test_case_idx, int i, int j );
- int prepare_test_case( int test_case_idx );
- void run_func();
- void prepare_to_validation( int test_case_idx );
- int method, rank;
- double result;
-};
-
-
-CxCore_SolveTest::CxCore_SolveTest() :
- CxCore_MatrixTest( "matrix-solve", "cvSolve, cvSVD, cvSVBkSb", 2, 1, false, false, 1 ), method(0), rank(0), result(0.)
-{
- test_case_count = 100;
- max_log_array_size = 7;
- test_array[TEMP].push(NULL);
- test_array[TEMP].push(NULL);
-
- default_timing_param_names = matrix_solve_invert_param_names;
-}
-
-
-void CxCore_SolveTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- int bits = cvTsRandInt(rng);
- CxCore_MatrixTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- CvSize in_sz = sizes[INPUT][0];
- CxCore_MatrixTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- sizes[INPUT][0] = in_sz;
- int min_size = MIN( sizes[INPUT][0].width, sizes[INPUT][0].height );
-
- if( (bits & 3) == 0 )
- {
- method = CV_SVD;
- if( bits & 4 )
- {
- sizes[INPUT][0] = cvSize(min_size, min_size);
- /*if( bits & 8 )
- method = CV_SVD_SYM;*/
- }
- }
- else
- {
- method = CV_LU;
- sizes[INPUT][0] = cvSize(min_size, min_size);
- }
-
- sizes[INPUT][1].height = sizes[INPUT][0].height;
- sizes[TEMP][0].width = sizes[INPUT][1].width;
- sizes[TEMP][0].height = sizes[INPUT][0].width;
- sizes[TEMP][1] = sizes[INPUT][0];
- types[TEMP][0] = types[INPUT][0];
- types[TEMP][1] = CV_64FC1;
- sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = cvSize(sizes[INPUT][1].width, min_size);
-}
-
-void CxCore_SolveTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types,
- CvSize** whole_sizes, bool* are_images )
-{
- CxCore_MatrixTest::get_timing_test_array_types_and_sizes( test_case_idx,
- sizes, types, whole_sizes, are_images );
- const char* method_str = cvReadString( find_timing_param("method"), "LU" );
- sizes[INPUT][1].width = sizes[TEMP][0].width = sizes[OUTPUT][0].width = sizes[REF_OUTPUT][0].width = 1;
- method = strcmp( method_str, "LU" ) == 0 ? CV_LU : CV_SVD;
-}
-
-
-int CxCore_SolveTest::write_default_params( CvFileStorage* fs )
-{
- int code = CxCore_MatrixTest::write_default_params(fs);
- if( code < 0 || ts->get_testing_mode() != CvTS::TIMING_MODE )
- return code;
- write_string_list( fs, "method", matrix_solve_invert_methods );
- return code;
-}
-
-
-void CxCore_SolveTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- sprintf( ptr, "%s,", method == CV_LU ? "LU" : "SVD" );
- ptr += strlen(ptr);
- params_left--;
- CxCore_MatrixTest::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-
-int CxCore_SolveTest::prepare_test_case( int test_case_idx )
-{
- int code = CxCore_MatrixTest::prepare_test_case( test_case_idx );
-
- /*if( method == CV_SVD_SYM )
- {
- cvTsGEMM( test_array[INPUT][0], test_array[INPUT][0], 1.,
- 0, 0., test_array[TEMP][0], CV_GEMM_B_T );
- cvTsCopy( test_array[TEMP][0], test_array[INPUT][0] );
- }*/
-
- return code;
-}
-
-
-void CxCore_SolveTest::get_minmax_bounds( int /*i*/, int /*j*/, int /*type*/, CvScalar* low, CvScalar* high )
-{
- *low = cvScalarAll(-1.);
- *high = cvScalarAll(1.);
-}
-
-
-double CxCore_SolveTest::get_success_error_level( int /*test_case_idx*/, int, int )
-{
- return CV_MAT_DEPTH(cvGetElemType(test_array[OUTPUT][0])) == CV_32F ? 5e-2 : 1e-8;
-}
-
-
-void CxCore_SolveTest::run_func()
-{
- result = cvSolve(test_array[INPUT][0], test_array[INPUT][1], test_array[TEMP][0], method);
-}
-
-void CxCore_SolveTest::prepare_to_validation( int )
-{
- //int rank = test_mat[REF_OUTPUT][0].rows;
- CvMat* dst;
- CvMat* input = &test_mat[INPUT][0];
-
- if( method == CV_LU )
- {
- if( result == 0 )
- {
- if( CV_MAT_TYPE(input->type) == CV_32FC1 )
- cvTsConvert( input, &test_mat[TEMP][1] );
- else
- cvTsCopy( input, &test_mat[TEMP][1], 0 );
-
- cvTsZero( &test_mat[OUTPUT][0] );
- double det = cvTsLU( &test_mat[TEMP][1], 0, 0 );
- cvTsAdd( 0, cvScalarAll(0.), 0, cvScalarAll(0.), cvScalarAll(det != 0),
- &test_mat[REF_OUTPUT][0], 0 );
- return;
- }
-
- double threshold = (CV_MAT_DEPTH(input->type) == CV_32F ? FLT_EPSILON : DBL_EPSILON)*1000;
- double ratio = 0, det = cvTsSVDet( input, &ratio );
- if( det < threshold || ratio < threshold )
- {
- cvTsZero( &test_mat[OUTPUT][0] );
- cvTsZero( &test_mat[REF_OUTPUT][0] );
- return;
- }
- }
-
-
- dst = input->rows <= input->cols ? &test_mat[OUTPUT][0] : &test_mat[INPUT][1];
-
- cvTsGEMM( input, &test_mat[TEMP][0], 1., &test_mat[INPUT][1], -1., dst, 0 );
- if( dst != &test_mat[OUTPUT][0] )
- cvTsGEMM( input, dst, 1., 0, 0., &test_mat[OUTPUT][0], CV_GEMM_A_T );
- cvTsZero( &test_mat[REF_OUTPUT][0] );
-}
-
-CxCore_SolveTest solve_test;
-
-
-///////////////// SVD /////////////////////
-
-static const char* matrix_svd_param_names[] = { "size", "output", "depth", 0 };
-static const char* matrix_svd_output_modes[] = { "w", "all", 0 };
-
-class CxCore_SVDTest : public CxCore_MatrixTest
-{
-public:
- CxCore_SVDTest();
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types,
- CvSize** whole_sizes, bool* are_images );
- double get_success_error_level( int test_case_idx, int i, int j );
- int write_default_params( CvFileStorage* fs );
- void print_timing_params( int test_case_idx, char* ptr, int params_left );
- void get_minmax_bounds( int /*i*/, int /*j*/, int /*type*/, CvScalar* low, CvScalar* high );
- int prepare_test_case( int test_case_idx );
- void run_func();
- void prepare_to_validation( int test_case_idx );
- int flags;
- bool have_u, have_v, symmetric, compact, vector_w;
-};
-
-
-CxCore_SVDTest::CxCore_SVDTest() :
- CxCore_MatrixTest( "matrix-svd", "cvSVD", 1, 4, false, false, 1 ),
- flags(0), have_u(false), have_v(false), symmetric(false), compact(false), vector_w(false)
-{
- test_case_count = 100;
- test_array[TEMP].push(NULL);
- test_array[TEMP].push(NULL);
- test_array[TEMP].push(NULL);
- test_array[TEMP].push(NULL);
-
- default_timing_param_names = matrix_svd_param_names;
-}
-
-
-void CxCore_SVDTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- int bits = cvTsRandInt(rng);
- CxCore_MatrixTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- int min_size, i, m, n;
-
- min_size = MIN( sizes[INPUT][0].width, sizes[INPUT][0].height );
-
- flags = bits & (CV_SVD_MODIFY_A+CV_SVD_U_T+CV_SVD_V_T);
- have_u = (bits & 8) != 0;
- have_v = (bits & 16) != 0;
- symmetric = (bits & 32) != 0;
- compact = (bits & 64) != 0;
- vector_w = (bits & 128) != 0;
-
- if( symmetric )
- sizes[INPUT][0] = cvSize(min_size, min_size);
-
- m = sizes[INPUT][0].height;
- n = sizes[INPUT][0].width;
-
- if( compact )
- sizes[TEMP][0] = cvSize(min_size, min_size);
- else
- sizes[TEMP][0] = sizes[INPUT][0];
- sizes[TEMP][3] = cvSize(0,0);
-
- if( vector_w )
- {
- sizes[TEMP][3] = sizes[TEMP][0];
- if( bits & 256 )
- sizes[TEMP][0] = cvSize(1, min_size);
- else
- sizes[TEMP][0] = cvSize(min_size, 1);
- }
-
- if( have_u )
- {
- sizes[TEMP][1] = compact ? cvSize(min_size, m) : cvSize(m, m);
-
- if( flags & CV_SVD_U_T )
- CV_SWAP( sizes[TEMP][1].width, sizes[TEMP][1].height, i );
- }
- else
- sizes[TEMP][1] = cvSize(0,0);
-
- if( have_v )
- {
- sizes[TEMP][2] = compact ? cvSize(n, min_size) : cvSize(n, n);
-
- if( !(flags & CV_SVD_V_T) )
- CV_SWAP( sizes[TEMP][2].width, sizes[TEMP][2].height, i );
- }
- else
- sizes[TEMP][2] = cvSize(0,0);
-
- types[TEMP][0] = types[TEMP][1] = types[TEMP][2] = types[TEMP][3] = types[INPUT][0];
- types[OUTPUT][0] = types[OUTPUT][1] = types[OUTPUT][2] = types[INPUT][0];
- types[OUTPUT][3] = CV_8UC1;
- sizes[OUTPUT][0] = !have_u || !have_v ? cvSize(0,0) : sizes[INPUT][0];
- sizes[OUTPUT][1] = !have_u ? cvSize(0,0) : compact ? cvSize(min_size,min_size) : cvSize(m,m);
- sizes[OUTPUT][2] = !have_v ? cvSize(0,0) : compact ? cvSize(min_size,min_size) : cvSize(n,n);
- sizes[OUTPUT][3] = cvSize(min_size,1);
-
- for( i = 0; i < 4; i++ )
- {
- sizes[REF_OUTPUT][i] = sizes[OUTPUT][i];
- types[REF_OUTPUT][i] = types[OUTPUT][i];
- }
-}
-
-
-void CxCore_SVDTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types,
- CvSize** whole_sizes, bool* are_images )
-{
- CxCore_MatrixTest::get_timing_test_array_types_and_sizes( test_case_idx,
- sizes, types, whole_sizes, are_images );
- const char* output_str = cvReadString( find_timing_param("output"), "all" );
- bool need_all = strcmp( output_str, "all" ) == 0;
- int i, count = test_array[OUTPUT].size();
- vector_w = true;
- symmetric = false;
- compact = true;
- sizes[TEMP][0] = cvSize(1,sizes[INPUT][0].height);
- if( need_all )
- {
- have_u = have_v = true;
- }
- else
- {
- have_u = have_v = false;
- sizes[TEMP][1] = sizes[TEMP][2] = cvSize(0,0);
- }
-
- flags = CV_SVD_U_T + CV_SVD_V_T;
- for( i = 0; i < count; i++ )
- sizes[OUTPUT][i] = sizes[REF_OUTPUT][i] = cvSize(0,0);
- sizes[OUTPUT][0] = cvSize(1,1);
-}
-
-
-int CxCore_SVDTest::write_default_params( CvFileStorage* fs )
-{
- int code = CxCore_MatrixTest::write_default_params(fs);
- if( code < 0 || ts->get_testing_mode() != CvTS::TIMING_MODE )
- return code;
- write_string_list( fs, "output", matrix_svd_output_modes );
- return code;
-}
-
-
-void CxCore_SVDTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
-{
- sprintf( ptr, "%s,", have_u ? "all" : "w" );
- ptr += strlen(ptr);
- params_left--;
- CxCore_MatrixTest::print_timing_params( test_case_idx, ptr, params_left );
-}
-
-
-int CxCore_SVDTest::prepare_test_case( int test_case_idx )
-{
- int code = CxCore_MatrixTest::prepare_test_case( test_case_idx );
- if( code > 0 )
- {
- CvMat* input = &test_mat[INPUT][0];
- cvTsFloodWithZeros( input, ts->get_rng() );
-
- if( symmetric && (have_u || have_v) )
- {
- CvMat* temp = &test_mat[TEMP][have_u ? 1 : 2];
- cvTsGEMM( input, input, 1.,
- 0, 0., temp, CV_GEMM_B_T );
- cvTsCopy( temp, input );
- }
-
- if( (flags & CV_SVD_MODIFY_A) && test_array[OUTPUT][0] )
- cvTsCopy( input, &test_mat[OUTPUT][0] );
- }
-
- return code;
-}
-
-
-void CxCore_SVDTest::get_minmax_bounds( int /*i*/, int /*j*/, int /*type*/, CvScalar* low, CvScalar* high )
-{
- *low = cvScalarAll(-2.);
- *high = cvScalarAll(2.);
-}
-
-double CxCore_SVDTest::get_success_error_level( int test_case_idx, int i, int j )
-{
- int input_depth = CV_MAT_DEPTH(cvGetElemType( test_array[INPUT][0] ));
- double input_precision = input_depth < CV_32F ? 0 : input_depth == CV_32F ?
- 5e-5 : 5e-11;
- double output_precision = CvArrTest::get_success_error_level( test_case_idx, i, j );
- return MAX(input_precision, output_precision);
-}
-
-void CxCore_SVDTest::run_func()
-{
- CvArr* src = test_array[!(flags & CV_SVD_MODIFY_A) ? INPUT : OUTPUT][0];
- if( !src )
- src = test_array[INPUT][0];
- cvSVD( src, test_array[TEMP][0], test_array[TEMP][1], test_array[TEMP][2], flags );
-}
-
-
-void CxCore_SVDTest::prepare_to_validation( int )
-{
- CvMat* input = &test_mat[INPUT][0];
- int m = input->rows, n = input->cols, min_size = MIN(m, n);
- CvMat *src, *dst, *w;
- double prev = 0, threshold = CV_MAT_TYPE(input->type) == CV_32FC1 ? FLT_EPSILON : DBL_EPSILON;
- int i, j = 0, step;
-
- if( have_u )
- {
- src = &test_mat[TEMP][1];
- dst = &test_mat[OUTPUT][1];
- cvTsGEMM( src, src, 1., 0, 0., dst, src->rows == dst->rows ? CV_GEMM_B_T : CV_GEMM_A_T );
- cvTsSetIdentity( &test_mat[REF_OUTPUT][1], cvScalarAll(1.) );
- }
-
- if( have_v )
- {
- src = &test_mat[TEMP][2];
- dst = &test_mat[OUTPUT][2];
- cvTsGEMM( src, src, 1., 0, 0., dst, src->rows == dst->rows ? CV_GEMM_B_T : CV_GEMM_A_T );
- cvTsSetIdentity( &test_mat[REF_OUTPUT][2], cvScalarAll(1.) );
- }
-
- w = &test_mat[TEMP][0];
- step = w->rows == 1 ? 1 : w->step/CV_ELEM_SIZE(w->type);
- for( i = 0; i < min_size; i++ )
- {
- double norm = 0, aii;
- uchar* row_ptr;
- if( w->rows > 1 && w->cols > 1 )
- {
- CvMat row;
- cvGetRow( w, &row, i );
- norm = cvNorm( &row, 0, CV_L1 );
- j = i;
- row_ptr = row.data.ptr;
- }
- else
- {
- row_ptr = w->data.ptr;
- j = i*step;
- }
-
- aii = CV_MAT_TYPE(w->type) == CV_32FC1 ?
- (double)((float*)row_ptr)[j] : ((double*)row_ptr)[j];
- if( w->rows == 1 || w->cols == 1 )
- norm = aii;
- norm = fabs(norm - aii);
- test_mat[OUTPUT][3].data.ptr[i] = aii >= 0 && norm < threshold && (i == 0 || aii <= prev);
- prev = aii;
- }
-
- cvTsAdd( 0, cvScalarAll(0.), 0, cvScalarAll(0.),
- cvScalarAll(1.), &test_mat[REF_OUTPUT][3], 0 );
-
- if( have_u && have_v )
- {
- if( vector_w )
- {
- cvTsZero( &test_mat[TEMP][3] );
- for( i = 0; i < min_size; i++ )
- {
- double val = cvGetReal1D( w, i );
- cvSetReal2D( &test_mat[TEMP][3], i, i, val );
- }
- w = &test_mat[TEMP][3];
- }
-
- if( m >= n )
- {
- cvTsGEMM( &test_mat[TEMP][1], w, 1., 0, 0., &test_mat[REF_OUTPUT][0],
- flags & CV_SVD_U_T ? CV_GEMM_A_T : 0 );
- cvTsGEMM( &test_mat[REF_OUTPUT][0], &test_mat[TEMP][2], 1., 0, 0.,
- &test_mat[OUTPUT][0], flags & CV_SVD_V_T ? 0 : CV_GEMM_B_T );
- }
- else
- {
- cvTsGEMM( w, &test_mat[TEMP][2], 1., 0, 0., &test_mat[REF_OUTPUT][0],
- flags & CV_SVD_V_T ? 0 : CV_GEMM_B_T );
- cvTsGEMM( &test_mat[TEMP][1], &test_mat[REF_OUTPUT][0], 1., 0, 0.,
- &test_mat[OUTPUT][0], flags & CV_SVD_U_T ? CV_GEMM_A_T : 0 );
- }
-
- cvTsCopy( &test_mat[INPUT][0], &test_mat[REF_OUTPUT][0], 0 );
- }
-}
-
-
-CxCore_SVDTest svd_test;
-
-
-///////////////// SVBkSb /////////////////////
-
-class CxCore_SVBkSbTest : public CxCore_MatrixTest
-{
-public:
- CxCore_SVBkSbTest();
-protected:
- void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- void get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types,
- CvSize** whole_sizes, bool* are_images );
- double get_success_error_level( int test_case_idx, int i, int j );
- void get_minmax_bounds( int /*i*/, int /*j*/, int /*type*/, CvScalar* low, CvScalar* high );
- int prepare_test_case( int test_case_idx );
- void run_func();
- void prepare_to_validation( int test_case_idx );
- int flags;
- bool have_b, symmetric, compact, vector_w;
-};
-
-
-CxCore_SVBkSbTest::CxCore_SVBkSbTest() :
- CxCore_MatrixTest( "matrix-svbksb", "cvSVBkSb", 2, 1, false, false, 1 ),
- flags(0), have_b(false), symmetric(false), compact(false), vector_w(false)
-{
- test_case_count = 100;
- test_array[TEMP].push(NULL);
- test_array[TEMP].push(NULL);
- test_array[TEMP].push(NULL);
-}
-
-
-void CxCore_SVBkSbTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- int bits = cvTsRandInt(rng);
- CxCore_MatrixTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
- int min_size, i, m, n;
- CvSize b_size;
-
- min_size = MIN( sizes[INPUT][0].width, sizes[INPUT][0].height );
-
- flags = bits & (CV_SVD_MODIFY_A+CV_SVD_U_T+CV_SVD_V_T);
- have_b = (bits & 16) != 0;
- symmetric = (bits & 32) != 0;
- compact = (bits & 64) != 0;
- vector_w = (bits & 128) != 0;
-
- if( symmetric )
- sizes[INPUT][0] = cvSize(min_size, min_size);
-
- m = sizes[INPUT][0].height;
- n = sizes[INPUT][0].width;
-
- sizes[INPUT][1] = cvSize(0,0);
- b_size = cvSize(m,m);
- if( have_b )
- {
- sizes[INPUT][1].height = sizes[INPUT][0].height;
- sizes[INPUT][1].width = cvTsRandInt(rng) % 100 + 1;
- b_size = sizes[INPUT][1];
- }
-
- if( compact )
- sizes[TEMP][0] = cvSize(min_size, min_size);
- else
- sizes[TEMP][0] = sizes[INPUT][0];
-
- if( vector_w )
- {
- if( bits & 256 )
- sizes[TEMP][0] = cvSize(1, min_size);
- else
- sizes[TEMP][0] = cvSize(min_size, 1);
- }
-
- sizes[TEMP][1] = compact ? cvSize(min_size, m) : cvSize(m, m);
-
- if( flags & CV_SVD_U_T )
- CV_SWAP( sizes[TEMP][1].width, sizes[TEMP][1].height, i );
-
- sizes[TEMP][2] = compact ? cvSize(n, min_size) : cvSize(n, n);
-
- if( !(flags & CV_SVD_V_T) )
- CV_SWAP( sizes[TEMP][2].width, sizes[TEMP][2].height, i );
-
- types[TEMP][0] = types[TEMP][1] = types[TEMP][2] = types[INPUT][0];
- types[OUTPUT][0] = types[REF_OUTPUT][0] = types[INPUT][0];
- sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = cvSize( b_size.width, n );
-}
-
-
-void CxCore_SVBkSbTest::get_timing_test_array_types_and_sizes( int test_case_idx,
- CvSize** sizes, int** types,
- CvSize** whole_sizes, bool* are_images )
-{
- CxCore_MatrixTest::get_timing_test_array_types_and_sizes( test_case_idx,
- sizes, types, whole_sizes, are_images );
- have_b = true;
- vector_w = true;
- compact = true;
- sizes[TEMP][0] = cvSize(1,sizes[INPUT][0].height);
- sizes[INPUT][1] = sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = cvSize(1,sizes[INPUT][0].height);
- flags = CV_SVD_U_T + CV_SVD_V_T;
-}
-
-
-int CxCore_SVBkSbTest::prepare_test_case( int test_case_idx )
-{
- int code = CxCore_MatrixTest::prepare_test_case( test_case_idx );
- if( code > 0 )
- {
- CvMat* input = &test_mat[INPUT][0];
- cvTsFloodWithZeros( input, ts->get_rng() );
-
- if( symmetric )
- {
- CvMat* temp = &test_mat[TEMP][1];
- cvTsGEMM( input, input, 1., 0, 0., temp, CV_GEMM_B_T );
- cvTsCopy( temp, input );
- }
-
- cvSVD( input, test_array[TEMP][0], test_array[TEMP][1], test_array[TEMP][2], flags );
- }
-
- return code;
-}
-
-
-void CxCore_SVBkSbTest::get_minmax_bounds( int /*i*/, int /*j*/, int /*type*/, CvScalar* low, CvScalar* high )
-{
- *low = cvScalarAll(-2.);
- *high = cvScalarAll(2.);
-}
-
-
-double CxCore_SVBkSbTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
-{
- return CV_MAT_DEPTH(cvGetElemType(test_array[INPUT][0])) == CV_32F ? 1e-3 : 1e-7;
-}
-
-
-void CxCore_SVBkSbTest::run_func()
-{
- cvSVBkSb( test_array[TEMP][0], test_array[TEMP][1], test_array[TEMP][2],
- test_array[INPUT][1], test_array[OUTPUT][0], flags );
-}
-
-
-void CxCore_SVBkSbTest::prepare_to_validation( int )
-{
- CvMat* input = &test_mat[INPUT][0];
- int i, m = input->rows, n = input->cols, min_size = MIN(m, n), nb;
- bool is_float = CV_MAT_DEPTH(input->type) == CV_32F;
- CvSize w_size = compact ? cvSize(min_size,min_size) : cvSize(m,n);
- CvMat* w = &test_mat[TEMP][0];
- CvMat* wdb = cvCreateMat( w_size.height, w_size.width, CV_64FC1 );
- // use exactly the same threshold as in icvSVD... ,
- // so the changes in the library and here should be synchronized.
- double threshold = cvSum( w ).val[0]*2*(is_float ? FLT_EPSILON : DBL_EPSILON);
- CvMat *u, *v, *b, *t0, *t1;
-
- cvTsZero(wdb);
- for( i = 0; i < min_size; i++ )
- {
- double wii = vector_w ? cvGetReal1D(w,i) : cvGetReal2D(w,i,i);
- cvSetReal2D( wdb, i, i, wii > threshold ? 1./wii : 0. );
- }
-
- u = &test_mat[TEMP][1];
- v = &test_mat[TEMP][2];
- b = 0;
- nb = m;
-
- if( test_array[INPUT][1] )
- {
- b = &test_mat[INPUT][1];
- nb = b->cols;
- }
-
- if( is_float )
- {
- u = cvCreateMat( u->rows, u->cols, CV_64F );
- cvTsConvert( &test_mat[TEMP][1], u );
- if( b )
- {
- b = cvCreateMat( b->rows, b->cols, CV_64F );
- cvTsConvert( &test_mat[INPUT][1], b );
- }
- }
-
- t0 = cvCreateMat( wdb->cols, nb, CV_64F );
-
- if( b )
- cvTsGEMM( u, b, 1., 0, 0., t0, !(flags & CV_SVD_U_T) ? CV_GEMM_A_T : 0 );
- else if( flags & CV_SVD_U_T )
- cvTsCopy( u, t0 );
- else
- cvTsTranspose( u, t0 );
-
- if( is_float )
- {
- cvReleaseMat( &b );
-
- if( !symmetric )
- {
- cvReleaseMat( &u );
- v = cvCreateMat( v->rows, v->cols, CV_64F );
- }
- else
- {
- v = u;
- u = 0;
- }
- cvTsConvert( &test_mat[TEMP][2], v );
- }
-
- t1 = cvCreateMat( wdb->rows, nb, CV_64F );
- cvTsGEMM( wdb, t0, 1, 0, 0, t1, 0 );
-
- if( !is_float || !symmetric )
- {
- cvReleaseMat( &t0 );
- t0 = !is_float ? &test_mat[REF_OUTPUT][0] : cvCreateMat( test_mat[REF_OUTPUT][0].rows, nb, CV_64F );
- }
-
- cvTsGEMM( v, t1, 1, 0, 0, t0, flags & CV_SVD_V_T ? CV_GEMM_A_T : 0 );
- cvReleaseMat( &t1 );
-
- if( t0 != &test_mat[REF_OUTPUT][0] )
- {
- cvTsConvert( t0, &test_mat[REF_OUTPUT][0] );
- cvReleaseMat( &t0 );
- }
-
- if( v != &test_mat[TEMP][2] )
- cvReleaseMat( &v );
-
- cvReleaseMat( &wdb );
-}
-
-
-CxCore_SVBkSbTest svbksb_test;
-
-
-// TODO: eigenvv, invsqrt, cbrt, fastarctan, (round, floor, ceil(?)),
-
-/* End of file. */
-
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////\r
-//\r
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.\r
-//\r
-// By downloading, copying, installing or using the software you agree to this license.\r
-// If you do not agree to this license, do not download, install,\r
-// copy or use the software.\r
-//\r
-//\r
-// Intel License Agreement\r
-// For Open Source Computer Vision Library\r
-//\r
-// Copyright (C) 2000, Intel Corporation, all rights reserved.\r
-// Third party copyrights are property of their respective owners.\r
-//\r
-// Redistribution and use in source and binary forms, with or without modification,\r
-// are permitted provided that the following conditions are met:\r
-//\r
-// * Redistribution's of source code must retain the above copyright notice,\r
-// this list of conditions and the following disclaimer.\r
-//\r
-// * Redistribution's in binary form must reproduce the above copyright notice,\r
-// this list of conditions and the following disclaimer in the documentation\r
-// and/or other materials provided with the distribution.\r
-//\r
-// * The name of Intel Corporation may not be used to endorse or promote products\r
-// derived from this software without specific prior written permission.\r
-//\r
-// This software is provided by the copyright holders and contributors "as is" and\r
-// any express or implied warranties, including, but not limited to, the implied\r
-// warranties of merchantability and fitness for a particular purpose are disclaimed.\r
-// In no event shall the Intel Corporation or contributors be liable for any direct,\r
-// indirect, incidental, special, exemplary, or consequential damages\r
-// (including, but not limited to, procurement of substitute goods or services;\r
-// loss of use, data, or profits; or business interruption) however caused\r
-// and on any theory of liability, whether in contract, strict liability,\r
-// or tort (including negligence or otherwise) arising in any way out of\r
-// the use of this software, even if advised of the possibility of such damage.\r
-//\r
-//M*/\r
-\r
-#include "cxcoretest.h"\r
-\r
-using namespace cv;\r
-\r
-#define CHECK_C\r
-\r
-Size sz( 200, 500);\r
-\r
-class CV_PCATest : public CvTest\r
-{\r
-public:\r
- CV_PCATest() : CvTest( "pca", "PCA funcs" ) {}\r
-protected:\r
- void run( int);\r
-};\r
-\r
-#if 0\r
-\r
-void CV_PCATest::run( int )\r
-{\r
- int code = CvTS::OK, err;\r
- int maxComponents = 1;\r
- Mat points( 1000, 3, CV_32FC1);\r
-\r
- RNG rng = *ts->get_rng(); // get ts->rng seed\r
- rng.fill( points, RNG::NORMAL, Scalar::all(0.0), Scalar::all(1.0) );\r
-\r
- float mp[] = { 3.0f, 3.0f, 3.0f }, cp[] = { 0.5f, 0.0f, 0.0f,\r
- 0.0f, 1.0f, 0.0f,\r
- 0.0f, 0.0f, 0.3f };\r
- Mat mean( 1, 3, CV_32FC1, mp ),\r
- cov( 3, 3, CV_32FC1, cp );\r
- for( int i = 0; i < points.rows; i++ )\r
- {\r
- Mat r(1, points.cols, CV_32FC1, points.ptr<float>(i));\r
- r = r * cov + mean; \r
- }\r
-\r
- PCA pca( points, Mat(), CV_PCA_DATA_AS_ROW, maxComponents );\r
-\r
- // check project\r
- Mat prjPoints = pca.project( points );\r
- err = 0;\r
- for( int i = 0; i < prjPoints.rows; i++ )\r
- {\r
- float val = prjPoints.at<float>(i,0);\r
- if( val > 3.0f || val < -3.0f )\r
- err++;\r
- }\r
- float projectErr = 0.02f;\r
- if( (float)err > prjPoints.rows * projectErr )\r
- {\r
- ts->printf( CvTS::LOG, "bad accuracy of project() (real = %f, permissible = %f)",\r
- (float)err/(float)prjPoints.rows, projectErr );\r
- code = CvTS::FAIL_BAD_ACCURACY;\r
- }\r
-\r
- // check backProject\r
- Mat points1 = pca.backProject( prjPoints );\r
- err = 0;\r
- for( int i = 0; i < points.rows; i++ ) \r
- {\r
- if( fabs(points1.at<float>(i,0) - mean.at<float>(0,0)) > 0.15 ||\r
- fabs(points1.at<float>(i,1) - points.at<float>(i,1)) > 0.05 ||\r
- fabs(points1.at<float>(i,2) - mean.at<float>(0,2)) > 0.15 )\r
- err++;\r
- }\r
- float backProjectErr = 0.05f;\r
- if( (float)err > prjPoints.rows*backProjectErr )\r
- {\r
- ts->printf( CvTS::LOG, "bad accuracy of backProject() (real = %f, permissible = %f)",\r
- (float)err/(float)prjPoints.rows, backProjectErr );\r
- code = CvTS::FAIL_BAD_ACCURACY;\r
- }\r
-\r
- CvRNG *oldRng = ts->get_rng(); // set ts->rng seed\r
- *oldRng = rng.state;\r
-\r
- ts->set_failed_test_info( code );\r
-}\r
-#else\r
-void CV_PCATest::run( int )\r
-{\r
- int code = CvTS::OK;\r
- \r
- double diffPrjEps, diffBackPrjEps,\r
- prjEps, backPrjEps,\r
- evalEps, evecEps;\r
- int maxComponents = 100;\r
- Mat rPoints(sz, CV_32FC1), rTestPoints(sz, CV_32FC1);\r
- RNG rng = *ts->get_rng(); \r
-\r
- rng.fill( rPoints, RNG::UNIFORM, Scalar::all(0.0), Scalar::all(1.0) );\r
- rng.fill( rTestPoints, RNG::UNIFORM, Scalar::all(0.0), Scalar::all(1.0) );\r
-\r
- PCA rPCA( rPoints, Mat(), CV_PCA_DATA_AS_ROW, maxComponents ), cPCA;\r
-\r
- // 1. check C++ PCA & ROW\r
- Mat rPrjTestPoints = rPCA.project( rTestPoints );\r
- Mat rBackPrjTestPoints = rPCA.backProject( rPrjTestPoints );\r
-\r
- Mat avg(1, sz.width, CV_32FC1 );\r
- reduce( rPoints, avg, 0, CV_REDUCE_AVG );\r
- Mat Q = rPoints - repeat( avg, rPoints.rows, 1 ), Qt = Q.t(), eval, evec;\r
- Q = Qt * Q;\r
- Q = Q /(float)rPoints.rows;\r
-\r
- eigen( Q, eval, evec );\r
- /*SVD svd(Q);\r
- evec = svd.vt;\r
- eval = svd.w;*/\r
-\r
- Mat subEval( maxComponents, 1, eval.type(), eval.data ),\r
- subEvec( maxComponents, evec.cols, evec.type(), evec.data );\r
-\r
-#ifdef CHECK_C\r
- Mat prjTestPoints, backPrjTestPoints, cPoints = rPoints.t(), cTestPoints = rTestPoints.t();\r
- CvMat _points, _testPoints, _avg, _eval, _evec, _prjTestPoints, _backPrjTestPoints;\r
-#endif\r
-\r
- // check eigen()\r
- double eigenEps = 1e-6;\r
- double err;\r
- for(int i = 0; i < Q.rows; i++ )\r
- {\r
- Mat v = evec.row(i).t();\r
- Mat Qv = Q * v;\r
-\r
- Mat lv = eval.at<float>(i,0) * v;\r
- err = norm( Qv, lv );\r
- if( err > eigenEps )\r
- {\r
- ts->printf( CvTS::LOG, "bad accuracy of eigen(); err = %f\n", err );\r
- code = CvTS::FAIL_BAD_ACCURACY;\r
- goto exit_func;\r
- }\r
- }\r
- // check pca eigenvalues\r
- evalEps = 1e-6, evecEps = 1;\r
- err = norm( rPCA.eigenvalues, subEval );\r
- if( err > evalEps )\r
- {\r
- ts->printf( CvTS::LOG, "pca.eigenvalues is incorrect (CV_PCA_DATA_AS_ROW); err = %f\n", err );\r
- code = CvTS::FAIL_BAD_ACCURACY;\r
- goto exit_func;\r
- }\r
- // check pca eigenvectors\r
- err = norm( rPCA.eigenvectors, subEvec, CV_RELATIVE_L2 );\r
- if( err > evecEps )\r
- {\r
- ts->printf( CvTS::LOG, "pca.eigenvectors is incorrect (CV_PCA_DATA_AS_ROW); err = %f\n", err );\r
- code = CvTS::FAIL_BAD_ACCURACY;\r
- goto exit_func;\r
- }\r
- \r
- prjEps = 1.265, backPrjEps = 1.265;\r
- for( int i = 0; i < rTestPoints.rows; i++ )\r
- {\r
- // check pca project\r
- Mat subEvec_t = subEvec.t();\r
- Mat prj = rTestPoints.row(i) - avg; prj *= subEvec_t;\r
- err = norm(rPrjTestPoints.row(i), prj, CV_RELATIVE_L2);\r
- if( err > prjEps )\r
- {\r
- ts->printf( CvTS::LOG, "bad accuracy of project() (CV_PCA_DATA_AS_ROW); err = %f\n", err );\r
- code = CvTS::FAIL_BAD_ACCURACY;\r
- goto exit_func;\r
- }\r
- // check pca backProject\r
- Mat backPrj = rPrjTestPoints.row(i) * subEvec + avg;\r
- err = norm( rBackPrjTestPoints.row(i), backPrj, CV_RELATIVE_L2 );\r
- if( err > backPrjEps )\r
- {\r
- ts->printf( CvTS::LOG, "bad accuracy of backProject() (CV_PCA_DATA_AS_ROW); err = %f\n", err );\r
- code = CvTS::FAIL_BAD_ACCURACY;\r
- goto exit_func;\r
- }\r
- }\r
-\r
- // 2. check C++ PCA & COL\r
- cPCA( rPoints.t(), Mat(), CV_PCA_DATA_AS_COL, maxComponents );\r
- diffPrjEps = 1, diffBackPrjEps = 1;\r
- err = norm(cPCA.project(rTestPoints.t()), rPrjTestPoints.t(), CV_RELATIVE_L2 );\r
- if( err > diffPrjEps )\r
- {\r
- ts->printf( CvTS::LOG, "bad accuracy of project() (CV_PCA_DATA_AS_COL); err = %f\n", err );\r
- code = CvTS::FAIL_BAD_ACCURACY;\r
- goto exit_func;\r
- }\r
- err = norm(cPCA.backProject(rPrjTestPoints.t()), rBackPrjTestPoints.t(), CV_RELATIVE_L2 );\r
- if( err > diffBackPrjEps )\r
- {\r
- ts->printf( CvTS::LOG, "bad accuracy of backProject() (CV_PCA_DATA_AS_COL); err = %f\n", err );\r
- code = CvTS::FAIL_BAD_ACCURACY;\r
- goto exit_func;\r
- }\r
-\r
-#ifdef CHECK_C\r
- // 3. check C PCA & ROW\r
- _points = rPoints;\r
- _testPoints = rTestPoints;\r
- _avg = avg;\r
- _eval = eval;\r
- _evec = evec;\r
- prjTestPoints.create(rTestPoints.rows, maxComponents, rTestPoints.type() );\r
- backPrjTestPoints.create(rPoints.size(), rPoints.type() );\r
- _prjTestPoints = prjTestPoints;\r
- _backPrjTestPoints = backPrjTestPoints;\r
-\r
- cvCalcPCA( &_points, &_avg, &_eval, &_evec, CV_PCA_DATA_AS_ROW );\r
- cvProjectPCA( &_testPoints, &_avg, &_evec, &_prjTestPoints );\r
- cvBackProjectPCA( &_prjTestPoints, &_avg, &_evec, &_backPrjTestPoints );\r
-\r
- err = norm(prjTestPoints, rPrjTestPoints, CV_RELATIVE_L2);\r
- if( err > diffPrjEps )\r
- {\r
- ts->printf( CvTS::LOG, "bad accuracy of cvProjectPCA() (CV_PCA_DATA_AS_ROW); err = %f\n", err );\r
- code = CvTS::FAIL_BAD_ACCURACY;\r
- goto exit_func;\r
- }\r
- err = norm(backPrjTestPoints, rBackPrjTestPoints, CV_RELATIVE_L2);\r
- if( err > diffBackPrjEps )\r
- {\r
- ts->printf( CvTS::LOG, "bad accuracy of cvBackProjectPCA() (CV_PCA_DATA_AS_ROW); err = %f\n", err );\r
- code = CvTS::FAIL_BAD_ACCURACY;\r
- goto exit_func;\r
- }\r
-\r
- // 3. check C PCA & COL\r
- _points = cPoints;\r
- _testPoints = cTestPoints;\r
- avg = avg.t(); _avg = avg;\r
- eval = eval.t(); _eval = eval;\r
- evec = evec.t(); _evec = evec;\r
- prjTestPoints = prjTestPoints.t(); _prjTestPoints = prjTestPoints;\r
- backPrjTestPoints = backPrjTestPoints.t(); _backPrjTestPoints = backPrjTestPoints;\r
-\r
- cvCalcPCA( &_points, &_avg, &_eval, &_evec, CV_PCA_DATA_AS_COL );\r
- cvProjectPCA( &_testPoints, &_avg, &_evec, &_prjTestPoints );\r
- cvBackProjectPCA( &_prjTestPoints, &_avg, &_evec, &_backPrjTestPoints );\r
-\r
- err = norm(prjTestPoints, rPrjTestPoints.t(), CV_RELATIVE_L2 );\r
- if( err > diffPrjEps )\r
- {\r
- ts->printf( CvTS::LOG, "bad accuracy of cvProjectPCA() (CV_PCA_DATA_AS_COL); err = %f\n", err );\r
- code = CvTS::FAIL_BAD_ACCURACY;\r
- goto exit_func;\r
- }\r
- err = norm(backPrjTestPoints, rBackPrjTestPoints.t(), CV_RELATIVE_L2);\r
- if( err > diffBackPrjEps )\r
- {\r
- ts->printf( CvTS::LOG, "bad accuracy of cvBackProjectPCA() (CV_PCA_DATA_AS_COL); err = %f\n", err );\r
- code = CvTS::FAIL_BAD_ACCURACY;\r
- goto exit_func;\r
- }\r
-#endif\r
-\r
-exit_func:\r
-\r
- CvRNG* _rng = ts->get_rng(); \r
- *_rng = rng.state;\r
- ts->set_failed_test_info( code );\r
-}\r
-\r
-#endif\r
-\r
-CV_PCATest pca_test;\r
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cxcoretest.h"
-
-using namespace cv;
-
-
-class CV_RandTest : public CvTest
-{
-public:
- CV_RandTest();
-protected:
- void run(int);
- bool check_pdf(const Mat& hist, double scale, int dist_type,
- double& refval, double& realval);
-};
-
-
-CV_RandTest::CV_RandTest():
-CvTest( "rand", "cvRandArr, cvRNG" )
-{
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;
-}
-
-static double chi2_p95(int n)
-{
- static float chi2_tab95[] = {
- 3.841f, 5.991f, 7.815f, 9.488f, 11.07f, 12.59f, 14.07f, 15.51f,
- 16.92f, 18.31f, 19.68f, 21.03f, 21.03f, 22.36f, 23.69f, 25.00f,
- 26.30f, 27.59f, 28.87f, 30.14f, 31.41f, 32.67f, 33.92f, 35.17f,
- 36.42f, 37.65f, 38.89f, 40.11f, 41.34f, 42.56f, 43.77f };
- static const double xp = 1.64;
- CV_Assert(n >= 1);
-
- if( n <= 30 )
- return chi2_tab95[n-1];
- return n + sqrt((double)2*n)*xp + 0.6666666666666*(xp*xp - 1);
-}
-
-bool CV_RandTest::check_pdf(const Mat& hist, double scale,
- int dist_type, double& refval, double& realval)
-{
- Mat hist0(hist.size(), CV_32F);
- const int* H = (const int*)hist.data;
- float* H0 = ((float*)hist0.data);
- int i, hsz = hist.cols;
-
- double sum = 0;
- for( i = 0; i < hsz; i++ )
- sum += H[i];
- CV_Assert( fabs(1./sum - scale) < FLT_EPSILON );
-
- if( dist_type == CV_RAND_UNI )
- {
- float scale0 = (float)(1./hsz);
- for( i = 0; i < hsz; i++ )
- H0[i] = scale0;
- }
- else
- {
- double sum = 0, r = (hsz-1.)/2;
- double alpha = 2*sqrt(2.)/r, beta = -alpha*r;
- for( i = 0; i < hsz; i++ )
- {
- double x = i*alpha + beta;
- H0[i] = (float)exp(-x*x);
- sum += H0[i];
- }
- sum = 1./sum;
- for( i = 0; i < hsz; i++ )
- H0[i] = (float)(H0[i]*sum);
- }
-
- double chi2 = 0;
- for( i = 0; i < hsz; i++ )
- {
- double a = H0[i];
- double b = H[i]*scale;
- if( a > DBL_EPSILON )
- chi2 += (a - b)*(a - b)/(a + b);
- }
- realval = chi2;
-
- double chi2_pval = chi2_p95(hsz - 1 - (dist_type == CV_RAND_NORMAL ? 2 : 0));
- refval = chi2_pval*0.01;
- return realval <= refval;
-}
-
-void CV_RandTest::run( int )
-{
- static int _ranges[][2] =
- {{ 0, 256 }, { -128, 128 }, { 0, 65536 }, { -32768, 32768 },
- { -1000000, 1000000 }, { -1000, 1000 }, { -1000, 1000 }};
-
- const int MAX_SDIM = 10;
- const int N = 2000000;
- const int maxSlice = 1000;
- const int MAX_HIST_SIZE = 1000;
- int progress = 0;
-
- CvRNG* rng = ts->get_rng();
- RNG tested_rng = theRNG();
- test_case_count = 200;
-
- for( int idx = 0; idx < test_case_count; idx++ )
- {
- progress = update_progress( progress, idx, test_case_count, 0 );
- ts->update_context( this, idx, false );
-
- int depth = cvTsRandInt(rng) % (CV_64F+1);
- int c, cn = (cvTsRandInt(rng) % 4) + 1;
- int type = CV_MAKETYPE(depth, cn);
- int dist_type = cvTsRandInt(rng) % (CV_RAND_NORMAL+1);
- int i, k, SZ = N/cn;
- Scalar A, B;
-
- bool do_sphere_test = dist_type == CV_RAND_UNI;
- Mat arr[2], hist[4];
- int W[] = {0,0,0,0};
-
- arr[0].create(1, SZ, type);
- arr[1].create(1, SZ, type);
- bool fast_algo = dist_type == CV_RAND_UNI && depth < CV_32F;
-
- for( c = 0; c < cn; c++ )
- {
- int a, b, hsz;
- if( dist_type == CV_RAND_UNI )
- {
- a = (int)(cvTsRandInt(rng) % (_ranges[depth][1] -
- _ranges[depth][0])) + _ranges[depth][0];
- do
- {
- b = (int)(cvTsRandInt(rng) % (_ranges[depth][1] -
- _ranges[depth][0])) + _ranges[depth][0];
- }
- while( abs(a-b) <= 1 );
- if( a > b )
- std::swap(a, b);
-
- unsigned r = (unsigned)(b - a);
- fast_algo = fast_algo && r <= 256 && (r & (r-1)) == 0;
- hsz = min((unsigned)(b - a), (unsigned)MAX_HIST_SIZE);
- do_sphere_test = do_sphere_test && b - a >= 100;
- }
- else
- {
- int vrange = _ranges[depth][1] - _ranges[depth][0];
- int meanrange = vrange/16;
- int mindiv = MAX(vrange/20, 5);
- int maxdiv = MIN(vrange/8, 10000);
-
- a = cvTsRandInt(rng) % meanrange - meanrange/2 +
- (_ranges[depth][0] + _ranges[depth][1])/2;
- b = cvTsRandInt(rng) % (maxdiv - mindiv) + mindiv;
- hsz = min((unsigned)b*9, (unsigned)MAX_HIST_SIZE);
- }
- A[c] = a;
- B[c] = b;
- hist[c].create(1, hsz, CV_32S);
- }
-
- cv::RNG saved_rng = tested_rng;
- int maxk = fast_algo ? 0 : 1;
- for( k = 0; k <= maxk; k++ )
- {
- tested_rng = saved_rng;
- int sz = 0, dsz = 0, slice;
- for( slice = 0; slice < maxSlice; slice++, sz += dsz )
- {
- dsz = slice+1 < maxSlice ? cvTsRandInt(rng) % (SZ - sz + 1) : SZ - sz;
- Mat aslice = arr[k].colRange(sz, sz + dsz);
- tested_rng.fill(aslice, dist_type, A, B);
- }
- }
-
- if( maxk >= 1 && norm(arr[0], arr[1], NORM_INF) != 0 )
- {
- ts->printf( CvTS::LOG, "RNG output depends on the array lengths (some generated numbers get lost?)" );
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- return;
- }
-
- for( c = 0; c < cn; c++ )
- {
- const uchar* data = arr[0].data;
- int* H = hist[c].ptr<int>();
- int HSZ = hist[c].cols;
- double minVal = dist_type == CV_RAND_UNI ? A[c] : A[c] - B[c]*4;
- double maxVal = dist_type == CV_RAND_UNI ? B[c] : A[c] + B[c]*4;
- double scale = HSZ/(maxVal - minVal);
- double delta = -minVal*scale;
-
- hist[c] = Scalar::all(0);
-
- for( i = c; i < SZ*cn; i += cn )
- {
- double val = depth == CV_8U ? ((const uchar*)data)[i] :
- depth == CV_8S ? ((const schar*)data)[i] :
- depth == CV_16U ? ((const ushort*)data)[i] :
- depth == CV_16S ? ((const short*)data)[i] :
- depth == CV_32S ? ((const int*)data)[i] :
- depth == CV_32F ? ((const float*)data)[i] :
- ((const double*)data)[i];
- int ival = cvFloor(val*scale + delta);
- if( (unsigned)ival < (unsigned)HSZ )
- {
- H[ival]++;
- W[c]++;
- }
- else if( dist_type == CV_RAND_UNI )
- {
- if( (minVal <= val && val < maxVal) || (depth >= CV_32F && val == maxVal) )
- {
- H[ival < 0 ? 0 : HSZ-1]++;
- W[c]++;
- }
- else
- {
- putchar('^');
- }
- }
- }
-
- if( dist_type == CV_RAND_UNI && W[c] != SZ )
- {
- ts->printf( CvTS::LOG, "Uniform RNG gave values out of the range [%g,%g) on channel %d/%d\n",
- A[c], B[c], c, cn);
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- return;
- }
- if( dist_type == CV_RAND_NORMAL && W[c] < SZ*.90)
- {
- ts->printf( CvTS::LOG, "Normal RNG gave too many values out of the range (%g+4*%g,%g+4*%g) on channel %d/%d\n",
- A[c], B[c], A[c], B[c], c, cn);
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- return;
- }
- double refval = 0, realval = 0;
-
- if( !check_pdf(hist[c], 1./W[c], dist_type, refval, realval) )
- {
- ts->printf( CvTS::LOG, "RNG failed Chi-square test "
- "(got %g vs probable maximum %g) on channel %d/%d\n",
- realval, refval, c, cn);
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- return;
- }
- }
-
- // Monte-Carlo test. Compute volume of SDIM-dimensional sphere
- // inscribed in [-1,1]^SDIM cube.
- if( do_sphere_test )
- {
- int SDIM = cvTsRandInt(rng) % (MAX_SDIM-1) + 2;
- int N0 = (SZ*cn/SDIM), N = 0;
- double r2 = 0;
- const uchar* data = arr[0].data;
- double scale[4], delta[4];
- for( c = 0; c < cn; c++ )
- {
- scale[c] = 2./(B[c] - A[c]);
- delta[c] = -A[c]*scale[c] - 1;
- }
-
- for( i = k = c = 0; i <= SZ*cn - SDIM; i++, k++, c++ )
- {
- double val = depth == CV_8U ? ((const uchar*)data)[i] :
- depth == CV_8S ? ((const schar*)data)[i] :
- depth == CV_16U ? ((const ushort*)data)[i] :
- depth == CV_16S ? ((const short*)data)[i] :
- depth == CV_32S ? ((const int*)data)[i] :
- depth == CV_32F ? ((const float*)data)[i] : ((const double*)data)[i];
- c &= c < cn ? -1 : 0;
- val = val*scale[c] + delta[c];
- r2 += val*val;
- if( k == SDIM-1 )
- {
- N += r2 <= 1;
- r2 = 0;
- k = -1;
- }
- }
-
- double V = ((double)N/N0)*(1 << SDIM);
-
- // the theoretically computed volume
- int sdim = SDIM % 2;
- double V0 = sdim + 1;
- for( sdim += 2; sdim <= SDIM; sdim += 2 )
- V0 *= 2*CV_PI/sdim;
-
- if( fabs(V - V0) > 0.3*fabs(V0) )
- {
- ts->printf( CvTS::LOG, "RNG failed %d-dim sphere volume test (got %g instead of %g)\n",
- SDIM, V, V0);
- ts->printf( CvTS::LOG, "depth = %d, N0 = %d\n", depth, N0);
- ts->set_failed_test_info( CvTS::FAIL_INVALID_OUTPUT );
- return;
- }
- }
- }
-}
-
-CV_RandTest rand_test;
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////\r
-//\r
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.\r
-//\r
-// By downloading, copying, installing or using the software you agree to this license.\r
-// If you do not agree to this license, do not download, install,\r
-// copy or use the software.\r
-//\r
-//\r
-// Intel License Agreement\r
-// For Open Source Computer Vision Library\r
-//\r
-// Copyright (C) 2000, Intel Corporation, all rights reserved.\r
-// Third party copyrights are property of their respective owners.\r
-//\r
-// Redistribution and use in source and binary forms, with or without modification,\r
-// are permitted provided that the following conditions are met:\r
-//\r
-// * Redistribution's of source code must retain the above copyright notice,\r
-// this list of conditions and the following disclaimer.\r
-//\r
-// * Redistribution's in binary form must reproduce the above copyright notice,\r
-// this list of conditions and the following disclaimer in the documentation\r
-// and/or other materials provided with the distribution.\r
-//\r
-// * The name of Intel Corporation may not be used to endorse or promote products\r
-// derived from this software without specific prior written permission.\r
-//\r
-// This software is provided by the copyright holders and contributors "as is" and\r
-// any express or implied warranties, including, but not limited to, the implied\r
-// warranties of merchantability and fitness for a particular purpose are disclaimed.\r
-// In no event shall the Intel Corporation or contributors be liable for any direct,\r
-// indirect, incidental, special, exemplary, or consequential damages\r
-// (including, but not limited to, procurement of substitute goods or services;\r
-// loss of use, data, or profits; or business interruption) however caused\r
-// and on any theory of liability, whether in contract, strict liability,\r
-// or tort (including negligence or otherwise) arising in any way out of\r
-// the use of this software, even if advised of the possibility of such damage.\r
-//\r
-//M*/\r
-\r
-#include "cxcoretest.h"\r
-\r
-using namespace cv;\r
-\r
-\r
-class CV_ReduceTest : public CvTest\r
-{\r
-public:\r
- CV_ReduceTest() : CvTest( "reduce", "reduce" ) {}\r
-protected:\r
- void run( int);\r
- int checkOp( const Mat& src, int dstType, int opType, const Mat& opRes, int dim, double eps );\r
- int checkCase( int srcType, int dstType, int dim, Size sz );\r
- int checkDim( int dim, Size sz );\r
- int checkSize( Size sz );\r
-};\r
-\r
-template<class Type>\r
-void testReduce( const Mat& src, Mat& sum, Mat& avg, Mat& max, Mat& min, int dim )\r
-{\r
- assert( src.channels() == 1 );\r
- if( dim == 0 ) // row\r
- {\r
- sum.create( 1, src.cols, CV_64FC1 ); \r
- max.create( 1, src.cols, CV_64FC1 );\r
- min.create( 1, src.cols, CV_64FC1 );\r
- }\r
- else\r
- {\r
- sum.create( src.rows, 1, CV_64FC1 ); \r
- max.create( src.rows, 1, CV_64FC1 );\r
- min.create( src.rows, 1, CV_64FC1 );\r
- }\r
- sum.setTo(Scalar(0));\r
- max.setTo(Scalar(-DBL_MAX));\r
- min.setTo(Scalar(DBL_MAX));\r
- \r
- const Mat_<Type>& src_ = src;\r
- Mat_<double>& sum_ = (Mat_<double>&)sum;\r
- Mat_<double>& min_ = (Mat_<double>&)min;\r
- Mat_<double>& max_ = (Mat_<double>&)max;\r
-\r
- if( dim == 0 )\r
- {\r
- for( int ri = 0; ri < src.rows; ri++ )\r
- {\r
- for( int ci = 0; ci < src.cols; ci++ )\r
- {\r
- sum_(0, ci) += src_(ri, ci);\r
- max_(0, ci) = std::max( max_(0, ci), (double)src_(ri, ci) );\r
- min_(0, ci) = std::min( min_(0, ci), (double)src_(ri, ci) );\r
- }\r
- }\r
- }\r
- else\r
- {\r
- for( int ci = 0; ci < src.cols; ci++ )\r
- {\r
- for( int ri = 0; ri < src.rows; ri++ )\r
- {\r
- sum_(ri, 0) += src_(ri, ci);\r
- max_(ri, 0) = std::max( max_(ri, 0), (double)src_(ri, ci) );\r
- min_(ri, 0) = std::min( min_(ri, 0), (double)src_(ri, ci) );\r
- }\r
- }\r
- }\r
- sum.convertTo( avg, CV_64FC1 );\r
- avg = avg * (1.0 / (dim==0 ? (double)src.rows : (double)src.cols));\r
-}\r
-\r
-void getMatTypeStr( int type, string& str)\r
-{\r
- str = type == CV_8UC1 ? "CV_8UC1" :\r
- type == CV_8SC1 ? "CV_8SC1" :\r
- type == CV_16UC1 ? "CV_16UC1" :\r
- type == CV_16SC1 ? "CV_16SC1" :\r
- type == CV_32SC1 ? "CV_32SC1" :\r
- type == CV_32FC1 ? "CV_32FC1" :\r
- type == CV_64FC1 ? "CV_64FC1" : "unsupported matrix type";\r
-}\r
-\r
-int CV_ReduceTest::checkOp( const Mat& src, int dstType, int opType, const Mat& opRes, int dim, double eps )\r
-{\r
- int srcType = src.type();\r
- bool support = false;\r
- if( opType == CV_REDUCE_SUM || opType == CV_REDUCE_AVG )\r
- {\r
- if( srcType == CV_8U && (dstType == CV_32S || dstType == CV_32F || dstType == CV_64F) )\r
- support = true;\r
- if( srcType == CV_16U && (dstType == CV_32F || dstType == CV_64F) )\r
- support = true;\r
- if( srcType == CV_16S && (dstType == CV_32F || dstType == CV_64F) )\r
- support = true;\r
- if( srcType == CV_32F && (dstType == CV_32F || dstType == CV_64F) )\r
- support = true;\r
- if( srcType == CV_64F && dstType == CV_64F)\r
- support = true;\r
- }\r
- else if( opType == CV_REDUCE_MAX )\r
- {\r
- if( srcType == CV_8U && dstType == CV_8U )\r
- support = true;\r
- if( srcType == CV_32F && dstType == CV_32F )\r
- support = true;\r
- if( srcType == CV_64F && dstType == CV_64F )\r
- support = true;\r
- }\r
- else if( opType == CV_REDUCE_MIN )\r
- {\r
- if( srcType == CV_8U && dstType == CV_8U)\r
- support = true;\r
- if( srcType == CV_32F && dstType == CV_32F)\r
- support = true;\r
- if( srcType == CV_64F && dstType == CV_64F)\r
- support = true;\r
- }\r
- if( !support )\r
- return CvTS::OK;\r
-\r
- assert( opRes.type() == CV_64FC1 );\r
- Mat _dst, dst;\r
- reduce( src, _dst, dim, opType, dstType );\r
- _dst.convertTo( dst, CV_64FC1 );\r
- if( norm( opRes, dst, NORM_INF ) > eps )\r
- {\r
- char msg[100];\r
- const char* opTypeStr = opType == CV_REDUCE_SUM ? "CV_REDUCE_SUM" :\r
- opType == CV_REDUCE_AVG ? "CV_REDUCE_AVG" :\r
- opType == CV_REDUCE_MAX ? "CV_REDUCE_MAX" :\r
- opType == CV_REDUCE_MIN ? "CV_REDUCE_MIN" : "unknown operation type";\r
- string srcTypeStr, dstTypeStr;\r
- getMatTypeStr( src.type(), srcTypeStr );\r
- getMatTypeStr( dstType, dstTypeStr );\r
- const char* dimStr = dim == 0 ? "ROWS" : "COLS";\r
-\r
- sprintf( msg, "bad accuracy with srcType = %s, dstType = %s, opType = %s, dim = %s",\r
- srcTypeStr.c_str(), dstTypeStr.c_str(), opTypeStr, dimStr );\r
- ts->printf( CvTS::LOG, msg );\r
- return CvTS::FAIL_BAD_ACCURACY;\r
- }\r
- return CvTS::OK;\r
-}\r
-\r
-int CV_ReduceTest::checkCase( int srcType, int dstType, int dim, Size sz )\r
-{\r
- int code = CvTS::OK, tempCode;\r
- Mat src, sum, avg, max, min;\r
-\r
- src.create( sz, srcType );\r
- randu( src, Scalar(0), Scalar(100) );\r
-\r
- if( srcType == CV_8UC1 )\r
- testReduce<uchar>( src, sum, avg, max, min, dim );\r
- else if( srcType == CV_8SC1 )\r
- testReduce<char>( src, sum, avg, max, min, dim );\r
- else if( srcType == CV_16UC1 )\r
- testReduce<unsigned short int>( src, sum, avg, max, min, dim );\r
- else if( srcType == CV_16SC1 )\r
- testReduce<short int>( src, sum, avg, max, min, dim );\r
- else if( srcType == CV_32SC1 )\r
- testReduce<int>( src, sum, avg, max, min, dim );\r
- else if( srcType == CV_32FC1 )\r
- testReduce<float>( src, sum, avg, max, min, dim );\r
- else if( srcType == CV_64FC1 )\r
- testReduce<double>( src, sum, avg, max, min, dim );\r
- else \r
- assert( 0 );\r
-\r
- // 1. sum\r
- tempCode = checkOp( src, dstType, CV_REDUCE_SUM, sum, dim, \r
- srcType == CV_32FC1 && dstType == CV_32FC1 ? 0.05 : FLT_EPSILON );\r
- code = tempCode != CvTS::OK ? tempCode : code;\r
-\r
- // 2. avg\r
- tempCode = checkOp( src, dstType, CV_REDUCE_AVG, avg, dim, \r
- dstType == CV_32SC1 ? 0.6 : 0.00007 );\r
- code = tempCode != CvTS::OK ? tempCode : code;\r
-\r
- // 3. max\r
- tempCode = checkOp( src, dstType, CV_REDUCE_MAX, max, dim, FLT_EPSILON );\r
- code = tempCode != CvTS::OK ? tempCode : code;\r
-\r
- // 4. min\r
- tempCode = checkOp( src, dstType, CV_REDUCE_MIN, min, dim, FLT_EPSILON );\r
- code = tempCode != CvTS::OK ? tempCode : code;\r
- \r
- return code;\r
-}\r
-\r
-int CV_ReduceTest::checkDim( int dim, Size sz )\r
-{\r
- int code = CvTS::OK, tempCode;\r
-\r
- // CV_8UC1\r
- tempCode = checkCase( CV_8UC1, CV_8UC1, dim, sz );\r
- code = tempCode != CvTS::OK ? tempCode : code;\r
-\r
- tempCode = checkCase( CV_8UC1, CV_32SC1, dim, sz );\r
- code = tempCode != CvTS::OK ? tempCode : code;\r
-\r
- tempCode = checkCase( CV_8UC1, CV_32FC1, dim, sz );\r
- code = tempCode != CvTS::OK ? tempCode : code;\r
-\r
- tempCode = checkCase( CV_8UC1, CV_64FC1, dim, sz );\r
- code = tempCode != CvTS::OK ? tempCode : code;\r
-\r
- // CV_16UC1\r
- tempCode = checkCase( CV_16UC1, CV_32FC1, dim, sz );\r
- code = tempCode != CvTS::OK ? tempCode : code;\r
-\r
- tempCode = checkCase( CV_16UC1, CV_64FC1, dim, sz );\r
- code = tempCode != CvTS::OK ? tempCode : code;\r
-\r
- // CV_16SC1\r
- tempCode = checkCase( CV_16SC1, CV_32FC1, dim, sz );\r
- code = tempCode != CvTS::OK ? tempCode : code;\r
-\r
- tempCode = checkCase( CV_16SC1, CV_64FC1, dim, sz );\r
- code = tempCode != CvTS::OK ? tempCode : code;\r
-\r
- // CV_32FC1\r
- tempCode = checkCase( CV_32FC1, CV_32FC1, dim, sz );\r
- code = tempCode != CvTS::OK ? tempCode : code;\r
-\r
- tempCode = checkCase( CV_32FC1, CV_64FC1, dim, sz );\r
- code = tempCode != CvTS::OK ? tempCode : code;\r
-\r
- // CV_64FC1\r
- tempCode = checkCase( CV_64FC1, CV_64FC1, dim, sz );\r
- code = tempCode != CvTS::OK ? tempCode : code;\r
-\r
- return code;\r
-}\r
-\r
-int CV_ReduceTest::checkSize( Size sz )\r
-{\r
- int code = CvTS::OK, tempCode;\r
-\r
- tempCode = checkDim( 0, sz ); // rows\r
- code = tempCode != CvTS::OK ? tempCode : code;\r
-\r
- tempCode = checkDim( 1, sz ); // cols \r
- code = tempCode != CvTS::OK ? tempCode : code;\r
-\r
- return code;\r
-}\r
-\r
-void CV_ReduceTest::run( int )\r
-{\r
- int code = CvTS::OK, tempCode;\r
- \r
- tempCode = checkSize( Size(1,1) );\r
- code = tempCode != CvTS::OK ? tempCode : code;\r
- \r
- tempCode = checkSize( Size(1,100) );\r
- code = tempCode != CvTS::OK ? tempCode : code;\r
-\r
- tempCode = checkSize( Size(100,1) );\r
- code = tempCode != CvTS::OK ? tempCode : code;\r
-\r
- tempCode = checkSize( Size(1000,500) );\r
- code = tempCode != CvTS::OK ? tempCode : code;\r
-\r
- ts->set_failed_test_info( code );\r
-}\r
-\r
-CV_ReduceTest reduce_test;\r
+++ /dev/null
-// 2008-05-14, Xavier Delacour <xavier.delacour@gmail.com>
-
-#include "cxcoretest.h"
-
-#include <algorithm>
-#include <complex>
-#include <vector>
-#include <iostream>
-
-typedef std::complex<double> complex_type;
-
-struct pred_complex
-{
- bool operator() (const complex_type& lhs, const complex_type& rhs) const
- {
- return fabs(lhs.real() - rhs.real()) > fabs(rhs.real())*FLT_EPSILON ? lhs.real() < rhs.real() : lhs.imag() < rhs.imag();
- }
-};
-
-struct pred_double
-{
- bool operator() (const double& lhs, const double& rhs) const
- {
- return lhs < rhs;
- }
-};
-
-class CV_SolvePolyTest : public CvTest
-{
-public:
- CV_SolvePolyTest();
- ~CV_SolvePolyTest();
-protected:
- virtual void run( int start_from );
-};
-
-CV_SolvePolyTest::CV_SolvePolyTest() : CvTest( "solve-poly", "cvSolvePoly" ) {}
-
-CV_SolvePolyTest::~CV_SolvePolyTest() {}
-
-void CV_SolvePolyTest::run( int )
-{
- CvRNG rng = cvRNG();
- int fig = 100;
- double range = 50;
- double err_eps = 1e-4;
-
- for (int idx = 0, max_idx = 1000, progress = 0; idx < max_idx; ++idx)
- {
- progress = update_progress(progress, idx-1, max_idx, 0);
- int n = cvRandInt(&rng) % 13 + 1;
- std::vector<complex_type> r(n), ar(n), c(n + 1, 0);
- std::vector<double> a(n + 1), u(n * 2), ar1(n), ar2(n);
-
- int rr_odds = 3; // odds that we get a real root
- for (int j = 0; j < n;)
- {
- if (cvRandInt(&rng) % rr_odds == 0 || j == n - 1)
- r[j++] = cvRandReal(&rng) * range;
- else
- {
- r[j] = complex_type(cvRandReal(&rng) * range,
- cvRandReal(&rng) * range + 1);
- r[j + 1] = std::conj(r[j]);
- j += 2;
- }
- }
-
- for (int j = 0, k = 1 << n, jj, kk; j < k; ++j)
- {
- int p = 0;
- complex_type v(1);
- for (jj = 0, kk = 1; jj < n && !(j & kk); ++jj, ++p, kk <<= 1)
- ;
- for (; jj < n; ++jj, kk <<= 1)
- {
- if (j & kk)
- v *= -r[jj];
- else
- ++p;
- }
- c[p] += v;
- }
-
- bool pass = false;
- double div = 0, s = 0;
- int cubic_case = idx & 1;
- for (int maxiter = 100; !pass && maxiter < 10000; maxiter *= 2, cubic_case = (cubic_case + 1) % 2)
- {
- for (int j = 0; j < n + 1; ++j)
- a[j] = c[j].real();
-
- CvMat amat, umat;
- cvInitMatHeader(&amat, n + 1, 1, CV_64FC1, &a[0]);
- cvInitMatHeader(&umat, n, 1, CV_64FC2, &u[0]);
- cvSolvePoly(&amat, &umat, maxiter, fig);
-
- for (int j = 0; j < n; ++j)
- ar[j] = complex_type(u[j * 2], u[j * 2 + 1]);
-
- std::sort(r.begin(), r.end(), pred_complex());
- std::sort(ar.begin(), ar.end(), pred_complex());
-
- pass = true;
- if( n == 3 )
- {
- ar2.resize(n);
- cv::Mat _umat2(3, 1, CV_64F, &ar2[0]), umat2 = _umat2;
- cvFlip(&amat, &amat, 0);
- int nr2;
- if( cubic_case == 0 )
- nr2 = cv::solveCubic(cv::Mat(&amat),umat2);
- else
- nr2 = cv::solveCubic(cv::Mat_<float>(cv::Mat(&amat)), umat2);
- cvFlip(&amat, &amat, 0);
- if(nr2 > 0)
- std::sort(ar2.begin(), ar2.begin()+nr2, pred_double());
- ar2.resize(nr2);
-
- int nr1 = 0;
- for(int j = 0; j < n; j++)
- if( fabs(r[j].imag()) < DBL_EPSILON )
- ar1[nr1++] = r[j].real();
-
- pass = pass && nr1 == nr2;
- if( nr2 > 0 )
- {
- div = s = 0;
- for(int j = 0; j < nr1; j++)
- {
- s += fabs(ar1[j]);
- div += fabs(ar1[j] - ar2[j]);
- }
- div /= s;
- pass = pass && div < err_eps;
- }
- }
-
- div = s = 0;
- for (int j = 0; j < n; ++j)
- {
- s += fabs(r[j].real()) + fabs(r[j].imag());
- div += sqrt(pow(r[j].real() - ar[j].real(), 2) + pow(r[j].imag() - ar[j].imag(), 2));
- }
- div /= s;
- pass = pass && div < err_eps;
- }
-
- if (!pass)
- {
- ts->set_failed_test_info(CvTS::FAIL_INVALID_OUTPUT);
- ts->printf( CvTS::LOG, "too big diff = %g\n", div );
-
- for (size_t j=0;j<ar2.size();++j)
- ts->printf( CvTS::LOG, "ar2[%d]=%g\n", j, ar2[j]);
- ts->printf(CvTS::LOG, "\n");
-
- for (size_t j=0;j<r.size();++j)
- ts->printf( CvTS::LOG, "r[%d]=(%g, %g)\n", j, r[j].real(), r[j].imag());
- ts->printf( CvTS::LOG, "\n" );
- for (size_t j=0;j<ar.size();++j)
- ts->printf( CvTS::LOG, "ar[%d]=(%g, %g)\n", j, ar[j].real(), ar[j].imag());
- break;
- }
- }
-}
-
-CV_SolvePolyTest solve_poly_test;
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#ifndef _CXCORE_TEST_H_
-#define _CXCORE_TEST_H_
-
-#if defined WIN32 || defined _WIN32
-#include <windows.h>
-#undef min
-#undef max
-#endif
-
-#include "opencv2/core/core.hpp"
-#include "opencv2/core/internal.hpp"
-#include "cxts.h"
-
-/****************************************************************************************/
-/* Warnings Disabling */
-/****************************************************************************************/
-#if _MSC_VER > 1000
-#pragma warning(disable : 4514) /* unreferenced inline function has been */
- /* removed */
-#pragma warning(disable : 4127) /* conditional expression is constant */
- /* for no warnings in _ASSERT */
-#pragma warning(disable : 4996) /* deprecated function */
-#endif
-
-#endif /* _CXCORE_TEST_H_ */
-
-/* End of file. */
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cxcoretest.h"
-
-CvTS test_system("core");
-
-const char* blacklist[] =
-{
- //"matrix-dotproduct", //ticket 447
- //"ds-graphscan", //ticket 504
- //"matrix-invert", //ticket 536
- //"pca", //ticket 566
- //"rand", //ticket 449
- 0
-};
-
-int main( int argc, char** argv )
-{
- return test_system.run( argc, argv, blacklist );
-}
-
-/* End of file. */
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////\r
-//\r
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.\r
-//\r
-// By downloading, copying, installing or using the software you agree to this license.\r
-// If you do not agree to this license, do not download, install,\r
-// copy or use the software.\r
-//\r
-//\r
-// License Agreement\r
-// For Open Source Computer Vision Library\r
-//\r
-// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.\r
-// Copyright (C) 2009, Willow Garage Inc., all rights reserved.\r
-// Third party copyrights are property of their respective owners.\r
-//\r
-// Redistribution and use in source and binary forms, with or without modification,\r
-// are permitted provided that the following conditions are met:\r
-//\r
-// * Redistribution's of source code must retain the above copyright notice,\r
-// this list of conditions and the following disclaimer.\r
-//\r
-// * Redistribution's in binary form must reproduce the above copyright notice,\r
-// this list of conditions and the following disclaimer in the documentation\r
-// and/or other materials provided with the distribution.\r
-//\r
-// * The name of the copyright holders may not be used to endorse or promote products\r
-// derived from this software without specific prior written permission.\r
-//\r
-// This software is provided by the copyright holders and contributors "as is" and\r
-// any express or implied warranties, including, but not limited to, the implied\r
-// warranties of merchantability and fitness for a particular purpose are disclaimed.\r
-// In no event shall the Intel Corporation or contributors be liable for any direct,\r
-// indirect, incidental, special, exemplary, or consequential damages\r
-// (including, but not limited to, procurement of substitute goods or services;\r
-// loss of use, data, or profits; or business interruption) however caused\r
-// and on any theory of liability, whether in contract, strict liability,\r
-// or tort (including negligence or otherwise) arising in any way out of\r
-// the use of this software, even if advised of the possibility of such damage.\r
-//\r
-//M*/\r
-\r
-#include "cxcoretest.h"\r
-#include <string>\r
-#include <iostream>\r
-#include <fstream>\r
-#include <iterator>\r
-#include <limits>\r
-#include <numeric>\r
-\r
-using namespace cv;\r
-using namespace std;\r
-\r
-class CV_MatrOpTest : public CvTest\r
-{\r
-public:\r
- CV_MatrOpTest();\r
- ~CV_MatrOpTest(); \r
-protected:\r
- void run(int); \r
-\r
- bool TestMat();\r
- bool TestMatND();\r
- bool TestSparseMat();\r
-\r
-\r
- bool checkMatSetError(const Mat& m1, const Mat& m2);\r
-};\r
-\r
-CV_MatrOpTest::CV_MatrOpTest(): CvTest( "matrix-operations", "?" )\r
-{\r
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;\r
-}\r
-CV_MatrOpTest::~CV_MatrOpTest() {}\r
-\r
-bool CV_MatrOpTest::checkMatSetError(const Mat& m1, const Mat& m2)\r
-{\r
- if (norm(m1, m2, NORM_INF) == 0)\r
- return true;\r
- \r
- ts->set_failed_test_info(CvTS::FAIL_MISMATCH);\r
- return false; \r
-}\r
-\r
-bool CV_MatrOpTest::TestMat()\r
-{\r
- Mat one_3x1(3, 1, CV_32F, Scalar(1.0));\r
- Mat shi_3x1(3, 1, CV_32F, Scalar(1.2));\r
- Mat shi_2x1(2, 1, CV_32F, Scalar(-1));\r
- Scalar shift = Scalar::all(15);\r
-\r
- float data[] = { sqrt(2.f)/2, -sqrt(2.f)/2, 1.f, sqrt(2.f)/2, sqrt(2.f)/2, 10.f };\r
- Mat rot_2x3(2, 3, CV_32F, data);\r
- \r
- Mat res = rot_2x3 * (one_3x1 + shi_3x1 + shi_3x1 + shi_3x1) - shi_2x1 + shift;\r
-\r
- Mat tmp, res2;\r
- add(one_3x1, shi_3x1, tmp);\r
- add(tmp, shi_3x1, tmp);\r
- add(tmp, shi_3x1, tmp);\r
- gemm(rot_2x3, tmp, 1, shi_2x1, -1, res2, 0);\r
- add(res2, Mat(2, 1, CV_32F, shift), res2);\r
- \r
- if (!checkMatSetError(res, res2))\r
- return false;\r
- \r
- Mat mat4x4(4, 4, CV_32F);\r
- randu(mat4x4, Scalar(0), Scalar(10));\r
-\r
- Mat roi1 = mat4x4(Rect(Point(1, 1), Size(2, 2)));\r
- Mat roi2 = mat4x4(Range(1, 3), Range(1, 3));\r
-\r
- if (!checkMatSetError(roi1, roi2))\r
- return false;\r
-\r
- if (!checkMatSetError(mat4x4, mat4x4(Rect(Point(0,0), mat4x4.size()))))\r
- return false;\r
-\r
- \r
- return true;\r
-}\r
-\r
-bool CV_MatrOpTest::TestMatND()\r
-{ \r
- int sizes[] = { 3, 3, 3};\r
- cv::MatND nd(3, sizes, CV_32F);\r
-\r
- /* MatND res = nd * nd + nd; \r
- MatND res2;\r
- cv::gemm(nd, nd, 1, nd, 1, res2);\r
- \r
- if (!checkMatSetError(res1, res2))\r
- return false;*/\r
-\r
- return true;\r
-}\r
-\r
-bool CV_MatrOpTest::TestSparseMat()\r
-{ \r
- int sizes[] = { 10, 10, 10};\r
- SparseMat mat(sizeof(sizes)/sizeof(sizes[0]), sizes, CV_32F);\r
-\r
- return true;\r
-}\r
-\r
-\r
-\r
-void CV_MatrOpTest::run( int /* start_from */)\r
-{\r
- if (!TestMat())\r
- return;\r
-\r
- if (!TestMatND())\r
- return;\r
-\r
- if (!TestSparseMat())\r
- return;\r
- \r
- ts->set_failed_test_info(CvTS::OK);\r
-}\r
-\r
-CV_MatrOpTest cv_MatrOp_test;\r
-\r
-\r
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "cxcoretest.h"
+++ /dev/null
-# ----------------------------------------------------------------------------
-# CMake file for cxts. See root CMakeLists.txt
-#
-# ----------------------------------------------------------------------------
-project(opencv_ts)
-
-file(GLOB lib_srcs "*.cpp")
-source_group("Src" FILES ${lib_srcs})
-file(GLOB lib_hdrs "*.h*")
-source_group("Include" FILES ${lib_hdrs})
-
-include_directories(.
- "${CMAKE_SOURCE_DIR}/modules/core/include")
-
-if(WIN32 AND MSVC)
- set(pch_header "_cxts.h")
- set(pch_src "precomp.cpp")
- list(REMOVE_ITEM lib_srcs ${CMAKE_CURRENT_SOURCE_DIR}/${pch_src})
- set(lib_srcs ${CMAKE_CURRENT_SOURCE_DIR}/${pch_src} ${lib_srcs})
- foreach(src_file ${lib_srcs})
- if(${src_file} MATCHES ${pch_src})
- set_source_files_properties(
- ${src_file}
- PROPERTIES
- COMPILE_FLAGS "/Yc${pch_header}"
- )
- else()
- set_source_files_properties(
- ${src_file}
- PROPERTIES
- COMPILE_FLAGS "/Yu${pch_header}"
- )
- endif()
- endforeach()
-endif()
-
-# ----------------------------------------------------------------------------------
-# Define the library target:
-# ----------------------------------------------------------------------------------
-set(the_target "opencv_ts")
-
-add_library(${the_target} ${lib_srcs} ${lib_hdrs})
-
-# For dynamic link numbering convenions
-set_target_properties(${the_target} PROPERTIES
- VERSION ${OPENCV_VERSION}
- SOVERSION ${OPENCV_SOVERSION}
- OUTPUT_NAME "${the_target}${OPENCV_DLLVERSION}"
- )
-
-# Additional target properties
-set_target_properties(${the_target} PROPERTIES
- DEBUG_POSTFIX "${OPENCV_DEBUG_POSTFIX}"
- ARCHIVE_OUTPUT_DIRECTORY "${CMAKE_BINARY_DIR}/lib/"
- RUNTIME_OUTPUT_DIRECTORY "${CMAKE_BINARY_DIR}/bin/"
- DEFINE_SYMBOL "CVAPI_EXPORTS"
- )
-
-add_dependencies(${the_target} opencv_core)
-
-# Add the required libraries for linking:
-target_link_libraries(${the_target} ${OPENCV_LINKER_LIBS} opencv_core)
-
-if(WIN32)
-install(TARGETS ${the_target}
- RUNTIME DESTINATION bin COMPONENT main
- LIBRARY DESTINATION lib COMPONENT main
- ARCHIVE DESTINATION lib COMPONENT main)
-endif()
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#ifndef __CXTS_INTERNAL_H__
-#define __CXTS_INTERNAL_H__
-
-#if (defined WIN32 || defined _WIN32) && (_MSC_VER >= 1200 || defined _ICL)
-#pragma warning( disable: 4251 4514 4996 )
-#endif
-
-#include "cxts.h"
-#include "opencv2/core/internal.hpp"
-#include <assert.h>
-#include <float.h>
-#include <limits.h>
-#include <math.h>
-#include <stdio.h>
-#include <stdlib.h>
-#include <string.h>
-
-#endif/*__CXTS_INTERNAL_H__*/
-
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "_cxts.h"
-#include <ctype.h>
-#include <stdarg.h>
-#include <fcntl.h>
-#include <time.h>
-#if defined WIN32 || defined _WIN32 || defined WIN64 || defined _WIN64
-#include <io.h>
-#else
-#include <unistd.h>
-#endif
-
-CvTest* CvTest::first = 0;
-CvTest* CvTest::last = 0;
-int CvTest::test_count = 0;
-
-/*****************************************************************************************\
-* Exception and memory handlers *
-\*****************************************************************************************/
-
-// a few platform-dependent declarations
-
-#define CV_TS_NORMAL 0
-#define CV_TS_BLUE 1
-#define CV_TS_GREEN 2
-#define CV_TS_RED 4
-
-#if defined WIN32 || defined _WIN32 || defined WIN64 || defined _WIN64
-#include <windows.h>
-
-#ifdef _MSC_VER
-#include <eh.h>
-#endif
-
-#ifdef _MSC_VER
-static void cv_seh_translator( unsigned int /*u*/, EXCEPTION_POINTERS* pExp )
-{
- int code = CvTS::FAIL_EXCEPTION;
- switch( pExp->ExceptionRecord->ExceptionCode )
- {
- case EXCEPTION_ACCESS_VIOLATION:
- case EXCEPTION_ARRAY_BOUNDS_EXCEEDED:
- case EXCEPTION_DATATYPE_MISALIGNMENT:
- case EXCEPTION_FLT_STACK_CHECK:
- case EXCEPTION_STACK_OVERFLOW:
- case EXCEPTION_IN_PAGE_ERROR:
- code = CvTS::FAIL_MEMORY_EXCEPTION;
- break;
- case EXCEPTION_FLT_DENORMAL_OPERAND:
- case EXCEPTION_FLT_DIVIDE_BY_ZERO:
- case EXCEPTION_FLT_INEXACT_RESULT:
- case EXCEPTION_FLT_INVALID_OPERATION:
- case EXCEPTION_FLT_OVERFLOW:
- case EXCEPTION_FLT_UNDERFLOW:
- case EXCEPTION_INT_DIVIDE_BY_ZERO:
- case EXCEPTION_INT_OVERFLOW:
- code = CvTS::FAIL_ARITHM_EXCEPTION;
- break;
- case EXCEPTION_BREAKPOINT:
- case EXCEPTION_ILLEGAL_INSTRUCTION:
- case EXCEPTION_INVALID_DISPOSITION:
- case EXCEPTION_NONCONTINUABLE_EXCEPTION:
- case EXCEPTION_PRIV_INSTRUCTION:
- case EXCEPTION_SINGLE_STEP:
- code = CvTS::FAIL_EXCEPTION;
- }
- throw code;
-}
-#endif
-
-static void change_color( int color )
-{
- static int normal_attributes = -1;
- HANDLE hstdout = GetStdHandle(STD_OUTPUT_HANDLE);
- fflush(stdout);
-
- if( normal_attributes < 0 )
- {
- CONSOLE_SCREEN_BUFFER_INFO info;
- GetConsoleScreenBufferInfo( hstdout, &info );
- normal_attributes = info.wAttributes;
- }
-
- SetConsoleTextAttribute( hstdout,
- (WORD)(color == CV_TS_NORMAL ? normal_attributes :
- ((color & CV_TS_BLUE ? FOREGROUND_BLUE : 0)|
- (color & CV_TS_GREEN ? FOREGROUND_GREEN : 0)|
- (color & CV_TS_RED ? FOREGROUND_RED : 0)|FOREGROUND_INTENSITY)) );
-}
-
-#else
-
-#include <signal.h>
-
-static const int cv_ts_sig_id[] = { SIGSEGV, SIGBUS, SIGFPE, SIGILL, SIGABRT, -1 };
-
-static jmp_buf cv_ts_jmp_mark;
-
-void cv_signal_handler( int sig_code )
-{
- int code = CvTS::FAIL_EXCEPTION;
- switch( sig_code )
- {
- case SIGFPE:
- code = CvTS::FAIL_ARITHM_EXCEPTION;
- break;
- case SIGSEGV:
- case SIGBUS:
- code = CvTS::FAIL_ARITHM_EXCEPTION;
- break;
- case SIGILL:
- code = CvTS::FAIL_EXCEPTION;
- }
-
- longjmp( cv_ts_jmp_mark, code );
-}
-
-static void change_color( int color )
-{
- static const uchar ansi_tab[] = { 30, 34, 32, 36, 31, 35, 33, 37 };
- char buf[16];
- int code = 0;
- fflush( stdout );
- if( color != CV_TS_NORMAL )
- code = ansi_tab[color & (CV_TS_BLUE|CV_TS_GREEN|CV_TS_RED)];
- sprintf( buf, "\x1b[%dm", code );
- fputs( buf, stdout );
-}
-
-#endif
-
-
-// reads 16-digit hexadecimal number (i.e. 64-bit integer)
-static int64 read_seed( const char* str )
-{
- int64 val = 0;
- if( str && strlen(str) == 16 )
- {
- for( int i = 0; str[i]; i++ )
- {
- int c = tolower(str[i]);
- if( !isxdigit(c) )
- return 0;
- val = val * 16 +
- (str[i] < 'a' ? str[i] - '0' : str[i] - 'a' + 10);
- }
- }
- return val;
-}
-
-
-/***************************** memory manager *****************************/
-
-typedef struct CvTestAllocBlock
-{
- struct CvTestAllocBlock* prev;
- struct CvTestAllocBlock* next;
- char* origin;
- char* data;
- size_t size;
- int index;
-}
-CvTestAllocBlock;
-
-
-class CvTestMemoryManager
-{
-public:
- CvTestMemoryManager( CvTS* ts );
- virtual ~CvTestMemoryManager();
-
- virtual void clear_and_check( int min_index = -1 );
- virtual void start_tracking( int index_to_stop_at=-1 );
- virtual void stop_tracking_and_check();
- int get_alloc_index() { return index; }
-
- static void* alloc_proxy( size_t size, void* userdata );
- static int free_proxy( void* ptr, void* userdata );
-
-protected:
- virtual void* alloc( size_t size );
- virtual int free( void* ptr );
- virtual int free_block( CvTestAllocBlock* block );
-
- int index;
- int track_blocks;
- int show_msg_box;
- int index_to_stop_at;
- const char* guard_pattern;
- int guard_size;
- int block_align;
- enum { MAX_MARKS = 1024 };
- int marks[MAX_MARKS];
- int marks_top;
- CvTS* ts;
- CvTestAllocBlock* first;
- CvTestAllocBlock* last;
-};
-
-
-void* CvTestMemoryManager::alloc_proxy( size_t size, void* userdata )
-{
- return ((CvTestMemoryManager*)userdata)->alloc( size );
-}
-
-
-int CvTestMemoryManager::free_proxy( void* ptr, void* userdata )
-{
- return ((CvTestMemoryManager*)userdata)->free( ptr );
-}
-
-
-CvTestMemoryManager::CvTestMemoryManager( CvTS* _test_system )
-{
- ts = _test_system;
- guard_pattern = "THIS IS A GUARD PATTERN!";
- guard_size = (int)strlen(guard_pattern);
- block_align = CV_MALLOC_ALIGN;
- track_blocks = 0;
- marks_top = 0;
- first = last = 0;
- index = 0;
- index_to_stop_at = -1;
- show_msg_box = 1;
-}
-
-
-CvTestMemoryManager::~CvTestMemoryManager()
-{
- clear_and_check();
-}
-
-
-void CvTestMemoryManager::clear_and_check( int min_index )
-{
- int alloc_index = -1;
- CvTestAllocBlock* block;
- int leak_size = 0, leak_block_count = 0, mem_size = 0;
- void* mem_addr = 0;
-
- while( marks_top > 0 && marks[marks_top - 1] >= min_index )
- marks_top--;
-
- for( block = last; block != 0; )
- {
- CvTestAllocBlock* prev = block->prev;
- if( block->index < min_index )
- break;
- leak_size += (int)block->size;
- leak_block_count++;
- alloc_index = block->index;
- mem_addr = block->data;
- mem_size = (int)block->size;
- free_block( block );
- block = prev;
- }
- track_blocks--;
- if( leak_block_count > 0 )
- {
- ts->set_failed_test_info( CvTS::FAIL_MEMORY_LEAK, alloc_index );
- ts->printf( CvTS::LOG, "Memory leaks: %u blocks, %u bytes total\n"
- "%s leaked block: %p, %u bytes\n",
- leak_block_count, leak_size, leak_block_count > 1 ? "The first" : "The",
- mem_addr, mem_size );
- }
-
- index = block ? block->index + 1 : 0;
-}
-
-
-void CvTestMemoryManager::start_tracking( int _index_to_stop_at )
-{
- track_blocks--;
- marks[marks_top++] = index;
- assert( marks_top <= MAX_MARKS );
- track_blocks+=2;
- index_to_stop_at = _index_to_stop_at >= index ? _index_to_stop_at : -1;
-}
-
-
-void CvTestMemoryManager::stop_tracking_and_check()
-{
- if( marks_top > 0 )
- {
- int min_index = marks[--marks_top];
- clear_and_check( min_index );
- }
-}
-
-
-int CvTestMemoryManager::free_block( CvTestAllocBlock* block )
-{
- int code = 0;
- char* data = block->data;
-
- if( block->origin == 0 || ((size_t)block->origin & (sizeof(double)-1)) != 0 )
- code = CvTS::FAIL_MEMORY_CORRUPTION_BEGIN;
-
- if( memcmp( data - guard_size, guard_pattern, guard_size ) != 0 )
- code = CvTS::FAIL_MEMORY_CORRUPTION_BEGIN;
- else if( memcmp( data + block->size, guard_pattern, guard_size ) != 0 )
- code = CvTS::FAIL_MEMORY_CORRUPTION_END;
-
- if( code >= 0 )
- {
- if( block->prev )
- block->prev->next = block->next;
- else if( first == block )
- first = block->next;
-
- if( block->next )
- block->next->prev = block->prev;
- else if( last == block )
- last = block->prev;
-
- free( block->origin );
- }
- else
- {
- ts->set_failed_test_info( code, block->index );
- ts->printf( CvTS::LOG, "Corrupted block (%s): %p, %u bytes\n",
- code == CvTS::FAIL_MEMORY_CORRUPTION_BEGIN ? "beginning" : "end",
- block->data, block->size );
- }
-
- return code;
-}
-
-
-void* CvTestMemoryManager::alloc( size_t size )
-{
- char* data;
- CvTestAllocBlock* block;
- size_t new_size = sizeof(*block) + size + guard_size*2 + block_align + sizeof(size_t)*2;
- char* ptr = (char*)malloc( new_size );
-
- if( !ptr )
- return 0;
-
- data = (char*)cvAlignPtr( ptr + sizeof(size_t) + sizeof(*block) + guard_size, block_align );
- block = (CvTestAllocBlock*)cvAlignPtr( data - guard_size -
- sizeof(size_t) - sizeof(*block), sizeof(size_t) );
- block->origin = ptr;
- block->data = data;
- block->size = 0;
- block->index = -1;
- block->next = block->prev = 0;
- memcpy( data - guard_size, guard_pattern, guard_size );
- memcpy( data + size, guard_pattern, guard_size );
-
- if( track_blocks > 0 )
- {
- track_blocks--;
- block->size = size;
-
- if( index == index_to_stop_at )
- {
- if( show_msg_box )
- {
- #if defined WIN32 || defined _WIN32
- MessageBox( NULL, "The block that is corrupted and/or not deallocated has been just allocated\n"
- "Press Ok to start debugging", "Memory Manager", MB_ICONERROR|MB_OK|MB_SYSTEMMODAL );
- #endif
- }
- CV_DBG_BREAK();
- }
-
- block->index = index++;
-
- block->prev = last;
- block->next = 0;
- if( last )
- last = last->next = block;
- else
- first = last = block;
-
- track_blocks++;
- }
-
- return data;
-}
-
-
-int CvTestMemoryManager::free( void* ptr )
-{
- char* data = (char*)ptr;
- CvTestAllocBlock* block = (CvTestAllocBlock*)
- cvAlignPtr( data - guard_size - sizeof(size_t) - sizeof(*block), sizeof(size_t) );
-
- int code = free_block( block );
- if( code < 0 && ts->is_debug_mode() )
- CV_DBG_BREAK();
- return 0;
-}
-
-
-/***************************** error handler *****************************/
-
-#if 0
-static int cvTestErrorCallback( int status, const char* func_name, const char* err_msg,
- const char* file_name, int line, void* userdata )
-{
- if( status < 0 && status != CV_StsBackTrace && status != CV_StsAutoTrace )
- ((CvTS*)userdata)->set_failed_test_info( CvTS::FAIL_ERROR_IN_CALLED_FUNC );
-
- // print error message
- return cvStdErrReport( status, func_name, err_msg, file_name, line, 0 );
-}
-#endif
-
-/*****************************************************************************************\
-* Base Class for Tests *
-\*****************************************************************************************/
-
-CvTest::CvTest( const char* _test_name, const char* _test_funcs, const char* _test_descr ) :
- name(_test_name ? _test_name : ""), tested_functions(_test_funcs ? _test_funcs : ""),
- description(_test_descr ? _test_descr : ""), ts(0)
-{
- if( last )
- last->next = this;
- else
- first = this;
- last = this;
- test_count++;
- ts = 0;
- hdr_state = 0;
-
- timing_param_names = 0;
- timing_param_current = 0;
- timing_param_seqs = 0;
- timing_param_idxs = 0;
- timing_param_count = -1;
-
- test_case_count = -1;
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE;
-}
-
-CvTest::~CvTest()
-{
- clear();
-}
-
-CvTest* CvTest::get_first_test()
-{
- return first;
-}
-
-void CvTest::clear()
-{
- if( timing_param_current )
- free( timing_param_current );
- if( timing_param_seqs )
- free( timing_param_seqs );
- if( timing_param_idxs )
- free( timing_param_idxs );
-
- timing_param_current = 0;
- timing_param_seqs = 0;
- timing_param_idxs = 0;
- timing_param_count = -1;
-}
-
-
-int CvTest::init( CvTS* _test_system )
-{
- clear();
- ts = _test_system;
- return read_params( ts->get_file_storage() );
-}
-
-
-const char* CvTest::get_parent_name( const char* name, char* buffer )
-{
- const char* dash_pos = strrchr( name ? name : "", '-' );
- if( !dash_pos )
- return 0;
-
- if( name != (const char*)buffer )
- strncpy( buffer, name, dash_pos - name );
- buffer[dash_pos - name] = '\0';
- return buffer;
-}
-
-
-const CvFileNode* CvTest::find_param( CvFileStorage* fs, const char* param_name )
-{
- char buffer[256];
- const char* name = get_name();
- CvFileNode* node = 0;
-
- for(;;)
- {
- if( !name )
- break;
- node = cvGetFileNodeByName( fs, 0, name );
- if( node )
- {
- node = cvGetFileNodeByName( fs, node, param_name );
- if( node )
- break;
- }
- name = get_parent_name( name, buffer );
- }
-
- return node;
-}
-
-
-void CvTest::start_write_param( CvFileStorage* fs )
-{
- if( hdr_state == 0 )
- {
- cvStartWriteStruct( fs, get_name(), CV_NODE_MAP );
- hdr_state = 1;
- }
-}
-
-
-void CvTest::write_param( CvFileStorage* fs, const char* paramname, int val )
-{
- if( !ts->find_written_param( this, paramname, CV_NODE_INT, &val) )
- {
- start_write_param( fs );
- cvWriteInt( fs, paramname, val );
- }
-}
-
-
-void CvTest::write_param( CvFileStorage* fs, const char* paramname, double val )
-{
- if( !ts->find_written_param( this, paramname, CV_NODE_REAL, &val) )
- {
- start_write_param( fs );
- cvWriteReal( fs, paramname, val );
- }
-}
-
-
-void CvTest::write_param( CvFileStorage* fs, const char* paramname, const char* val )
-{
- if( !ts->find_written_param( this, paramname, CV_NODE_STRING, &val) )
- {
- start_write_param( fs );
- cvWriteString( fs, paramname, val );
- }
-}
-
-
-void CvTest::write_string_list( CvFileStorage* fs, const char* paramname, const char** val, int count )
-{
- if( val )
- {
- start_write_param( fs );
- int i;
- if( count < 0 )
- count = INT_MAX;
-
- cvStartWriteStruct( fs, paramname, CV_NODE_SEQ + CV_NODE_FLOW );
- for( i = 0; i < count && val[i] != 0; i++ )
- cvWriteString( fs, 0, val[i] );
- cvEndWriteStruct( fs );
- }
-}
-
-
-void CvTest::write_int_list( CvFileStorage* fs, const char* paramname,
- const int* val, int count, int stop_value )
-{
- if( val )
- {
- start_write_param( fs );
- int i;
- if( count < 0 )
- count = INT_MAX;
-
- cvStartWriteStruct( fs, paramname, CV_NODE_SEQ + CV_NODE_FLOW );
- for( i = 0; i < count && val[i] != stop_value; i++ )
- cvWriteInt( fs, 0, val[i] );
- cvEndWriteStruct( fs );
- }
-}
-
-
-void CvTest::write_real_list( CvFileStorage* fs, const char* paramname,
- const double* val, int count, double stop_value )
-{
- if( val )
- {
- start_write_param( fs );
- int i;
- if( count < 0 )
- count = INT_MAX;
-
- cvStartWriteStruct( fs, paramname, CV_NODE_SEQ + CV_NODE_FLOW );
- for( i = 0; i < count && val[i] != stop_value; i++ )
- cvWriteReal( fs, 0, val[i] );
- cvEndWriteStruct( fs );
- }
-}
-
-
-int CvTest::read_params( CvFileStorage* fs )
-{
- int code = 0;
-
- if(fs == NULL)
- return code;
-
- if( ts->get_testing_mode() == CvTS::TIMING_MODE )
- {
- timing_param_names = find_param( fs, "timing_params" );
- if(!timing_param_names)
- return code;
-
- if( CV_NODE_IS_SEQ(timing_param_names->tag) )
- {
- CvSeq* seq = timing_param_names->data.seq;
- CvSeqReader reader;
- cvStartReadSeq( seq, &reader );
- int i;
-
- timing_param_count = seq->total;
- timing_param_seqs = (const CvFileNode**)malloc( timing_param_count*sizeof(timing_param_seqs[0]));
- timing_param_idxs = (int*)malloc( timing_param_count*sizeof(timing_param_idxs[0]));
- timing_param_current = (const CvFileNode**)malloc( timing_param_count*sizeof(timing_param_current[0]));
- test_case_count = 1;
-
- for( i = 0; i < timing_param_count; i++ )
- {
- CvFileNode* param_name = (CvFileNode*)(reader.ptr);
-
- if( !CV_NODE_IS_STRING(param_name->tag) )
- {
- ts->printf( CvTS::LOG, "ERROR: name of timing parameter #%d is not a string\n", i );
- code = -1;
- break;
- }
-
- timing_param_idxs[i] = 0;
- timing_param_current[i] = 0;
- timing_param_seqs[i] = find_param( fs, param_name->data.str.ptr );
- if( !timing_param_seqs[i] )
- {
- ts->printf( CvTS::LOG, "ERROR: timing parameter %s is not found\n", param_name->data.str.ptr );
- code = -1;
- break;
- }
-
- if( CV_NODE_IS_SEQ(timing_param_seqs[i]->tag) )
- test_case_count *= timing_param_seqs[i]->data.seq->total;
-
- CV_NEXT_SEQ_ELEM( seq->elem_size, reader );
- }
-
- if( i < timing_param_count )
- timing_param_count = 0;
- }
- else
- {
- ts->printf( CvTS::LOG, "ERROR: \"timing_params\" is not found" );
- code = -1;
- }
- }
-
- return code;
-}
-
-
-int CvTest::get_next_timing_param_tuple(void)
-{
- bool increment;
- int i;
-
- if( timing_param_count <= 0 || !timing_param_names || !timing_param_seqs )
- return -1;
-
- increment = timing_param_current[0] != 0; // if already have some valid test tuple, move to the next
- for( i = 0; i < timing_param_count; i++ )
- {
- const CvFileNode* node = timing_param_seqs[i];
- int total = CV_NODE_IS_SEQ(node->tag) ? node->data.seq->total : 1;
- int new_idx = timing_param_idxs[i];
-
- if( !timing_param_current[i] )
- timing_param_idxs[i] = new_idx = 0;
- else if( increment )
- {
- new_idx++;
- if( new_idx >= total )
- new_idx = 0;
- else if( total > 1 )
- increment = false;
- }
-
- if( !timing_param_current[i] || new_idx != timing_param_idxs[i] )
- {
- if( CV_NODE_IS_SEQ(node->tag) )
- timing_param_current[i] = (CvFileNode*)cvGetSeqElem( node->data.seq, new_idx );
- else
- timing_param_current[i] = node;
- timing_param_idxs[i] = new_idx;
- }
- }
-
- return !increment; // return 0 in case of overflow (i.e. if there is no more test cases)
-}
-
-
-const CvFileNode* CvTest::find_timing_param( const char* paramname )
-{
- if( timing_param_names )
- {
- int i;
- CvSeqReader reader;
- cvStartReadSeq( timing_param_names->data.seq, &reader, 0 );
-
- for( i = 0; i < timing_param_count; i++ )
- {
- const char* ptr = ((const CvFileNode*)(reader.ptr))->data.str.ptr;
- if( ptr[0] == paramname[0] && strcmp(ptr, paramname) == 0 )
- return timing_param_current[i];
- CV_NEXT_SEQ_ELEM( reader.seq->elem_size, reader );
- }
- }
- return 0;
-}
-
-
-int CvTest::write_defaults(CvTS* _ts)
-{
- ts = _ts;
- hdr_state = 0;
- write_default_params( ts->get_file_storage() );
- if( hdr_state )
- cvEndWriteStruct( ts->get_file_storage() );
- return 0;
-}
-
-
-int CvTest::write_default_params( CvFileStorage* fs )
-{
- if( ts->get_testing_mode() == CvTS::TIMING_MODE )
- write_string_list( fs, "timing_params", default_timing_param_names, timing_param_count );
- return 0;
-}
-
-
-bool CvTest::can_do_fast_forward()
-{
- return true;
-}
-
-
-int CvTest::get_support_testing_modes()
-{
- return support_testing_modes;
-}
-
-void CvTest::safe_run( int start_from )
-{
- if(ts->is_debug_mode())
- run( start_from );
- else
- {
- try
- {
- #if !defined WIN32 && !defined _WIN32
- int _code = setjmp( cv_ts_jmp_mark );
- if( !_code )
- run( start_from );
- else
- throw _code;
- #else
- run( start_from );
- #endif
- }
- catch (const cv::Exception& exc)
- {
- const char* errorStr = cvErrorStr(exc.code);
- char buf[1 << 16];
-
- sprintf( buf, "OpenCV Error: %s (%s) in %s, file %s, line %d",
- errorStr, exc.err.c_str(), exc.func.size() > 0 ?
- exc.func.c_str() : "unknown function", exc.file.c_str(), exc.line );
- ts->printf(CvTS::LOG, "%s\n", buf);
- ts->set_failed_test_info( CvTS::FAIL_ERROR_IN_CALLED_FUNC );
- }
- catch (...)
- {
- ts->set_failed_test_info( CvTS::FAIL_EXCEPTION );
- }
- }
-}
-
-
-void CvTest::run( int start_from )
-{
- int i, test_case_idx, count = get_test_case_count();
- int64 t_start = cvGetTickCount();
- double freq = cv::getTickFrequency();
- bool ff = can_do_fast_forward();
- int progress = 0, code;
- std::vector<double> v_cpe, v_time;
- int64 t1 = t_start;
-
- for( test_case_idx = ff && start_from >= 0 ? start_from : 0;
- count < 0 || test_case_idx < count; test_case_idx++ )
- {
- ts->update_context( this, test_case_idx, ff );
- progress = update_progress( progress, test_case_idx, count, (double)(t1 - t_start)/(freq*1000) );
-
- int64 t00 = 0, t0 = 0, t2 = 0, t3 = 0;
- double t_acc = 0, t_cpu_acc = 0;
-
- if( ts->get_testing_mode() == CvTS::TIMING_MODE )
- {
- const int iterations = 20;
- code = prepare_test_case( test_case_idx );
-
- if( code < 0 || ts->get_err_code() < 0 )
- return;
-
- if( code == 0 )
- continue;
-
- v_cpe.resize(0);
- v_time.resize(0);
-
- for( i = 0; i < iterations; i++ )
- {
- for(;;)
- {
- t0 = cv::getTickCount();
- t2 = cv::getCPUTickCount();
-
- run_func();
-
- t3 = cv::getCPUTickCount();
- t1 = cv::getTickCount();
-
- if( ts->get_err_code() < 0 )
- return;
-
- if( t3 - t2 > 0 && t1 - t0 > 1 )
- break;
- }
-
- if( i == 0 )
- t00 = t0;
-
- v_cpe.push_back((double)(t3 - t2));
- v_time.push_back((double)(t1 - t0));
-
- if( i >= 5 && t1 - t00 > freq*5 )
- break;
- }
-
- std::sort(v_cpe.begin(), v_cpe.end());
- std::sort(v_time.begin(), v_time.end());
-
- t_cpu_acc = v_cpe[i/2];
- t_acc = v_time[i/2];
-
- print_time( test_case_idx, t_acc, t_cpu_acc );
- }
- else
- {
- code = prepare_test_case( test_case_idx );
- if( code < 0 || ts->get_err_code() < 0 )
- return;
-
- if( code == 0 )
- continue;
-
- run_func();
-
- if( ts->get_err_code() < 0 )
- return;
-
- if( validate_test_results( test_case_idx ) < 0 || ts->get_err_code() < 0 )
- return;
- }
- }
-}
-
-
-void CvTest::run_func(void)
-{
- assert(0);
-}
-
-
-int CvTest::get_test_case_count(void)
-{
- return test_case_count;
-}
-
-
-int CvTest::prepare_test_case( int )
-{
- return 0;
-}
-
-
-int CvTest::validate_test_results( int )
-{
- return 0;
-}
-
-
-void CvTest::print_time( int /*test_case_idx*/, double /*time_usecs*/, double /*time_cpu_clocks*/ )
-{
-}
-
-
-int CvTest::update_progress( int progress, int test_case_idx, int count, double dt )
-{
- int width = 60 - (int)strlen(get_name());
- if( count > 0 )
- {
- int t = cvRound( ((double)test_case_idx * width)/count );
- if( t > progress )
- {
- ts->printf( CvTS::CONSOLE, "." );
- progress = t;
- }
- }
- else if( cvRound(dt) > progress )
- {
- ts->printf( CvTS::CONSOLE, "." );
- progress = cvRound(dt);
- }
-
- return progress;
-}
-
-
-CvBadArgTest::CvBadArgTest( const char* _test_name, const char* _test_funcs, const char* _test_descr )
- : CvTest( _test_name, _test_funcs, _test_descr )
-{
- progress = -1;
- test_case_idx = -1;
- freq = cv::getTickFrequency();
-}
-
-CvBadArgTest::~CvBadArgTest(void)
-{
-}
-
-int CvBadArgTest::run_test_case( int expected_code, const char* descr )
-{
- double new_t = (double)cv::getTickCount(), dt;
- if( test_case_idx < 0 )
- {
- test_case_idx = 0;
- progress = 0;
- dt = 0;
- }
- else
- {
- dt = (new_t - t)/(freq*1000);
- t = new_t;
- }
- progress = update_progress(progress, test_case_idx, 0, dt);
-
- int errcount = 0;
- bool thrown = false;
-
- if(!descr)
- descr = "";
-
- try
- {
- run_func();
- }
-
- catch(const cv::Exception& e)
- {
- thrown = true;
- if( e.code != expected_code )
- {
- ts->printf(CvTS::LOG, "%s (test case #%d): the error code %d is different from the expected %d\n",
- descr, test_case_idx, e.code, expected_code);
- errcount = 1;
- }
- }
-
- catch(...)
- {
- thrown = true;
- ts->printf(CvTS::LOG, "%s (test case #%d): unknown exception was thrown (the function has likely crashed)\n",
- descr, test_case_idx);
- errcount = 1;
- }
-
- if(!thrown)
- {
- ts->printf(CvTS::LOG, "%s (test case #%d): no expected exception was thrown\n",
- descr, test_case_idx);
- errcount = 1;
- }
- test_case_idx++;
-
- return errcount;
-}
-
-
-/*****************************************************************************************\
-* Base Class for Test System *
-\*****************************************************************************************/
-
-/******************************** Constructors/Destructors ******************************/
-
-CvTS::CvTS(const char* _module_name)
-{
- module_name = _module_name;
- start_time = 0;
- version = CV_TS_VERSION;
- memory_manager = 0;
-
- /*
- memory_manager = new CvTestMemoryManager(this);
- cvSetMemoryManager( CvTestMemoryManager::alloc_proxy,
- CvTestMemoryManager::free_proxy,
- memory_manager );*/
-
- ostrm_suffixes[SUMMARY_IDX] = ".sum";
- ostrm_suffixes[LOG_IDX] = ".log";
- ostrm_suffixes[CSV_IDX] = ".csv";
- ostrm_suffixes[CONSOLE_IDX] = 0;
-
- ostrm_base_name = 0;
-
- memset( output_streams, 0, sizeof(output_streams) );
- memset( ¶ms, 0, sizeof(params) );
-
- selected_tests = new CvTestPtrVec();
- failed_tests = new CvTestInfoVec();
- written_params = new CvTestPtrVec();
-
- clear();
-
- return;
-} // ctor
-
-
-void CvTS::clear(void)
-{
- int i;
- CvTest* test;
-
- for( test = get_first_test(); test != 0; test = test->get_next() )
- test->clear();
-
- for( i = 0; i <= CONSOLE_IDX; i++ )
- {
- if( i == LOG_IDX )
- fflush( stderr );
- else if( i == CONSOLE_IDX )
- fflush( stdout );
-
- if( i < CONSOLE_IDX && output_streams[i].f )
- {
- fclose( output_streams[i].f );
- output_streams[i].f = 0;
- }
-
- if( i == LOG_IDX && output_streams[i].default_handle > 0 )
- {
- dup2( output_streams[i].default_handle, 2 );
- output_streams[i].default_handle = 0;
- }
- output_streams[i].enable = 1;
- }
-
- cvReleaseFileStorage( &fs );
-
- selected_tests->clear();
- failed_tests->clear();
-
- if( ostrm_base_name )
- {
- free( ostrm_base_name );
- ostrm_base_name = 0;
- }
-
- params.rng_seed = 0;
- params.debug_mode = -1;
- params.print_only_failed = 0;
- params.skip_header = -1;
- params.ignore_blacklist = -1;
- params.test_mode = CORRECTNESS_CHECK_MODE;
- params.timing_mode = MIN_TIME;
- params.use_optimized = -1;
- params.color_terminal = 1;
-
- if( memory_manager )
- memory_manager->clear_and_check();
-} // clear()
-
-
-CvTS::~CvTS(void)
-{
- clear();
- set_data_path(0);
-
- if( written_params )
- {
- for( int i = 0; i < written_params->size(); i++ )
- free( written_params->at(i) );
- delete written_params;
- }
-
- delete selected_tests;
- delete failed_tests;
-
- return;
-} // dtor
-
-
-const char* CvTS::str_from_code( int code )
-{
- switch( code )
- {
- case OK: return "Ok";
- case FAIL_GENERIC: return "Generic/Unknown";
- case FAIL_MISSING_TEST_DATA: return "No test data";
- case FAIL_INVALID_TEST_DATA: return "Invalid test data";
- case FAIL_ERROR_IN_CALLED_FUNC: return "cvError invoked";
- case FAIL_EXCEPTION: return "Hardware/OS exception";
- case FAIL_MEMORY_EXCEPTION: return "Invalid memory access";
- case FAIL_ARITHM_EXCEPTION: return "Arithmetic exception";
- case FAIL_MEMORY_CORRUPTION_BEGIN: return "Corrupted memblock (beginning)";
- case FAIL_MEMORY_CORRUPTION_END: return "Corrupted memblock (end)";
- case FAIL_MEMORY_LEAK: return "Memory leak";
- case FAIL_INVALID_OUTPUT: return "Invalid function output";
- case FAIL_MISMATCH: return "Unexpected output";
- case FAIL_BAD_ACCURACY: return "Bad accuracy";
- case FAIL_HANG: return "Infinite loop(?)";
- case FAIL_BAD_ARG_CHECK: return "Incorrect handling of bad arguments";
- default: return "Generic/Unknown";
- }
-}
-
-/************************************** Running tests **********************************/
-
-void CvTS::make_output_stream_base_name( const char* config_name )
-{
- int k, len = (int)strlen( config_name );
-
- if( ostrm_base_name )
- free( ostrm_base_name );
-
- for( k = len-1; k >= 0; k-- )
- {
- char c = config_name[k];
- if( c == '.' || c == '/' || c == '\\' || c == ':' )
- break;
- }
-
- if( k > 0 && config_name[k] == '.' )
- len = k;
-
- ostrm_base_name = (char*)malloc( len + 1 );
- memcpy( ostrm_base_name, config_name, len );
- ostrm_base_name[len] = '\0';
-}
-
-
-void CvTS::set_handlers( bool on )
-{
- if( on )
- {
- cvSetErrMode( CV_ErrModeParent );
- cvRedirectError( cvStdErrReport );
- #if defined WIN32 || defined _WIN32
- #ifdef _MSC_VER
- _set_se_translator( cv_seh_translator );
- #endif
- #else
- for( int i = 0; cv_ts_sig_id[i] >= 0; i++ )
- signal( cv_ts_sig_id[i], cv_signal_handler );
- #endif
- }
- else
- {
- cvSetErrMode( CV_ErrModeLeaf );
- cvRedirectError( cvGuiBoxReport );
- #if defined WIN32 || defined _WIN32
- #ifdef _MSC_VER
- _set_se_translator( 0 );
- #endif
- #else
- for( int i = 0; cv_ts_sig_id[i] >= 0; i++ )
- signal( cv_ts_sig_id[i], SIG_DFL );
- #endif
- }
-}
-
-
-void CvTS::set_data_path( const char* data_path )
-{
- if( data_path == params.data_path )
- return;
-
- if( params.data_path )
- delete[] params.data_path;
- if( data_path )
- {
- int size = (int)strlen(data_path)+1;
- bool append_slash = data_path[size-1] != '/' && data_path[size-1] != '\\';
- params.data_path = new char[size+1];
- memcpy( params.data_path, data_path, size );
- if( append_slash )
- strcat( params.data_path, "/" );
- }
-}
-
-
-typedef struct CvTsParamVal
-{
- const char* fullname;
- const void* val;
-
-} CvTsParamVal;
-
-
-int CvTS::find_written_param( CvTest* test, const char* paramname, int valtype, const void* val )
-{
- const char* testname = test->get_name();
- bool add_to_list = test->get_func_list()[0] == '\0';
- char buffer[256];
- int paramname_len = (int)strlen(paramname);
- int paramval_len = valtype == CV_NODE_INT ? (int)sizeof(int) :
- valtype == CV_NODE_REAL ? (int)sizeof(double) : -1;
- const char* name = CvTest::get_parent_name( testname, buffer );
-
- if( !fs )
- return -1;
-
- if( paramval_len < 0 )
- {
- assert(0); // unsupported parameter type
- return -1;
- }
-
- while( name )
- {
- int i, len = (int)strlen(buffer);
- buffer[len] = '.';
- memcpy( buffer + len + 1, paramname, paramname_len + 1 );
- for( i = 0; i < written_params->size(); i++ )
- {
- CvTsParamVal* param = (CvTsParamVal*)written_params->at(i);
- if( strcmp( param->fullname, buffer ) == 0 )
- {
- if( (paramval_len > 0 && memcmp( param->val, val, paramval_len ) == 0) ||
- (paramval_len < 0 && strcmp( (const char*)param->val, (const char*)val ) == 0) )
- return 1;
- break;
- }
- }
- if( i < written_params->size() )
- break;
- buffer[len] = '\0';
- name = CvTest::get_parent_name( buffer, buffer );
- }
-
- if( add_to_list )
- {
- int bufsize, fullname_len = (int)strlen(testname) + paramname_len + 2;
- CvTsParamVal* param;
- if( paramval_len < 0 )
- paramval_len = (int)strlen((const char*)val) + 1;
- bufsize = sizeof(*param) + fullname_len + paramval_len;
- param = (CvTsParamVal*)malloc(bufsize);
- param->fullname = (const char*)(param + 1);
- param->val = param->fullname + fullname_len;
- sprintf( (char*)param->fullname, "%s.%s", testname, paramname );
- memcpy( (void*)param->val, val, paramval_len );
- written_params->push( param );
- }
-
- return 0;
-}
-
-
-#ifndef MAX_PATH
-#define MAX_PATH 1024
-#endif
-
-static int CV_CDECL cmp_test_names( const void* a, const void* b )
-{
- return strcmp( (*(const CvTest**)a)->get_name(), (*(const CvTest**)b)->get_name() );
-}
-
-int CvTS::run( int argc, char** argv, const char** blacklist )
-{
- time( &start_time );
-
- int i, write_params = 0;
- int list_tests = 0;
- CvTestPtrVec all_tests;
- CvTest* test;
-
- // 0. reset all the parameters, reorder tests
- clear();
-
-/*#if defined WIN32 || defined _WIN32
- cv::setBreakOnError(true);
-#endif*/
-
- for( test = get_first_test(), i = 0; test != 0; test = test->get_next(), i++ )
- all_tests.push(test);
-
- if( all_tests.size() > 0 && all_tests.data() )
- qsort( all_tests.data(), all_tests.size(), sizeof(CvTest*), cmp_test_names );
-
- // 1. parse command line options
- for( i = 1; i < argc; i++ )
- {
- if( strcmp( argv[i], "-h" ) == 0 || strcmp( argv[i], "--help" ) == 0 )
- {
- print_help();
- return 0;
- }
- else if( strcmp( argv[i], "-f" ) == 0 )
- config_name = argv[++i];
- else if( strcmp( argv[i], "-w" ) == 0 )
- write_params = 1;
- else if( strcmp( argv[i], "-t" ) == 0 )
- params.test_mode = TIMING_MODE;
- else if( strcmp( argv[i], "-O0" ) == 0 || strcmp( argv[i], "-O1" ) == 0 )
- params.use_optimized = argv[i][2] - '0';
- else if( strcmp( argv[i], "-l" ) == 0 )
- list_tests = 1;
- else if( strcmp( argv[i], "-d" ) == 0 )
- set_data_path(argv[++i]);
- else if( strcmp( argv[i], "-nc" ) == 0 )
- params.color_terminal = 0;
- else if( strcmp( argv[i], "-nh" ) == 0 )
- params.skip_header = 1;
- else if( strcmp( argv[i], "-nb" ) == 0 )
- params.ignore_blacklist = 1;
- else if( strcmp( argv[i], "-r" ) == 0 )
- params.debug_mode = 0;
- else if( strcmp( argv[i], "-tn" ) == 0 )
- {
- params.test_filter_pattern = argv[++i];
- params.test_filter_mode = CHOOSE_TESTS;
- }
- else if( strcmp( argv[i], "-seed" ) == 0 )
- {
- params.rng_seed = read_seed(argv[++i]);
- if( params.rng_seed == 0 )
- fprintf(stderr, "Invalid or zero RNG seed. Will use the seed from the config file or default one\n");
- }
- }
-
- // this is the fallback for the current OpenCV autotools setup
- if( !params.data_path || !params.data_path[0] )
- {
- char* datapath_dir = getenv("OPENCV_TEST_DATA_PATH");
- char buf[1024];
- if( datapath_dir )
- {
- sprintf( buf, "%s/%s", datapath_dir, module_name ? module_name : "" );
- //printf( LOG + SUMMARY, "Data Path = %s\n", buf);
- set_data_path(buf);
- }
- }
-
- if( write_params )
- {
- if( !config_name )
- {
- printf( LOG, "ERROR: output config name is not specified\n" );
- return -1;
- }
-
- fs = cvOpenFileStorage( config_name, 0, CV_STORAGE_WRITE );
- if( !fs )
- {
- printf( LOG, "ERROR: could not open config file %s\n", config_name );
- return -1;
- }
-
- cvWriteComment( fs, CV_TS_VERSION " config file", 0 );
- cvStartWriteStruct( fs, "common", CV_NODE_MAP );
- write_default_params( fs );
- cvEndWriteStruct( fs );
-
- for( i = 0; i < all_tests.size(); i++ )
- {
- test = (CvTest*)all_tests[i];
- if( !(test->get_support_testing_modes() & get_testing_mode()) )
- continue;
-
- test->write_defaults( this );
- test->clear();
- }
-
- cvReleaseFileStorage( &fs );
-
- return 0;
- }
-
- if( !config_name )
- ;
- //printf( LOG, "WARNING: config name is not specified, using default parameters\n" );
- else
- {
- // 2. read common parameters of test system
- fs = cvOpenFileStorage( config_name, 0, CV_STORAGE_READ );
- if( !fs )
- {
- printf( LOG, "ERROR: could not open config file %s", config_name );
- return -1;
- }
- }
-
- if( params.test_mode == CORRECTNESS_CHECK_MODE || fs )
- {
- // in the case of algorithmic tests we always run read_params,
- // even if there is no config file
- if( read_params(fs) < 0 )
- return -1;
- }
-
- if( !ostrm_base_name )
- make_output_stream_base_name( config_name ? config_name : argv[0] );
-
- ostream_testname_mask = -1; // disable printing test names at initial stage
-
- // 3. open file streams
- for( i = 0; i < CONSOLE_IDX; i++ )
- {
- char filename[MAX_PATH];
- sprintf( filename, "%s%s", ostrm_base_name, ostrm_suffixes[i] );
- output_streams[i].f = fopen( filename, "wt" );
- if( !output_streams[i].f )
- {
- printf( LOG, "ERROR: could not open %s\n", filename );
- return -1;
- }
-
- if( i == LOG_IDX )
- {
- // redirect stderr to log file
- fflush( stderr );
- output_streams[i].default_handle = dup(2);
- dup2( fileno(output_streams[i].f), 2 );
- }
- }
-
- int filter_state = 0;
-
- // 4. traverse through the list of all registered tests.
- // Initialize the selected tests and put them into the separate sequence
- for( i = 0; i < all_tests.size(); i++ )
- {
- test = (CvTest*)all_tests[i];
- if( !(test->get_support_testing_modes() & get_testing_mode()) )
- continue;
-
- if( strcmp( test->get_func_list(), "" ) != 0 && filter(test, filter_state, blacklist) )
- {
- if( test->init(this) >= 0 )
- {
- selected_tests->push( test );
- if( list_tests )
- ::printf( "%s\n", test->get_name() );
- }
- else
- printf( LOG, "WARNING: an error occured during test %s initialization\n", test->get_name() );
- }
- }
-
- if( list_tests )
- {
- clear();
- return 0;
- }
-
- // 5. setup all the neccessary handlers and print header
- set_handlers( !params.debug_mode );
-
- if( params.use_optimized == 0 )
- cvUseOptimized(0);
-
- if( !params.skip_header )
- print_summary_header( SUMMARY + LOG + CONSOLE + CSV );
- rng = params.rng_seed;
- update_context( 0, -1, true );
-
- // 6. run all the tests
- for( i = 0; i < selected_tests->size(); i++ )
- {
- CvTest* test = (CvTest*)selected_tests->at(i);
- int code;
- CvTestInfo temp;
-
- if( memory_manager )
- memory_manager->start_tracking();
-
- update_context( test, -1, true );
- current_test_info.rng_seed0 = current_test_info.rng_seed;
-
- ostream_testname_mask = 0; // reset "test name was printed" flags
- logbuf = std::string();
- if( output_streams[LOG_IDX].f )
- fflush( output_streams[LOG_IDX].f );
-
- temp = current_test_info;
- test->safe_run(0);
- if( get_err_code() >= 0 )
- {
- update_context( test, -1, false );
- current_test_info.rng_seed = temp.rng_seed;
- current_test_info.base_alloc_index = temp.base_alloc_index;
- }
-
- test->clear();
-
- if( memory_manager )
- memory_manager->stop_tracking_and_check();
-
- code = get_err_code();
- if( code >= 0 )
- {
- if( !params.print_only_failed )
- {
- printf( SUMMARY + CONSOLE, "\t" );
- set_color( CV_TS_GREEN );
- printf( SUMMARY + CONSOLE, "Ok\n" );
- set_color( CV_TS_NORMAL );
- }
- }
- else
- {
- printf( SUMMARY + CONSOLE, "\t" );
- set_color( CV_TS_RED );
- printf( SUMMARY + CONSOLE, "FAIL(%s)\n", str_from_code(code) );
- set_color( CV_TS_NORMAL );
- printf( LOG, "context: test case = %d, seed = %08x%08x\n",
- current_test_info.test_case_idx,
- (unsigned)(current_test_info.rng_seed>>32),
- (unsigned)(current_test_info.rng_seed));
- if(logbuf.size() > 0)
- {
- printf( SUMMARY + CONSOLE, ">>>\n%s\n", logbuf.c_str());
- }
- failed_tests->push(current_test_info);
- if( params.rerun_immediately )
- break;
- }
- }
-
- ostream_testname_mask = -1;
- print_summary_tailer( SUMMARY + CONSOLE + LOG );
-
- if( !params.debug_mode && (params.rerun_failed || params.rerun_immediately) )
- {
- set_handlers(0);
- update_context( 0, -1, true );
- for( i = 0; i < failed_tests->size(); i++ )
- {
- CvTestInfo info = failed_tests->at(i);
- if( (info.code == FAIL_MEMORY_CORRUPTION_BEGIN ||
- info.code == FAIL_MEMORY_CORRUPTION_END ||
- info.code == FAIL_MEMORY_LEAK) && memory_manager )
- memory_manager->start_tracking( info.alloc_index - info.base_alloc_index
- + memory_manager->get_alloc_index() );
- rng = info.rng_seed;
- test->safe_run( info.test_case_idx );
- }
- }
-
- int nfailed = failed_tests ? (int)failed_tests->size() : 0;
-
- clear();
-
- return nfailed;
-}
-
-
-void CvTS::print_help(void)
-{
- ::printf(
- "Usage: <test_executable> [{-h|--help}][-l] [-r] [-w] [-t] [-f <config_name>] [-d <data_path>] [-O{0|1}] [-tn <test_name>]\n\n"
- "-d - specify the test data path\n"
- "-f - use parameters from the provided XML/YAML config file\n"
- " instead of the default parameters\n"
- "-h or --help - print this help information\n"
- "-l - list all the registered tests or subset of the tests,\n"
- " selected in the config file, and exit\n"
- "-tn - only run a specific test\n"
- "-nc - do not use colors in the console output\n"
- "-nh - do not print the header\n"
- "-O{0|1} - disable/enable on-fly detection of IPP and other\n"
- " supported optimized libs. It's enabled by default\n"
- "-r - continue running tests after OS/Hardware exception occured\n"
- "-t - switch to the performance testing mode instead of\n"
- " the default algorithmic/correctness testing mode\n"
- "-w - write default parameters of the algorithmic or\n"
- " performance (when -t is passed) tests to the specifed\n"
- " config file (see -f) and exit\n\n"
- //"Test data path and config file can also be specified by the environment variables 'config' and 'datapath'.\n\n"
- );
-}
-
-
-#if defined WIN32 || defined _WIN32
-const char* default_data_path = "../tests/cv/testdata/";
-#else
-const char* default_data_path = "../../../../tests/cv/testdata/";
-#endif
-
-
-int CvTS::read_params( CvFileStorage* fs )
-{
- CvFileNode* node = fs ? cvGetFileNodeByName( fs, 0, "common" ) : 0;
-
- if(params.debug_mode < 0)
- params.debug_mode = cvReadIntByName( fs, node, "debug_mode", 1 ) != 0;
-
- if( params.skip_header < 0 )
- params.skip_header = cvReadIntByName( fs, node, "skip_header", 0 ) > 0;
-
- if( params.ignore_blacklist < 0 )
- params.ignore_blacklist = cvReadIntByName( fs, node, "ignore_blacklist", 0 ) > 0;
-
- params.print_only_failed = cvReadIntByName( fs, node, "print_only_failed", 0 ) != 0;
- params.rerun_failed = cvReadIntByName( fs, node, "rerun_failed", 0 ) != 0;
- params.rerun_immediately = cvReadIntByName( fs, node, "rerun_immediately", 0 ) != 0;
- const char* str = cvReadStringByName( fs, node, "filter_mode", "tests" );
- params.test_filter_mode = strcmp( str, "functions" ) == 0 ? CHOOSE_FUNCTIONS : CHOOSE_TESTS;
-
- str = cvReadStringByName( fs, node, "test_mode", params.test_mode == TIMING_MODE ? "timing" : "correctness" );
-
- params.test_mode = strcmp( str, "timing" ) == 0 || strcmp( str, "performance" ) == 0 ?
- TIMING_MODE : CORRECTNESS_CHECK_MODE;
-
- str = cvReadStringByName( fs, node, "timing_mode", params.timing_mode == AVG_TIME ? "avg" : "min" );
-
- params.timing_mode = strcmp( str, "average" ) == 0 || strcmp( str, "avg" ) == 0 ? AVG_TIME : MIN_TIME;
- params.test_filter_pattern = params.test_filter_pattern != 0 &&
- strlen(params.test_filter_pattern) > 0 ? params.test_filter_pattern :
- cvReadStringByName( fs, node, params.test_filter_mode == CHOOSE_FUNCTIONS ?
- "functions" : "tests", "" );
- params.resource_path = cvReadStringByName( fs, node, "." );
-
- if( params.use_optimized < 0 )
- params.use_optimized = cvReadIntByName( fs, node, "use_optimized", -1 );
-
- if( !params.data_path || !params.data_path[0] )
- {
- const char* data_path =
- cvReadStringByName( fs, node, "data_path", default_data_path );
- set_data_path(data_path);
- }
-
- params.test_case_count_scale = cvReadRealByName( fs, node, "test_case_count_scale", 1. );
-
- if( params.test_case_count_scale <= 0 )
- params.test_case_count_scale = 1.;
-
- str = cvReadStringByName( fs, node, "seed", 0 );
-
- if( str && params.rng_seed == 0 )
- params.rng_seed = read_seed(str);
-
- if( params.rng_seed == 0 )
- params.rng_seed = cvGetTickCount();
-
- str = cvReadStringByName( fs, node, "output_file_base_name", 0 );
- if( str )
- make_output_stream_base_name( str );
-
- return 0;
-}
-
-
-void CvTS::write_default_params( CvFileStorage* fs )
-{
- read_params(0); // fill parameters with default values
-
- cvWriteInt( fs, "debug_mode", params.debug_mode );
- cvWriteInt( fs, "skip_header", params.skip_header );
- cvWriteInt( fs, "print_only_failed", params.print_only_failed );
- cvWriteInt( fs, "rerun_failed", params.rerun_failed );
- cvWriteInt( fs, "rerun_immediately", params.rerun_immediately );
- cvWriteString( fs, "filter_mode", params.test_filter_mode == CHOOSE_FUNCTIONS ? "functions" : "tests" );
- cvWriteString( fs, "test_mode", params.test_mode == TIMING_MODE ? "timing" : "correctness" );
- cvWriteString( fs, "data_path", params.data_path ? params.data_path : default_data_path, 1 );
- if( params.test_mode == TIMING_MODE )
- cvWriteString( fs, "timing_mode", params.timing_mode == AVG_TIME ? "avg" : "min" );
- // test_filter, seed & output_file_base_name are not written
-}
-
-
-void CvTS::enable_output_streams( int stream_mask, int value )
-{
- for( int i = 0; i < MAX_IDX; i++ )
- if( stream_mask & (1 << i) )
- output_streams[i].enable = value != 0;
-}
-
-
-void CvTS::update_context( CvTest* test, int test_case_idx, bool update_ts_context )
-{
- current_test_info.test = test;
- current_test_info.test_case_idx = test_case_idx;
- current_test_info.alloc_index = 0;
- current_test_info.code = 0;
- cvSetErrStatus( CV_StsOk );
- if( update_ts_context )
- {
- current_test_info.rng_seed = rng;
- current_test_info.base_alloc_index = memory_manager ?
- memory_manager->get_alloc_index() : 0;
- }
-}
-
-
-void CvTS::set_failed_test_info( int fail_code, int alloc_index )
-{
- if( fail_code == FAIL_MEMORY_CORRUPTION_BEGIN ||
- fail_code == FAIL_MEMORY_CORRUPTION_END ||
- current_test_info.code >= 0 )
- {
- current_test_info.code = fail_code;
- current_test_info.alloc_index = alloc_index;
- }
-}
-
-
-const char* CvTS::get_libs_info( const char** addon_modules )
-{
- const char* all_info = 0;
- cvGetModuleInfo( 0, &all_info, addon_modules );
- return all_info;
-}
-
-
-void CvTS::print_summary_header( int streams )
-{
- char csv_header[256], *ptr = csv_header;
- int i;
-#ifdef HAVE_IPP
- const IppLibraryVersion* ippver = ippGetLibVersion();
-#endif
-
- printf( streams, "Engine: %s\n", version );
- time_t t1;
- time( &t1 );
- struct tm *t2 = localtime( &t1 );
- char buf[1024];
- strftime( buf, sizeof(buf)-1, "%c", t2 );
- printf( streams, "Execution Date & Time: %s\n", buf );
- printf( streams, "Config File: %s\n", config_name );
- const char* plugins = 0;
- const char* lib_verinfo = get_libs_info( &plugins );
- printf( streams, "Tested Libraries: %s\n", lib_verinfo );
- printf( streams, "Optimized Low-level Plugin\'s: %s\n", plugins );
- printf( streams, "=================================================\n");
-#ifdef HAVE_IPP
- printf( streams, "Built with Intel(R) IPP\n" );
- printf( streams, " %s {%d.%d.%d.%d %s}\n", ippver->Version, ippver->major, ippver->minor, ippver->majorBuild, ippver->build, ippver->BuildDate );
- printf( streams, "=================================================\n");
-#endif
- sprintf( ptr, "funcName,dataType,channels,size," );
- ptr += strlen(ptr);
-
- for( i = 0; i < CvTest::TIMING_EXTRA_PARAMS; i++ )
- {
- sprintf( ptr, "param%d,", i );
- ptr += strlen(ptr);
- }
-
- sprintf( ptr, "CPE,Time(uSecs)" );
- printf( CSV, "%s\n", csv_header );
-}
-
-
-void CvTS::print_summary_tailer( int streams )
-{
- printf( streams, "=================================================\n");
- if( selected_tests && failed_tests )
- {
- time_t end_time;
- time( &end_time );
- double total_time = difftime( end_time, start_time );
- printf( streams, "Summary: %d out of %d tests failed\n",
- failed_tests->size(), selected_tests->size() );
- int minutes = cvFloor(total_time/60.);
- int seconds = cvRound(total_time - minutes*60);
- int hours = minutes / 60;
- minutes %= 60;
- printf( streams, "Running time: %02d:%02d:%02d\n", hours, minutes, seconds );
- }
-}
-
-#if defined _MSC_VER && _MSC_VER < 1400
-#undef vsnprintf
-#define vsnprintf _vsnprintf
-#endif
-
-void CvTS::vprintf( int streams, const char* fmt, va_list l )
-{
- if( streams )
- {
- char str[1 << 14];
- vsnprintf( str, sizeof(str)-1, fmt, l );
-
- for( int i = 0; i < MAX_IDX; i++ )
- {
- if( (streams & (1 << i)) && output_streams[i].enable )
- {
- FILE* f = i == CONSOLE_IDX ? stdout :
- i == LOG_IDX ? stderr : output_streams[i].f;
- if( f )
- {
- if( i != CSV_IDX && !(ostream_testname_mask & (1 << i)) && current_test_info.test )
- {
- fprintf( f, "-------------------------------------------------\n" );
- if( i == CONSOLE_IDX || i == SUMMARY_IDX )
- fprintf( f, "[%08x%08x]\n", (int)(current_test_info.rng_seed0 >> 32),
- (int)(current_test_info.rng_seed0));
- fprintf( f, "%s: ", current_test_info.test->get_name() );
- fflush( f );
- ostream_testname_mask |= 1 << i;
- if( i == LOG_IDX )
- logbuf = std::string();
- }
- fputs( str, f );
- if( i == LOG_IDX )
- logbuf += std::string(str);
- if( i == CONSOLE_IDX )
- fflush(f);
- }
- }
- }
- }
-}
-
-
-void CvTS::printf( int streams, const char* fmt, ... )
-{
- if( streams )
- {
- va_list l;
- va_start( l, fmt );
- vprintf( streams, fmt, l );
- va_end( l );
- }
-}
-
-
-void CvTS::set_color(int color)
-{
- if( params.color_terminal )
- change_color(color);
-}
-
-
-static char* cv_strnstr( const char* str, int len,
- const char* pattern,
- int pattern_len = -1,
- int whole_word = 1 )
-{
- int i;
-
- if( len < 0 && pattern_len < 0 )
- return (char*)strstr( str, pattern );
-
- if( len < 0 )
- len = (int)strlen( str );
-
- if( pattern_len < 0 )
- pattern_len = (int)strlen( pattern );
-
- for( i = 0; i < len - pattern_len + 1; i++ )
- {
- int j = i + pattern_len;
- if( str[i] == pattern[0] &&
- memcmp( str + i, pattern, pattern_len ) == 0 &&
- (!whole_word ||
- ((i == 0 || (!isalnum(str[i-1]) && str[i-1] != '_')) &&
- (j == len || (!isalnum(str[j]) && str[j] != '_')))))
- return (char*)(str + i);
- }
-
- return 0;
-}
-
-
-int CvTS::filter( CvTest* test, int& filter_state, const char** blacklist )
-{
- const char* pattern = params.test_filter_pattern;
- const char* test_name = test->get_name();
- int inverse = 0;
- int greater_or_equal = 0;
-
- if( blacklist && !params.ignore_blacklist )
- {
- for( ; *blacklist != 0; blacklist++ )
- {
- if( strcmp( *blacklist, test_name ) == 0 )
- return 0;
- }
- }
-
- if( pattern && pattern[0] == '!' )
- {
- inverse = 1;
- pattern++;
- }
-
- if( pattern && pattern[0] == '>' )
- {
- greater_or_equal = 1;
- pattern++;
- if( pattern[0] == '=' )
- {
- greater_or_equal = 2;
- pattern++;
- }
- }
-
- if( !pattern || strcmp( pattern, "" ) == 0 || strcmp( pattern, "*" ) == 0 )
- return 1 ^ inverse;
-
- if( params.test_filter_mode == CHOOSE_TESTS )
- {
- int found = 0;
-
- while( pattern && *pattern )
- {
- char *ptr, *endptr = (char*)strchr( pattern, ',' );
- int len, have_wildcard;
- int t_name_len;
-
- if( endptr )
- *endptr = '\0';
-
- ptr = (char*)strchr( pattern, '*' );
- if( ptr )
- {
- len = (int)(ptr - pattern);
- have_wildcard = 1;
- }
- else
- {
- len = (int)strlen( pattern );
- have_wildcard = 0;
- }
-
- t_name_len = (int)strlen( test_name );
- found = (t_name_len == len || (have_wildcard && t_name_len > len)) &&
- (len == 0 || memcmp( test_name, pattern, len ) == 0);
- if( endptr )
- {
- *endptr = ',';
- pattern = endptr + 1;
- while( isspace(*pattern) )
- pattern++;
- }
-
- if( found || !endptr )
- break;
- }
-
- if( greater_or_equal == 0 )
- return found ^ inverse;
- if( filter_state )
- return inverse^1;
- if( !found )
- return inverse;
- if( greater_or_equal == 1 )
- {
- filter_state = 1;
- return inverse;
- }
- else
- {
- assert(filter_state == 2);
- filter_state = 1;
- return inverse ^ 1;
- }
- }
- else
- {
- assert( params.test_filter_mode == CHOOSE_FUNCTIONS );
- int glob_len = (int)strlen( pattern );
- const char* ptr = test->get_func_list();
- const char *tmp_ptr;
-
- while( ptr && *ptr )
- {
- const char* endptr = ptr - 1;
- const char* name_ptr;
- const char* name_first_match;
- int name_len;
- char c;
-
- do c = *++endptr;
- while( isspace(c) );
-
- if( !c )
- break;
-
- assert( isalpha(c) );
- name_ptr = endptr;
-
- do c = *++endptr;
- while( isalnum(c) || c == '_' );
-
- if( c == ':' ) // class
- {
- assert( endptr[1] == ':' );
- endptr = endptr + 2;
- name_len = (int)(endptr - name_ptr);
-
- // find the first occurence of the class name
- // in pattern
- name_first_match = cv_strnstr( pattern,
- glob_len, name_ptr, name_len, 1 );
-
- if( *endptr == '*' )
- {
- if( name_first_match )
- return 1 ^ inverse;
- }
- else
- {
- assert( *endptr == '{' ); // a list of methods
-
- if( !name_first_match )
- {
- // skip all the methods, if there is no such a class name
- // in pattern
- endptr = strchr( endptr, '}' );
- assert( endptr != 0 );
- endptr--;
- }
-
- for( ;; )
- {
- const char* method_name_ptr;
- int method_name_len;
-
- do c = *++endptr;
- while( isspace(c) );
-
- if( c == '}' )
- break;
- assert( isalpha(c) );
-
- method_name_ptr = endptr;
-
- do c = *++endptr;
- while( isalnum(c) || c == '_' );
-
- method_name_len = (int)(endptr - method_name_ptr);
-
- // search for class_name::* or
- // class_name::{...method_name...}
- tmp_ptr = name_first_match;
- do
- {
- const char* tmp_ptr2;
- tmp_ptr += name_len;
- if( *tmp_ptr == '*' )
- return 1;
- assert( *tmp_ptr == '{' );
- tmp_ptr2 = strchr( tmp_ptr, '}' );
- assert( tmp_ptr2 );
-
- if( cv_strnstr( tmp_ptr, (int)(tmp_ptr2 - tmp_ptr) + 1,
- method_name_ptr, method_name_len, 1 ))
- return 1 ^ inverse;
-
- tmp_ptr = cv_strnstr( tmp_ptr2, glob_len -
- (int)(tmp_ptr2 - pattern),
- name_ptr, name_len, 1 );
- }
- while( tmp_ptr );
-
- endptr--;
- do c = *++endptr;
- while( isspace(c) );
-
- if( c != ',' )
- endptr--;
- }
- }
- }
- else
- {
- assert( !c || isspace(c) || c == ',' );
- name_len = (int)(endptr - name_ptr);
- tmp_ptr = pattern;
-
- for(;;)
- {
- const char *tmp_ptr2, *tmp_ptr3;
-
- tmp_ptr = cv_strnstr( tmp_ptr, glob_len -
- (int)(tmp_ptr - pattern), name_ptr, name_len, 1 );
-
- if( !tmp_ptr )
- break;
-
- // make sure it is not a method
- tmp_ptr2 = strchr( tmp_ptr, '}' );
- if( !tmp_ptr2 )
- return 1 ^ inverse;
-
- tmp_ptr3 = strchr( tmp_ptr, '{' );
- if( tmp_ptr3 < tmp_ptr2 )
- return 1 ^ inverse;
-
- tmp_ptr = tmp_ptr2 + 1;
- }
-
- endptr--;
- }
-
- do c = *++endptr;
- while( isspace(c) );
-
- if( c == ',' )
- endptr++;
- ptr = endptr;
- }
-
- return 0 ^ inverse;
- }
-}
-
-/* End of file. */
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#ifndef __CXTS_H__
-#define __CXTS_H__
-
-#include "opencv2/core/core.hpp"
-#include "opencv2/core/core_c.h"
-#include <assert.h>
-#include <limits.h>
-#include <setjmp.h>
-#include <stdarg.h>
-#include <stdio.h>
-#include <string.h>
-#include <time.h>
-#include <string>
-
-#if _MSC_VER >= 1200
-#pragma warning( disable: 4710 )
-#endif
-
-#define CV_TS_VERSION "CxTest 0.1"
-
-#define __BEGIN__ __CV_BEGIN__
-#define __END__ __CV_END__
-#define EXIT __CV_EXIT__
-
-// Helper class for growing vector (to avoid dependency from STL)
-template < typename T > class CvTestVec
-{
-public:
- CvTestVec() { _max_size = _size = 0; _buf = 0; }
- ~CvTestVec() { delete[] _buf; }
- T& operator []( int i ) { assert( (unsigned)i < (unsigned)_size ); return _buf[i]; }
- T at( int i ) { assert( (unsigned)i < (unsigned)_size ); return _buf[i]; }
- T pop() { assert( _size > 0 ); return _buf[--_size]; }
- void push( const T& elem )
- {
- if( _size >= _max_size )
- {
- int i, _new_size = _max_size < 16 ? 16 : _max_size*3/2;
- T* temp = new T[_new_size];
- for( i = 0; i < _size; i++ )
- temp[i] = _buf[i];
- delete[] _buf;
- _max_size = _new_size;
- _buf = temp;
- }
- _buf[_size++] = elem;
- }
-
- int size() { return _size; }
- T* data() { return _buf; }
- void clear() { _size = 0; }
-
-protected:
- T* _buf;
- int _size, _max_size;
-};
-
-/*****************************************************************************************\
-* Base class for tests *
-\*****************************************************************************************/
-
-class CvTest;
-class CvTS;
-
-class CV_EXPORTS CvTest
-{
-public:
- // constructor(s) and destructor
- CvTest( const char* test_name, const char* test_funcs, const char* test_descr = "" );
- virtual ~CvTest();
-
- virtual int init( CvTS* system );
-
- // writes default parameters to file storage
- virtual int write_defaults(CvTS* ts);
-
- // the main procedure of the test
- virtual void run( int start_from );
-
- // the wrapper for run that cares of exceptions
- virtual void safe_run( int start_from );
-
- const char* get_name() const { return name; }
- const char* get_func_list() const { return tested_functions; }
- const char* get_description() const { return description; }
- const char* get_group_name( char* buffer ) const;
- CvTest* get_next() { return next; }
- static CvTest* get_first_test();
- static const char* get_parent_name( const char* name, char* buffer );
-
- // returns true if and only if the different test cases do not depend on each other
- // (so that test system could get right to a problematic test case)
- virtual bool can_do_fast_forward();
-
- // deallocates all the memory.
- // called by init() (before initialization) and by the destructor
- virtual void clear();
-
- // returns the testing modes supported by the particular test
- int get_support_testing_modes();
-
- enum { TIMING_EXTRA_PARAMS=5 };
-
-protected:
- static CvTest* first;
- static CvTest* last;
- static int test_count;
- CvTest* next;
-
- const char** default_timing_param_names; // the names of timing parameters to write
- const CvFileNode* timing_param_names; // and the read param names
- const CvFileNode** timing_param_current; // the current tuple of timing parameters
- const CvFileNode** timing_param_seqs; // the array of parameter sequences
- int* timing_param_idxs; // the array of indices
- int timing_param_count; // the number of parameters in the tuple
- int support_testing_modes;
-
- int test_case_count; // the total number of test cases
-
- // called from write_defaults
- virtual int write_default_params(CvFileStorage* fs);
-
- // read test params
- virtual int read_params( CvFileStorage* fs );
-
- // returns the number of tests or -1 if it is unknown a-priori
- virtual int get_test_case_count();
-
- // prepares data for the next test case. rng seed is updated by the function
- virtual int prepare_test_case( int test_case_idx );
-
- // checks if the test output is valid and accurate
- virtual int validate_test_results( int test_case_idx );
-
- // calls the tested function. the method is called from run_test_case()
- virtual void run_func(); // runs tested func(s)
-
- // prints results of timing test
- virtual void print_time( int test_case_idx, double time_usecs, double time_cpu_clocks );
-
- // updates progress bar
- virtual int update_progress( int progress, int test_case_idx, int count, double dt );
-
- // finds test parameter
- const CvFileNode* find_param( CvFileStorage* fs, const char* param_name );
-
- // writes parameters
- void write_param( CvFileStorage* fs, const char* paramname, int val );
- void write_param( CvFileStorage* fs, const char* paramname, double val );
- void write_param( CvFileStorage* fs, const char* paramname, const char* val );
- void write_string_list( CvFileStorage* fs, const char* paramname, const char** val, int count=-1 );
- void write_int_list( CvFileStorage* fs, const char* paramname, const int* val,
- int count, int stop_value=INT_MIN );
- void write_real_list( CvFileStorage* fs, const char* paramname, const double* val,
- int count, double stop_value=DBL_MIN );
- void start_write_param( CvFileStorage* fs );
-
- // returns the specified parameter from the current parameter tuple
- const CvFileNode* find_timing_param( const char* paramname );
-
- // gets the next tuple of timing parameters
- int get_next_timing_param_tuple();
-
- // name of the test (it is possible to locate a test by its name)
- const char* name;
-
- // comma-separated list of functions that are invoked
- // (and, thus, tested explicitly or implicitly) by the test
- // methods of classes can be grouped using {}.
- // a few examples:
- // "cvCanny, cvAdd, cvSub, cvMul"
- // "CvImage::{Create, CopyOf}, cvMatMulAdd, CvCalibFilter::{PushFrame, SetCameraCount}"
- const char* tested_functions;
-
- // description of the test
- const char* description;
-
- // pointer to the system that includes the test
- CvTS* ts;
-
- int hdr_state;
-};
-
-
-/*****************************************************************************************\
-* Information about a failed test *
-\*****************************************************************************************/
-
-typedef struct CvTestInfo
-{
- // pointer to the test
- CvTest* test;
-
- // failure code (CV_FAIL*)
- int code;
-
- // seed value right before the data for the failed test case is prepared.
- uint64 rng_seed;
-
- // seed value right before running the test
- uint64 rng_seed0;
-
- // index of test case, can be then passed to CvTest::proceed_to_test_case()
- int test_case_idx;
-
- // index of the corrupted or leaked block
- int alloc_index;
-
- // index of the first block in the group
- // (used to adjust alloc_index when some test/test cases are skipped).
- int base_alloc_index;
-}
-CvTestInfo;
-
-/*****************************************************************************************\
-* Base Class for test system *
-\*****************************************************************************************/
-
-class CvTestMemoryManager;
-
-typedef CvTestVec<int> CvTestIntVec;
-typedef CvTestVec<void*> CvTestPtrVec;
-typedef CvTestVec<CvTestInfo> CvTestInfoVec;
-
-class CV_EXPORTS CvTS
-{
-public:
-
- // constructor(s) and destructor
- CvTS(const char* _module_name=0);
- virtual ~CvTS();
-
- enum
- {
- NUL=0,
- SUMMARY_IDX=0,
- SUMMARY=1 << SUMMARY_IDX,
- LOG_IDX=1,
- LOG=1 << LOG_IDX,
- CSV_IDX=2,
- CSV=1 << CSV_IDX,
- CONSOLE_IDX=3,
- CONSOLE=1 << CONSOLE_IDX,
- MAX_IDX=4
- };
-
- // low-level printing functions that are used by individual tests and by the system itself
- virtual void printf( int streams, const char* fmt, ... );
- virtual void vprintf( int streams, const char* fmt, va_list arglist );
-
- // runs the tests (the whole set or some selected tests)
- virtual int run( int argc, char** argv, const char** blacklist=0 );
-
- // updates the context: current test, test case, rng state
- virtual void update_context( CvTest* test, int test_case_idx, bool update_ts_context );
-
- const CvTestInfo* get_current_test_info() { return ¤t_test_info; }
-
- // sets information about a failed test
- virtual void set_failed_test_info( int fail_code, int alloc_index = -1 );
-
- // types of tests
- enum
- {
- CORRECTNESS_CHECK_MODE = 1,
- TIMING_MODE = 2
- };
-
- // the modes of timing tests:
- enum { AVG_TIME = 1, MIN_TIME = 2 };
-
- // test error codes
- enum
- {
- // everything is Ok
- OK=0,
-
- // generic error: stub value to be used
- // temporarily if the error's cause is unknown
- FAIL_GENERIC=-1,
-
- // the test is missing some essential data to proceed further
- FAIL_MISSING_TEST_DATA=-2,
-
- // the tested function raised an error via cxcore error handler
- FAIL_ERROR_IN_CALLED_FUNC=-3,
-
- // an exception has been raised;
- // for memory and arithmetic exception
- // there are two specialized codes (see below...)
- FAIL_EXCEPTION=-4,
-
- // a memory exception
- // (access violation, access to missed page, stack overflow etc.)
- FAIL_MEMORY_EXCEPTION=-5,
-
- // arithmetic exception (overflow, division by zero etc.)
- FAIL_ARITHM_EXCEPTION=-6,
-
- // the tested function corrupted memory (no exception have been raised)
- FAIL_MEMORY_CORRUPTION_BEGIN=-7,
- FAIL_MEMORY_CORRUPTION_END=-8,
-
- // the tested function (or test ifself) do not deallocate some memory
- FAIL_MEMORY_LEAK=-9,
-
- // the tested function returned invalid object, e.g. matrix, containing NaNs,
- // structure with NULL or out-of-range fields (while it should not)
- FAIL_INVALID_OUTPUT=-10,
-
- // the tested function returned valid object, but it does not match to
- // the original (or produced by the test) object
- FAIL_MISMATCH=-11,
-
- // the tested function returned valid object (a single number or numerical array),
- // but it differs too much from the original (or produced by the test) object
- FAIL_BAD_ACCURACY=-12,
-
- // the tested function hung. Sometimes, can be determined by unexpectedly long
- // processing time (in this case there should be possibility to interrupt such a function
- FAIL_HANG=-13,
-
- // unexpected responce on passing bad arguments to the tested function
- // (the function crashed, proceed succesfully (while it should not), or returned
- // error code that is different from what is expected)
- FAIL_BAD_ARG_CHECK=-14,
-
- // the test data (in whole or for the particular test case) is invalid
- FAIL_INVALID_TEST_DATA=-15,
-
- // the test has been skipped because it is not in the selected subset of the tests to run,
- // because it has been run already within the same run with the same parameters, or because
- // of some other reason and this is not considered as an error.
- // Normally CvTS::run() (or overrided method in the derived class) takes care of what
- // needs to be run, so this code should not occur.
- SKIPPED=1
- };
-
- // get file storage
- CvFileStorage* get_file_storage() { return fs; }
-
- // get RNG to generate random input data for a test
- CvRNG* get_rng() { return &rng; }
-
- // returns the current error code
- int get_err_code() { return current_test_info.code; }
-
- // retrieves the first registered test
- CvTest* get_first_test() { return CvTest::get_first_test(); }
-
- // retrieves one of global options of the test system
- int is_debug_mode() { return params.debug_mode; }
-
- // returns the current testing mode
- int get_testing_mode() { return params.test_mode; }
-
- // returns the current timing mode
- int get_timing_mode() { return params.timing_mode; }
-
- // returns the test extensivity scale
- double get_test_case_count_scale() { return params.test_case_count_scale; }
-
- int find_written_param( CvTest* test, const char* paramname,
- int valtype, const void* val );
-
- const char* get_data_path() { return params.data_path ? params.data_path : ""; }
-
-protected:
- // deallocates memory buffers and closes all the streams;
- // called by init() and from destructor. It does not remove any tests!!!
- virtual void clear();
-
- // retrieves information about the test libraries (names, versions, build dates etc.)
- virtual const char* get_libs_info( const char** loaded_ipp_modules );
-
- // returns textual description of failure code
- virtual const char* str_from_code( int code );
-
- // prints header of summary of test suite run.
- // It goes before the results of individual tests and contains information about tested libraries
- // (as reported by get_libs_info()), information about test environment (CPU, test machine name),
- // date and time etc.
- virtual void print_summary_header( int streams );
-
- // prints tailer of summary of test suite run.
- // it goes after the results of individual tests and contains the number of
- // failed tests, total running time, exit code (whether the system has been crashed,
- // interrupted by the user etc.), names of files with additional information etc.
- virtual void print_summary_tailer( int streams );
-
- // reads common parameters of the test system; called from init()
- virtual int read_params( CvFileStorage* fs );
-
- // checks, whether the test needs to be run (1) or not (0); called from run()
- virtual int filter( CvTest* test, int& filter_state, const char** blacklist=0 );
-
- // makes base name of output files
- virtual void make_output_stream_base_name( const char* config_name );
-
- // forms default test configuration file that can be
- // customized further
- virtual void write_default_params( CvFileStorage* fs );
-
- // enables/disables the specific output stream[s]
- virtual void enable_output_streams( int streams, int flag );
-
- // sets memory and exception handlers
- virtual void set_handlers( bool on );
-
- // changes the path to test data files
- virtual void set_data_path( const char* data_path );
-
- // prints the information about command-line parameters
- virtual void print_help();
-
- // changes the text color in console
- virtual void set_color(int color);
-
- // a sequence of tests to run
- CvTestPtrVec* selected_tests;
-
- // a sequence of written test params
- CvTestPtrVec* written_params;
-
- // a sequence of failed tests
- CvTestInfoVec* failed_tests;
-
- // base name for output streams
- char* ostrm_base_name;
- const char* ostrm_suffixes[MAX_IDX];
-
- // parameters that can be read from file storage
- CvFileStorage* fs;
-
- enum { CHOOSE_TESTS = 0, CHOOSE_FUNCTIONS = 1 };
-
- // common parameters:
- struct
- {
- // if non-zero, the tests are run in unprotected mode to debug possible crashes,
- // otherwise the system tries to catch the exceptions and continue with other tests
- int debug_mode;
-
- // if > 0, the header is not print
- int skip_header;
-
- // if > 0, the blacklist is ignored
- int ignore_blacklist;
-
- // if non-zero, the system includes only failed tests into summary
- bool print_only_failed;
-
- // rerun failed tests in debug mode
- bool rerun_failed;
-
- // if non-zero, the failed tests are rerun immediately
- bool rerun_immediately;
-
- // choose_tests or choose_functions;
- int test_filter_mode;
-
- // correctness or performance [or bad-arg, stress etc.]
- int test_mode;
-
- // timing mode
- int timing_mode;
-
- // pattern for choosing tests
- const char* test_filter_pattern;
-
- // RNG seed, passed to and updated by every test executed.
- uint64 rng_seed;
-
- // relative or absolute path of directory containing subfolders with test data
- const char* resource_path;
-
- // whether to use IPP, MKL etc. or not
- int use_optimized;
-
- // extensivity of the tests, scale factor for test_case_count
- double test_case_count_scale;
-
- // the path to data files used by tests
- char* data_path;
-
- // whether the output to console should be colored
- int color_terminal;
- }
- params;
-
- // these are allocated within a test to try keep them valid in case of stack corruption
- CvRNG rng;
-
- // test system start time
- time_t start_time;
-
- // test system version (=CV_TS_VERSION by default)
- const char* version;
-
- // name of config file
- const char* config_name;
-
- const char* module_name;
-
- // information about the current test
- CvTestInfo current_test_info;
-
- // memory manager used to detect memory corruptions and leaks
- CvTestMemoryManager* memory_manager;
-
- // output streams
- struct StreamInfo
- {
- FILE* f;
- //const char* filename;
- int default_handle; // for stderr
- int enable;
- };
-
- StreamInfo output_streams[MAX_IDX];
- int ostream_testname_mask;
- std::string logbuf;
-};
-
-
-/*****************************************************************************************\
-* Subclass of CvTest for testing functions that process dense arrays *
-\*****************************************************************************************/
-
-class CV_EXPORTS CvArrTest : public CvTest
-{
-public:
- // constructor(s) and destructor
- CvArrTest( const char* test_name, const char* test_funcs, const char* test_descr = "" );
- virtual ~CvArrTest();
-
- virtual int write_default_params( CvFileStorage* fs );
- virtual void clear();
-
-protected:
-
- virtual int read_params( CvFileStorage* fs );
- virtual int prepare_test_case( int test_case_idx );
- virtual int validate_test_results( int test_case_idx );
-
- virtual void prepare_to_validation( int test_case_idx );
- virtual void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
- virtual void get_timing_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types,
- CvSize** whole_sizes, bool *are_images );
- virtual void fill_array( int test_case_idx, int i, int j, CvMat* arr );
- virtual void get_minmax_bounds( int i, int j, int type, CvScalar* low, CvScalar* high );
- virtual double get_success_error_level( int test_case_idx, int i, int j );
- virtual void print_time( int test_case_idx, double time_usecs, double time_cpu_clocks );
- virtual void print_timing_params( int test_case_idx, char* ptr, int params_left=TIMING_EXTRA_PARAMS );
-
- bool cvmat_allowed;
- bool iplimage_allowed;
- bool optional_mask;
- bool element_wise_relative_error;
-
- int min_log_array_size;
- int max_log_array_size;
-
- int max_arr; // = MAX_ARR by default, the number of different types of arrays
- int max_hdr; // size of header buffer
- enum { INPUT, INPUT_OUTPUT, OUTPUT, REF_INPUT_OUTPUT, REF_OUTPUT, TEMP, MASK, MAX_ARR };
-
- const CvSize* size_list;
- const CvSize* whole_size_list;
- const int* depth_list;
- const int* cn_list;
-
- CvTestPtrVec* test_array;
- CvMat* test_mat[MAX_ARR];
- CvMat* hdr;
- float buf[4];
-};
-
-
-class CV_EXPORTS CvBadArgTest : public CvTest
-{
-public:
- // constructor(s) and destructor
- CvBadArgTest( const char* test_name, const char* test_funcs, const char* test_descr = "" );
- virtual ~CvBadArgTest();
-
-protected:
- virtual int run_test_case( int expected_code, const char* descr );
- virtual void run_func(void) = 0;
- int test_case_idx;
- int progress;
- double t, freq;
-
- template<class F>
- int run_test_case( int expected_code, const char* descr, F f)
- {
- double new_t = (double)cv::getTickCount(), dt;
- if( test_case_idx < 0 )
- {
- test_case_idx = 0;
- progress = 0;
- dt = 0;
- }
- else
- {
- dt = (new_t - t)/(freq*1000);
- t = new_t;
- }
- progress = update_progress(progress, test_case_idx, 0, dt);
-
- int errcount = 0;
- bool thrown = false;
- if(!descr)
- descr = "";
-
- try
- {
- f();
- }
- catch(const cv::Exception& e)
- {
- thrown = true;
- if( e.code != expected_code )
- {
- ts->printf(CvTS::LOG, "%s (test case #%d): the error code %d is different from the expected %d\n",
- descr, test_case_idx, e.code, expected_code);
- errcount = 1;
- }
- }
- catch(...)
- {
- thrown = true;
- ts->printf(CvTS::LOG, "%s (test case #%d): unknown exception was thrown (the function has likely crashed)\n",
- descr, test_case_idx);
- errcount = 1;
- }
- if(!thrown)
- {
- ts->printf(CvTS::LOG, "%s (test case #%d): no expected exception was thrown\n",
- descr, test_case_idx);
- errcount = 1;
- }
- test_case_idx++;
-
- return errcount;
- }
-};
-
-/****************************************************************************************\
-* Utility Functions *
-\****************************************************************************************/
-
-CV_EXPORTS const char* cvTsGetTypeName( int type );
-CV_EXPORTS int cvTsTypeByName( const char* type_name );
-
-inline int cvTsClipInt( int val, int min_val, int max_val )
-{
- if( val < min_val )
- val = min_val;
- if( val > max_val )
- val = max_val;
- return val;
-}
-
-// return min & max values for given type, e.g. for CV_8S ~ -128 and 127, respectively.
-CV_EXPORTS double cvTsMinVal( int type );
-CV_EXPORTS double cvTsMaxVal( int type );
-
-// returns c-norm of the array
-CV_EXPORTS double cvTsMaxVal( const CvMat* arr );
-
-inline CvMat* cvTsGetMat( const CvMat* arr, CvMat* stub, int* coi=0 )
-{
- return cvGetMat( arr, stub, coi );
-}
-
-// fills array with random numbers
-CV_EXPORTS void cvTsRandUni( CvRNG* rng, CvMat* a, CvScalar param1, CvScalar param2 );
-
-inline unsigned cvTsRandInt( CvRNG* rng )
-{
- uint64 temp = *rng;
- temp = (uint64)(unsigned)temp*1554115554 + (temp >> 32);
- *rng = temp;
- return (unsigned)temp;
-}
-
-inline double cvTsRandReal( CvRNG* rng )
-{
- return cvTsRandInt( rng ) * 2.3283064365386962890625e-10 /* 2^-32 */;
-}
-
-// fills c with zeros
-CV_EXPORTS void cvTsZero( CvMat* c, const CvMat* mask=0 );
-
-// initializes scaled identity matrix
-CV_EXPORTS void cvTsSetIdentity( CvMat* c, CvScalar diag_value );
-
-// copies a to b (whole matrix or only the selected region)
-CV_EXPORTS void cvTsCopy( const CvMat* a, CvMat* b, const CvMat* mask=0 );
-
-// converts one array to another
-CV_EXPORTS void cvTsConvert( const CvMat* src, CvMat* dst );
-
-// working with multi-channel arrays
-CV_EXPORTS void cvTsExtract( const CvMat* a, CvMat* plane, int coi );
-CV_EXPORTS void cvTsInsert( const CvMat* plane, CvMat* a, int coi );
-
-// c = alpha*a + beta*b + gamma
-CV_EXPORTS void cvTsAdd( const CvMat* a, CvScalar alpha, const CvMat* b, CvScalar beta,
- CvScalar gamma, CvMat* c, int calc_abs );
-
-// c = a*b*alpha
-CV_EXPORTS void cvTsMul( const CvMat* _a, const CvMat* _b, CvScalar alpha, CvMat* _c );
-
-// c = a*alpha/b
-CV_EXPORTS void cvTsDiv( const CvMat* _a, const CvMat* _b, CvScalar alpha, CvMat* _c );
-
-enum { CV_TS_MIN = 0, CV_TS_MAX = 1 };
-
-// min/max
-CV_EXPORTS void cvTsMinMax( const CvMat* _a, const CvMat* _b, CvMat* _c, int op_type );
-CV_EXPORTS void cvTsMinMaxS( const CvMat* _a, double scalar, CvMat* _c, int op_type );
-
-// checks that the array does not have NaNs and/or Infs and all the elements are
-// within [min_val,max_val). idx is the index of the first "bad" element.
-CV_EXPORTS int cvTsCheck( const CvMat* data, double min_val, double max_val, CvPoint* idx );
-
-// compares two arrays. max_diff is the maximum actual difference,
-// success_err_level is maximum allowed difference, idx is the index of the first
-// element for which difference is >success_err_level
-// (or index of element with the maximum difference)
-CV_EXPORTS int cvTsCmpEps( const CvMat* data, const CvMat* etalon, double* max_diff,
- double success_err_level, CvPoint* idx,
- bool element_wise_relative_error );
-
-// a wrapper for the previous function. in case of error prints the message to log file.
-CV_EXPORTS int cvTsCmpEps2( CvTS* ts, const CvArr* _a, const CvArr* _b, double success_err_level,
- bool element_wise_relative_error, const char* desc );
-
-CV_EXPORTS int cvTsCmpEps2_64f( CvTS* ts, const double* val, const double* ref_val, int len,
- double eps, const char* param_name );
-
-// compares two arrays. the result is 8s image that takes values -1, 0, 1
-CV_EXPORTS void cvTsCmp( const CvMat* a, const CvMat* b, CvMat* result, int cmp_op );
-
-// compares array and a scalar.
-CV_EXPORTS void cvTsCmpS( const CvMat* a, double fval, CvMat* result, int cmp_op );
-
-// retrieves C, L1 or L2 norm of array or its region
-CV_EXPORTS double cvTsNorm( const CvMat* _arr, const CvMat* _mask, int norm_type, int coi );
-
-// retrieves mean, standard deviation and the number of nonzero mask pixels
-CV_EXPORTS int cvTsMeanStdDevNonZero( const CvMat* _arr, const CvMat* _mask,
- CvScalar* _mean, CvScalar* _stddev, int coi );
-
-// retrieves global extremums and their positions
-CV_EXPORTS void cvTsMinMaxLoc( const CvMat* _arr, const CvMat* _mask,
- double* _minval, double* _maxval,
- CvPoint* _minidx, CvPoint* _maxidx, int coi );
-
-enum { CV_TS_LOGIC_AND = 0, CV_TS_LOGIC_OR = 1, CV_TS_LOGIC_XOR = 2, CV_TS_LOGIC_NOT = 3 };
-
-CV_EXPORTS void cvTsLogic( const CvMat* a, const CvMat* b, CvMat* c, int logic_op );
-CV_EXPORTS void cvTsLogicS( const CvMat* a, CvScalar s, CvMat* c, int logic_op );
-
-enum { CV_TS_GEMM_A_T = 1, CV_TS_GEMM_B_T = 2, CV_TS_GEMM_C_T = 4 };
-
-CV_EXPORTS void cvTsGEMM( const CvMat* a, const CvMat* b, double alpha,
- const CvMat* c, double beta, CvMat* d, int flags );
-
-CV_EXPORTS void cvTsConvolve2D( const CvMat* a, CvMat* b, const CvMat* kernel, CvPoint anchor );
-// op_type == CV_TS_MIN/CV_TS_MAX
-CV_EXPORTS void cvTsMinMaxFilter( const CvMat* a, CvMat* b,
- const IplConvKernel* element, int op_type );
-
-enum { CV_TS_BORDER_REPLICATE=0, CV_TS_BORDER_REFLECT=1, CV_TS_BORDER_FILL=2 };
-
-CV_EXPORTS void cvTsPrepareToFilter( const CvMat* a, CvMat* b, CvPoint ofs,
- int border_mode = CV_TS_BORDER_REPLICATE,
- CvScalar fill_val=cvScalarAll(0));
-
-CV_EXPORTS double cvTsCrossCorr( const CvMat* a, const CvMat* b );
-
-CV_EXPORTS CvMat* cvTsSelect( const CvMat* a, CvMat* header, CvRect rect );
-
-CV_EXPORTS CvMat* cvTsTranspose( const CvMat* a, CvMat* b );
-CV_EXPORTS void cvTsFlip( const CvMat* a, CvMat* b, int flip_type );
-
-CV_EXPORTS void cvTsTransform( const CvMat* a, CvMat* b, const CvMat* transmat, const CvMat* shift );
-
-// modifies values that are close to zero
-CV_EXPORTS void cvTsPatchZeros( CvMat* mat, double level );
-
-#endif/*__CXTS_H__*/
-
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "_cxts.h"
-
-static const int default_test_case_count = 500;
-static const int default_max_log_array_size = 9;
-
-CvArrTest::CvArrTest( const char* _test_name, const char* _test_funcs, const char* _test_descr ) :
- CvTest( _test_name, _test_funcs, _test_descr )
-{
- test_case_count = default_test_case_count;
-
- iplimage_allowed = true;
- cvmat_allowed = true;
- optional_mask = false;
- min_log_array_size = 0;
- max_log_array_size = default_max_log_array_size;
- element_wise_relative_error = true;
-
- size_list = 0;
- whole_size_list = 0;
- depth_list = 0;
- cn_list = 0;
-
- max_arr = MAX_ARR;
- test_array = new CvTestPtrVec[max_arr];
- max_hdr = 0;
- hdr = 0;
-
- support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE + CvTS::TIMING_MODE;
-}
-
-
-CvArrTest::~CvArrTest()
-{
- clear();
- delete[] test_array;
- test_array = 0;
-}
-
-
-int CvArrTest::write_default_params( CvFileStorage* fs )
-{
- int code = CvTest::write_default_params( fs );
- if( code < 0 )
- return code;
-
- if( ts->get_testing_mode() == CvTS::CORRECTNESS_CHECK_MODE )
- {
- write_param( fs, "test_case_count", test_case_count );
- write_param( fs, "min_log_array_size", min_log_array_size );
- write_param( fs, "max_log_array_size", max_log_array_size );
- }
- else if( ts->get_testing_mode() == CvTS::TIMING_MODE )
- {
- int i;
-
- start_write_param( fs ); // make sure we have written the entry header containing the test name
- if( size_list )
- {
- cvStartWriteStruct( fs, "size", CV_NODE_SEQ+CV_NODE_FLOW );
- for( i = 0; size_list[i].width >= 0; i++ )
- {
- cvStartWriteStruct( fs, 0, CV_NODE_SEQ+CV_NODE_FLOW );
- cvWriteInt( fs, 0, size_list[i].width );
- cvWriteInt( fs, 0, size_list[i].height );
- if( whole_size_list &&
- (whole_size_list[i].width > size_list[i].width ||
- whole_size_list[i].height > size_list[i].height) )
- {
- cvWriteInt( fs, 0, whole_size_list[i].width );
- cvWriteInt( fs, 0, whole_size_list[i].height );
- }
- cvEndWriteStruct( fs );
- }
- cvEndWriteStruct(fs);
- }
-
- if( depth_list )
- {
- cvStartWriteStruct( fs, "depth", CV_NODE_SEQ+CV_NODE_FLOW );
- for( i = 0; depth_list[i] >= 0; i++ )
- cvWriteString( fs, 0, cvTsGetTypeName(depth_list[i]) );
- cvEndWriteStruct(fs);
- }
-
- write_int_list( fs, "channels", cn_list, -1, -1 );
-
- if( optional_mask )
- {
- static const int use_mask[] = { 0, 1 };
- write_int_list( fs, "use_mask", use_mask, 2 );
- }
- }
- return 0;
-}
-
-
-void CvArrTest::clear()
-{
- if( test_array )
- {
- int i, j, n;
-
- for( i = 0; i < max_arr; i++ )
- {
- n = test_array[i].size();
- for( j = 0; j < n; j++ )
- cvRelease( &test_array[i][j] );
- }
- }
- delete[] hdr;
- hdr = 0;
- max_hdr = 0;
- CvTest::clear();
-}
-
-
-int CvArrTest::read_params( CvFileStorage* fs )
-{
- int code = CvTest::read_params( fs );
- if( code < 0 )
- return code;
-
- if( ts->get_testing_mode() == CvTS::CORRECTNESS_CHECK_MODE )
- {
- min_log_array_size = cvReadInt( find_param( fs, "min_log_array_size" ), min_log_array_size );
- max_log_array_size = cvReadInt( find_param( fs, "max_log_array_size" ), max_log_array_size );
- test_case_count = cvReadInt( find_param( fs, "test_case_count" ), test_case_count );
- test_case_count = cvRound( test_case_count*ts->get_test_case_count_scale() );
-
- min_log_array_size = cvTsClipInt( min_log_array_size, 0, 20 );
- max_log_array_size = cvTsClipInt( max_log_array_size, min_log_array_size, 20 );
- test_case_count = cvTsClipInt( test_case_count, 0, 100000 );
- }
-
- return code;
-}
-
-
-void CvArrTest::get_test_array_types_and_sizes( int /*test_case_idx*/, CvSize** sizes, int** types )
-{
- CvRNG* rng = ts->get_rng();
- CvSize size;
- double val;
- int i, j;
-
- val = cvRandReal(rng) * (max_log_array_size - min_log_array_size) + min_log_array_size;
- size.width = cvRound( exp(val*CV_LOG2) );
- val = cvRandReal(rng) * (max_log_array_size - min_log_array_size) + min_log_array_size;
- size.height = cvRound( exp(val*CV_LOG2) );
-
- for( i = 0; i < max_arr; i++ )
- {
- int count = test_array[i].size();
- for( j = 0; j < count; j++ )
- {
- sizes[i][j] = size;
- types[i][j] = CV_8UC1;
- }
- }
-}
-
-
-void CvArrTest::get_timing_test_array_types_and_sizes( int /*test_case_idx*/, CvSize** sizes, int** types,
- CvSize** whole_sizes, bool *are_images )
-{
- const CvFileNode* size_node = find_timing_param( "size" );
- const CvFileNode* depth_node = find_timing_param( "depth" );
- const CvFileNode* channels_node = find_timing_param( "channels" );
- int i, j;
- int depth = 0, channels = 1;
- CvSize size = {1,1}, whole_size = size;
-
- if( size_node && CV_NODE_IS_SEQ(size_node->tag) )
- {
- CvSeq* seq = size_node->data.seq;
- size.width = cvReadInt((const CvFileNode*)cvGetSeqElem(seq,0), 1);
- size.height = cvReadInt((const CvFileNode*)cvGetSeqElem(seq,1), 1);
- whole_size = size;
- if( seq->total > 2 )
- {
- whole_size.width = cvReadInt((const CvFileNode*)cvGetSeqElem(seq,2), 1);
- whole_size.height = cvReadInt((const CvFileNode*)cvGetSeqElem(seq,3), 1);
- whole_size.width = MAX( whole_size.width, size.width );
- whole_size.height = MAX( whole_size.height, size.height );
- }
- }
-
- if( depth_node && CV_NODE_IS_STRING(depth_node->tag) )
- {
- depth = cvTsTypeByName( depth_node->data.str.ptr );
- if( depth < 0 || depth > CV_64F )
- depth = 0;
- }
-
- if( channels_node && CV_NODE_IS_INT(channels_node->tag) )
- {
- channels = cvReadInt( channels_node, 1 );
- if( channels < 0 || channels > CV_CN_MAX )
- channels = 1;
- }
-
- for( i = 0; i < max_arr; i++ )
- {
- int count = test_array[i].size();
- for( j = 0; j < count; j++ )
- {
- sizes[i][j] = size;
- whole_sizes[i][j] = whole_size;
- if( i != MASK )
- types[i][j] = CV_MAKETYPE(depth,channels);
- else
- types[i][j] = CV_8UC1;
- if( i == REF_OUTPUT || i == REF_INPUT_OUTPUT )
- sizes[i][j] = cvSize(0,0);
- }
- }
-
- if( are_images )
- *are_images = false; // by default CvMat is used in performance tests
-}
-
-
-void CvArrTest::print_timing_params( int /*test_case_idx*/, char* ptr, int params_left )
-{
- int i;
- for( i = 0; i < params_left; i++ )
- {
- sprintf( ptr, "-," );
- ptr += 2;
- }
-}
-
-
-void CvArrTest::print_time( int test_case_idx, double time_clocks, double time_cpu_clocks )
-{
- int in_type = -1, out_type = -1;
- CvSize size = { -1, -1 };
- const CvFileNode* size_node = find_timing_param( "size" );
- char str[1024], *ptr = str;
- int len;
- bool have_mask;
- double cpe;
-
- if( size_node )
- {
- if( !CV_NODE_IS_SEQ(size_node->tag) )
- {
- size.width = cvReadInt(size_node,-1);
- size.height = 1;
- }
- else
- {
- size.width = cvReadInt((const CvFileNode*)cvGetSeqElem(size_node->data.seq,0),-1);
- size.height = cvReadInt((const CvFileNode*)cvGetSeqElem(size_node->data.seq,1),-1);
- }
- }
-
- if( test_array[INPUT].size() )
- {
- in_type = CV_MAT_TYPE(test_mat[INPUT][0].type);
- if( size.width == -1 )
- size = cvGetMatSize(&test_mat[INPUT][0]);
- }
-
- if( test_array[OUTPUT].size() )
- {
- out_type = CV_MAT_TYPE(test_mat[OUTPUT][0].type);
- if( in_type < 0 )
- in_type = out_type;
- if( size.width == -1 )
- size = cvGetMatSize(&test_mat[OUTPUT][0]);
- }
-
- if( out_type < 0 && test_array[INPUT_OUTPUT].size() )
- {
- out_type = CV_MAT_TYPE(test_mat[INPUT_OUTPUT][0].type);
- if( in_type < 0 )
- in_type = out_type;
- if( size.width == -1 )
- size = cvGetMatSize(&test_mat[INPUT_OUTPUT][0]);
- }
-
- have_mask = test_array[MASK].size() > 0 && test_array[MASK][0] != 0;
-
- if( in_type < 0 && out_type < 0 )
- return;
-
- if( out_type < 0 )
- out_type = in_type;
-
- ptr = strchr( (char*)tested_functions, ',' );
- if( ptr )
- {
- len = (int)(ptr - tested_functions);
- strncpy( str, tested_functions, len );
- }
- else
- {
- len = (int)strlen( tested_functions );
- strcpy( str, tested_functions );
- }
- ptr = str + len;
- *ptr = '\0';
- if( have_mask )
- {
- sprintf( ptr, "(Mask)" );
- ptr += strlen(ptr);
- }
- *ptr++ = ',';
- sprintf( ptr, "%s", cvTsGetTypeName(in_type) );
- ptr += strlen(ptr);
-
- if( CV_MAT_DEPTH(out_type) != CV_MAT_DEPTH(in_type) )
- {
- sprintf( ptr, "%s", cvTsGetTypeName(out_type) );
- ptr += strlen(ptr);
- }
- *ptr++ = ',';
-
- sprintf( ptr, "C%d", CV_MAT_CN(in_type) );
- ptr += strlen(ptr);
-
- if( CV_MAT_CN(out_type) != CV_MAT_CN(in_type) )
- {
- sprintf( ptr, "C%d", CV_MAT_CN(out_type) );
- ptr += strlen(ptr);
- }
- *ptr++ = ',';
-
- sprintf( ptr, "%dx%d,", size.width, size.height );
- ptr += strlen(ptr);
-
- print_timing_params( test_case_idx, ptr );
- ptr += strlen(ptr);
- cpe = time_cpu_clocks / ((double)size.width * size.height);
- if( cpe >= 100 )
- sprintf( ptr, "%.0f,", cpe );
- else
- sprintf( ptr, "%.1f,", cpe );
- ptr += strlen(ptr);
- sprintf( ptr, "%g", time_clocks*1e6/cv::getTickFrequency() );
-
- ts->printf( CvTS::CSV, "%s\n", str );
-}
-
-
-static const int icvTsTypeToDepth[] =
-{
- IPL_DEPTH_8U, IPL_DEPTH_8S, IPL_DEPTH_16U, IPL_DEPTH_16S,
- IPL_DEPTH_32S, IPL_DEPTH_32F, IPL_DEPTH_64F
-};
-
-
-int CvArrTest::prepare_test_case( int test_case_idx )
-{
- int code = 1;
- CvSize** sizes = (CvSize**)malloc( max_arr*sizeof(sizes[0]) );
- CvSize** whole_sizes = (CvSize**)malloc( max_arr*sizeof(whole_sizes[0]) );
- int** types = (int**)malloc( max_arr*sizeof(types[0]) );
- int i, j, total = 0;
- CvRNG* rng = ts->get_rng();
- bool is_image = false;
- bool is_timing_test = false;
-
- CV_FUNCNAME( "CvArrTest::prepare_test_case" );
-
- __BEGIN__;
-
- is_timing_test = ts->get_testing_mode() == CvTS::TIMING_MODE;
-
- if( is_timing_test )
- {
- if( !get_next_timing_param_tuple() )
- {
- code = -1;
- EXIT;
- }
- }
-
- for( i = 0; i < max_arr; i++ )
- {
- int count = test_array[i].size();
- count = MAX(count, 1);
- sizes[i] = (CvSize*)malloc( count*sizeof(sizes[i][0]) );
- types[i] = (int*)malloc( count*sizeof(types[i][0]) );
- whole_sizes[i] = (CvSize*)malloc( count*sizeof(whole_sizes[i][0]) );
- }
-
- if( !is_timing_test )
- get_test_array_types_and_sizes( test_case_idx, sizes, types );
- else
- {
- get_timing_test_array_types_and_sizes( test_case_idx, sizes, types,
- whole_sizes, &is_image );
- }
-
- for( i = 0; i < max_arr; i++ )
- {
- int count = test_array[i].size();
- total += count;
- for( j = 0; j < count; j++ )
- {
- unsigned t = cvRandInt(rng);
- bool create_mask = true, use_roi = false;
- CvSize size = sizes[i][j], whole_size = size;
- CvRect roi = {0,0,0,0};
-
- if( !is_timing_test )
- {
- is_image = !cvmat_allowed ? true : iplimage_allowed ? (t & 1) != 0 : false;
- create_mask = (t & 6) == 0; // ~ each of 3 tests will use mask
- use_roi = (t & 8) != 0;
- if( use_roi )
- {
- whole_size.width += cvRandInt(rng) % 10;
- whole_size.height += cvRandInt(rng) % 10;
- }
- }
- else
- {
- whole_size = whole_sizes[i][j];
- use_roi = whole_size.width != size.width || whole_size.height != size.height;
- create_mask = cvReadInt(find_timing_param( "use_mask" ),0) != 0;
- }
-
- cvRelease( &test_array[i][j] );
- if( size.width > 0 && size.height > 0 &&
- types[i][j] >= 0 && (i != MASK || create_mask) )
- {
- if( use_roi )
- {
- roi.width = size.width;
- roi.height = size.height;
- if( whole_size.width > size.width )
- {
- if( !is_timing_test )
- roi.x = cvRandInt(rng) % (whole_size.width - size.width);
- else
- roi.x = 1;
- }
-
- if( whole_size.height > size.height )
- {
- if( !is_timing_test )
- roi.y = cvRandInt(rng) % (whole_size.height - size.height);
- else
- roi.y = 1;
- }
- }
-
- if( is_image )
- {
- CV_CALL( test_array[i][j] = cvCreateImage( whole_size,
- icvTsTypeToDepth[CV_MAT_DEPTH(types[i][j])],
- CV_MAT_CN(types[i][j]) ));
- if( use_roi )
- cvSetImageROI( (IplImage*)test_array[i][j], roi );
- }
- else
- {
- CV_CALL( test_array[i][j] = cvCreateMat( whole_size.height,
- whole_size.width, types[i][j] ));
- if( use_roi )
- {
- CvMat submat, *mat = (CvMat*)test_array[i][j];
- cvGetSubRect( test_array[i][j], &submat, roi );
- submat.refcount = mat->refcount;
- *mat = submat;
- }
- }
- }
- }
- }
-
- if( total > max_hdr )
- {
- delete hdr;
- max_hdr = total;
- hdr = new CvMat[max_hdr];
- }
-
- total = 0;
- for( i = 0; i < max_arr; i++ )
- {
- int count = test_array[i].size();
- test_mat[i] = count > 0 ? hdr + total : 0;
- for( j = 0; j < count; j++ )
- {
- CvArr* arr = test_array[i][j];
- CvMat* mat = &test_mat[i][j];
- if( !arr )
- memset( mat, 0, sizeof(*mat) );
- else if( CV_IS_MAT( arr ))
- {
- *mat = *(CvMat*)arr;
- mat->refcount = 0;
- }
- else
- cvGetMat( arr, mat, 0, 0 );
- if( mat->data.ptr )
- fill_array( test_case_idx, i, j, mat );
- }
- total += count;
- }
-
- __END__;
-
- for( i = 0; i < max_arr; i++ )
- {
- if( sizes )
- free( sizes[i] );
- if( whole_sizes )
- free( whole_sizes[i] );
- if( types )
- free( types[i] );
- }
-
- free( sizes );
- free( whole_sizes );
- free( types );
-
- return code;
-}
-
-
-void CvArrTest::get_minmax_bounds( int i, int /*j*/, int type, CvScalar* low, CvScalar* high )
-{
- double l, u;
-
- if( i == MASK )
- {
- l = -2;
- u = 2;
- }
- else
- {
- l = cvTsMinVal(type);
- u = cvTsMaxVal(type);
- }
-
- *low = cvScalarAll(l);
- *high = cvScalarAll(u);
-}
-
-
-void CvArrTest::fill_array( int /*test_case_idx*/, int i, int j, CvMat* arr )
-{
- if( i == REF_INPUT_OUTPUT )
- cvTsCopy( &test_mat[INPUT_OUTPUT][j], arr, 0 );
- else if( i == INPUT || i == INPUT_OUTPUT || i == MASK )
- {
- int type = cvGetElemType( arr );
- CvScalar low, high;
-
- get_minmax_bounds( i, j, type, &low, &high );
- cvTsRandUni( ts->get_rng(), arr, low, high );
- }
-}
-
-
-double CvArrTest::get_success_error_level( int /*test_case_idx*/, int i, int j )
-{
- int elem_depth = CV_MAT_DEPTH(cvGetElemType(test_array[i][j]));
- assert( i == OUTPUT || i == INPUT_OUTPUT );
- return elem_depth < CV_32F ? 0 : elem_depth == CV_32F ? FLT_EPSILON*100: DBL_EPSILON*5000;
-}
-
-
-void CvArrTest::prepare_to_validation( int /*test_case_idx*/ )
-{
- assert(0);
-}
-
-
-int CvArrTest::validate_test_results( int test_case_idx )
-{
- static const char* arr_names[] = { "input", "input/output", "output",
- "ref input/output", "ref output",
- "temporary", "mask" };
- int i, j;
- prepare_to_validation( test_case_idx );
-
- for( i = 0; i < 2; i++ )
- {
- int i0 = i == 0 ? OUTPUT : INPUT_OUTPUT;
- int i1 = i == 0 ? REF_OUTPUT : REF_INPUT_OUTPUT;
- int count = test_array[i0].size();
-
- assert( count == test_array[i1].size() );
- for( j = 0; j < count; j++ )
- {
- double err_level;
- CvPoint idx = {0,0};
- double max_diff = 0;
- int code;
- char msg[100];
-
- if( !test_array[i1][j] )
- continue;
-
- err_level = get_success_error_level( test_case_idx, i0, j );
- code = cvTsCmpEps( &test_mat[i0][j], &test_mat[i1][j], &max_diff, err_level, &idx,
- element_wise_relative_error );
-
- switch( code )
- {
- case -1:
- sprintf( msg, "Too big difference (=%g)", max_diff );
- code = CvTS::FAIL_BAD_ACCURACY;
- break;
- case -2:
- strcpy( msg, "Invalid output" );
- code = CvTS::FAIL_INVALID_OUTPUT;
- break;
- case -3:
- strcpy( msg, "Invalid output in the reference array" );
- code = CvTS::FAIL_INVALID_OUTPUT;
- break;
- default:
- continue;
- }
- ts->printf( CvTS::LOG, "%s in %s array %d at (%d,%d)\n", msg,
- arr_names[i0], j, idx.x, idx.y );
- for( i0 = 0; i0 < max_arr; i0++ )
- {
- int count = test_array[i0].size();
- if( i0 == REF_INPUT_OUTPUT || i0 == OUTPUT || i0 == TEMP )
- continue;
- for( i1 = 0; i1 < count; i1++ )
- {
- CvArr* arr = test_array[i0][i1];
- if( arr )
- {
- CvSize size = cvGetSize(arr);
- int type = cvGetElemType(arr);
- ts->printf( CvTS::LOG, "%s array %d type=%sC%d, size=(%d,%d)\n",
- arr_names[i0], i1, cvTsGetTypeName(type),
- CV_MAT_CN(type), size.width, size.height );
- }
- }
- }
- ts->set_failed_test_info( code );
- return code;
- }
- }
-
- return 0;
-}
-
-/* End of file. */
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "_cxts.h"
-
-/****************************************************************************************\
-* Utility Functions *
-\****************************************************************************************/
-
-const char* cvTsGetTypeName( int type )
-{
- static const char* type_names[] = { "8u", "8s", "16u", "16s", "32s", "32f", "64f", "ptr" };
- return type_names[CV_MAT_DEPTH(type)];
-}
-
-
-int cvTsTypeByName( const char* name )
-{
- int i;
- for( i = 0; i < CV_DEPTH_MAX; i++ )
- if( strcmp(name, cvTsGetTypeName(i)) == 0 )
- return i;
- return -1;
-}
-
-
-void cvTsRandUni( CvRNG* rng, CvMat* a, CvScalar param0, CvScalar param1 )
-{
- int i, j, k, cn, ncols;
- CvScalar scale = param0;
- CvScalar delta = param1;
- double C = 1./(65536.*65536.);
-
- cn = CV_MAT_CN(a->type);
- ncols = a->cols*cn;
-
- for( k = 0; k < 4; k++ )
- {
- double s = scale.val[k] - delta.val[k];
- if( s >= 0 )
- scale.val[k] = s;
- else
- {
- delta.val[k] = scale.val[k];
- scale.val[k] = -s;
- }
- scale.val[k] *= C;
- }
-
- for( i = 0; i < a->rows; i++ )
- {
- uchar* data = a->data.ptr + i*a->step;
-
- switch( CV_MAT_DEPTH(a->type) )
- {
- case CV_8U:
- for( j = 0; j < ncols; j += cn )
- for( k = 0; k < cn; k++ )
- {
- int val = cvFloor( cvTsRandInt(rng)*scale.val[k] + delta.val[k] );
- ((uchar*)data)[j + k] = CV_CAST_8U(val);
- }
- break;
- case CV_8S:
- for( j = 0; j < ncols; j += cn )
- for( k = 0; k < cn; k++ )
- {
- int val = cvFloor( cvTsRandInt(rng)*scale.val[k] + delta.val[k] );
- ((schar*)data)[j + k] = CV_CAST_8S(val);
- }
- break;
- case CV_16U:
- for( j = 0; j < ncols; j += cn )
- for( k = 0; k < cn; k++ )
- {
- int val = cvFloor( cvTsRandInt(rng)*scale.val[k] + delta.val[k] );
- ((ushort*)data)[j + k] = CV_CAST_16U(val);
- }
- break;
- case CV_16S:
- for( j = 0; j < ncols; j += cn )
- for( k = 0; k < cn; k++ )
- {
- int val = cvFloor( cvTsRandInt(rng)*scale.val[k] + delta.val[k] );
- ((short*)data)[j + k] = CV_CAST_16S(val);
- }
- break;
- case CV_32S:
- for( j = 0; j < ncols; j += cn )
- for( k = 0; k < cn; k++ )
- {
- int val = cvFloor( cvTsRandInt(rng)*scale.val[k] + delta.val[k] );
- ((int*)data)[j + k] = val;
- }
- break;
- case CV_32F:
- for( j = 0; j < ncols; j += cn )
- for( k = 0; k < cn; k++ )
- {
- double val = cvTsRandInt(rng)*scale.val[k] + delta.val[k];
- ((float*)data)[j + k] = (float)val;
- }
- break;
- case CV_64F:
- for( j = 0; j < ncols; j += cn )
- for( k = 0; k < cn; k++ )
- {
- double val = cvTsRandInt(rng);
- val = (val + cvTsRandInt(rng)*C)*scale.val[k] + delta.val[k];
- ((double*)data)[j + k] = val;
- }
- break;
- default:
- assert(0);
- return;
- }
- }
-}
-
-
-void cvTsZero( CvMat* c, const CvMat* mask )
-{
- int i, j, elem_size = CV_ELEM_SIZE(c->type), width = c->cols;
-
- for( i = 0; i < c->rows; i++ )
- {
- if( !mask )
- memset( c->data.ptr + i*c->step, 0, width*elem_size );
- else
- {
- const uchar* mrow = mask->data.ptr + mask->step*i;
- uchar* cptr = c->data.ptr + c->step*i;
- for( j = 0; j < width; j++, cptr += elem_size )
- if( mrow[j] )
- memset( cptr, 0, elem_size );
- }
- }
-}
-
-
-// initializes scaled identity matrix
-void cvTsSetIdentity( CvMat* c, CvScalar diag_value )
-{
- int i, width;
- cvTsZero( c );
- width = MIN(c->rows, c->cols);
- for( i = 0; i < width; i++ )
- cvSet2D( c, i, i, diag_value );
-}
-
-
-// copies selected region of one array to another array
-void cvTsCopy( const CvMat* a, CvMat* b, const CvMat* mask )
-{
- int i = 0, j = 0, k;
- int el_size, ncols;
-
- el_size = CV_ELEM_SIZE(a->type);
- ncols = a->cols;
- if( mask )
- {
- assert( CV_ARE_SIZES_EQ(a,mask) &&
- (CV_MAT_TYPE(mask->type) == CV_8UC1 ||
- CV_MAT_TYPE(mask->type) == CV_8SC1 ));
- }
-
- assert( CV_ARE_TYPES_EQ(a,b) && CV_ARE_SIZES_EQ(a,b) );
-
- if( !mask )
- ncols *= el_size;
-
- for( i = 0; i < a->rows; i++ )
- {
- uchar* a_data = a->data.ptr + a->step*i;
- uchar* b_data = b->data.ptr + b->step*i;
-
- if( !mask )
- memcpy( b_data, a_data, ncols );
- else
- {
- uchar* m_data = mask->data.ptr + mask->step*i;
-
- for( j = 0; j < ncols; j++, b_data += el_size, a_data += el_size )
- {
- if( m_data[j] )
- {
- for( k = 0; k < el_size; k++ )
- b_data[k] = a_data[k];
- }
- }
- }
- }
-}
-
-
-void cvTsConvert( const CvMat* a, CvMat* b )
-{
- int i, j, ncols = b->cols*CV_MAT_CN(b->type);
- double* buf = 0;
-
- assert( CV_ARE_SIZES_EQ(a,b) && CV_ARE_CNS_EQ(a,b) );
- buf = (double*)cvStackAlloc(ncols*sizeof(buf[0]));
-
- for( i = 0; i < b->rows; i++ )
- {
- uchar* a_data = a->data.ptr + i*a->step;
- uchar* b_data = b->data.ptr + i*b->step;
-
- switch( CV_MAT_DEPTH(a->type) )
- {
- case CV_8U:
- for( j = 0; j < ncols; j++ )
- buf[j] = ((uchar*)a_data)[j];
- break;
- case CV_8S:
- for( j = 0; j < ncols; j++ )
- buf[j] = ((schar*)a_data)[j];
- break;
- case CV_16U:
- for( j = 0; j < ncols; j++ )
- buf[j] = ((ushort*)a_data)[j];
- break;
- case CV_16S:
- for( j = 0; j < ncols; j++ )
- buf[j] = ((short*)a_data)[j];
- break;
- case CV_32S:
- for( j = 0; j < ncols; j++ )
- buf[j] = ((int*)a_data)[j];
- break;
- case CV_32F:
- for( j = 0; j < ncols; j++ )
- buf[j] = ((float*)a_data)[j];
- break;
- case CV_64F:
- for( j = 0; j < ncols; j++ )
- buf[j] = ((double*)a_data)[j];
- break;
- default:
- assert(0);
- return;
- }
-
- switch( CV_MAT_DEPTH(b->type) )
- {
- case CV_8U:
- for( j = 0; j < ncols; j++ )
- {
- int val = cvRound(buf[j]);
- ((uchar*)b_data)[j] = CV_CAST_8U(val);
- }
- break;
- case CV_8S:
- for( j = 0; j < ncols; j++ )
- {
- int val = cvRound(buf[j]);
- ((schar*)b_data)[j] = CV_CAST_8S(val);
- }
- break;
- case CV_16U:
- for( j = 0; j < ncols; j++ )
- {
- int val = cvRound(buf[j]);
- ((ushort*)b_data)[j] = CV_CAST_16U(val);
- }
- break;
- case CV_16S:
- for( j = 0; j < ncols; j++ )
- {
- int val = cvRound(buf[j]);
- ((short*)b_data)[j] = CV_CAST_16S(val);
- }
- break;
- case CV_32S:
- for( j = 0; j < ncols; j++ )
- {
- int val = cvRound(buf[j]);
- ((int*)b_data)[j] = CV_CAST_32S(val);
- }
- break;
- case CV_32F:
- for( j = 0; j < ncols; j++ )
- ((float*)b_data)[j] = CV_CAST_32F(buf[j]);
- break;
- case CV_64F:
- for( j = 0; j < ncols; j++ )
- ((double*)b_data)[j] = CV_CAST_64F(buf[j]);
- break;
- default:
- assert(0);
- }
- }
-}
-
-
-// extracts a single channel from a multi-channel array
-void cvTsExtract( const CvMat* a, CvMat* b, int coi )
-{
- int i = 0, j = 0, k;
- int el_size, el_size1, ncols;
-
- el_size = CV_ELEM_SIZE(a->type);
- el_size1 = CV_ELEM_SIZE(b->type);
- ncols = a->cols;
-
- assert( CV_ARE_DEPTHS_EQ(a,b) && CV_ARE_SIZES_EQ(a,b) &&
- (unsigned)coi < (unsigned)CV_MAT_CN(a->type) &&
- CV_MAT_CN(b->type) == 1 );
-
- for( i = 0; i < a->rows; i++ )
- {
- uchar* a_data = a->data.ptr + a->step*i;
- uchar* b_data = b->data.ptr + b->step*i;
- a_data += el_size1*coi;
- for( j = 0; j < ncols; j++, b_data += el_size1, a_data += el_size )
- {
- for( k = 0; k < el_size1; k++ )
- b_data[k] = a_data[k];
- }
- }
-}
-
-// replaces a single channel in a multi-channel array
-void cvTsInsert( const CvMat* a, CvMat* b, int coi )
-{
- int i = 0, j = 0, k;
- int el_size, el_size1, ncols;
-
- el_size = CV_ELEM_SIZE(b->type);
- el_size1 = CV_ELEM_SIZE(a->type);
- ncols = a->cols;
-
- assert( CV_ARE_DEPTHS_EQ(a,b) && CV_ARE_SIZES_EQ(a,b) &&
- (unsigned)coi < (unsigned)CV_MAT_CN(b->type) &&
- CV_MAT_CN(a->type) == 1 );
-
- for( i = 0; i < a->rows; i++ )
- {
- uchar* a_data = a->data.ptr + a->step*i;
- uchar* b_data = b->data.ptr + b->step*i;
- b_data += el_size1*coi;
- for( j = 0; j < ncols; j++, b_data += el_size, a_data += el_size1 )
- {
- for( k = 0; k < el_size1; k++ )
- b_data[k] = a_data[k];
- }
- }
-}
-
-
-// c = alpha*a + beta*b + gamma
-void cvTsAdd( const CvMat* a, CvScalar alpha, const CvMat* b, CvScalar beta,
- CvScalar gamma, CvMat* c, int calc_abs )
-{
- int i, j, k, cn, ncols;
- double* buf = 0;
- double* alpha_buf = 0;
- double* beta_buf = 0;
- double* gamma_buf = 0;
-
- if( !c )
- {
- assert(0);
- return;
- }
-
- cn = CV_MAT_CN(c->type);
- ncols = c->cols;
-
- if( !a )
- {
- a = b;
- alpha = beta;
- b = 0;
- beta = cvScalar(0);
- }
-
- if( a )
- {
- assert( CV_ARE_SIZES_EQ(a,c) && CV_MAT_CN(a->type) == cn );
- buf = (double*)malloc( a->cols * cn * sizeof(buf[0]) );
- alpha_buf = (double*)malloc( a->cols * cn * sizeof(alpha_buf[0]) );
- }
-
- if( b )
- {
- assert( CV_ARE_SIZES_EQ(b,c) && CV_MAT_CN(b->type) == cn );
- beta_buf = (double*)malloc( b->cols * cn * sizeof(beta_buf[0]) );
- }
-
- ncols *= cn;
- gamma_buf = (double*)malloc( ncols * sizeof(gamma_buf[0]) );
- if( !buf )
- buf = gamma_buf;
-
- if( !a && !b && calc_abs )
- {
- for( k = 0; k < cn; k++ )
- gamma.val[k] = fabs(gamma.val[k]);
- }
-
- for( i = 0; i < 1 + (a != 0) + (b != 0); i++ )
- {
- double* scalar_buf = i == 0 ? gamma_buf : i == 1 ? alpha_buf : beta_buf;
- CvScalar scalar = i == 0 ? gamma : i == 1 ? alpha : beta;
- for( j = 0; j < ncols; j += cn )
- for( k = 0; k < cn; k++ )
- scalar_buf[j + k] = scalar.val[k];
- }
-
- for( i = 0; i < c->rows; i++ )
- {
- uchar* c_data = c->data.ptr + i*c->step;
-
- if( a )
- {
- uchar* a_data = a->data.ptr + i*a->step;
-
- switch( CV_MAT_DEPTH(a->type) )
- {
- case CV_8U:
- for( j = 0; j < ncols; j++ )
- buf[j] = ((uchar*)a_data)[j]*alpha_buf[j] + gamma_buf[j];
- break;
- case CV_8S:
- for( j = 0; j < ncols; j++ )
- buf[j] = ((schar*)a_data)[j]*alpha_buf[j] + gamma_buf[j];
- break;
- case CV_16U:
- for( j = 0; j < ncols; j++ )
- buf[j] = ((ushort*)a_data)[j]*alpha_buf[j] + gamma_buf[j];
- break;
- case CV_16S:
- for( j = 0; j < ncols; j++ )
- buf[j] = ((short*)a_data)[j]*alpha_buf[j] + gamma_buf[j];
- break;
- case CV_32S:
- for( j = 0; j < ncols; j++ )
- buf[j] = ((int*)a_data)[j]*alpha_buf[j] + gamma_buf[j];
- break;
- case CV_32F:
- for( j = 0; j < ncols; j++ )
- buf[j] = ((float*)a_data)[j]*alpha_buf[j] + gamma_buf[j];
- break;
- case CV_64F:
- for( j = 0; j < ncols; j++ )
- buf[j] = ((double*)a_data)[j]*alpha_buf[j] + gamma_buf[j];
- break;
- default:
- assert(0);
- return;
- }
- }
-
- if( b )
- {
- uchar* b_data = b->data.ptr + i*b->step;
-
- switch( CV_MAT_DEPTH(b->type) )
- {
- case CV_8U:
- for( j = 0; j < ncols; j++ )
- buf[j] += ((uchar*)b_data)[j]*beta_buf[j];
- break;
- case CV_8S:
- for( j = 0; j < ncols; j++ )
- buf[j] += ((schar*)b_data)[j]*beta_buf[j];
- break;
- case CV_16U:
- for( j = 0; j < ncols; j++ )
- buf[j] += ((ushort*)b_data)[j]*beta_buf[j];
- break;
- case CV_16S:
- for( j = 0; j < ncols; j++ )
- buf[j] += ((short*)b_data)[j]*beta_buf[j];
- break;
- case CV_32S:
- for( j = 0; j < ncols; j++ )
- buf[j] += ((int*)b_data)[j]*beta_buf[j];
- break;
- case CV_32F:
- for( j = 0; j < ncols; j++ )
- buf[j] += ((float*)b_data)[j]*beta_buf[j];
- break;
- case CV_64F:
- for( j = 0; j < ncols; j++ )
- buf[j] += ((double*)b_data)[j]*beta_buf[j];
- break;
- default:
- assert(0);
- return;
- }
- }
-
- if( a || b )
- {
- if( calc_abs )
- {
- for( j = 0; j < ncols; j++ )
- buf[j] = fabs(buf[j]);
- }
- }
- else if( i > 0 )
- {
- memcpy( c_data, c_data - c->step, c->cols*CV_ELEM_SIZE(c->type) );
- continue;
- }
-
- switch( CV_MAT_DEPTH(c->type) )
- {
- case CV_8U:
- for( j = 0; j < ncols; j++ )
- {
- int val = cvRound(buf[j]);
- ((uchar*)c_data)[j] = CV_CAST_8U(val);
- }
- break;
- case CV_8S:
- for( j = 0; j < ncols; j++ )
- {
- int val = cvRound(buf[j]);
- ((schar*)c_data)[j] = CV_CAST_8S(val);
- }
- break;
- case CV_16U:
- for( j = 0; j < ncols; j++ )
- {
- int val = cvRound(buf[j]);
- ((ushort*)c_data)[j] = CV_CAST_16U(val);
- }
- break;
- case CV_16S:
- for( j = 0; j < ncols; j++ )
- {
- int val = cvRound(buf[j]);
- ((short*)c_data)[j] = CV_CAST_16S(val);
- }
- break;
- case CV_32S:
- for( j = 0; j < ncols; j++ )
- {
- int val = cvRound(buf[j]);
- ((int*)c_data)[j] = CV_CAST_32S(val);
- }
- break;
- case CV_32F:
- for( j = 0; j < ncols; j++ )
- ((float*)c_data)[j] = CV_CAST_32F(buf[j]);
- break;
- case CV_64F:
- for( j = 0; j < ncols; j++ )
- ((double*)c_data)[j] = CV_CAST_64F(buf[j]);
- break;
- default:
- assert(0);
- }
- }
-
- if( buf && buf != gamma_buf )
- free( buf );
- if( gamma_buf )
- free( gamma_buf );
- if( alpha_buf )
- free( alpha_buf );
- if( beta_buf )
- free( beta_buf );
-}
-
-
-// c = a*b*alpha
-void cvTsMul( const CvMat* a, const CvMat* b, CvScalar alpha, CvMat* c )
-{
- int i, j, k, cn, ncols;
- double* buf = 0;
- double* alpha_buf = 0;
-
- if( !a || !b || !c )
- {
- assert(0);
- return;
- }
-
- assert( CV_ARE_SIZES_EQ(a,c) && CV_ARE_SIZES_EQ(b,c) &&
- CV_ARE_TYPES_EQ(a,b) && CV_ARE_CNS_EQ(a,c) );
-
- cn = CV_MAT_CN(c->type);
- ncols = c->cols * cn;
- alpha_buf = (double*)malloc( ncols * sizeof(alpha_buf[0]) );
- buf = (double*)malloc( ncols * sizeof(buf[0]) );
-
- for( j = 0; j < ncols; j += cn )
- for( k = 0; k < cn; k++ )
- alpha_buf[j + k] = alpha.val[k];
-
- for( i = 0; i < c->rows; i++ )
- {
- uchar* c_data = c->data.ptr + i*c->step;
- uchar* a_data = a->data.ptr + i*a->step;
- uchar* b_data = b->data.ptr + i*b->step;
-
- switch( CV_MAT_DEPTH(a->type) )
- {
- case CV_8U:
- for( j = 0; j < ncols; j++ )
- buf[j] = (alpha_buf[j]*((uchar*)a_data)[j])*((uchar*)b_data)[j];
- break;
- case CV_8S:
- for( j = 0; j < ncols; j++ )
- buf[j] = (alpha_buf[j]*((schar*)a_data)[j])*((schar*)b_data)[j];
- break;
- case CV_16U:
- for( j = 0; j < ncols; j++ )
- buf[j] = (alpha_buf[j]*((ushort*)a_data)[j])*((ushort*)b_data)[j];
- break;
- case CV_16S:
- for( j = 0; j < ncols; j++ )
- buf[j] = (alpha_buf[j]*((short*)a_data)[j])*((short*)b_data)[j];
- break;
- case CV_32S:
- for( j = 0; j < ncols; j++ )
- buf[j] = (alpha_buf[j]*((int*)a_data)[j])*((int*)b_data)[j];
- break;
- case CV_32F:
- for( j = 0; j < ncols; j++ )
- buf[j] = (alpha_buf[j]*((float*)a_data)[j])*((float*)b_data)[j];
- break;
- case CV_64F:
- for( j = 0; j < ncols; j++ )
- buf[j] = (alpha_buf[j]*((double*)a_data)[j])*((double*)b_data)[j];
- break;
- default:
- assert(0);
- return;
- }
-
- switch( CV_MAT_DEPTH(c->type) )
- {
- case CV_8U:
- for( j = 0; j < ncols; j++ )
- {
- int val = cvRound(buf[j]);
- ((uchar*)c_data)[j] = CV_CAST_8U(val);
- }
- break;
- case CV_8S:
- for( j = 0; j < ncols; j++ )
- {
- int val = cvRound(buf[j]);
- ((schar*)c_data)[j] = CV_CAST_8S(val);
- }
- break;
- case CV_16U:
- for( j = 0; j < ncols; j++ )
- {
- int val = cvRound(buf[j]);
- ((ushort*)c_data)[j] = CV_CAST_16U(val);
- }
- break;
- case CV_16S:
- for( j = 0; j < ncols; j++ )
- {
- int val = cvRound(buf[j]);
- ((short*)c_data)[j] = CV_CAST_16S(val);
- }
- break;
- case CV_32S:
- for( j = 0; j < ncols; j++ )
- {
- int val = cvRound(buf[j]);
- ((int*)c_data)[j] = CV_CAST_32S(val);
- }
- break;
- case CV_32F:
- for( j = 0; j < ncols; j++ )
- ((float*)c_data)[j] = CV_CAST_32F(buf[j]);
- break;
- case CV_64F:
- for( j = 0; j < ncols; j++ )
- ((double*)c_data)[j] = CV_CAST_64F(buf[j]);
- break;
- default:
- assert(0);
- }
- }
-
- if( alpha_buf )
- free( alpha_buf );
-
- if( buf )
- free( buf );
-}
-
-
-// c = a*alpha/b
-void cvTsDiv( const CvMat* a, const CvMat* b, CvScalar alpha, CvMat* c )
-{
- int i, j, k, cn, ncols;
- double* buf = 0;
- double* alpha_buf = 0;
-
- if( !b || !c )
- {
- assert(0);
- return;
- }
-
- if( a )
- {
- assert( CV_ARE_SIZES_EQ(a,c) &&
- CV_ARE_TYPES_EQ(a,b) && CV_ARE_CNS_EQ(a,c) );
- }
-
- assert( CV_ARE_SIZES_EQ(b,c) && CV_ARE_CNS_EQ(b,c) );
-
- cn = CV_MAT_CN(c->type);
- ncols = c->cols * cn;
- alpha_buf = (double*)malloc( ncols * sizeof(alpha_buf[0]) );
- buf = (double*)malloc( ncols * sizeof(buf[0]) );
-
- for( j = 0; j < ncols; j += cn )
- for( k = 0; k < cn; k++ )
- alpha_buf[j + k] = alpha.val[k];
-
- for( i = 0; i < c->rows; i++ )
- {
- uchar* c_data = c->data.ptr + i*c->step;
- uchar* a_data = a ? a->data.ptr + i*a->step : 0;
- uchar* b_data = b->data.ptr + i*b->step;
-
- switch( CV_MAT_DEPTH(b->type) )
- {
- case CV_8U:
- for( j = 0; j < ncols; j++ )
- {
- int denom = ((uchar*)b_data)[j];
- int num = a_data ? ((uchar*)a_data)[j] : 1;
- buf[j] = !denom ? 0 : (alpha_buf[j]*num/denom);
- }
- break;
- case CV_8S:
- for( j = 0; j < ncols; j++ )
- {
- int denom = ((schar*)b_data)[j];
- int num = a_data ? ((schar*)a_data)[j] : 1;
- buf[j] = !denom ? 0 : (alpha_buf[j]*num/denom);
- }
- break;
- case CV_16U:
- for( j = 0; j < ncols; j++ )
- {
- int denom = ((ushort*)b_data)[j];
- int num = a_data ? ((ushort*)a_data)[j] : 1;
- buf[j] = !denom ? 0 : (alpha_buf[j]*num/denom);
- }
- break;
- case CV_16S:
- for( j = 0; j < ncols; j++ )
- {
- int denom = ((short*)b_data)[j];
- int num = a_data ? ((short*)a_data)[j] : 1;
- buf[j] = !denom ? 0 : (alpha_buf[j]*num/denom);
- }
- break;
- case CV_32S:
- for( j = 0; j < ncols; j++ )
- {
- int denom = ((int*)b_data)[j];
- int num = a_data ? ((int*)a_data)[j] : 1;
- buf[j] = !denom ? 0 : (alpha_buf[j]*num/denom);
- }
- break;
- case CV_32F:
- for( j = 0; j < ncols; j++ )
- {
- double denom = ((float*)b_data)[j];
- double num = a_data ? ((float*)a_data)[j] : 1;
- buf[j] = !denom ? 0 : (alpha_buf[j]*num/denom);
- }
- break;
- case CV_64F:
- for( j = 0; j < ncols; j++ )
- {
- double denom = ((double*)b_data)[j];
- double num = a_data ? ((double*)a_data)[j] : 1;
- buf[j] = !denom ? 0 : (alpha_buf[j]*num/denom);
- }
- break;
- default:
- assert(0);
- return;
- }
-
- switch( CV_MAT_DEPTH(c->type) )
- {
- case CV_8U:
- for( j = 0; j < ncols; j++ )
- {
- int val = cvRound(buf[j]);
- ((uchar*)c_data)[j] = CV_CAST_8U(val);
- }
- break;
- case CV_8S:
- for( j = 0; j < ncols; j++ )
- {
- int val = cvRound(buf[j]);
- ((schar*)c_data)[j] = CV_CAST_8S(val);
- }
- break;
- case CV_16U:
- for( j = 0; j < ncols; j++ )
- {
- int val = cvRound(buf[j]);
- ((ushort*)c_data)[j] = CV_CAST_16U(val);
- }
- break;
- case CV_16S:
- for( j = 0; j < ncols; j++ )
- {
- int val = cvRound(buf[j]);
- ((short*)c_data)[j] = CV_CAST_16S(val);
- }
- break;
- case CV_32S:
- for( j = 0; j < ncols; j++ )
- {
- int val = cvRound(buf[j]);
- ((int*)c_data)[j] = CV_CAST_32S(val);
- }
- break;
- case CV_32F:
- for( j = 0; j < ncols; j++ )
- ((float*)c_data)[j] = CV_CAST_32F(buf[j]);
- break;
- case CV_64F:
- for( j = 0; j < ncols; j++ )
- ((double*)c_data)[j] = CV_CAST_64F(buf[j]);
- break;
- default:
- assert(0);
- }
- }
-
- if( alpha_buf )
- free( alpha_buf );
-
- if( buf )
- free( buf );
-}
-
-
-// c = min(a,b) or c = max(a,b)
-void cvTsMinMax( const CvMat* a, const CvMat* b, CvMat* c, int op_type )
-{
- int i, j, ncols;
- int calc_max = op_type == CV_TS_MAX;
-
- if( !a || !b || !c )
- {
- assert(0);
- return;
- }
-
- assert( CV_ARE_SIZES_EQ(a,c) && CV_ARE_TYPES_EQ(a,c) &&
- CV_ARE_SIZES_EQ(b,c) && CV_ARE_TYPES_EQ(b,c) &&
- CV_MAT_CN(a->type) == 1 );
- ncols = c->cols;
-
- for( i = 0; i < c->rows; i++ )
- {
- uchar* c_data = c->data.ptr + i*c->step;
- uchar* a_data = a->data.ptr + i*a->step;
- uchar* b_data = b->data.ptr + i*b->step;
-
- switch( CV_MAT_DEPTH(a->type) )
- {
- case CV_8U:
- for( j = 0; j < ncols; j++ )
- {
- int aj = ((uchar*)a_data)[j];
- int bj = ((uchar*)b_data)[j];
- ((uchar*)c_data)[j] = (uchar)(calc_max ? MAX(aj, bj) : MIN(aj,bj));
- }
- break;
- case CV_8S:
- for( j = 0; j < ncols; j++ )
- {
- int aj = ((schar*)a_data)[j];
- int bj = ((schar*)b_data)[j];
- ((schar*)c_data)[j] = (schar)(calc_max ? MAX(aj, bj) : MIN(aj,bj));
- }
- break;
- case CV_16U:
- for( j = 0; j < ncols; j++ )
- {
- int aj = ((ushort*)a_data)[j];
- int bj = ((ushort*)b_data)[j];
- ((ushort*)c_data)[j] = (ushort)(calc_max ? MAX(aj, bj) : MIN(aj,bj));
- }
- break;
- case CV_16S:
- for( j = 0; j < ncols; j++ )
- {
- int aj = ((short*)a_data)[j];
- int bj = ((short*)b_data)[j];
- ((short*)c_data)[j] = (short)(calc_max ? MAX(aj, bj) : MIN(aj,bj));
- }
- break;
- case CV_32S:
- for( j = 0; j < ncols; j++ )
- {
- int aj = ((int*)a_data)[j];
- int bj = ((int*)b_data)[j];
- ((int*)c_data)[j] = calc_max ? MAX(aj, bj) : MIN(aj,bj);
- }
- break;
- case CV_32F:
- for( j = 0; j < ncols; j++ )
- {
- float aj = ((float*)a_data)[j];
- float bj = ((float*)b_data)[j];
- ((float*)c_data)[j] = calc_max ? MAX(aj, bj) : MIN(aj,bj);
- }
- break;
- case CV_64F:
- for( j = 0; j < ncols; j++ )
- {
- double aj = ((double*)a_data)[j];
- double bj = ((double*)b_data)[j];
- ((double*)c_data)[j] = calc_max ? MAX(aj, bj) : MIN(aj,bj);
- }
- break;
- default:
- assert(0);
- return;
- }
- }
-}
-
-// c = min(a,b) or c = max(a,b)
-void cvTsMinMaxS( const CvMat* a, double s, CvMat* c, int op_type )
-{
- int i, j, ncols;
- int calc_max = op_type == CV_TS_MAX;
- float fs = (float)s;
- int is = cvRound(s);
-
- if( !a || !c )
- {
- assert(0);
- return;
- }
-
- assert( CV_ARE_SIZES_EQ(a,c) && CV_ARE_TYPES_EQ(a,c) &&
- CV_MAT_CN(a->type) == 1 );
- ncols = c->cols;
-
- switch( CV_MAT_DEPTH(a->type) )
- {
- case CV_8U:
- is = CV_CAST_8U(is);
- break;
- case CV_8S:
- is = CV_CAST_8S(is);
- break;
- case CV_16U:
- is = CV_CAST_16U(is);
- break;
- case CV_16S:
- is = CV_CAST_16S(is);
- break;
- default:
- ;
- }
-
- for( i = 0; i < c->rows; i++ )
- {
- uchar* c_data = c->data.ptr + i*c->step;
- uchar* a_data = a->data.ptr + i*a->step;
-
- switch( CV_MAT_DEPTH(a->type) )
- {
- case CV_8U:
- for( j = 0; j < ncols; j++ )
- {
- int aj = ((uchar*)a_data)[j];
- ((uchar*)c_data)[j] = (uchar)(calc_max ? MAX(aj, is) : MIN(aj, is));
- }
- break;
- case CV_8S:
- for( j = 0; j < ncols; j++ )
- {
- int aj = ((schar*)a_data)[j];
- ((schar*)c_data)[j] = (schar)(calc_max ? MAX(aj, is) : MIN(aj, is));
- }
- break;
- case CV_16U:
- for( j = 0; j < ncols; j++ )
- {
- int aj = ((ushort*)a_data)[j];
- ((ushort*)c_data)[j] = (ushort)(calc_max ? MAX(aj, is) : MIN(aj, is));
- }
- break;
- case CV_16S:
- for( j = 0; j < ncols; j++ )
- {
- int aj = ((short*)a_data)[j];
- ((short*)c_data)[j] = (short)(calc_max ? MAX(aj, is) : MIN(aj, is));
- }
- break;
- case CV_32S:
- for( j = 0; j < ncols; j++ )
- {
- int aj = ((int*)a_data)[j];
- ((int*)c_data)[j] = calc_max ? MAX(aj, is) : MIN(aj, is);
- }
- break;
- case CV_32F:
- for( j = 0; j < ncols; j++ )
- {
- float aj = ((float*)a_data)[j];
- ((float*)c_data)[j] = calc_max ? MAX(aj, fs) : MIN(aj, fs);
- }
- break;
- case CV_64F:
- for( j = 0; j < ncols; j++ )
- {
- double aj = ((double*)a_data)[j];
- ((double*)c_data)[j] = calc_max ? MAX(aj, s) : MIN(aj, s);
- }
- break;
- default:
- assert(0);
- return;
- }
- }
-}
-
-// checks that the array does not have NaNs and/or Infs and all the elements are
-// within [min_val,max_val). idx is the index of the first "bad" element.
-int cvTsCheck( const CvMat* a, double min_val, double max_val, CvPoint* idx )
-{
- int i = 0, j = 0;
- int cn, ncols;
- int imin = 0, imax = 0;
- cn = CV_MAT_CN(a->type);
- ncols = a->cols*cn;
-
- if( CV_MAT_DEPTH(a->type) <= CV_32S )
- {
- imin = cvCeil(min_val);
- imax = cvFloor(max_val);
- }
-
- for( i = 0; i < a->rows; i++ )
- {
- uchar* data = a->data.ptr + a->step*i;
-
- switch( CV_MAT_DEPTH(a->type) )
- {
- case CV_8U:
- for( j = 0; j < ncols; j++ )
- {
- int val = ((uchar*)data)[j];
- if( val < imin || imax < val )
- goto _exit_;
- }
- break;
- case CV_8S:
- for( j = 0; j < ncols; j++ )
- {
- int val = ((schar*)data)[j];
- if( val < imin || imax < val )
- goto _exit_;
- }
- break;
- case CV_16U:
- for( j = 0; j < ncols; j++ )
- {
- int val = ((ushort*)data)[j];
- if( val < imin || imax < val )
- goto _exit_;
- }
- break;
- case CV_16S:
- for( j = 0; j < ncols; j++ )
- {
- int val = ((short*)data)[j];
- if( val < imin || imax < val )
- goto _exit_;
- }
- break;
- case CV_32S:
- for( j = 0; j < ncols; j++ )
- {
- int val = ((int*)data)[j];
- if( val < imin || imax < val )
- goto _exit_;
- }
- break;
- case CV_32F:
- for( j = 0; j < ncols; j++ )
- {
- double val = ((float*)data)[j];
- if( cvIsNaN(val) || cvIsInf(val) || val < min_val || max_val < val )
- goto _exit_;
- }
- break;
- case CV_64F:
- for( j = 0; j < ncols; j++ )
- {
- double val = ((double*)data)[j];
- if( cvIsNaN(val) || cvIsInf(val) || val < min_val || max_val < val )
- goto _exit_;
- }
- break;
- default:
- assert(0);
- return -1;
- }
- }
-
- return 0;
-_exit_:
-
- idx->x = j;
- idx->y = i;
- return -1;
-}
-
-// compares two arrays. max_diff is the maximum actual difference,
-// success_err_level is maximum allowed difference, idx is the index of the first
-// element for which difference is >success_err_level
-// (or index of element with the maximum difference)
-int cvTsCmpEps( const CvMat* check_arr, const CvMat* etalon, double* _max_diff,
- double success_err_level, CvPoint* _idx, bool element_wise_relative_error )
-{
- int i = 0, j = 0;
- int cn, ncols;
- double maxdiff = 0;
- double maxval = 0;
- int imaxdiff = 0;
- int ilevel = 0;
- int result = -1;
- CvPoint stub, *idx = _idx ? _idx : &stub;
-
- cn = CV_MAT_CN(check_arr->type);
- ncols = check_arr->cols*cn;
-
- *idx = cvPoint(0,0);
-
- assert( CV_ARE_TYPES_EQ(check_arr,etalon) && CV_ARE_SIZES_EQ(check_arr,etalon) );
-
- if( CV_MAT_DEPTH(check_arr->type) < CV_32S )
- ilevel = cvFloor(success_err_level);
-
- if( CV_MAT_DEPTH(check_arr->type) >= CV_32F && !element_wise_relative_error )
- {
- double maxval0 = 1.;
- maxval = cvTsNorm( etalon, 0, CV_C, 0 );
- maxval = MAX(maxval, maxval0);
- }
-
- for( i = 0; i < check_arr->rows; i++ )
- {
- uchar* a_data = check_arr->data.ptr + check_arr->step*i;
- uchar* b_data = etalon->data.ptr + etalon->step*i;
-
- switch( CV_MAT_DEPTH(check_arr->type) )
- {
- case CV_8U:
- for( j = 0; j < ncols; j++ )
- {
- int val = abs(((uchar*)a_data)[j] - ((uchar*)b_data)[j]);
- if( val > imaxdiff )
- {
- imaxdiff = val;
- *idx = cvPoint(j,i);
- if( val > ilevel )
- goto _exit_;
- }
- }
- break;
- case CV_8S:
- for( j = 0; j < ncols; j++ )
- {
- int val = abs(((schar*)a_data)[j] - ((schar*)b_data)[j]);
- if( val > imaxdiff )
- {
- imaxdiff = val;
- *idx = cvPoint(j,i);
- if( val > ilevel )
- goto _exit_;
- }
- }
- break;
- case CV_16U:
- for( j = 0; j < ncols; j++ )
- {
- int val = abs(((ushort*)a_data)[j] - ((ushort*)b_data)[j]);
- if( val > imaxdiff )
- {
- imaxdiff = val;
- *idx = cvPoint(j,i);
- if( val > ilevel )
- goto _exit_;
- }
- }
- break;
- case CV_16S:
- for( j = 0; j < ncols; j++ )
- {
- int val = abs(((short*)a_data)[j] - ((short*)b_data)[j]);
- if( val > imaxdiff )
- {
- imaxdiff = val;
- *idx = cvPoint(j,i);
- if( val > ilevel )
- goto _exit_;
- }
- }
- break;
- case CV_32S:
- for( j = 0; j < ncols; j++ )
- {
- double val = fabs((double)((int*)a_data)[j] - (double)((int*)b_data)[j]);
- if( val > maxdiff )
- {
- maxdiff = val;
- *idx = cvPoint(j,i);
- if( val > success_err_level )
- goto _exit_;
- }
- }
- break;
- case CV_32F:
- for( j = 0; j < ncols; j++ )
- {
- double a_val = ((float*)a_data)[j];
- double b_val = ((float*)b_data)[j];
- double threshold;
- if( ((int*)a_data)[j] == ((int*)b_data)[j] )
- continue;
- if( cvIsNaN(a_val) || cvIsInf(a_val) )
- {
- result = -2;
- *idx = cvPoint(j,i);
- goto _exit_;
- }
- if( cvIsNaN(b_val) || cvIsInf(b_val) )
- {
- result = -3;
- *idx = cvPoint(j,i);
- goto _exit_;
- }
- a_val = fabs(a_val - b_val);
- threshold = element_wise_relative_error ? fabs(b_val) + 1 : maxval;
- if( a_val > threshold*success_err_level )
- {
- maxdiff = a_val/threshold;
- *idx = cvPoint(j,i);
- goto _exit_;
- }
- }
- break;
- case CV_64F:
- for( j = 0; j < ncols; j++ )
- {
- double a_val = ((double*)a_data)[j];
- double b_val = ((double*)b_data)[j];
- double threshold;
- if( ((int64*)a_data)[j] == ((int64*)b_data)[j] )
- continue;
- if( cvIsNaN(a_val) || cvIsInf(a_val) )
- {
- result = -2;
- *idx = cvPoint(j,i);
- goto _exit_;
- }
- if( cvIsNaN(b_val) || cvIsInf(b_val) )
- {
- result = -3;
- *idx = cvPoint(j,i);
- goto _exit_;
- }
- a_val = fabs(a_val - b_val);
- threshold = element_wise_relative_error ? fabs(b_val) + 1 : maxval;
- if( a_val > threshold*success_err_level )
- {
- maxdiff = a_val/threshold;
- *idx = cvPoint(j,i);
- goto _exit_;
- }
- }
- break;
- default:
- assert(0);
- return -1;
- }
- }
-
- result = 0;
-_exit_:
-
- if( CV_MAT_DEPTH(check_arr->type) < CV_32S )
- maxdiff = imaxdiff;
-
- if( result < -1 )
- maxdiff = exp(1000.);
- *_max_diff = maxdiff;
- return result;
-}
-
-
-int cvTsCmpEps2( CvTS* ts, const CvArr* _a, const CvArr* _b, double success_err_level,
- bool element_wise_relative_error, const char* desc )
-{
- char msg[100];
- double diff = 0;
- CvMat astub, bstub, *a, *b;
- CvPoint idx = {0,0};
- int code;
-
- a = cvGetMat( _a, &astub );
- b = cvGetMat( _b, &bstub );
- code = cvTsCmpEps( a, b, &diff, success_err_level, &idx,
- element_wise_relative_error );
-
- switch( code )
- {
- case -1:
- sprintf( msg, "%s: Too big difference (=%g)", desc, diff );
- code = CvTS::FAIL_BAD_ACCURACY;
- break;
- case -2:
- sprintf( msg, "%s: Invalid output", desc );
- code = CvTS::FAIL_INVALID_OUTPUT;
- break;
- case -3:
- sprintf( msg, "%s: Invalid reference output", desc );
- code = CvTS::FAIL_INVALID_OUTPUT;
- break;
- default:
- ;
- }
-
- if( code < 0 )
- {
- if( a->rows == 1 && a->cols == 1 )
- {
- assert( idx.x == 0 && idx.y == 0 );
- ts->printf( CvTS::LOG, "%s\n", msg );
- }
- else if( a->rows == 1 || a->cols == 1 )
- {
- assert( idx.x == 0 || idx.y == 0 );
- ts->printf( CvTS::LOG, "%s at element %d\n", msg, idx.x + idx.y );
- }
- else
- ts->printf( CvTS::LOG, "%s at (%d,%d)\n", msg, idx.x, idx.y );
- }
-
- return code;
-}
-
-
-int cvTsCmpEps2_64f( CvTS* ts, const double* val, const double* ref_val, int len,
- double eps, const char* param_name )
-{
- CvMat _val = cvMat( 1, len, CV_64F, (void*)val );
- CvMat _ref_val = cvMat( 1, len, CV_64F, (void*)ref_val );
-
- return cvTsCmpEps2( ts, &_val, &_ref_val, eps, true, param_name );
-}
-
-// compares two arrays. the result is 8s image that takes values -1, 0, 1
-void cvTsCmp( const CvMat* a, const CvMat* b, CvMat* result, int cmp_op )
-{
- int i = 0, j = 0, ncols;
- ncols = a->cols;
-
- assert( CV_ARE_TYPES_EQ(a,b) && CV_ARE_SIZES_EQ(a,b) && CV_MAT_CN(a->type) == 1 );
- assert( CV_ARE_SIZES_EQ(a,result) &&
- (CV_MAT_TYPE(result->type) == CV_8UC1 ||
- CV_MAT_TYPE(result->type) == CV_8SC1 ));
-
- for( i = 0; i < a->rows; i++ )
- {
- uchar* a_data = a->data.ptr + a->step*i;
- uchar* b_data = b->data.ptr + b->step*i;
- schar* r_data = (schar*)(result->data.ptr + result->step*i);
-
- switch( CV_MAT_DEPTH(a->type) )
- {
- case CV_8U:
- for( j = 0; j < ncols; j++ )
- {
- int a_val = ((uchar*)a_data)[j];
- int b_val = ((uchar*)b_data)[j];
- r_data[j] = (schar)CV_CMP(a_val,b_val);
- }
- break;
- case CV_8S:
- for( j = 0; j < ncols; j++ )
- {
- int a_val = ((schar*)a_data)[j];
- int b_val = ((schar*)b_data)[j];
- r_data[j] = (schar)CV_CMP(a_val,b_val);
- }
- break;
- case CV_16U:
- for( j = 0; j < ncols; j++ )
- {
- int a_val = ((ushort*)a_data)[j];
- int b_val = ((ushort*)b_data)[j];
- r_data[j] = (schar)CV_CMP(a_val,b_val);
- }
- break;
- case CV_16S:
- for( j = 0; j < ncols; j++ )
- {
- int a_val = ((short*)a_data)[j];
- int b_val = ((short*)b_data)[j];
- r_data[j] = (schar)CV_CMP(a_val,b_val);
- }
- break;
- case CV_32S:
- for( j = 0; j < ncols; j++ )
- {
- int a_val = ((int*)a_data)[j];
- int b_val = ((int*)b_data)[j];
- r_data[j] = (schar)CV_CMP(a_val,b_val);
- }
- break;
- case CV_32F:
- for( j = 0; j < ncols; j++ )
- {
- float a_val = ((float*)a_data)[j];
- float b_val = ((float*)b_data)[j];
- r_data[j] = (schar)CV_CMP(a_val,b_val);
- }
- break;
- case CV_64F:
- for( j = 0; j < ncols; j++ )
- {
- double a_val = ((double*)a_data)[j];
- double b_val = ((double*)b_data)[j];
- r_data[j] = (schar)CV_CMP(a_val,b_val);
- }
- break;
- default:
- assert(0);
- }
-
- switch( cmp_op )
- {
- case CV_CMP_EQ:
- for( j = 0; j < ncols; j++ )
- r_data[j] = (schar)(r_data[j] == 0 ? -1 : 0);
- break;
- case CV_CMP_NE:
- for( j = 0; j < ncols; j++ )
- r_data[j] = (schar)(r_data[j] != 0 ? -1 : 0);
- break;
- case CV_CMP_LT:
- for( j = 0; j < ncols; j++ )
- r_data[j] = (schar)(r_data[j] < 0 ? -1 : 0);
- break;
- case CV_CMP_LE:
- for( j = 0; j < ncols; j++ )
- r_data[j] = (schar)(r_data[j] <= 0 ? -1 : 0);
- break;
- case CV_CMP_GE:
- for( j = 0; j < ncols; j++ )
- r_data[j] = (schar)(r_data[j] >= 0 ? -1 : 0);
- break;
- case CV_CMP_GT:
- for( j = 0; j < ncols; j++ )
- r_data[j] = (schar)(r_data[j] > 0 ? -1 : 0);
- break;
- default:
- ;
- }
- }
-}
-
-// compares two arrays. the result is 8s image that takes values -1, 0, 1
-void cvTsCmpS( const CvMat* a, double fval, CvMat* result, int cmp_op )
-{
- int i = 0, j = 0;
- int ncols, ival = 0;
- ncols = a->cols;
-
- if( CV_MAT_DEPTH(a->type) <= CV_32S )
- ival = cvRound(fval);
-
- assert( CV_MAT_CN(a->type) == 1 );
- assert( CV_ARE_SIZES_EQ(a,result) &&
- (CV_MAT_TYPE(result->type) == CV_8UC1 ||
- CV_MAT_TYPE(result->type) == CV_8SC1 ));
-
- for( i = 0; i < a->rows; i++ )
- {
- uchar* a_data = a->data.ptr + a->step*i;
- schar* r_data = (schar*)(result->data.ptr + result->step*i);
-
- switch( CV_MAT_DEPTH(a->type) )
- {
- case CV_8U:
- for( j = 0; j < ncols; j++ )
- {
- int a_val = ((uchar*)a_data)[j];
- r_data[j] = (schar)CV_CMP(a_val,ival);
- }
- break;
- case CV_8S:
- for( j = 0; j < ncols; j++ )
- {
- int a_val = ((schar*)a_data)[j];
- r_data[j] = (schar)CV_CMP(a_val,ival);
- }
- break;
- case CV_16U:
- for( j = 0; j < ncols; j++ )
- {
- int a_val = ((ushort*)a_data)[j];
- r_data[j] = (schar)CV_CMP(a_val,ival);
- }
- break;
- case CV_16S:
- for( j = 0; j < ncols; j++ )
- {
- int a_val = ((short*)a_data)[j];
- r_data[j] = (schar)CV_CMP(a_val,ival);
- }
- break;
- case CV_32S:
- for( j = 0; j < ncols; j++ )
- {
- int a_val = ((int*)a_data)[j];
- r_data[j] = (schar)CV_CMP(a_val,ival);
- }
- break;
- case CV_32F:
- for( j = 0; j < ncols; j++ )
- {
- float a_val = ((float*)a_data)[j];
- r_data[j] = (schar)CV_CMP(a_val,fval);
- }
- break;
- case CV_64F:
- for( j = 0; j < ncols; j++ )
- {
- double a_val = ((double*)a_data)[j];
- r_data[j] = (schar)CV_CMP(a_val,fval);
- }
- break;
- default:
- assert(0);
- }
-
- switch( cmp_op )
- {
- case CV_CMP_EQ:
- for( j = 0; j < ncols; j++ )
- r_data[j] = (schar)(r_data[j] == 0 ? -1 : 0);
- break;
- case CV_CMP_NE:
- for( j = 0; j < ncols; j++ )
- r_data[j] = (schar)(r_data[j] != 0 ? -1 : 0);
- break;
- case CV_CMP_LT:
- for( j = 0; j < ncols; j++ )
- r_data[j] = (schar)(r_data[j] < 0 ? -1 : 0);
- break;
- case CV_CMP_LE:
- for( j = 0; j < ncols; j++ )
- r_data[j] = (schar)(r_data[j] <= 0 ? -1 : 0);
- break;
- case CV_CMP_GE:
- for( j = 0; j < ncols; j++ )
- r_data[j] = (schar)(r_data[j] >= 0 ? -1 : 0);
- break;
- case CV_CMP_GT:
- for( j = 0; j < ncols; j++ )
- r_data[j] = (schar)(r_data[j] > 0 ? -1 : 0);
- break;
- default:
- ;
- }
- }
-}
-
-
-// calculates norm of a matrix
-double cvTsNorm( const CvMat* arr, const CvMat* mask, int norm_type, int coi )
-{
- int i = 0, j = 0, k;
- int depth, cn0, cn, ncols, el_size1;
- int inorm = 0;
- double fnorm = 0;
- void* buffer = 0;
- uchar* zerobuf = 0;
-
- cn0 = cn = CV_MAT_CN(arr->type);
- ncols = arr->cols*cn;
- depth = CV_MAT_DEPTH(arr->type);
- el_size1 = CV_ELEM_SIZE(depth);
- zerobuf = (uchar*)cvStackAlloc(el_size1*cn);
- memset( zerobuf, 0, el_size1*cn);
-
- if( mask )
- {
- assert( CV_ARE_SIZES_EQ( arr, mask ) && CV_IS_MASK_ARR(mask) );
- buffer = cvStackAlloc( el_size1*ncols );
- }
-
- if( coi == 0 )
- cn = 1;
-
- for( i = 0; i < arr->rows; i++ )
- {
- const uchar* data = arr->data.ptr + arr->step*i + (coi - (coi != 0))*el_size1;
-
- if( mask )
- {
- const uchar* mdata = mask->data.ptr + mask->step*i;
- switch( depth )
- {
- case CV_8U:
- case CV_8S:
- for( j = 0; j < ncols; j += cn0 )
- {
- const uchar* src = *mdata++ ? (uchar*)data + j : zerobuf;
- for( k = 0; k < cn0; k++ )
- ((uchar*)buffer)[j+k] = src[k];
- }
- break;
- case CV_16U:
- case CV_16S:
- for( j = 0; j < ncols; j += cn0 )
- {
- const short* src = *mdata++ ? (short*)data + j : (short*)zerobuf;
- for( k = 0; k < cn0; k++ )
- ((short*)buffer)[j+k] = src[k];
- }
- break;
- case CV_32S:
- case CV_32F:
- for( j = 0; j < ncols; j += cn0 )
- {
- const int* src = *mdata++ ? (int*)data + j : (int*)zerobuf;
- for( k = 0; k < cn0; k++ )
- ((int*)buffer)[j+k] = src[k];
- }
- break;
- case CV_64F:
- for( j = 0; j < ncols; j += cn0 )
- {
- const double* src = *mdata++ ? (double*)data + j : (double*)zerobuf;
- for( k = 0; k < cn0; k++ )
- ((double*)buffer)[j+k] = src[k];
- }
- break;
- default:
- assert(0);
- return -1;
- }
- data = (const uchar*)buffer;
- }
-
- switch( depth )
- {
- case CV_8U:
- if( norm_type == CV_C )
- {
- for( j = 0; j < ncols; j += cn )
- {
- int val = ((const uchar*)data)[j];
- inorm = MAX( inorm, val );
- }
- }
- else if( norm_type == CV_L1 )
- {
- inorm = 0;
- for( j = 0; j < ncols; j += cn )
- {
- int val = ((const uchar*)data)[j];
- inorm += val;
- }
- fnorm += inorm;
- }
- else
- {
- inorm = 0;
- for( j = 0; j < ncols; j += cn )
- {
- int val = ((const uchar*)data)[j];
- inorm += val*val;
- }
- fnorm += inorm;
- }
- break;
- case CV_8S:
- if( norm_type == CV_C )
- {
- for( j = 0; j < ncols; j += cn )
- {
- int val = abs(((const schar*)data)[j]);
- inorm = MAX( inorm, val );
- }
- }
- else if( norm_type == CV_L1 )
- {
- inorm = 0;
- for( j = 0; j < ncols; j += cn )
- {
- int val = abs(((const schar*)data)[j]);
- inorm += val;
- }
- fnorm += inorm;
- }
- else
- {
- inorm = 0;
- for( j = 0; j < ncols; j += cn )
- {
- int val = ((const schar*)data)[j];
- inorm += val*val;
- }
- fnorm += inorm;
- }
- break;
- case CV_16U:
- if( norm_type == CV_C )
- {
- for( j = 0; j < ncols; j += cn )
- {
- int val = ((const ushort*)data)[j];
- inorm = MAX( inorm, val );
- }
- }
- else if( norm_type == CV_L1 )
- {
- inorm = 0;
- for( j = 0; j < ncols; j += cn )
- {
- int val = ((const ushort*)data)[j];
- inorm += val;
- }
- fnorm += inorm;
- }
- else
- {
- for( j = 0; j < ncols; j += cn )
- {
- double val = ((const ushort*)data)[j];
- fnorm += val*val;
- }
- }
- break;
- case CV_16S:
- if( norm_type == CV_C )
- {
- for( j = 0; j < ncols; j += cn )
- {
- int val = abs(((const short*)data)[j]);
- inorm = MAX( inorm, val );
- }
- }
- else if( norm_type == CV_L1 )
- {
- inorm = 0;
- for( j = 0; j < ncols; j += cn )
- {
- int val = abs(((const short*)data)[j]);
- inorm += val;
- }
- fnorm += inorm;
- }
- else
- {
- for( j = 0; j < ncols; j += cn )
- {
- double val = ((const short*)data)[j];
- fnorm += val*val;
- }
- }
- break;
- case CV_32S:
- if( norm_type == CV_C )
- {
- for( j = 0; j < ncols; j += cn )
- {
- int val = abs(((const int*)data)[j]);
- inorm = MAX( inorm, val );
- }
- }
- else if( norm_type == CV_L1 )
- {
- for( j = 0; j < ncols; j += cn )
- {
- double val = fabs((double)((const int*)data)[j]);
- fnorm += val;
- }
- }
- else
- {
- for( j = 0; j < ncols; j += cn )
- {
- double val = ((const int*)data)[j];
- fnorm += val*val;
- }
- }
- break;
- case CV_32F:
- if( norm_type == CV_C )
- {
- for( j = 0; j < ncols; j += cn )
- {
- double val = fabs((double)((const float*)data)[j]);
- fnorm = MAX( fnorm, val );
- }
- }
- else if( norm_type == CV_L1 )
- {
- for( j = 0; j < ncols; j += cn )
- {
- double val = fabs((double)((const float*)data)[j]);
- fnorm += val;
- }
- }
- else
- {
- for( j = 0; j < ncols; j += cn )
- {
- double val = ((const float*)data)[j];
- fnorm += val*val;
- }
- }
- break;
- case CV_64F:
- if( norm_type == CV_C )
- {
- for( j = 0; j < ncols; j += cn )
- {
- double val = fabs(((const double*)data)[j]);
- fnorm = MAX( fnorm, val );
- }
- }
- else if( norm_type == CV_L1 )
- {
- for( j = 0; j < ncols; j += cn )
- {
- double val = fabs(((const double*)data)[j]);
- fnorm += val;
- }
- }
- else
- {
- for( j = 0; j < ncols; j += cn )
- {
- double val = ((const double*)data)[j];
- fnorm += val*val;
- }
- }
- break;
- default:
- assert(0);
- return -1;
- }
- }
-
- if( norm_type == CV_L2 )
- fnorm = sqrt( fnorm );
- else if( depth < CV_32F && norm_type == CV_C )
- fnorm = inorm;
-
- return fnorm;
-}
-
-
-// retrieves mean, standard deviation and the number of nonzero mask pixels
-int cvTsMeanStdDevNonZero( const CvMat* arr, const CvMat* mask,
- CvScalar* _mean, CvScalar* _stddev, int coi )
-{
- int i = 0, j = 0, k;
- int depth, cn0, cn, cols, ncols, el_size1;
- CvScalar sum = cvScalar(0), sqsum = cvScalar(0);
- double inv_area;
- int isum[4], isqsum[4];
- int nonzero = 0;
- uchar* maskbuf = 0;
-
- cn0 = cn = CV_MAT_CN(arr->type);
- cols = arr->cols;
- ncols = arr->cols*cn;
- depth = CV_MAT_DEPTH(arr->type);
- el_size1 = CV_ELEM_SIZE(depth);
- if( mask )
- {
- assert( CV_ARE_SIZES_EQ( arr, mask ) && CV_IS_MASK_ARR(mask) );
- }
- else
- {
- maskbuf = (uchar*)cvStackAlloc( cols );
- memset( maskbuf, 1, cols );
- nonzero = cols*arr->rows;
- }
-
- if( coi != 0 )
- cn = 1;
-
- for( i = 0; i < arr->rows; i++ )
- {
- const uchar* data = arr->data.ptr + arr->step*i + (coi - (coi != 0))*el_size1;
- const uchar* mdata;
-
- if( mask )
- {
- mdata = mask->data.ptr + mask->step*i;
- for( j = 0; j < cols; j++ )
- nonzero += mdata[j] != 0;
- }
- else
- {
- mdata = maskbuf;
- }
-
- // if only a number of pixels in the mask is needed, skip the rest of the loop body
- if( !_mean && !_stddev )
- continue;
-
- switch( depth )
- {
- case CV_8U:
- for( k = 0; k < cn; k++ )
- isum[k] = isqsum[k] = 0;
- for( j = 0; j < ncols; j += cn0 )
- if( *mdata++ )
- {
- for( k = 0; k < cn; k++ )
- {
- int val = ((const uchar*)data)[j+k];
- isum[k] += val;
- isqsum[k] += val*val;
- }
- }
- for( k = 0; k < cn; k++ )
- {
- sum.val[k] += isum[k];
- sqsum.val[k] += isqsum[k];
- }
- break;
- case CV_8S:
- for( k = 0; k < cn; k++ )
- isum[k] = isqsum[k] = 0;
- for( j = 0; j < ncols; j += cn0 )
- if( *mdata++ )
- {
- for( k = 0; k < cn; k++ )
- {
- int val = ((const schar*)data)[j+k];
- isum[k] += val;
- isqsum[k] += val*val;
- }
- }
- for( k = 0; k < cn; k++ )
- {
- sum.val[k] += isum[k];
- sqsum.val[k] += isqsum[k];
- }
- break;
- case CV_16U:
- for( k = 0; k < cn; k++ )
- isum[k] = 0;
- for( j = 0; j < ncols; j += cn0 )
- if( *mdata++ )
- {
- for( k = 0; k < cn; k++ )
- {
- int val = ((const ushort*)data)[j+k];
- isum[k] += val;
- sqsum.val[k] += ((double)val)*val;
- }
- }
- for( k = 0; k < cn; k++ )
- sum.val[k] += isum[k];
- break;
- case CV_16S:
- for( k = 0; k < cn; k++ )
- isum[k] = 0;
- for( j = 0; j < ncols; j += cn0 )
- if( *mdata++ )
- {
- for( k = 0; k < cn; k++ )
- {
- int val = ((const short*)data)[j+k];
- isum[k] += val;
- sqsum.val[k] += ((double)val)*val;
- }
- }
- for( k = 0; k < cn; k++ )
- sum.val[k] += isum[k];
- break;
- case CV_32S:
- for( j = 0; j < ncols; j += cn0 )
- if( *mdata++ )
- {
- for( k = 0; k < cn; k++ )
- {
- double val = ((const int*)data)[j+k];
- sum.val[k] += val;
- sqsum.val[k] += val*val;
- }
- }
- break;
- case CV_32F:
- for( j = 0; j < ncols; j += cn0 )
- if( *mdata++ )
- {
- for( k = 0; k < cn; k++ )
- {
- double val = ((const float*)data)[j+k];
- sum.val[k] += val;
- sqsum.val[k] += val*val;
- }
- }
- break;
- case CV_64F:
- for( j = 0; j < ncols; j += cn0 )
- if( *mdata++ )
- {
- for( k = 0; k < cn; k++ )
- {
- double val = ((const double*)data)[j+k];
- sum.val[k] += val;
- sqsum.val[k] += val*val;
- }
- }
- break;
- default:
- assert(0);
- return -1;
- }
- }
-
- inv_area = nonzero ? 1./nonzero : 0.;
- for( k = 0; k < cn; k++ )
- {
- sum.val[k] *= inv_area;
- double t = sqsum.val[k]*inv_area - sum.val[k]*sum.val[k];
- sqsum.val[k] = sqrt(MAX(t, 0));
- }
- if( _mean )
- *_mean = sum;
- if( _stddev )
- *_stddev = sqsum;
- return nonzero;
-}
-
-// retrieves global extremums and their positions
-void cvTsMinMaxLoc( const CvMat* arr, const CvMat* mask,
- double* _minval, double* _maxval,
- CvPoint* _minidx, CvPoint* _maxidx, int coi )
-{
- int i = 0, j = 0;
- int depth, cn, cols, ncols, el_size1;
- CvPoint minidx = {-1,-1}, maxidx = {-1,-1};
- uchar* maskbuf = 0;
- int iminval = INT_MAX, imaxval = INT_MIN;
- double minval = DBL_MAX, maxval = -minval;
-
- cn = CV_MAT_CN(arr->type);
- cols = arr->cols;
- ncols = arr->cols*cn;
- depth = CV_MAT_DEPTH(arr->type);
- el_size1 = CV_ELEM_SIZE(depth);
-
- if( mask )
- {
- assert( CV_ARE_SIZES_EQ( arr, mask ) && CV_IS_MASK_ARR(mask) );
- }
- else
- {
- maskbuf = (uchar*)cvStackAlloc( cols );
- memset( maskbuf, 1, cols );
- }
-
- if( coi == 0 && cn > 1 )
- {
- assert(0);
- return;
- }
-
- for( i = 0; i < arr->rows; i++ )
- {
- const uchar* data = arr->data.ptr + arr->step*i + (coi - (coi != 0))*el_size1;
- const uchar* mdata = mask ? mask->data.ptr + mask->step*i : maskbuf;
-
- switch( depth )
- {
- case CV_8U:
- for( j = 0; j < ncols; j += cn, mdata++ )
- {
- int val = ((const uchar*)data)[j];
- if( val < iminval && *mdata )
- {
- iminval = val;
- minidx = cvPoint(j,i);
- }
- if( val > imaxval && *mdata )
- {
- imaxval = val;
- maxidx = cvPoint(j,i);
- }
- }
- break;
- case CV_8S:
- for( j = 0; j < ncols; j += cn, mdata++ )
- {
- int val = ((const schar*)data)[j];
- if( val < iminval && *mdata )
- {
- iminval = val;
- minidx = cvPoint(j,i);
- }
- if( val > imaxval && *mdata )
- {
- imaxval = val;
- maxidx = cvPoint(j,i);
- }
- }
- break;
- case CV_16U:
- for( j = 0; j < ncols; j += cn, mdata++ )
- {
- int val = ((const ushort*)data)[j];
- if( val < iminval && *mdata )
- {
- iminval = val;
- minidx = cvPoint(j,i);
- }
- if( val > imaxval && *mdata )
- {
- imaxval = val;
- maxidx = cvPoint(j,i);
- }
- }
- break;
- case CV_16S:
- for( j = 0; j < ncols; j += cn, mdata++ )
- {
- int val = ((const short*)data)[j];
- if( val < iminval && *mdata )
- {
- iminval = val;
- minidx = cvPoint(j,i);
- }
- if( val > imaxval && *mdata )
- {
- imaxval = val;
- maxidx = cvPoint(j,i);
- }
- }
- break;
- case CV_32S:
- for( j = 0; j < ncols; j += cn, mdata++ )
- {
- int val = ((const int*)data)[j];
- if( val < iminval && *mdata )
- {
- iminval = val;
- minidx = cvPoint(j,i);
- }
- if( val > imaxval && *mdata )
- {
- imaxval = val;
- maxidx = cvPoint(j,i);
- }
- }
- break;
- case CV_32F:
- for( j = 0; j < ncols; j += cn, mdata++ )
- {
- float val = ((const float*)data)[j];
- if( val < minval && *mdata )
- {
- minval = val;
- minidx = cvPoint(j,i);
- }
- if( val > maxval && *mdata )
- {
- maxval = val;
- maxidx = cvPoint(j,i);
- }
- }
- break;
- case CV_64F:
- for( j = 0; j < ncols; j += cn, mdata++ )
- {
- double val = ((const double*)data)[j];
- if( val < minval && *mdata )
- {
- minval = val;
- minidx = cvPoint(j,i);
- }
- if( val > maxval && *mdata )
- {
- maxval = val;
- maxidx = cvPoint(j,i);
- }
- }
- break;
- default:
- assert(0);
- return;
- }
- }
-
- if( minidx.x < 0 )
- minval = maxval = 0;
- else
- {
- if( depth < CV_32F )
- minval = iminval, maxval = imaxval;
- minidx.x /= cn;
- maxidx.x /= cn;
- }
-
- if( _minval )
- *_minval = minval;
-
- if( _maxval )
- *_maxval = maxval;
-
- if( _minidx )
- *_minidx = minidx;
-
- if( _maxidx )
- *_maxidx = maxidx;
-}
-
-
-void cvTsLogic( const CvMat* a, const CvMat* b, CvMat* c, int logic_op )
-{
- int i = 0, j = 0, ncols;
- ncols = a->cols*CV_ELEM_SIZE(a->type);
-
- assert( CV_ARE_TYPES_EQ(a,b) && CV_ARE_SIZES_EQ(a,b) );
- assert( CV_ARE_TYPES_EQ(a,c) && CV_ARE_SIZES_EQ(a,c) );
-
- for( i = 0; i < a->rows; i++ )
- {
- uchar* a_data = a->data.ptr + a->step*i;
- uchar* b_data = b->data.ptr + b->step*i;
- uchar* c_data = c->data.ptr + c->step*i;
-
- switch( logic_op )
- {
- case CV_TS_LOGIC_AND:
- for( j = 0; j < ncols; j++ )
- c_data[j] = (uchar)(a_data[j] & b_data[j]);
- break;
- case CV_TS_LOGIC_OR:
- for( j = 0; j < ncols; j++ )
- c_data[j] = (uchar)(a_data[j] | b_data[j]);
- break;
- case CV_TS_LOGIC_XOR:
- for( j = 0; j < ncols; j++ )
- c_data[j] = (uchar)(a_data[j] ^ b_data[j]);
- break;
- default:
- assert(0);
- return;
- }
- }
-}
-
-void cvTsLogicS( const CvMat* a, CvScalar s, CvMat* c, int logic_op )
-{
- int i = 0, j = 0, k;
- int cn, ncols, elem_size;
- uchar* b_data;
- union
- {
- uchar ptr[4];
- schar c[4];
- short s[4];
- ushort w[4];
- int i[4];
- float f[4];
- double d[4];
- } buf;
- cn = CV_MAT_CN(a->type);
- elem_size = CV_ELEM_SIZE(a->type);
- ncols = a->cols * elem_size;
- b_data = (uchar*)malloc( ncols );
-
- assert( CV_ARE_TYPES_EQ(a,c) && CV_ARE_SIZES_EQ(a,c) );
-
- if( logic_op == CV_TS_LOGIC_NOT )
- {
- memset( b_data, -1, ncols );
- logic_op = CV_TS_LOGIC_XOR;
- }
- else
- {
- switch( CV_MAT_DEPTH(a->type) )
- {
- case CV_8U:
- for( k = 0; k < cn; k++ )
- {
- int val = cvRound(s.val[k]);
- buf.ptr[k] = CV_CAST_8U(val);
- }
- break;
- case CV_8S:
- for( k = 0; k < cn; k++ )
- {
- int val = cvRound(s.val[k]);
- buf.c[k] = CV_CAST_8S(val);
- }
- break;
- case CV_16U:
- for( k = 0; k < cn; k++ )
- {
- int val = cvRound(s.val[k]);
- buf.w[k] = CV_CAST_16U(val);
- }
- break;
- case CV_16S:
- for( k = 0; k < cn; k++ )
- {
- int val = cvRound(s.val[k]);
- buf.s[k] = CV_CAST_16S(val);
- }
- break;
- case CV_32S:
- for( k = 0; k < cn; k++ )
- {
- int val = cvRound(s.val[k]);
- buf.i[k] = CV_CAST_32S(val);
- }
- break;
- case CV_32F:
- for( k = 0; k < cn; k++ )
- {
- double val = s.val[k];
- buf.f[k] = CV_CAST_32F(val);
- }
- break;
- case CV_64F:
- for( k = 0; k < cn; k++ )
- {
- double val = s.val[k];
- buf.d[k] = CV_CAST_64F(val);
- }
- break;
- default:
- assert(0);
- return;
- }
-
- for( j = 0; j < ncols; j += elem_size )
- memcpy( b_data + j, buf.ptr, elem_size );
- }
-
- for( i = 0; i < a->rows; i++ )
- {
- uchar* a_data = a->data.ptr + a->step*i;
- uchar* c_data = c->data.ptr + c->step*i;
-
- switch( logic_op )
- {
- case CV_TS_LOGIC_AND:
- for( j = 0; j < ncols; j++ )
- c_data[j] = (uchar)(a_data[j] & b_data[j]);
- break;
- case CV_TS_LOGIC_OR:
- for( j = 0; j < ncols; j++ )
- c_data[j] = (uchar)(a_data[j] | b_data[j]);
- break;
- case CV_TS_LOGIC_XOR:
- for( j = 0; j < ncols; j++ )
- c_data[j] = (uchar)(a_data[j] ^ b_data[j]);
- break;
- default:
- assert(0);
- return;
- }
- }
-
- if( b_data )
- free( b_data );
-}
-
-
-void cvTsGEMM( const CvMat* a, const CvMat* b, double alpha,
- const CvMat* c, double beta, CvMat* d, int flags )
-{
- int i, j, k;
- int a_rows, a_cols, b_rows, b_cols;
- int c_rows, c_cols, d_rows, d_cols;
- int cn, el_size;
- int a_step, a_delta, b_step, b_delta;
- int c_step, c_delta, d_step;
-
- a_rows = a->rows; a_cols = a->cols;
- cn = CV_MAT_CN(a->type);
- el_size = CV_ELEM_SIZE(a->type & ~CV_MAT_CN_MASK);
- a_step = a->step / el_size; a_delta = cn;
- d_rows = d->rows; d_cols = d->cols;
- b_rows = b->rows; b_cols = b->cols;
- b_step = b->step / el_size; b_delta = cn;
- c_rows = c ? c->rows : 0; c_cols = c ? c->cols : 0;
- c_step = c ? c->step / el_size : 0; c_delta = c ? cn : 0;
- d_step = d->step / el_size;
-
- assert( CV_ARE_TYPES_EQ(a,b) && CV_ARE_TYPES_EQ(a,d) );
- assert( CV_MAT_CN(a->type) <= 2 );
-
- if( flags & CV_TS_GEMM_A_T )
- {
- CV_SWAP( a_rows, a_cols, i );
- CV_SWAP( a_step, a_delta, i );
- }
-
- if( flags & CV_TS_GEMM_B_T )
- {
- CV_SWAP( b_rows, b_cols, i );
- CV_SWAP( b_step, b_delta, i );
- }
-
- if( flags & CV_TS_GEMM_C_T )
- {
- CV_SWAP( c_rows, c_cols, i );
- CV_SWAP( c_step, c_delta, i );
- }
-
- assert( a_rows == d_rows && a_cols == b_rows && b_cols == d_cols );
- assert( a->data.ptr != d->data.ptr && b->data.ptr != d->data.ptr );
-
- if( c )
- {
- assert( CV_ARE_TYPES_EQ(a,c) && c_rows == d_rows && c_cols == d_cols );
- assert( c->data.ptr != d->data.ptr || (flags & CV_TS_GEMM_C_T) == 0 );
- }
-
- if( CV_MAT_DEPTH(a->type) == CV_32F )
- {
- float* a_data0 = a->data.fl;
- float* b_data0 = b->data.fl;
- float* c_data0 = c ? c->data.fl : 0;
- float* d_data = d->data.fl;
-
- for( i = 0; i < d_rows; i++, d_data += d_step, c_data0 += c_step, a_data0 += a_step )
- {
- for( j = 0; j < d_cols; j++ )
- {
- float* a_data = a_data0;
- float* b_data = b_data0 + j*b_delta;
- float* c_data = c_data0 + j*c_delta;
-
- if( cn == 1 )
- {
- double s = 0;
- for( k = 0; k < a_cols; k++ )
- {
- s += ((double)a_data[0])*b_data[0];
- a_data += a_delta;
- b_data += b_step;
- }
- d_data[j] = (float)(s*alpha + (c_data ? c_data[0]*beta : 0));
- }
- else
- {
- double s_re = 0, s_im = 0;
-
- for( k = 0; k < a_cols; k++ )
- {
- s_re += ((double)a_data[0])*b_data[0] - ((double)a_data[1])*b_data[1];
- s_im += ((double)a_data[0])*b_data[1] + ((double)a_data[1])*b_data[0];
- a_data += a_delta;
- b_data += b_step;
- }
-
- s_re *= alpha;
- s_im *= alpha;
-
- if( c_data )
- {
- s_re += c_data[0]*beta;
- s_im += c_data[1]*beta;
- }
-
- d_data[j*2] = (float)s_re;
- d_data[j*2+1] = (float)s_im;
- }
- }
- }
- }
- else if( CV_MAT_DEPTH(a->type) == CV_64F )
- {
- double* a_data0 = a->data.db;
- double* b_data0 = b->data.db;
- double* c_data0 = c ? c->data.db : 0;
- double* d_data = d->data.db;
-
- for( i = 0; i < d_rows; i++, d_data += d_step, c_data0 += c_step, a_data0 += a_step )
- {
- for( j = 0; j < d_cols; j++ )
- {
- double* a_data = a_data0;
- double* b_data = b_data0 + j*b_delta;
- double* c_data = c_data0 + j*c_delta;
-
- if( cn == 1 )
- {
- double s = 0;
- for( k = 0; k < a_cols; k++ )
- {
- s += a_data[0]*b_data[0];
- a_data += a_delta;
- b_data += b_step;
- }
- d_data[j] = s*alpha + (c_data ? c_data[0]*beta : 0);
- }
- else
- {
- double s_re = 0, s_im = 0;
-
- for( k = 0; k < a_cols; k++ )
- {
- s_re += a_data[0]*b_data[0] - a_data[1]*b_data[1];
- s_im += a_data[0]*b_data[1] + a_data[1]*b_data[0];
- a_data += a_delta;
- b_data += b_step;
- }
- s_re *= alpha;
- s_im *= alpha;
-
- if( c_data )
- {
- s_re += c_data[0]*beta;
- s_im += c_data[1]*beta;
- }
-
- d_data[j*2] = s_re;
- d_data[j*2+1] = s_im;
- }
- }
- }
- }
- else
- {
- assert(0);
- }
-}
-
-
-CvMat* cvTsSelect( const CvMat* a, CvMat* header, CvRect rect )
-{
- CvMat h;
- int el_size;
-
- h = cvMat( rect.height, rect.width, a->type );
- el_size = CV_ELEM_SIZE(a->type);
-
- h.data.ptr = a->data.ptr + rect.y*a->step + rect.x*el_size;
- h.step = rect.height > 1 ? a->step : 0;
- h.type &= ~CV_MAT_CONT_FLAG;
- if( rect.height == 1 || h.step == h.cols*el_size )
- h.type |= CV_MAT_CONT_FLAG;
- *header = h;
- return header;
-}
-
-
-double cvTsMinVal( int type )
-{
- switch( CV_MAT_DEPTH(type) )
- {
- case CV_8U:
- return 0;
- case CV_8S:
- return -128;
- case CV_16U:
- return 0;
- case CV_16S:
- return -32768;
- case CV_32S:
- return -1000000;
- case CV_32F:
- return -1000.;
- case CV_64F:
- return -1000.;
- }
- return log(-1.);
-}
-
-
-double cvTsMaxVal( int type )
-{
- switch( CV_MAT_DEPTH(type) )
- {
- case CV_8U:
- return 256;
- case CV_8S:
- return 128;
- case CV_16U:
- return 65536;
- case CV_16S:
- return 32768;
- case CV_32S:
- return 1000000;
- case CV_32F:
- return 1000.;
- case CV_64F:
- return 1000.;
- }
- return log(-1.);
-}
-
-
-void cvTsPrepareToFilter( const CvMat* a, CvMat* b, CvPoint ofs,
- int border_mode, CvScalar fill_val )
-{
- int i, j, dir;
- CvMat temp, temp2;
-
- assert( 0 <= ofs.x && ofs.x <= b->cols - a->cols &&
- 0 <= ofs.y && ofs.y <= b->rows - a->rows );
-
- cvTsSelect( b, &temp, cvRect( ofs.x, ofs.y, a->cols, a->rows ));
- cvTsCopy( a, &temp, 0 );
-
- assert( border_mode == CV_TS_BORDER_FILL ||
- border_mode == CV_TS_BORDER_REPLICATE ||
- border_mode == CV_TS_BORDER_REFLECT );
-
- if( ofs.y > 0 )
- {
- if( border_mode == CV_TS_BORDER_FILL )
- {
- cvTsSelect( b, &temp, cvRect( ofs.x, 0, a->cols, ofs.y ));
- cvTsAdd( 0, cvScalar(0), 0, cvScalar(0), fill_val, &temp, 0 );
- }
- else if( border_mode == CV_TS_BORDER_REPLICATE || a->rows == 1 )
- {
- cvTsSelect( b, &temp, cvRect( ofs.x, ofs.y, a->cols, 1 ));
- for( i = ofs.y-1; i >= 0; i-- )
- {
- cvTsSelect( b, &temp2, cvRect( ofs.x, i, a->cols, 1 ));
- cvTsCopy( &temp, &temp2, 0 );
- }
- }
- else if( border_mode == CV_TS_BORDER_REFLECT )
- {
- j = 1; dir = 1;
- for( i = ofs.y-1; i >= 0; i-- )
- {
- cvTsSelect( b, &temp, cvRect( ofs.x, ofs.y+j, a->cols, 1 ));
- cvTsSelect( b, &temp2, cvRect( ofs.x, i, a->cols, 1 ));
- cvTsCopy( &temp, &temp2, 0 );
- if( (unsigned)(j + dir) >= (unsigned)a->rows )
- dir = -dir;
- j += dir;
- }
- }
- }
-
- ofs.y += a->rows;
- if( ofs.y < b->rows )
- {
- if( border_mode == CV_TS_BORDER_FILL )
- {
- cvTsSelect( b, &temp, cvRect( ofs.x, ofs.y, a->cols, b->rows - ofs.y ));
- cvTsAdd( 0, cvScalar(0), 0, cvScalar(0), fill_val, &temp, 0 );
- }
- else if( border_mode == CV_TS_BORDER_REPLICATE || a->rows == 1 )
- {
- cvTsSelect( b, &temp, cvRect( ofs.x, ofs.y - 1, a->cols, 1 ));
- for( i = ofs.y; i < b->rows; i++ )
- {
- cvTsSelect( b, &temp2, cvRect( ofs.x, i, a->cols, 1 ));
- cvTsCopy( &temp, &temp2, 0 );
- }
- }
- else
- {
- j = a->rows - 2; dir = -1;
- for( i = ofs.y; i < b->rows; i++ )
- {
- cvTsSelect( b, &temp, cvRect( ofs.x, ofs.y-a->rows+j, a->cols, 1 ));
- cvTsSelect( b, &temp2, cvRect( ofs.x, i, a->cols, 1 ));
- cvTsCopy( &temp, &temp2, 0 );
- if( (unsigned)(j + dir) >= (unsigned)a->rows )
- dir = -dir;
- j += dir;
- }
- }
- }
-
- if( ofs.x > 0 )
- {
- if( border_mode == CV_TS_BORDER_FILL )
- {
- cvTsSelect( b, &temp, cvRect( 0, 0, ofs.x, b->rows ));
- cvTsAdd( 0, cvScalar(0), 0, cvScalar(0), fill_val, &temp, 0 );
- }
- else if( border_mode == CV_TS_BORDER_REPLICATE || a->cols == 1 )
- {
- cvTsSelect( b, &temp, cvRect( ofs.x, 0, 1, b->rows ));
- for( i = ofs.x-1; i >= 0; i-- )
- {
- cvTsSelect( b, &temp2, cvRect( i, 0, 1, b->rows ));
- cvTsCopy( &temp, &temp2, 0 );
- }
- }
- else if( border_mode == CV_TS_BORDER_REFLECT )
- {
- j = 1; dir = 1;
- for( i = ofs.x-1; i >= 0; i-- )
- {
- cvTsSelect( b, &temp, cvRect( ofs.x+j, 0, 1, b->rows ));
- cvTsSelect( b, &temp2, cvRect( i, 0, 1, b->rows ));
- cvTsCopy( &temp, &temp2, 0 );
- if( (unsigned)(j + dir) >= (unsigned)a->cols )
- dir = -dir;
- j += dir;
- }
- }
- }
-
- ofs.x += a->cols;
- if( ofs.x < b->cols )
- {
- if( border_mode == CV_TS_BORDER_FILL )
- {
- cvTsSelect( b, &temp, cvRect( ofs.x, 0, b->cols - ofs.x, b->rows ));
- cvTsAdd( 0, cvScalar(0), 0, cvScalar(0), fill_val, &temp, 0 );
- }
- else if( border_mode == CV_TS_BORDER_REPLICATE || a->cols == 1 )
- {
- cvTsSelect( b, &temp, cvRect( ofs.x-1, 0, 1, b->rows ));
- for( i = ofs.x; i < b->cols; i++ )
- {
- cvTsSelect( b, &temp2, cvRect( i, 0, 1, b->rows ));
- cvTsCopy( &temp, &temp2, 0 );
- }
- }
- else if( border_mode == CV_TS_BORDER_REFLECT )
- {
- j = a->cols - 2; dir = -1;
- for( i = ofs.x; i < b->cols; i++ )
- {
- cvTsSelect( b, &temp, cvRect( ofs.x-a->cols+j, 0, 1, b->rows ));
- cvTsSelect( b, &temp2, cvRect( i, 0, 1, b->rows ));
- cvTsCopy( &temp, &temp2, 0 );
- if( (unsigned)(j + dir) >= (unsigned)a->cols )
- dir = -dir;
- j += dir;
- }
- }
- }
-}
-
-
-void cvTsConvolve2D( const CvMat* a, CvMat* b, const CvMat* kernel, CvPoint anchor )
-{
- int i, j, k;
- int cn, ncols, a_step;
- int ker_size = kernel->rows*kernel->cols;
- int* offset = (int*)malloc( ker_size*sizeof(offset[0]));
- float* k_data = (float*)malloc( ker_size*sizeof(k_data[0]));
- int all_same = 1;
- float first = kernel->data.fl[0];
- uchar *a_data, *b_data;
-
- cn = CV_MAT_CN(a->type);
- ncols = b->cols*cn;
- a_step = a->step / CV_ELEM_SIZE(a->type & ~CV_MAT_CN_MASK);
-
- assert( a->cols == b->cols + kernel->cols - 1 &&
- a->rows == b->rows + kernel->rows - 1 && CV_ARE_TYPES_EQ( a, b ) );
- assert( CV_MAT_TYPE(kernel->type) == CV_32FC1 );
- assert( 0 <= anchor.x && anchor.x < kernel->cols &&
- 0 <= anchor.y && anchor.y < kernel->rows );
-
- for( i = 0, k = 0; i < kernel->rows; i++ )
- for( j = 0; j < kernel->cols; j++ )
- {
- float f = ((float*)(kernel->data.ptr + kernel->step*i))[j];
- if( f )
- {
- k_data[k] = f;
- offset[k++] = (i - anchor.y)*a_step + (j - anchor.x)*cn;
- }
- if( f != first )
- all_same = 0;
- }
-
- ker_size = k;
- a_data = a->data.ptr + a->step*anchor.y + CV_ELEM_SIZE(a->type)*anchor.x;
- b_data = b->data.ptr;
-
- for( i = 0; i < b->rows; i++, a_data += a->step, b_data += b->step )
- {
- switch( CV_MAT_DEPTH(a->type) )
- {
- case CV_8U:
- for( j = 0; j < ncols; j++ )
- {
- double s = 0;
- int val;
- for( k = 0; k < ker_size; k++ )
- s += ((uchar*)a_data)[j+offset[k]]*k_data[k];
- val = cvRound(s);
- ((uchar*)b_data)[j] = CV_CAST_8U(val);
- }
- break;
- case CV_8S:
- for( j = 0; j < ncols; j++ )
- {
- double s = 0;
- int val;
- for( k = 0; k < ker_size; k++ )
- s += ((schar*)a_data)[j+offset[k]]*k_data[k];
- val = cvRound(s);
- ((schar*)b_data)[j] = CV_CAST_8S(val);
- }
- break;
- case CV_16U:
- for( j = 0; j < ncols; j++ )
- {
- double s = 0;
- int val;
- for( k = 0; k < ker_size; k++ )
- s += ((ushort*)a_data)[j+offset[k]]*k_data[k];
- val = cvRound(s);
- ((ushort*)b_data)[j] = CV_CAST_16U(val);
- }
- break;
- case CV_16S:
- for( j = 0; j < ncols; j++ )
- {
- double s = 0;
- int val;
- for( k = 0; k < ker_size; k++ )
- s += ((short*)a_data)[j+offset[k]]*k_data[k];
- val = cvRound(s);
- ((short*)b_data)[j] = CV_CAST_16S(val);
- }
- break;
- case CV_32S:
- for( j = 0; j < ncols; j++ )
- {
- double s = 0;
- for( k = 0; k < ker_size; k++ )
- s += ((int*)a_data)[j+offset[k]]*k_data[k];
- ((int*)b_data)[j] = cvRound(s);
- }
- break;
- case CV_32F:
- if( !all_same )
- {
- for( j = 0; j < ncols; j++ )
- {
- double s = 0;
- for( k = 0; k < ker_size; k++ )
- s += (double)((float*)a_data)[j+offset[k]]*k_data[k];
- ((float*)b_data)[j] = (float)s;
- }
- }
- else
- {
- // special branch to speedup feature selection and blur tests
- for( j = 0; j < ncols; j++ )
- {
- double s = 0;
- for( k = 0; k < ker_size; k++ )
- s += (double)((float*)a_data)[j+offset[k]];
- ((float*)b_data)[j] = (float)(s*first);
- }
- }
- break;
- case CV_64F:
- for( j = 0; j < ncols; j++ )
- {
- double s = 0;
- for( k = 0; k < ker_size; k++ )
- s += ((double*)a_data)[j+offset[k]]*k_data[k];
- ((double*)b_data)[j] = (double)s;
- }
- break;
- default:
- assert(0);
- }
- }
-
- free( offset );
- free( k_data );
-}
-
-
-void cvTsMinMaxFilter( const CvMat* a, CvMat* b, const IplConvKernel* kernel, int op_type )
-{
- int i, j, k;
- int cn, ncols, a_step;
- int ker_size = kernel->nRows*kernel->nCols;
- int* offset = (int*)malloc( ker_size*sizeof(offset[0]));
- int calc_max = op_type != 0;
- uchar *a_data, *b_data;
-
- cn = CV_MAT_CN(a->type);
- ncols = b->cols*cn;
- a_step = a->step / CV_ELEM_SIZE(a->type & ~CV_MAT_CN_MASK);
-
- assert( a->cols == b->cols + kernel->nCols - 1 &&
- a->rows == b->rows + kernel->nRows - 1 && CV_ARE_TYPES_EQ( a, b ) );
- assert( 0 <= kernel->anchorX && kernel->anchorX < kernel->nCols &&
- 0 <= kernel->anchorY && kernel->anchorY < kernel->nRows );
-
- for( i = 0, k = 0; i < kernel->nRows; i++ )
- for( j = 0; j < kernel->nCols; j++ )
- {
- if( !kernel->values || kernel->values[i*kernel->nCols + j] )
- offset[k++] = (i - kernel->anchorY)*a_step + (j - kernel->anchorX)*cn;
- }
-
- if( k == 0 )
- offset[k++] = 0;
-
- ker_size = k;
-
- a_data = a->data.ptr + kernel->anchorY*a->step + kernel->anchorX*CV_ELEM_SIZE(a->type);
- b_data = b->data.ptr;
-
- for( i = 0; i < b->rows; i++, a_data += a->step, b_data += b->step )
- {
- switch( CV_MAT_DEPTH(a->type) )
- {
- case CV_8U:
- for( j = 0; j < ncols; j++ )
- {
- int m = ((uchar*)a_data)[j+offset[0]];
- for( k = 1; k < ker_size; k++ )
- {
- int v = ((uchar*)a_data)[j+offset[k]];
- if( calc_max )
- {
- if( m < v )
- m = v;
- }
- else if( m > v )
- m = v;
- }
- ((uchar*)b_data)[j] = (uchar)m;
- }
- break;
- case CV_16U:
- for( j = 0; j < ncols; j++ )
- {
- int m = ((ushort*)a_data)[j+offset[0]];
- for( k = 1; k < ker_size; k++ )
- {
- int v = ((ushort*)a_data)[j+offset[k]];
- if( calc_max )
- {
- if( m < v )
- m = v;
- }
- else if( m > v )
- m = v;
- }
- ((ushort*)b_data)[j] = (ushort)m;
- }
- break;
- case CV_16S:
- for( j = 0; j < ncols; j++ )
- {
- int m = ((short*)a_data)[j+offset[0]];
- for( k = 1; k < ker_size; k++ )
- {
- int v = ((short*)a_data)[j+offset[k]];
- if( calc_max )
- {
- if( m < v )
- m = v;
- }
- else if( m > v )
- m = v;
- }
- ((short*)b_data)[j] = (short)m;
- }
- break;
- case CV_32S:
- for( j = 0; j < ncols; j++ )
- {
- int m = ((int*)a_data)[j+offset[0]];
- for( k = 1; k < ker_size; k++ )
- {
- int v = ((int*)a_data)[j+offset[k]];
- if( calc_max )
- {
- if( m < v )
- m = v;
- }
- else if( m > v )
- m = v;
- }
- ((int*)b_data)[j] = m;
- }
- break;
- case CV_32F:
- for( j = 0; j < ncols; j++ )
- {
- float m = ((float*)a_data)[j+offset[0]];
- for( k = 1; k < ker_size; k++ )
- {
- float v = ((float*)a_data)[j+offset[k]];
- if( calc_max )
- {
- if( m < v )
- m = v;
- }
- else if( m > v )
- m = v;
- }
- ((float*)b_data)[j] = (float)m;
- }
- break;
- case CV_64F:
- for( j = 0; j < ncols; j++ )
- {
- double m = ((double*)a_data)[j+offset[0]];
- for( k = 1; k < ker_size; k++ )
- {
- double v = ((double*)a_data)[j+offset[k]];
- if( calc_max )
- {
- if( m < v )
- m = v;
- }
- else if( m > v )
- m = v;
- }
- ((double*)b_data)[j] = (double)m;
- }
- break;
- default:
- assert(0);
- }
- }
-
- free( offset );
-}
-
-
-double cvTsCrossCorr( const CvMat* a, const CvMat* b )
-{
- int i, j;
- int cn, ncols;
- double s = 0;
-
- cn = CV_MAT_CN(a->type);
- ncols = a->cols*cn;
-
- assert( CV_ARE_SIZES_EQ( a, b ) && CV_ARE_TYPES_EQ( a, b ) );
- for( i = 0; i < a->rows; i++ )
- {
- uchar* a_data = a->data.ptr + a->step*i;
- uchar* b_data = b->data.ptr + b->step*i;
-
- switch( CV_MAT_DEPTH(a->type) )
- {
- case CV_8U:
- for( j = 0; j < ncols; j++ )
- s += ((uchar*)a_data)[j]*((uchar*)b_data)[j];
- break;
- case CV_8S:
- for( j = 0; j < ncols; j++ )
- s += ((schar*)a_data)[j]*((schar*)b_data)[j];
- break;
- case CV_16U:
- for( j = 0; j < ncols; j++ )
- s += (double)((ushort*)a_data)[j]*((ushort*)b_data)[j];
- break;
- case CV_16S:
- for( j = 0; j < ncols; j++ )
- s += ((short*)a_data)[j]*((short*)b_data)[j];
- break;
- case CV_32S:
- for( j = 0; j < ncols; j++ )
- s += ((double)((int*)a_data)[j])*((int*)b_data)[j];
- break;
- case CV_32F:
- for( j = 0; j < ncols; j++ )
- s += ((double)((float*)a_data)[j])*((float*)b_data)[j];
- break;
- case CV_64F:
- for( j = 0; j < ncols; j++ )
- s += ((double*)a_data)[j]*((double*)b_data)[j];
- break;
- default:
- assert(0);
- return log(-1.);
- }
- }
-
- return s;
-}
-
-
-void cvTsTransform( const CvMat* a, CvMat* b, const CvMat* transmat, const CvMat* shift )
-{
- int i, j, k, cols, dst_cols;
- int cn, dst_cn, depth, mat_depth, shiftstep;
- double mat[20], *buf, *dst_buf;
-
- cn = CV_MAT_CN(a->type);
- dst_cn = CV_MAT_CN(b->type);
- depth = CV_MAT_DEPTH(a->type);
- mat_depth = CV_MAT_DEPTH(transmat->type);
- cols = transmat->cols;
-
- // prepare cn x (cn + 1) transform matrix
- if( mat_depth == CV_32F )
- {
- shiftstep = shift && shift->rows > 1 ? shift->step/sizeof(float) : 1;
- for( i = 0; i < transmat->rows; i++ )
- {
- mat[i*(cn+1) + cn] = 0.;
- for( j = 0; j < cols; j++ )
- mat[i*(cn+1) + j] = ((float*)(transmat->data.ptr + transmat->step*i))[j];
- if( shift )
- mat[i*(cn+1) + cn] = shift->data.fl[i*shiftstep];
- }
- }
- else
- {
- assert( mat_depth == CV_64F );
-
- shiftstep = shift && shift->rows > 1 ? shift->step/sizeof(double) : 1;
- for( i = 0; i < transmat->rows; i++ )
- {
- mat[i*(cn+1) + cn] = 0.;
- for( j = 0; j < cols; j++ )
- mat[i*(cn+1) + j] = ((double*)(transmat->data.ptr + transmat->step*i))[j];
- if( shift )
- mat[i*(cn+1) + cn] = shift->data.db[i*shiftstep];
- }
- }
-
- // transform data
- cols = a->cols * cn;
- dst_cols = a->cols * dst_cn;
- buf = (double*)cvStackAlloc( cols * sizeof(double) );
- dst_buf = (double*)cvStackAlloc( dst_cols * sizeof(double) );
-
- for( i = 0; i < a->rows; i++ )
- {
- uchar* src = a->data.ptr + i*a->step;
- uchar* dst = b->data.ptr + i*b->step;
- double* _dst = dst_buf;
-
- switch( depth )
- {
- case CV_8U:
- for( j = 0; j < cols; j++ )
- buf[j] = ((uchar*)src)[j];
- break;
- case CV_16U:
- for( j = 0; j < cols; j++ )
- buf[j] = ((ushort*)src)[j];
- break;
- case CV_16S:
- for( j = 0; j < cols; j++ )
- buf[j] = ((short*)src)[j];
- break;
- case CV_32S:
- for( j = 0; j < cols; j++ )
- buf[j] = ((int*)src)[j];
- break;
- case CV_32F:
- for( j = 0; j < cols; j++ )
- buf[j] = ((float*)src)[j];
- break;
- case CV_64F:
- for( j = 0; j < cols; j++ )
- buf[j] = ((double*)src)[j];
- break;
- default:
- assert(0);
- }
-
- switch( cn )
- {
- case 1:
- for( j = 0; j < cols; j++, _dst += dst_cn )
- for( k = 0; k < dst_cn; k++ )
- _dst[k] = buf[j]*mat[2*k] + mat[2*k+1];
- break;
- case 2:
- for( j = 0; j < cols; j += 2, _dst += dst_cn )
- for( k = 0; k < dst_cn; k++ )
- _dst[k] = buf[j]*mat[3*k] + buf[j+1]*mat[3*k+1] + mat[3*k+2];
- break;
- case 3:
- for( j = 0; j < cols; j += 3, _dst += dst_cn )
- for( k = 0; k < dst_cn; k++ )
- _dst[k] = buf[j]*mat[4*k] + buf[j+1]*mat[4*k+1] +
- buf[j+2]*mat[4*k+2] + mat[4*k+3];
- break;
- case 4:
- for( j = 0; j < cols; j += 4, _dst += dst_cn )
- for( k = 0; k < dst_cn; k++ )
- _dst[k] = buf[j]*mat[5*k] + buf[j+1]*mat[5*k+1] +
- buf[j+2]*mat[5*k+2] + buf[j+3]*mat[5*k+3] + mat[5*k+4];
- break;
- default:
- assert(0);
- }
-
- switch( depth )
- {
- case CV_8U:
- for( j = 0; j < dst_cols; j++ )
- {
- int val = cvRound(dst_buf[j]);
- ((uchar*)dst)[j] = CV_CAST_8U(val);
- }
- break;
- case CV_16U:
- for( j = 0; j < dst_cols; j++ )
- {
- int val = cvRound(dst_buf[j]);
- ((ushort*)dst)[j] = CV_CAST_16U(val);
- }
- break;
- case CV_16S:
- for( j = 0; j < dst_cols; j++ )
- {
- int val = cvRound(dst_buf[j]);
- ((short*)dst)[j] = CV_CAST_16S(val);
- }
- break;
- case CV_32S:
- for( j = 0; j < dst_cols; j++ )
- ((int*)dst)[j] = cvRound(dst_buf[j]);
- break;
- case CV_32F:
- for( j = 0; j < dst_cols; j++ )
- ((float*)dst)[j] = (float)dst_buf[j];
- break;
- case CV_64F:
- for( j = 0; j < dst_cols; j++ )
- ((double*)dst)[j] = dst_buf[j];
- break;
- default:
- assert(0);
- }
- }
-}
-
-
-CvMat* cvTsTranspose( const CvMat* a, CvMat* b )
-{
- int i, j, k, rows, cols, elem_size;
- uchar *a_data, *b_data;
- int a_step, b_step;
-
- elem_size = CV_ELEM_SIZE(a->type);
- rows = a->rows;
- cols = a->cols;
-
- assert( a->rows == b->cols && a->cols == b->rows && CV_ARE_TYPES_EQ(a,b) );
- a_data = a->data.ptr;
- a_step = a->step;
- b_data = b->data.ptr;
- b_step = b->step;
-
- if( rows == cols )
- {
- for( i = 0; i < rows; i++ )
- {
- for( j = 0; j <= i; j++ )
- {
- uchar* a_ij = a_data + a_step*i + elem_size*j;
- uchar* a_ji = a_data + a_step*j + elem_size*i;
- uchar* b_ij = b_data + b_step*i + elem_size*j;
- uchar* b_ji = b_data + b_step*j + elem_size*i;
- for( k = 0; k < elem_size; k++ )
- {
- uchar t0 = a_ij[k];
- uchar t1 = a_ji[k];
- b_ji[k] = t0;
- b_ij[k] = t1;
- }
- }
- }
- }
- else
- {
- for( i = 0; i < cols; i++ )
- {
- for( j = 0; j < rows; j++ )
- {
- uchar* a_ji = a_data + a_step*j + elem_size*i;
- uchar* b_ij = b_data + b_step*i + elem_size*j;
- for( k = 0; k < elem_size; k++ )
- b_ij[k] = a_ji[k];
- }
- }
- }
-
- return b;
-}
-
-
-void cvTsFlip( const CvMat* a, CvMat* b, int flip_type )
-{
- int i, j, k, rows, cols, elem_size;
- uchar *a_data, *b_data;
- int a_step, b_step;
-
- elem_size = CV_ELEM_SIZE(a->type);
- rows = a->rows;
- cols = a->cols*elem_size;
-
- assert( CV_ARE_SIZES_EQ(a,b) && CV_ARE_TYPES_EQ(a,b) && a->data.ptr != b->data.ptr );
- a_data = a->data.ptr;
- a_step = a->step;
- b_data = b->data.ptr;
- b_step = b->step;
-
- if( flip_type <= 0 )
- {
- a_data += a_step*(rows-1);
- a_step = -a_step;
- }
-
- for( i = 0; i < rows; i++ )
- {
- if( flip_type == 0 )
- memcpy( b_data, a_data, cols );
- else
- {
- for( j = 0; j < cols; j += elem_size )
- for( k = 0; k < elem_size; k++ )
- b_data[j+k] = a_data[cols - elem_size - j + k];
- }
- a_data += a_step;
- b_data += b_step;
- }
-}
-
-
-void cvTsPatchZeros( CvMat* mat, double level )
-{
- int i, j, ncols = mat->cols * CV_MAT_CN(mat->type);
-
- for( i = 0; i < mat->rows; i++ )
- {
- switch( CV_MAT_DEPTH(mat->type) )
- {
- case CV_32F:
- {
- float* data = (float*)(mat->data.ptr + i*mat->step);
- for( j = 0; j < ncols; j++ )
- if( fabs(data[j]) < level )
- data[j] += 1;
- }
- break;
- case CV_64F:
- {
- double* data = (double*)(mat->data.ptr + i*mat->step);
- for( j = 0; j < ncols; j++ )
- if( fabs(data[j]) < level )
- data[j] += 1;
- }
- break;
- default:
- assert(0);
- return;
- }
- }
-}
-
-
-/* End of file. */
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "_cxts.h"
-
-/* End of file. */
+++ /dev/null
-# ----------------------------------------------------------------------------
-# CMake file for cxcoretest. See root CMakeLists.txt
-#
-# ----------------------------------------------------------------------------
-project(opencv_test_ml)
-
-file(GLOB test_srcs "src/*.cpp")
-source_group("Src" FILES ${test_srcs})
-file(GLOB test_hdrs "src/*.h*")
-source_group("Include" FILES ${test_hdrs})
-
-if(WIN32 AND MSVC)
- set(pch_header "mltest.h")
- set(pch_src "precomp.cpp")
- list(REMOVE_ITEM test_srcs ${CMAKE_CURRENT_SOURCE_DIR}/src/${pch_src})
- set(test_srcs ${CMAKE_CURRENT_SOURCE_DIR}/src/${pch_src} ${test_srcs})
- foreach(src_file ${test_srcs})
- if(${src_file} MATCHES ${pch_src})
- set_source_files_properties(
- ${src_file}
- PROPERTIES
- COMPILE_FLAGS "/Yc${pch_header}"
- )
- else()
- set_source_files_properties(
- ${src_file}
- PROPERTIES
- COMPILE_FLAGS "/Yu${pch_header}"
- )
- endif()
- endforeach()
-endif()
-
-include_directories(../cxts
- "${CMAKE_SOURCE_DIR}/include/opencv"
- "${CMAKE_SOURCE_DIR}/modules/core/include"
- "${CMAKE_SOURCE_DIR}/modules/ml/include"
- )
-
-set(the_target "opencv_test_ml")
-
-add_executable(${the_target} ${test_srcs} ${test_hdrs})
-
-# Additional target properties
-set_target_properties(${the_target} PROPERTIES
- DEBUG_POSTFIX "${OPENCV_DEBUG_POSTFIX}"
- RUNTIME_OUTPUT_DIRECTORY "${CMAKE_BINARY_DIR}/bin/"
- )
-
-
-add_dependencies(${the_target} opencv_ts opencv_core opencv_ml)
-
-# Add the required libraries for linking:
-target_link_libraries(${the_target} ${OPENCV_LINKER_LIBS} opencv_ts opencv_core opencv_ml)
-
-enable_testing()
-get_target_property(LOC ${the_target} LOCATION)
-add_test(${the_target} "${LOC}")
-
-if(WIN32)
-install(TARGETS ${the_target} RUNTIME DESTINATION bin COMPONENT main)
-endif()
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "mltest.h"
-
-using namespace std;
-using namespace cv;
-
-void defaultDistribs( vector<Mat>& means, vector<Mat>& covs )
-{
- float mp0[] = {0.0f, 0.0f}, cp0[] = {0.67f, 0.0f, 0.0f, 0.67f};
- float mp1[] = {5.0f, 0.0f}, cp1[] = {1.0f, 0.0f, 0.0f, 1.0f};
- float mp2[] = {1.0f, 5.0f}, cp2[] = {1.0f, 0.0f, 0.0f, 1.0f};
- Mat m0( 1, 2, CV_32FC1, mp0 ), c0( 2, 2, CV_32FC1, cp0 );
- Mat m1( 1, 2, CV_32FC1, mp1 ), c1( 2, 2, CV_32FC1, cp1 );
- Mat m2( 1, 2, CV_32FC1, mp2 ), c2( 2, 2, CV_32FC1, cp2 );
- means.resize(3), covs.resize(3);
- m0.copyTo(means[0]), c0.copyTo(covs[0]);
- m1.copyTo(means[1]), c1.copyTo(covs[1]);
- m2.copyTo(means[2]), c2.copyTo(covs[2]);
-}
-
-// generate points sets by normal distributions
-void generateData( Mat& data, Mat& labels, const vector<int>& sizes, const vector<Mat>& means, const vector<Mat>& covs, int labelType )
-{
- vector<int>::const_iterator sit = sizes.begin();
- int total = 0;
- for( ; sit != sizes.end(); ++sit )
- total += *sit;
- assert( means.size() == sizes.size() && covs.size() == sizes.size() );
- assert( !data.empty() && data.rows == total );
- assert( data.type() == CV_32FC1 );
-
- labels.create( data.rows, 1, labelType );
-
- randn( data, Scalar::all(0.0), Scalar::all(1.0) );
- vector<Mat>::const_iterator mit = means.begin(), cit = covs.begin();
- int bi, ei = 0;
- sit = sizes.begin();
- for( int p = 0, l = 0; sit != sizes.end(); ++sit, ++mit, ++cit, l++ )
- {
- bi = ei;
- ei = bi + *sit;
- assert( mit->rows == 1 && mit->cols == data.cols );
- assert( cit->rows == data.cols && cit->cols == data.cols );
- for( int i = bi; i < ei; i++, p++ )
- {
- Mat r(1, data.cols, CV_32FC1, data.ptr<float>(i));
- r = r * (*cit) + *mit;
- if( labelType == CV_32FC1 )
- labels.at<float>(p, 0) = (float)l;
- else
- labels.at<int>(p, 0) = l;
- }
- }
-}
-
-int maxIdx( const vector<int>& count )
-{
- int idx = -1;
- int maxVal = -1;
- vector<int>::const_iterator it = count.begin();
- for( int i = 0; it != count.end(); ++it, i++ )
- {
- if( *it > maxVal)
- {
- maxVal = *it;
- idx = i;
- }
- }
- assert( idx >= 0);
- return idx;
-}
-
-bool getLabelsMap( const Mat& labels, const vector<int>& sizes, vector<int>& labelsMap )
-{
- int total = 0, setCount = (int)sizes.size();
- vector<int>::const_iterator sit = sizes.begin();
- for( ; sit != sizes.end(); ++sit )
- total += *sit;
- assert( !labels.empty() );
- assert( labels.rows == total && labels.cols == 1 );
- assert( labels.type() == CV_32SC1 || labels.type() == CV_32FC1 );
-
- bool isFlt = labels.type() == CV_32FC1;
- labelsMap.resize(setCount);
- vector<int>::iterator lmit = labelsMap.begin();
- vector<bool> buzy(setCount, false);
- int bi, ei = 0;
- for( sit = sizes.begin(); sit != sizes.end(); ++sit, ++lmit )
- {
- vector<int> count( setCount, 0 );
- bi = ei;
- ei = bi + *sit;
- if( isFlt )
- {
- for( int i = bi; i < ei; i++ )
- count[(int)labels.at<float>(i, 0)]++;
- }
- else
- {
- for( int i = bi; i < ei; i++ )
- count[labels.at<int>(i, 0)]++;
- }
-
- *lmit = maxIdx( count );
- if( buzy[*lmit] )
- return false;
- buzy[*lmit] = true;
- }
- return true;
-}
-
-float calcErr( const Mat& labels, const Mat& origLabels, const vector<int>& sizes, bool labelsEquivalent = true )
-{
- int err = 0;
- assert( !labels.empty() && !origLabels.empty() );
- assert( labels.cols == 1 && origLabels.cols == 1 );
- assert( labels.rows == origLabels.rows );
- assert( labels.type() == origLabels.type() );
- assert( labels.type() == CV_32SC1 || labels.type() == CV_32FC1 );
-
- vector<int> labelsMap;
- bool isFlt = labels.type() == CV_32FC1;
- if( !labelsEquivalent )
- {
- getLabelsMap( labels, sizes, labelsMap );
- for( int i = 0; i < labels.rows; i++ )
- if( isFlt )
- err += labels.at<float>(i, 0) != labelsMap[(int)origLabels.at<float>(i, 0)];
- else
- err += labels.at<int>(i, 0) != labelsMap[origLabels.at<int>(i, 0)];
- }
- else
- {
- for( int i = 0; i < labels.rows; i++ )
- if( isFlt )
- err += labels.at<float>(i, 0) != origLabels.at<float>(i, 0);
- else
- err += labels.at<int>(i, 0) != origLabels.at<int>(i, 0);
- }
- return (float)err / (float)labels.rows;
-}
-
-//--------------------------------------------------------------------------------------------
-class CV_KMeansTest : public CvTest {
-public:
- CV_KMeansTest() : CvTest( "kmeans", "kmeans" ) {}
-protected:
- virtual void run( int start_from );
-};
-
-void CV_KMeansTest::run( int /*start_from*/ )
-{
- const int iters = 100;
- int sizesArr[] = { 5000, 7000, 8000 };
- int pointsCount = sizesArr[0]+ sizesArr[1] + sizesArr[2];
-
- Mat data( pointsCount, 2, CV_32FC1 ), labels;
- vector<int> sizes( sizesArr, sizesArr + sizeof(sizesArr) / sizeof(sizesArr[0]) );
- vector<Mat> means, covs;
- defaultDistribs( means, covs );
- generateData( data, labels, sizes, means, covs, CV_32SC1 );
-
- int code = CvTS::OK;
- Mat bestLabels;
- // 1. flag==KMEANS_PP_CENTERS
- kmeans( data, 3, bestLabels, TermCriteria( TermCriteria::COUNT, iters, 0.0), 0, KMEANS_PP_CENTERS, 0 );
- if( calcErr( bestLabels, labels, sizes, false ) > 0.01f )
- {
- ts->printf( CvTS::LOG, "bad accuracy if flag==KMEANS_PP_CENTERS" );
- code = CvTS::FAIL_BAD_ACCURACY;
- }
-
- // 2. flag==KMEANS_RANDOM_CENTERS
- kmeans( data, 3, bestLabels, TermCriteria( TermCriteria::COUNT, iters, 0.0), 0, KMEANS_RANDOM_CENTERS, 0 );
- if( calcErr( bestLabels, labels, sizes, false ) > 0.01f )
- {
- ts->printf( CvTS::LOG, "bad accuracy if flag==KMEANS_PP_CENTERS" );
- code = CvTS::FAIL_BAD_ACCURACY;
- }
-
- // 3. flag==KMEANS_USE_INITIAL_LABELS
- labels.copyTo( bestLabels );
- RNG rng;
- for( int i = 0; i < 0.5f * pointsCount; i++ )
- bestLabels.at<int>( rng.next() % pointsCount, 0 ) = rng.next() % 3;
- kmeans( data, 3, bestLabels, TermCriteria( TermCriteria::COUNT, iters, 0.0), 0, KMEANS_USE_INITIAL_LABELS, 0 );
- if( calcErr( bestLabels, labels, sizes, false ) > 0.01f )
- {
- ts->printf( CvTS::LOG, "bad accuracy if flag==KMEANS_PP_CENTERS" );
- code = CvTS::FAIL_BAD_ACCURACY;
- }
-
- ts->set_failed_test_info( code );
-}
-
-//--------------------------------------------------------------------------------------------
-class CV_KNearestTest : public CvTest {
-public:
- CV_KNearestTest() : CvTest( "knearest", "CvKNearest funcs" ) {}
-protected:
- virtual void run( int start_from );
-};
-
-void CV_KNearestTest::run( int /*start_from*/ )
-{
- int sizesArr[] = { 500, 700, 800 };
- int pointsCount = sizesArr[0]+ sizesArr[1] + sizesArr[2];
-
- // train data
- Mat trainData( pointsCount, 2, CV_32FC1 ), trainLabels;
- vector<int> sizes( sizesArr, sizesArr + sizeof(sizesArr) / sizeof(sizesArr[0]) );
- vector<Mat> means, covs;
- defaultDistribs( means, covs );
- generateData( trainData, trainLabels, sizes, means, covs, CV_32FC1 );
-
- // test data
- Mat testData( pointsCount, 2, CV_32FC1 ), testLabels, bestLabels;
- generateData( testData, testLabels, sizes, means, covs, CV_32FC1 );
-
- int code = CvTS::OK;
- KNearest knearest;
- knearest.train( trainData, trainLabels );
- knearest.find_nearest( testData, 4, &bestLabels );
- if( calcErr( bestLabels, testLabels, sizes, true ) > 0.01f )
- {
- ts->printf( CvTS::LOG, "bad accuracy on test data" );
- code = CvTS::FAIL_BAD_ACCURACY;
- }
- ts->set_failed_test_info( code );
-}
-
-//--------------------------------------------------------------------------------------------
-class CV_EMTest : public CvTest {
-public:
- CV_EMTest() : CvTest( "em", "CvEM funcs" ) {}
-protected:
- virtual void run( int start_from );
-};
-
-void CV_EMTest::run( int /*start_from*/ )
-{
- int sizesArr[] = { 5000, 7000, 8000 };
- int pointsCount = sizesArr[0]+ sizesArr[1] + sizesArr[2];
-
- // train data
- Mat trainData( pointsCount, 2, CV_32FC1 ), trainLabels;
- vector<int> sizes( sizesArr, sizesArr + sizeof(sizesArr) / sizeof(sizesArr[0]) );
- vector<Mat> means, covs;
- defaultDistribs( means, covs );
- generateData( trainData, trainLabels, sizes, means, covs, CV_32SC1 );
-
- // test data
- Mat testData( pointsCount, 2, CV_32FC1 ), testLabels, bestLabels;
- generateData( testData, testLabels, sizes, means, covs, CV_32SC1 );
-
- int code = CvTS::OK;
- ExpectationMaximization em;
- CvEMParams params;
- params.nclusters = 3;
- em.train( trainData, Mat(), params, &bestLabels );
-
- // check train error
- if( calcErr( bestLabels, trainLabels, sizes, true ) > 0.002f )
- {
- ts->printf( CvTS::LOG, "bad accuracy on train data" );
- code = CvTS::FAIL_BAD_ACCURACY;
- }
-
- // check test error
- bestLabels.create( testData.rows, 1, CV_32SC1 );
- for( int i = 0; i < testData.rows; i++ )
- {
- Mat sample( 1, testData.cols, CV_32FC1, testData.ptr<float>(i));
- bestLabels.at<int>(i,0) = (int)em.predict( sample, 0 );
- }
- if( calcErr( bestLabels, testLabels, sizes, true ) > 0.005f )
- {
- ts->printf( CvTS::LOG, "bad accuracy on test data" );
- code = CvTS::FAIL_BAD_ACCURACY;
- }
-
- ts->set_failed_test_info( code );
-}
-
-CV_KMeansTest kmeans_test;
-CV_KNearestTest knearest_test;
-CV_EMTest em_test;
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////\r
-//\r
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.\r
-//\r
-// By downloading, copying, installing or using the software you agree to this license.\r
-// If you do not agree to this license, do not download, install,\r
-// copy or use the software.\r
-//\r
-//\r
-// Intel License Agreement\r
-// For Open Source Computer Vision Library\r
-//\r
-// Copyright (C) 2000, Intel Corporation, all rights reserved.\r
-// Third party copyrights are property of their respective owners.\r
-//\r
-// Redistribution and use in source and binary forms, with or without modification,\r
-// are permitted provided that the following conditions are met:\r
-//\r
-// * Redistribution's of source code must retain the above copyright notice,\r
-// this list of conditions and the following disclaimer.\r
-//\r
-// * Redistribution's in binary form must reproduce the above copyright notice,\r
-// this list of conditions and the following disclaimer in the documentation\r
-// and/or other materials provided with the distribution.\r
-//\r
-// * The name of Intel Corporation may not be used to endorse or promote products\r
-// derived from this software without specific prior written permission.\r
-//\r
-// This software is provided by the copyright holders and contributors "as is" and\r
-// any express or implied warranties, including, but not limited to, the implied\r
-// warranties of merchantability and fitness for a particular purpose are disclaimed.\r
-// In no event shall the Intel Corporation or contributors be liable for any direct,\r
-// indirect, incidental, special, exemplary, or consequential damages\r
-// (including, but not limited to, procurement of substitute goods or services;\r
-// loss of use, data, or profits; or business interruption) however caused\r
-// and on any theory of liability, whether in contract, strict liability,\r
-// or tort (including negligence or otherwise) arising in any way out of\r
-// the use of this software, even if advised of the possibility of such damage.\r
-//\r
-//M*/\r
-\r
-#include "mltest.h"\r
-\r
-CV_AMLTest::CV_AMLTest( const char* _modelName, const char* _testName ) :\r
- CV_MLBaseTest( _modelName, _testName, "train-predict" )\r
-{\r
- validationFN = "avalidation.xml";\r
-}\r
-\r
-int CV_AMLTest::run_test_case( int testCaseIdx )\r
-{\r
- int code = CvTS::OK;\r
- code = prepare_test_case( testCaseIdx );\r
-\r
- if (code == CvTS::OK)\r
- {\r
- //#define GET_STAT\r
-#ifdef GET_STAT\r
- const char* data_name = ((CvFileNode*)cvGetSeqElem( dataSetNames, testCaseIdx ))->data.str.ptr; \r
- printf("%s, %s ", name, data_name);\r
- const int icount = 100;\r
- float res[icount];\r
- for (int k = 0; k < icount; k++)\r
- {\r
-#endif\r
- data.mix_train_and_test_idx();\r
- code = train( testCaseIdx ); \r
-#ifdef GET_STAT\r
- float case_result = get_error();\r
-\r
- res[k] = case_result;\r
- }\r
- float mean = 0, sigma = 0;\r
- for (int k = 0; k < icount; k++)\r
- {\r
- mean += res[k];\r
- }\r
- mean = mean /icount;\r
- for (int k = 0; k < icount; k++)\r
- {\r
- sigma += (res[k] - mean)*(res[k] - mean);\r
- }\r
- sigma = sqrt(sigma/icount);\r
- printf("%f, %f\n", mean, sigma);\r
-#endif\r
- }\r
- return code;\r
-}\r
-\r
-int CV_AMLTest::validate_test_results( int testCaseIdx )\r
-{\r
- int iters;\r
- float mean, sigma;\r
- // read validation params\r
- FileNode resultNode = \r
- validationFS.getFirstTopLevelNode()["validation"][modelName][dataSetNames[testCaseIdx]]["result"];\r
- resultNode["iter_count"] >> iters; \r
- if ( iters > 0)\r
- {\r
- resultNode["mean"] >> mean;\r
- resultNode["sigma"] >> sigma;\r
- float curErr = get_error( testCaseIdx, CV_TEST_ERROR );\r
- const int coeff = 4;\r
- ts->printf( CvTS::LOG, "Test case = %d; test error = %f; mean error = %f (diff=%f), %d*sigma = %f",\r
- testCaseIdx, curErr, mean, abs( curErr - mean), coeff, coeff*sigma );\r
- if ( abs( curErr - mean) > coeff*sigma )\r
- {\r
- ts->printf( CvTS::LOG, "abs(%f - %f) > %f - OUT OF RANGE!\n", curErr, mean, coeff*sigma, coeff );\r
- return CvTS::FAIL_BAD_ACCURACY;\r
- }\r
- else\r
- ts->printf( CvTS::LOG, ".\n" );\r
-\r
- }\r
- else\r
- {\r
- ts->printf( CvTS::LOG, "validation info is not suitable" );\r
- return CvTS::FAIL_INVALID_TEST_DATA;\r
- }\r
- return CvTS::OK;\r
-}\r
-\r
-CV_AMLTest amldtree( CV_DTREE, "adtree" );\r
-CV_AMLTest amlboost( CV_BOOST, "aboost" );\r
-CV_AMLTest amlrtrees( CV_RTREES, "artrees" );\r
-CV_AMLTest amlertrees( CV_ERTREES, "aertrees" );\r
-\r
-/* End of file. */\r
+++ /dev/null
-\r
-#include "mltest.h"\r
-#include <string>\r
-#include <fstream>\r
-#include <iostream>\r
-\r
-using namespace std;\r
-\r
-\r
-class CV_GBTreesTest : public CvTest\r
-{\r
-public:\r
- CV_GBTreesTest();\r
- ~CV_GBTreesTest(); \r
- \r
-protected:\r
- void run(int);\r
-\r
- int TestTrainPredict(int test_num);\r
- int TestSaveLoad();\r
-\r
- int checkPredictError(int test_num);\r
- int checkLoadSave(); \r
- \r
- //string model_file_name1;\r
- //string model_file_name2;\r
- char model_file_name1[50];\r
- char model_file_name2[50];\r
- string* datasets;\r
- string data_path;\r
- \r
- CvMLData* data;\r
- CvGBTrees* gtb;\r
- \r
- vector<float> test_resps1;\r
- vector<float> test_resps2;\r
-};\r
-\r
-\r
-int _get_len(const CvMat* mat)\r
-{\r
- return (mat->cols > mat->rows) ? mat->cols : mat->rows;\r
-}\r
-\r
-\r
-CV_GBTreesTest::CV_GBTreesTest() :\r
- CvTest( "gbtrees",\r
- "all public methods (train, predict, save, load)" )\r
-{\r
- datasets = 0;\r
- data = 0;\r
- gtb = 0;\r
-}\r
-\r
-CV_GBTreesTest::~CV_GBTreesTest()\r
-{\r
- if (data)\r
- delete data;\r
- delete[] datasets;\r
-}\r
-\r
-\r
-int CV_GBTreesTest::TestTrainPredict(int test_num)\r
-{\r
- int code = CvTS::OK;\r
- \r
- int weak_count = 200;\r
- float shrinkage = 0.1f;\r
- float subsample_portion = 0.5f;\r
- int max_depth = 5;\r
- bool use_surrogates = true;\r
- int loss_function_type = 0;\r
- switch (test_num)\r
- {\r
- case (1) : loss_function_type = CvGBTrees::SQUARED_LOSS; break;\r
- case (2) : loss_function_type = CvGBTrees::ABSOLUTE_LOSS; break;\r
- case (3) : loss_function_type = CvGBTrees::HUBER_LOSS; break;\r
- case (0) : loss_function_type = CvGBTrees::DEVIANCE_LOSS; break;\r
- default : \r
- {\r
- ts->printf( CvTS::LOG, "Bad test_num value in CV_GBTreesTest::TestTrainPredict(..) function." );\r
- return CvTS::FAIL_BAD_ARG_CHECK;\r
- }\r
- }\r
-\r
- int dataset_num = test_num == 0 ? 0 : 1;\r
- if (!data)\r
- {\r
- data = new CvMLData();\r
- data->set_delimiter(',');\r
- \r
- if (data->read_csv(datasets[dataset_num].c_str()))\r
- {\r
- ts->printf( CvTS::LOG, "File reading error." );\r
- return CvTS::FAIL_INVALID_TEST_DATA;\r
- }\r
-\r
- if (test_num == 0)\r
- {\r
- data->set_response_idx(57);\r
- data->set_var_types("ord[0-56],cat[57]");\r
- }\r
- else\r
- {\r
- data->set_response_idx(13);\r
- data->set_var_types("ord[0-2,4-13],cat[3]");\r
- subsample_portion = 0.7f;\r
- }\r
-\r
- int train_sample_count = cvFloor(_get_len(data->get_responses())*0.5f);\r
- CvTrainTestSplit spl( train_sample_count );\r
- data->set_train_test_split( &spl );\r
- }\r
- \r
- data->mix_train_and_test_idx(); \r
- \r
- \r
- if (gtb) delete gtb;\r
- gtb = new CvGBTrees();\r
- bool tmp_code = true;\r
- tmp_code = gtb->train(data, CvGBTreesParams(loss_function_type, weak_count,\r
- shrinkage, subsample_portion,\r
- max_depth, use_surrogates));\r
- \r
- if (!tmp_code)\r
- {\r
- ts->printf( CvTS::LOG, "Model training was failed.");\r
- return CvTS::FAIL_INVALID_OUTPUT;\r
- }\r
- \r
- code = checkPredictError(test_num);\r
- \r
- return code;\r
-\r
-}\r
-\r
-\r
-int CV_GBTreesTest::checkPredictError(int test_num)\r
-{\r
- if (!gtb)\r
- return CvTS::FAIL_GENERIC;\r
- \r
- float mean[] = {5.430247f, 13.5654f, 12.6569f, 13.1661f};\r
- float sigma[] = {0.4162694f, 3.21161f, 3.43297f, 3.00624f};\r
- \r
- float current_error = gtb->calc_error(data, CV_TEST_ERROR);\r
- \r
- if ( abs( current_error - mean[test_num]) > 6*sigma[test_num] )\r
- {\r
- ts->printf( CvTS::LOG, "Test error is out of range:\n"\r
- "abs(%f/*curEr*/ - %f/*mean*/ > %f/*6*sigma*/",\r
- current_error, mean[test_num], 6*sigma[test_num] );\r
- return CvTS::FAIL_BAD_ACCURACY;\r
- }\r
-\r
- return CvTS::OK;\r
-\r
-}\r
-\r
-\r
-int CV_GBTreesTest::TestSaveLoad()\r
-{\r
- if (!gtb)\r
- return CvTS::FAIL_GENERIC;\r
- \r
- tmpnam(model_file_name1);\r
- tmpnam(model_file_name2);\r
-\r
- if(model_file_name1[0] == '\\')\r
- model_file_name1[0] = '_';\r
- if(model_file_name2[0] == '\\')\r
- model_file_name2[0] = '_';\r
-\r
- gtb->save(model_file_name1);\r
- gtb->calc_error(data, CV_TEST_ERROR, &test_resps1);\r
- gtb->load(model_file_name1);\r
- gtb->calc_error(data, CV_TEST_ERROR, &test_resps2);\r
- gtb->save(model_file_name2);\r
- \r
- return checkLoadSave();\r
- \r
-}\r
-\r
-\r
-\r
-int CV_GBTreesTest::checkLoadSave()\r
-{\r
- int code = CvTS::OK;\r
-\r
- // 1. compare files\r
- ifstream f1( model_file_name1 ), f2( model_file_name2 );\r
- string s1, s2;\r
- int lineIdx = 0; \r
- CV_Assert( f1.is_open() && f2.is_open() );\r
- for( ; !f1.eof() && !f2.eof(); lineIdx++ )\r
- {\r
- getline( f1, s1 );\r
- getline( f2, s2 );\r
- if( s1.compare(s2) )\r
- {\r
- ts->printf( CvTS::LOG, "first and second saved files differ in %n-line; first %n line: %s; second %n-line: %s",\r
- lineIdx, lineIdx, s1.c_str(), lineIdx, s2.c_str() );\r
- code = CvTS::FAIL_INVALID_OUTPUT;\r
- }\r
- }\r
- if( !f1.eof() || !f2.eof() )\r
- {\r
- ts->printf( CvTS::LOG, "First and second saved files differ in %n-line; first %n line: %s; second %n-line: %s",\r
- lineIdx, lineIdx, s1.c_str(), lineIdx, s2.c_str() );\r
- code = CvTS::FAIL_INVALID_OUTPUT;\r
- }\r
- f1.close();\r
- f2.close();\r
- // delete temporary files\r
- remove( model_file_name1 );\r
- remove( model_file_name2 );\r
-\r
- // 2. compare responses\r
- CV_Assert( test_resps1.size() == test_resps2.size() );\r
- vector<float>::const_iterator it1 = test_resps1.begin(), it2 = test_resps2.begin();\r
- for( ; it1 != test_resps1.end(); ++it1, ++it2 )\r
- {\r
- if( fabs(*it1 - *it2) > FLT_EPSILON )\r
- {\r
- ts->printf( CvTS::LOG, "Responses predicted before saving and after loading are different" );\r
- code = CvTS::FAIL_INVALID_OUTPUT;\r
- }\r
- }\r
- return code;\r
-}\r
-\r
-\r
-\r
-void CV_GBTreesTest::run(int)\r
-{\r
-\r
- string data_path = string(ts->get_data_path());\r
- datasets = new string[2];\r
- datasets[0] = data_path + string("spambase.data"); /*string("dataset_classification.csv");*/\r
- datasets[1] = data_path + string("housing_.data"); /*string("dataset_regression.csv");*/\r
-\r
- int code = CvTS::OK;\r
-\r
- for (int i = 0; i < 4; i++)\r
- {\r
- \r
- int temp_code = TestTrainPredict(i);\r
- if (temp_code != CvTS::OK)\r
- {\r
- code = temp_code;\r
- break;\r
- }\r
- \r
- else if (i==0)\r
- {\r
- temp_code = TestSaveLoad();\r
- if (temp_code != CvTS::OK)\r
- code = temp_code;\r
- delete data;\r
- data = 0;\r
- }\r
- \r
- delete gtb;\r
- gtb = 0;\r
- }\r
- delete data;\r
- data = 0;\r
- \r
- ts->set_failed_test_info( code );\r
-}\r
-\r
-/////////////////////////////////////////////////////////////////////////////\r
-//////////////////// test registration /////////////////////////////////////\r
-/////////////////////////////////////////////////////////////////////////////\r
-\r
-CV_GBTreesTest gbtrees_test;\r
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
-// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of the copyright holders may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#ifndef _OPENCV_MLTEST_H_
-#define _OPENCV_MLTEST_H_
-
-#if defined _MSC_VER && _MSC_VER >= 1200
-#pragma warning( disable: 4710 4711 4514 4996 )
-#endif
-
-#include "cxcore.h"
-#include "cxmisc.h"
-#include "cxts.h"
-#include "ml.h"
-#include <map>
-#include <string>
-#include <iostream>
-
-using namespace cv;
-
-#define CV_NBAYES "nbayes"
-#define CV_KNEAREST "knearest"
-#define CV_SVM "svm"
-#define CV_EM "em"
-#define CV_ANN "ann"
-#define CV_DTREE "dtree"
-#define CV_BOOST "boost"
-#define CV_RTREES "rtrees"
-#define CV_ERTREES "ertrees"
-
-class CV_MLBaseTest : public CvTest
-{
-public:
- CV_MLBaseTest( const char* _modelName, const char* _testName, const char* _testFuncs );
- virtual ~CV_MLBaseTest();
- virtual int init( CvTS* system );
-protected:
- virtual int read_params( CvFileStorage* fs );
- virtual void run( int startFrom );
- virtual int prepare_test_case( int testCaseIdx );
- virtual string& get_validation_filename();
- virtual int run_test_case( int testCaseIdx ) = 0;
- virtual int validate_test_results( int testCaseIdx ) = 0;
-
- int train( int testCaseIdx );
- float get_error( int testCaseIdx, int type, std::vector<float> *resp = 0 );
- void save( const char* filename );
- void load( const char* filename );
-
- CvMLData data;
- string modelName, validationFN;
- std::vector<string> dataSetNames;
- FileStorage validationFS;
-
- // MLL models
- CvNormalBayesClassifier* nbayes;
- CvKNearest* knearest;
- CvSVM* svm;
- CvEM* em;
- CvANN_MLP* ann;
- CvDTree* dtree;
- CvBoost* boost;
- CvRTrees* rtrees;
- CvERTrees* ertrees;
-
- std::map<int, int> cls_map;
-
- int64 initSeed;
-};
-
-class CV_AMLTest : public CV_MLBaseTest
-{
-public:
- CV_AMLTest( const char* _modelName, const char* _testName );
-protected:
- virtual int run_test_case( int testCaseIdx );
- virtual int validate_test_results( int testCaseIdx );
-};
-
-class CV_SLMLTest : public CV_MLBaseTest
-{
-public:
- CV_SLMLTest( const char* _modelName, const char* _testName );
-protected:
- virtual int run_test_case( int testCaseIdx );
- virtual int validate_test_results( int testCaseIdx );
-
- std::vector<float> test_resps1, test_resps2; // predicted responses for test data
- char fname1[50], fname2[50];
-};
-
-/* End of file. */
-
-#endif
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "mltest.h"
-
-CvTS test_system("ml");
-
-const char* blacklist[] =
-{
- "em", //ticket 754
- 0
-};
-
-int main( int argc, char** argv )
-{
- return test_system.run( argc, argv, blacklist );
-}
-
-/* End of file. */
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////\r
-//\r
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.\r
-//\r
-// By downloading, copying, installing or using the software you agree to this license.\r
-// If you do not agree to this license, do not download, install,\r
-// copy or use the software.\r
-//\r
-//\r
-// Intel License Agreement\r
-// For Open Source Computer Vision Library\r
-//\r
-// Copyright (C) 2000, Intel Corporation, all rights reserved.\r
-// Third party copyrights are property of their respective owners.\r
-//\r
-// Redistribution and use in source and binary forms, with or without modification,\r
-// are permitted provided that the following conditions are met:\r
-//\r
-// * Redistribution's of source code must retain the above copyright notice,\r
-// this list of conditions and the following disclaimer.\r
-//\r
-// * Redistribution's in binary form must reproduce the above copyright notice,\r
-// this list of conditions and the following disclaimer in the documentation\r
-// and/or other materials provided with the distribution.\r
-//\r
-// * The name of Intel Corporation may not be used to endorse or promote products\r
-// derived from this software without specific prior written permission.\r
-//\r
-// This software is provided by the copyright holders and contributors "as is" and\r
-// any express or implied warranties, including, but not limited to, the implied\r
-// warranties of merchantability and fitness for a particular purpose are disclaimed.\r
-// In no event shall the Intel Corporation or contributors be liable for any direct,\r
-// indirect, incidental, special, exemplary, or consequential damages\r
-// (including, but not limited to, procurement of substitute goods or services;\r
-// loss of use, data, or profits; or business interruption) however caused\r
-// and on any theory of liability, whether in contract, strict liability,\r
-// or tort (including negligence or otherwise) arising in any way out of\r
-// the use of this software, even if advised of the possibility of such damage.\r
-//\r
-//M*/\r
-\r
-#include "mltest.h"\r
-\r
-// auxiliary functions\r
-// 1. nbayes\r
-void nbayes_check_data( CvMLData* _data )\r
-{\r
- if( _data->get_missing() )\r
- CV_Error( CV_StsBadArg, "missing values are not supported" );\r
- const CvMat* var_types = _data->get_var_types();\r
- bool is_classifier = var_types->data.ptr[var_types->cols-1] == CV_VAR_CATEGORICAL;\r
- if( ( fabs( cvNorm( var_types, 0, CV_L1 ) - \r
- (var_types->rows + var_types->cols - 2)*CV_VAR_ORDERED - CV_VAR_CATEGORICAL ) > FLT_EPSILON ) ||\r
- !is_classifier )\r
- CV_Error( CV_StsBadArg, "incorrect types of predictors or responses" );\r
-}\r
-bool nbayes_train( CvNormalBayesClassifier* nbayes, CvMLData* _data )\r
-{\r
- nbayes_check_data( _data );\r
- const CvMat* values = _data->get_values();\r
- const CvMat* responses = _data->get_responses();\r
- const CvMat* train_sidx = _data->get_train_sample_idx();\r
- const CvMat* var_idx = _data->get_var_idx();\r
- return nbayes->train( values, responses, var_idx, train_sidx );\r
-}\r
-float nbayes_calc_error( CvNormalBayesClassifier* nbayes, CvMLData* _data, int type, vector<float> *resp )\r
-{\r
- float err = 0;\r
- nbayes_check_data( _data );\r
- const CvMat* values = _data->get_values();\r
- const CvMat* response = _data->get_responses();\r
- const CvMat* sample_idx = (type == CV_TEST_ERROR) ? _data->get_test_sample_idx() : _data->get_train_sample_idx();\r
- int* sidx = sample_idx ? sample_idx->data.i : 0;\r
- int r_step = CV_IS_MAT_CONT(response->type) ?\r
- 1 : response->step / CV_ELEM_SIZE(response->type);\r
- int sample_count = sample_idx ? sample_idx->cols : 0;\r
- sample_count = (type == CV_TRAIN_ERROR && sample_count == 0) ? values->rows : sample_count;\r
- float* pred_resp = 0;\r
- if( resp && (sample_count > 0) )\r
- {\r
- resp->resize( sample_count );\r
- pred_resp = &((*resp)[0]);\r
- }\r
-\r
- for( int i = 0; i < sample_count; i++ )\r
- {\r
- CvMat sample;\r
- int si = sidx ? sidx[i] : i;\r
- cvGetRow( values, &sample, si ); \r
- float r = (float)nbayes->predict( &sample, 0 );\r
- if( pred_resp )\r
- pred_resp[i] = r;\r
- int d = fabs((double)r - response->data.fl[si*r_step]) <= FLT_EPSILON ? 0 : 1;\r
- err += d;\r
- }\r
- err = sample_count ? err / (float)sample_count * 100 : -FLT_MAX;\r
- return err;\r
-}\r
-\r
-// 2. knearest\r
-void knearest_check_data_and_get_predictors( CvMLData* _data, CvMat* _predictors )\r
-{\r
- const CvMat* values = _data->get_values();\r
- const CvMat* var_idx = _data->get_var_idx();\r
- if( var_idx->cols + var_idx->rows != values->cols )\r
- CV_Error( CV_StsBadArg, "var_idx is not supported" );\r
- if( _data->get_missing() )\r
- CV_Error( CV_StsBadArg, "missing values are not supported" );\r
- int resp_idx = _data->get_response_idx();\r
- if( resp_idx == 0)\r
- cvGetCols( values, _predictors, 1, values->cols );\r
- else if( resp_idx == values->cols - 1 )\r
- cvGetCols( values, _predictors, 0, values->cols - 1 );\r
- else\r
- CV_Error( CV_StsBadArg, "responses must be in the first or last column; other cases are not supported" );\r
-}\r
-bool knearest_train( CvKNearest* knearest, CvMLData* _data )\r
-{\r
- const CvMat* responses = _data->get_responses();\r
- const CvMat* train_sidx = _data->get_train_sample_idx();\r
- bool is_regression = _data->get_var_type( _data->get_response_idx() ) == CV_VAR_ORDERED;\r
- CvMat predictors;\r
- knearest_check_data_and_get_predictors( _data, &predictors );\r
- return knearest->train( &predictors, responses, train_sidx, is_regression );\r
-}\r
-float knearest_calc_error( CvKNearest* knearest, CvMLData* _data, int k, int type, vector<float> *resp )\r
-{\r
- float err = 0;\r
- const CvMat* response = _data->get_responses();\r
- const CvMat* sample_idx = (type == CV_TEST_ERROR) ? _data->get_test_sample_idx() : _data->get_train_sample_idx();\r
- int* sidx = sample_idx ? sample_idx->data.i : 0;\r
- int r_step = CV_IS_MAT_CONT(response->type) ?\r
- 1 : response->step / CV_ELEM_SIZE(response->type);\r
- bool is_regression = _data->get_var_type( _data->get_response_idx() ) == CV_VAR_ORDERED;\r
- CvMat predictors;\r
- knearest_check_data_and_get_predictors( _data, &predictors );\r
- int sample_count = sample_idx ? sample_idx->cols : 0;\r
- sample_count = (type == CV_TRAIN_ERROR && sample_count == 0) ? predictors.rows : sample_count;\r
- float* pred_resp = 0;\r
- if( resp && (sample_count > 0) )\r
- {\r
- resp->resize( sample_count );\r
- pred_resp = &((*resp)[0]);\r
- }\r
- if ( !is_regression )\r
- {\r
- for( int i = 0; i < sample_count; i++ )\r
- {\r
- CvMat sample;\r
- int si = sidx ? sidx[i] : i;\r
- cvGetRow( &predictors, &sample, si ); \r
- float r = knearest->find_nearest( &sample, k );\r
- if( pred_resp )\r
- pred_resp[i] = r;\r
- int d = fabs((double)r - response->data.fl[si*r_step]) <= FLT_EPSILON ? 0 : 1;\r
- err += d;\r
- }\r
- err = sample_count ? err / (float)sample_count * 100 : -FLT_MAX;\r
- }\r
- else\r
- {\r
- for( int i = 0; i < sample_count; i++ )\r
- {\r
- CvMat sample;\r
- int si = sidx ? sidx[i] : i;\r
- cvGetRow( &predictors, &sample, si ); \r
- float r = knearest->find_nearest( &sample, k );\r
- if( pred_resp )\r
- pred_resp[i] = r;\r
- float d = r - response->data.fl[si*r_step];\r
- err += d*d;\r
- }\r
- err = sample_count ? err / (float)sample_count : -FLT_MAX; \r
- }\r
- return err;\r
-}\r
-\r
-// 3. svm\r
-int str_to_svm_type(string& str)\r
-{\r
- if( !str.compare("C_SVC") )\r
- return CvSVM::C_SVC;\r
- if( !str.compare("NU_SVC") )\r
- return CvSVM::NU_SVC;\r
- if( !str.compare("ONE_CLASS") )\r
- return CvSVM::ONE_CLASS;\r
- if( !str.compare("EPS_SVR") )\r
- return CvSVM::EPS_SVR;\r
- if( !str.compare("NU_SVR") )\r
- return CvSVM::NU_SVR;\r
- CV_Error( CV_StsBadArg, "incorrect svm type string" );\r
- return -1;\r
-}\r
-int str_to_svm_kernel_type( string& str )\r
-{\r
- if( !str.compare("LINEAR") )\r
- return CvSVM::LINEAR;\r
- if( !str.compare("POLY") )\r
- return CvSVM::POLY;\r
- if( !str.compare("RBF") )\r
- return CvSVM::RBF;\r
- if( !str.compare("SIGMOID") )\r
- return CvSVM::SIGMOID;\r
- CV_Error( CV_StsBadArg, "incorrect svm type string" );\r
- return -1;\r
-}\r
-void svm_check_data( CvMLData* _data )\r
-{\r
- if( _data->get_missing() )\r
- CV_Error( CV_StsBadArg, "missing values are not supported" );\r
- const CvMat* var_types = _data->get_var_types();\r
- for( int i = 0; i < var_types->cols-1; i++ )\r
- if (var_types->data.ptr[i] == CV_VAR_CATEGORICAL)\r
- {\r
- char msg[50];\r
- sprintf( msg, "incorrect type of %d-predictor", i );\r
- CV_Error( CV_StsBadArg, msg );\r
- }\r
-}\r
-bool svm_train( CvSVM* svm, CvMLData* _data, CvSVMParams _params )\r
-{\r
- svm_check_data(_data);\r
- const CvMat* _train_data = _data->get_values();\r
- const CvMat* _responses = _data->get_responses();\r
- const CvMat* _var_idx = _data->get_var_idx();\r
- const CvMat* _sample_idx = _data->get_train_sample_idx();\r
- return svm->train( _train_data, _responses, _var_idx, _sample_idx, _params );\r
-}\r
-bool svm_train_auto( CvSVM* svm, CvMLData* _data, CvSVMParams _params,\r
- int k_fold, CvParamGrid C_grid, CvParamGrid gamma_grid,\r
- CvParamGrid p_grid, CvParamGrid nu_grid, CvParamGrid coef_grid,\r
- CvParamGrid degree_grid )\r
-{\r
- svm_check_data(_data);\r
- const CvMat* _train_data = _data->get_values();\r
- const CvMat* _responses = _data->get_responses();\r
- const CvMat* _var_idx = _data->get_var_idx();\r
- const CvMat* _sample_idx = _data->get_train_sample_idx();\r
- return svm->train_auto( _train_data, _responses, _var_idx, \r
- _sample_idx, _params, k_fold, C_grid, gamma_grid, p_grid, nu_grid, coef_grid, degree_grid );\r
-}\r
-float svm_calc_error( CvSVM* svm, CvMLData* _data, int type, vector<float> *resp )\r
-{\r
- svm_check_data(_data);\r
- float err = 0;\r
- const CvMat* values = _data->get_values();\r
- const CvMat* response = _data->get_responses();\r
- const CvMat* sample_idx = (type == CV_TEST_ERROR) ? _data->get_test_sample_idx() : _data->get_train_sample_idx();\r
- const CvMat* var_types = _data->get_var_types();\r
- int* sidx = sample_idx ? sample_idx->data.i : 0;\r
- int r_step = CV_IS_MAT_CONT(response->type) ?\r
- 1 : response->step / CV_ELEM_SIZE(response->type);\r
- bool is_classifier = var_types->data.ptr[var_types->cols-1] == CV_VAR_CATEGORICAL;\r
- int sample_count = sample_idx ? sample_idx->cols : 0;\r
- sample_count = (type == CV_TRAIN_ERROR && sample_count == 0) ? values->rows : sample_count;\r
- float* pred_resp = 0;\r
- if( resp && (sample_count > 0) )\r
- {\r
- resp->resize( sample_count );\r
- pred_resp = &((*resp)[0]);\r
- }\r
- if ( is_classifier )\r
- {\r
- for( int i = 0; i < sample_count; i++ )\r
- {\r
- CvMat sample;\r
- int si = sidx ? sidx[i] : i;\r
- cvGetRow( values, &sample, si ); \r
- float r = svm->predict( &sample );\r
- if( pred_resp )\r
- pred_resp[i] = r;\r
- int d = fabs((double)r - response->data.fl[si*r_step]) <= FLT_EPSILON ? 0 : 1;\r
- err += d;\r
- }\r
- err = sample_count ? err / (float)sample_count * 100 : -FLT_MAX;\r
- }\r
- else\r
- {\r
- for( int i = 0; i < sample_count; i++ )\r
- {\r
- CvMat sample;\r
- int si = sidx ? sidx[i] : i;\r
- cvGetRow( values, &sample, si );\r
- float r = svm->predict( &sample );\r
- if( pred_resp )\r
- pred_resp[i] = r;\r
- float d = r - response->data.fl[si*r_step];\r
- err += d*d;\r
- }\r
- err = sample_count ? err / (float)sample_count : -FLT_MAX; \r
- }\r
- return err;\r
-}\r
-\r
-// 4. em\r
-// 5. ann\r
-int str_to_ann_train_method( string& str )\r
-{\r
- if( !str.compare("BACKPROP") )\r
- return CvANN_MLP_TrainParams::BACKPROP;\r
- if( !str.compare("RPROP") )\r
- return CvANN_MLP_TrainParams::RPROP;\r
- CV_Error( CV_StsBadArg, "incorrect ann train method string" );\r
- return -1;\r
-}\r
-void ann_check_data_and_get_predictors( CvMLData* _data, CvMat* _inputs )\r
-{\r
- const CvMat* values = _data->get_values();\r
- const CvMat* var_idx = _data->get_var_idx();\r
- if( var_idx->cols + var_idx->rows != values->cols )\r
- CV_Error( CV_StsBadArg, "var_idx is not supported" );\r
- if( _data->get_missing() )\r
- CV_Error( CV_StsBadArg, "missing values are not supported" );\r
- int resp_idx = _data->get_response_idx();\r
- if( resp_idx == 0)\r
- cvGetCols( values, _inputs, 1, values->cols );\r
- else if( resp_idx == values->cols - 1 )\r
- cvGetCols( values, _inputs, 0, values->cols - 1 );\r
- else\r
- CV_Error( CV_StsBadArg, "outputs must be in the first or last column; other cases are not supported" );\r
-}\r
-void ann_get_new_responses( CvMLData* _data, Mat& new_responses, map<int, int>& cls_map )\r
-{\r
- const CvMat* train_sidx = _data->get_train_sample_idx();\r
- int* train_sidx_ptr = train_sidx->data.i;\r
- const CvMat* responses = _data->get_responses();\r
- float* responses_ptr = responses->data.fl;\r
- int r_step = CV_IS_MAT_CONT(responses->type) ?\r
- 1 : responses->step / CV_ELEM_SIZE(responses->type);\r
- int cls_count = 0;\r
- // construct cls_map\r
- cls_map.clear();\r
- for( int si = 0; si < train_sidx->cols; si++ )\r
- {\r
- int sidx = train_sidx_ptr[si];\r
- int r = cvRound(responses_ptr[sidx*r_step]);\r
- CV_DbgAssert( fabs(responses_ptr[sidx*r_step]-r) < FLT_EPSILON );\r
- int cls_map_size = (int)cls_map.size();\r
- cls_map[r];\r
- if ( (int)cls_map.size() > cls_map_size )\r
- cls_map[r] = cls_count++;\r
- }\r
- new_responses.create( responses->rows, cls_count, CV_32F );\r
- new_responses.setTo( 0 );\r
- for( int si = 0; si < train_sidx->cols; si++ )\r
- {\r
- int sidx = train_sidx_ptr[si];\r
- int r = cvRound(responses_ptr[sidx*r_step]);\r
- int cidx = cls_map[r];\r
- new_responses.ptr<float>(sidx)[cidx] = 1;\r
- }\r
-}\r
-int ann_train( CvANN_MLP* ann, CvMLData* _data, Mat& new_responses, CvANN_MLP_TrainParams _params, int flags = 0 )\r
-{\r
- const CvMat* train_sidx = _data->get_train_sample_idx();\r
- CvMat predictors;\r
- ann_check_data_and_get_predictors( _data, &predictors );\r
- CvMat _new_responses = CvMat( new_responses );\r
- return ann->train( &predictors, &_new_responses, 0, train_sidx, _params, flags );\r
-}\r
-float ann_calc_error( CvANN_MLP* ann, CvMLData* _data, map<int, int>& cls_map, int type , vector<float> *resp_labels )\r
-{\r
- float err = 0;\r
- const CvMat* responses = _data->get_responses();\r
- const CvMat* sample_idx = (type == CV_TEST_ERROR) ? _data->get_test_sample_idx() : _data->get_train_sample_idx();\r
- int* sidx = sample_idx ? sample_idx->data.i : 0;\r
- int r_step = CV_IS_MAT_CONT(responses->type) ?\r
- 1 : responses->step / CV_ELEM_SIZE(responses->type);\r
- CvMat predictors;\r
- ann_check_data_and_get_predictors( _data, &predictors );\r
- int sample_count = sample_idx ? sample_idx->cols : 0;\r
- sample_count = (type == CV_TRAIN_ERROR && sample_count == 0) ? predictors.rows : sample_count;\r
- float* pred_resp = 0;\r
- vector<float> innresp;\r
- if( sample_count > 0 )\r
- {\r
- if( resp_labels )\r
- {\r
- resp_labels->resize( sample_count );\r
- pred_resp = &((*resp_labels)[0]);\r
- }\r
- else\r
- {\r
- innresp.resize( sample_count );\r
- pred_resp = &(innresp[0]);\r
- }\r
- }\r
- int cls_count = (int)cls_map.size();\r
- Mat output( 1, cls_count, CV_32FC1 );\r
- CvMat _output = CvMat(output);\r
- map<int, int>::iterator b_it = cls_map.begin();\r
- for( int i = 0; i < sample_count; i++ )\r
- {\r
- CvMat sample;\r
- int si = sidx ? sidx[i] : i;\r
- cvGetRow( &predictors, &sample, si ); \r
- ann->predict( &sample, &_output );\r
- CvPoint best_cls = {0,0};\r
- cvMinMaxLoc( &_output, 0, 0, 0, &best_cls, 0 );\r
- int r = cvRound(responses->data.fl[si*r_step]);\r
- CV_DbgAssert( fabs(responses->data.fl[si*r_step]-r) < FLT_EPSILON );\r
- r = cls_map[r];\r
- int d = best_cls.x == r ? 0 : 1;\r
- err += d;\r
- pred_resp[i] = (float)best_cls.x;\r
- }\r
- err = sample_count ? err / (float)sample_count * 100 : -FLT_MAX;\r
- return err;\r
-}\r
-\r
-// 6. dtree\r
-// 7. boost\r
-int str_to_boost_type( string& str )\r
-{\r
- if ( !str.compare("DISCRETE") )\r
- return CvBoost::DISCRETE;\r
- if ( !str.compare("REAL") )\r
- return CvBoost::REAL; \r
- if ( !str.compare("LOGIT") )\r
- return CvBoost::LOGIT;\r
- if ( !str.compare("GENTLE") )\r
- return CvBoost::GENTLE;\r
- CV_Error( CV_StsBadArg, "incorrect boost type string" );\r
- return -1;\r
-}\r
-\r
-// 8. rtrees\r
-// 9. ertrees\r
-\r
-// ---------------------------------- MLBaseTest ---------------------------------------------------\r
-\r
-CV_MLBaseTest::CV_MLBaseTest( const char* _modelName, const char* _testName, const char* _testFuncs ) :\r
-CvTest( _testName, _testFuncs )\r
-{\r
- int64 seeds[] = { CV_BIG_INT(0x00009fff4f9c8d52),\r
- CV_BIG_INT(0x0000a17166072c7c),\r
- CV_BIG_INT(0x0201b32115cd1f9a),\r
- CV_BIG_INT(0x0513cb37abcd1234),\r
- CV_BIG_INT(0x0001a2b3c4d5f678)\r
- };\r
-\r
- int seedCount = sizeof(seeds)/sizeof(seeds[0]);\r
- RNG& rng = theRNG();\r
-\r
- initSeed = rng.state;\r
-\r
- rng.state = seeds[rng(seedCount)];\r
-\r
- modelName = _modelName;\r
- nbayes = 0;\r
- knearest = 0;\r
- svm = 0;\r
- em = 0;\r
- ann = 0;\r
- dtree = 0;\r
- boost = 0;\r
- rtrees = 0;\r
- ertrees = 0;\r
- if( !modelName.compare(CV_NBAYES) )\r
- nbayes = new CvNormalBayesClassifier;\r
- else if( !modelName.compare(CV_KNEAREST) )\r
- knearest = new CvKNearest;\r
- else if( !modelName.compare(CV_SVM) )\r
- svm = new CvSVM;\r
- else if( !modelName.compare(CV_EM) )\r
- em = new CvEM;\r
- else if( !modelName.compare(CV_ANN) )\r
- ann = new CvANN_MLP;\r
- else if( !modelName.compare(CV_DTREE) )\r
- dtree = new CvDTree;\r
- else if( !modelName.compare(CV_BOOST) )\r
- boost = new CvBoost;\r
- else if( !modelName.compare(CV_RTREES) )\r
- rtrees = new CvRTrees;\r
- else if( !modelName.compare(CV_ERTREES) )\r
- ertrees = new CvERTrees;\r
-}\r
-\r
-int CV_MLBaseTest::init( CvTS* system )\r
-{\r
- clear();\r
- ts = system;\r
-\r
- string filename = ts->get_data_path();\r
- filename += get_validation_filename();\r
- validationFS.open( filename, FileStorage::READ );\r
- return read_params( *validationFS );\r
-}\r
-\r
-CV_MLBaseTest::~CV_MLBaseTest()\r
-{\r
- if( validationFS.isOpened() )\r
- validationFS.release();\r
- if( nbayes )\r
- delete nbayes;\r
- if( knearest ) \r
- delete knearest;\r
- if( svm )\r
- delete svm;\r
- if( em )\r
- delete em;\r
- if( ann )\r
- delete ann;\r
- if( dtree )\r
- delete dtree;\r
- if( boost )\r
- delete boost;\r
- if( rtrees )\r
- delete rtrees;\r
- if( ertrees )\r
- delete ertrees;\r
- theRNG().state = initSeed;\r
-}\r
-\r
-int CV_MLBaseTest::read_params( CvFileStorage* _fs )\r
-{\r
- if( !_fs )\r
- test_case_count = -1;\r
- else\r
- {\r
- CvFileNode* fn = cvGetRootFileNode( _fs, 0 );\r
- fn = (CvFileNode*)cvGetSeqElem( fn->data.seq, 0 );\r
- fn = cvGetFileNodeByName( _fs, fn, "run_params" );\r
- CvSeq* dataSetNamesSeq = cvGetFileNodeByName( _fs, fn, modelName.c_str() )->data.seq;\r
- test_case_count = dataSetNamesSeq ? dataSetNamesSeq->total : -1;\r
- if( test_case_count > 0 )\r
- {\r
- dataSetNames.resize( test_case_count );\r
- vector<string>::iterator it = dataSetNames.begin();\r
- for( int i = 0; i < test_case_count; i++, it++ )\r
- *it = ((CvFileNode*)cvGetSeqElem( dataSetNamesSeq, i ))->data.str.ptr;\r
- }\r
- }\r
- return CvTS::OK;;\r
-}\r
-\r
-void CV_MLBaseTest::run( int start_from )\r
-{\r
- int code = CvTS::OK;\r
- start_from = 0;\r
- for (int i = 0; i < test_case_count; i++)\r
- {\r
- int temp_code = run_test_case( i );\r
- if (temp_code == CvTS::OK)\r
- temp_code = validate_test_results( i );\r
- if (temp_code != CvTS::OK)\r
- code = temp_code;\r
- }\r
- if ( test_case_count <= 0)\r
- {\r
- ts->printf( CvTS::LOG, "validation file is not determined or not correct" );\r
- code = CvTS::FAIL_INVALID_TEST_DATA;\r
- }\r
- ts->set_failed_test_info( code );\r
-}\r
-\r
-int CV_MLBaseTest::prepare_test_case( int test_case_idx )\r
-{\r
- int trainSampleCount, respIdx;\r
- string varTypes;\r
- clear();\r
-\r
- string dataPath = ts->get_data_path();\r
- if ( dataPath.empty() )\r
- {\r
- ts->printf( CvTS::LOG, "data path is empty" );\r
- return CvTS::FAIL_INVALID_TEST_DATA;\r
- }\r
-\r
- string dataName = dataSetNames[test_case_idx],\r
- filename = dataPath + dataName + ".data";\r
- if ( data.read_csv( filename.c_str() ) != 0)\r
- {\r
- char msg[100];\r
- sprintf( msg, "file %s can not be read", filename.c_str() );\r
- ts->printf( CvTS::LOG, msg );\r
- return CvTS::FAIL_INVALID_TEST_DATA;\r
- }\r
-\r
- FileNode dataParamsNode = validationFS.getFirstTopLevelNode()["validation"][modelName][dataName]["data_params"];\r
- CV_DbgAssert( !dataParamsNode.empty() );\r
-\r
- CV_DbgAssert( !dataParamsNode["LS"].empty() );\r
- dataParamsNode["LS"] >> trainSampleCount;\r
- CvTrainTestSplit spl( trainSampleCount );\r
- data.set_train_test_split( &spl );\r
-\r
- CV_DbgAssert( !dataParamsNode["resp_idx"].empty() );\r
- dataParamsNode["resp_idx"] >> respIdx;\r
- data.set_response_idx( respIdx );\r
-\r
- CV_DbgAssert( !dataParamsNode["types"].empty() );\r
- dataParamsNode["types"] >> varTypes;\r
- data.set_var_types( varTypes.c_str() );\r
-\r
- return CvTS::OK;\r
-}\r
-\r
-string& CV_MLBaseTest::get_validation_filename()\r
-{\r
- return validationFN;\r
-}\r
-\r
-int CV_MLBaseTest::train( int testCaseIdx )\r
-{\r
- bool is_trained = false;\r
- FileNode modelParamsNode = \r
- validationFS.getFirstTopLevelNode()["validation"][modelName][dataSetNames[testCaseIdx]]["model_params"];\r
-\r
- if( !modelName.compare(CV_NBAYES) )\r
- is_trained = nbayes_train( nbayes, &data );\r
- else if( !modelName.compare(CV_KNEAREST) )\r
- {\r
- assert( 0 );\r
- //is_trained = knearest->train( &data );\r
- }\r
- else if( !modelName.compare(CV_SVM) )\r
- {\r
- string svm_type_str, kernel_type_str;\r
- modelParamsNode["svm_type"] >> svm_type_str;\r
- modelParamsNode["kernel_type"] >> kernel_type_str;\r
- CvSVMParams params;\r
- params.svm_type = str_to_svm_type( svm_type_str );\r
- params.kernel_type = str_to_svm_kernel_type( kernel_type_str );\r
- modelParamsNode["degree"] >> params.degree;\r
- modelParamsNode["gamma"] >> params.gamma;\r
- modelParamsNode["coef0"] >> params.coef0;\r
- modelParamsNode["C"] >> params.C;\r
- modelParamsNode["nu"] >> params.nu;\r
- modelParamsNode["p"] >> params.p;\r
- is_trained = svm_train( svm, &data, params );\r
- }\r
- else if( !modelName.compare(CV_EM) )\r
- {\r
- assert( 0 );\r
- }\r
- else if( !modelName.compare(CV_ANN) )\r
- {\r
- string train_method_str;\r
- double param1, param2;\r
- modelParamsNode["train_method"] >> train_method_str;\r
- modelParamsNode["param1"] >> param1;\r
- modelParamsNode["param2"] >> param2;\r
- Mat new_responses;\r
- ann_get_new_responses( &data, new_responses, cls_map );\r
- int layer_sz[] = { data.get_values()->cols - 1, 100, 100, (int)cls_map.size() };\r
- CvMat layer_sizes =\r
- cvMat( 1, (int)(sizeof(layer_sz)/sizeof(layer_sz[0])), CV_32S, layer_sz );\r
- ann->create( &layer_sizes );\r
- is_trained = ann_train( ann, &data, new_responses, CvANN_MLP_TrainParams(cvTermCriteria(CV_TERMCRIT_ITER,300,0.01),\r
- str_to_ann_train_method(train_method_str), param1, param2) ) >= 0;\r
- }\r
- else if( !modelName.compare(CV_DTREE) )\r
- {\r
- int MAX_DEPTH, MIN_SAMPLE_COUNT, MAX_CATEGORIES, CV_FOLDS;\r
- float REG_ACCURACY = 0;\r
- bool USE_SURROGATE, IS_PRUNED;\r
- modelParamsNode["max_depth"] >> MAX_DEPTH;\r
- modelParamsNode["min_sample_count"] >> MIN_SAMPLE_COUNT;\r
- modelParamsNode["use_surrogate"] >> USE_SURROGATE;\r
- modelParamsNode["max_categories"] >> MAX_CATEGORIES;\r
- modelParamsNode["cv_folds"] >> CV_FOLDS;\r
- modelParamsNode["is_pruned"] >> IS_PRUNED;\r
- is_trained = dtree->train( &data, \r
- CvDTreeParams(MAX_DEPTH, MIN_SAMPLE_COUNT, REG_ACCURACY, USE_SURROGATE,\r
- MAX_CATEGORIES, CV_FOLDS, false, IS_PRUNED, 0 )) != 0;\r
- }\r
- else if( !modelName.compare(CV_BOOST) )\r
- {\r
- int BOOST_TYPE, WEAK_COUNT, MAX_DEPTH;\r
- float WEIGHT_TRIM_RATE;\r
- bool USE_SURROGATE;\r
- string typeStr;\r
- modelParamsNode["type"] >> typeStr;\r
- BOOST_TYPE = str_to_boost_type( typeStr );\r
- modelParamsNode["weak_count"] >> WEAK_COUNT;\r
- modelParamsNode["weight_trim_rate"] >> WEIGHT_TRIM_RATE;\r
- modelParamsNode["max_depth"] >> MAX_DEPTH;\r
- modelParamsNode["use_surrogate"] >> USE_SURROGATE;\r
- is_trained = boost->train( &data,\r
- CvBoostParams(BOOST_TYPE, WEAK_COUNT, WEIGHT_TRIM_RATE, MAX_DEPTH, USE_SURROGATE, 0) ) != 0;\r
- }\r
- else if( !modelName.compare(CV_RTREES) )\r
- {\r
- int MAX_DEPTH, MIN_SAMPLE_COUNT, MAX_CATEGORIES, CV_FOLDS, NACTIVE_VARS, MAX_TREES_NUM;\r
- float REG_ACCURACY = 0, OOB_EPS = 0.0;\r
- bool USE_SURROGATE, IS_PRUNED;\r
- modelParamsNode["max_depth"] >> MAX_DEPTH;\r
- modelParamsNode["min_sample_count"] >> MIN_SAMPLE_COUNT;\r
- modelParamsNode["use_surrogate"] >> USE_SURROGATE;\r
- modelParamsNode["max_categories"] >> MAX_CATEGORIES;\r
- modelParamsNode["cv_folds"] >> CV_FOLDS;\r
- modelParamsNode["is_pruned"] >> IS_PRUNED;\r
- modelParamsNode["nactive_vars"] >> NACTIVE_VARS;\r
- modelParamsNode["max_trees_num"] >> MAX_TREES_NUM;\r
- is_trained = rtrees->train( &data, CvRTParams( MAX_DEPTH, MIN_SAMPLE_COUNT, REG_ACCURACY,\r
- USE_SURROGATE, MAX_CATEGORIES, 0, true, // (calc_var_importance == true) <=> RF processes variable importance\r
- NACTIVE_VARS, MAX_TREES_NUM, OOB_EPS, CV_TERMCRIT_ITER)) != 0;\r
- }\r
- else if( !modelName.compare(CV_ERTREES) )\r
- {\r
- int MAX_DEPTH, MIN_SAMPLE_COUNT, MAX_CATEGORIES, CV_FOLDS, NACTIVE_VARS, MAX_TREES_NUM;\r
- float REG_ACCURACY = 0, OOB_EPS = 0.0;\r
- bool USE_SURROGATE, IS_PRUNED;\r
- modelParamsNode["max_depth"] >> MAX_DEPTH;\r
- modelParamsNode["min_sample_count"] >> MIN_SAMPLE_COUNT;\r
- modelParamsNode["use_surrogate"] >> USE_SURROGATE;\r
- modelParamsNode["max_categories"] >> MAX_CATEGORIES;\r
- modelParamsNode["cv_folds"] >> CV_FOLDS;\r
- modelParamsNode["is_pruned"] >> IS_PRUNED;\r
- modelParamsNode["nactive_vars"] >> NACTIVE_VARS;\r
- modelParamsNode["max_trees_num"] >> MAX_TREES_NUM;\r
- is_trained = ertrees->train( &data, CvRTParams( MAX_DEPTH, MIN_SAMPLE_COUNT, REG_ACCURACY,\r
- USE_SURROGATE, MAX_CATEGORIES, 0, false, // (calc_var_importance == true) <=> RF processes variable importance\r
- NACTIVE_VARS, MAX_TREES_NUM, OOB_EPS, CV_TERMCRIT_ITER)) != 0;\r
- }\r
-\r
- if( !is_trained )\r
- {\r
- ts->printf( CvTS::LOG, "in test case %d model training was failed", testCaseIdx );\r
- return CvTS::FAIL_INVALID_OUTPUT;\r
- }\r
- return CvTS::OK;\r
-}\r
-\r
-float CV_MLBaseTest::get_error( int testCaseIdx, int type, vector<float> *resp )\r
-{\r
- float err = 0;\r
- if( !modelName.compare(CV_NBAYES) )\r
- err = nbayes_calc_error( nbayes, &data, type, resp );\r
- else if( !modelName.compare(CV_KNEAREST) )\r
- {\r
- assert( 0 );\r
- testCaseIdx = 0;\r
- /*int k = 2;\r
- validationFS.getFirstTopLevelNode()["validation"][modelName][dataSetNames[testCaseIdx]]["model_params"]["k"] >> k;\r
- err = knearest->calc_error( &data, k, type, resp );*/\r
- }\r
- else if( !modelName.compare(CV_SVM) )\r
- err = svm_calc_error( svm, &data, type, resp );\r
- else if( !modelName.compare(CV_EM) )\r
- assert( 0 );\r
- else if( !modelName.compare(CV_ANN) )\r
- err = ann_calc_error( ann, &data, cls_map, type, resp );\r
- else if( !modelName.compare(CV_DTREE) )\r
- err = dtree->calc_error( &data, type, resp );\r
- else if( !modelName.compare(CV_BOOST) )\r
- err = boost->calc_error( &data, type, resp );\r
- else if( !modelName.compare(CV_RTREES) )\r
- err = rtrees->calc_error( &data, type, resp );\r
- else if( !modelName.compare(CV_ERTREES) )\r
- err = ertrees->calc_error( &data, type, resp );\r
- return err;\r
-}\r
-\r
-void CV_MLBaseTest::save( const char* filename )\r
-{\r
- if( !modelName.compare(CV_NBAYES) )\r
- nbayes->save( filename );\r
- else if( !modelName.compare(CV_KNEAREST) )\r
- knearest->save( filename );\r
- else if( !modelName.compare(CV_SVM) )\r
- svm->save( filename );\r
- else if( !modelName.compare(CV_EM) )\r
- em->save( filename );\r
- else if( !modelName.compare(CV_ANN) )\r
- ann->save( filename );\r
- else if( !modelName.compare(CV_DTREE) )\r
- dtree->save( filename );\r
- else if( !modelName.compare(CV_BOOST) )\r
- boost->save( filename );\r
- else if( !modelName.compare(CV_RTREES) )\r
- rtrees->save( filename );\r
- else if( !modelName.compare(CV_ERTREES) )\r
- ertrees->save( filename );\r
-}\r
-\r
-void CV_MLBaseTest::load( const char* filename )\r
-{\r
- if( !modelName.compare(CV_NBAYES) )\r
- nbayes->load( filename );\r
- else if( !modelName.compare(CV_KNEAREST) )\r
- knearest->load( filename );\r
- else if( !modelName.compare(CV_SVM) )\r
- svm->load( filename );\r
- else if( !modelName.compare(CV_EM) )\r
- em->load( filename );\r
- else if( !modelName.compare(CV_ANN) )\r
- ann->load( filename );\r
- else if( !modelName.compare(CV_DTREE) )\r
- dtree->load( filename );\r
- else if( !modelName.compare(CV_BOOST) )\r
- boost->load( filename );\r
- else if( !modelName.compare(CV_RTREES) )\r
- rtrees->load( filename );\r
- else if( !modelName.compare(CV_ERTREES) )\r
- ertrees->load( filename );\r
-}\r
-\r
-/* End of file. */\r
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "mltest.h"
-/* End of file. */
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////\r
-//\r
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.\r
-//\r
-// By downloading, copying, installing or using the software you agree to this license.\r
-// If you do not agree to this license, do not download, install,\r
-// copy or use the software.\r
-//\r
-//\r
-// Intel License Agreement\r
-// For Open Source Computer Vision Library\r
-//\r
-// Copyright (C) 2000, Intel Corporation, all rights reserved.\r
-// Third party copyrights are property of their respective owners.\r
-//\r
-// Redistribution and use in source and binary forms, with or without modification,\r
-// are permitted provided that the following conditions are met:\r
-//\r
-// * Redistribution's of source code must retain the above copyright notice,\r
-// this list of conditions and the following disclaimer.\r
-//\r
-// * Redistribution's in binary form must reproduce the above copyright notice,\r
-// this list of conditions and the following disclaimer in the documentation\r
-// and/or other materials provided with the distribution.\r
-//\r
-// * The name of Intel Corporation may not be used to endorse or promote products\r
-// derived from this software without specific prior written permission.\r
-//\r
-// This software is provided by the copyright holders and contributors "as is" and\r
-// any express or implied warranties, including, but not limited to, the implied\r
-// warranties of merchantability and fitness for a particular purpose are disclaimed.\r
-// In no event shall the Intel Corporation or contributors be liable for any direct,\r
-// indirect, incidental, special, exemplary, or consequential damages\r
-// (including, but not limited to, procurement of substitute goods or services;\r
-// loss of use, data, or profits; or business interruption) however caused\r
-// and on any theory of liability, whether in contract, strict liability,\r
-// or tort (including negligence or otherwise) arising in any way out of\r
-// the use of this software, even if advised of the possibility of such damage.\r
-//\r
-//M*/\r
-\r
-#include "mltest.h"\r
-#include <iostream>\r
-#include <fstream>\r
-\r
-CV_SLMLTest::CV_SLMLTest( const char* _modelName, const char* _testName ) :\r
- CV_MLBaseTest( _modelName, _testName, "load-save" )\r
-{\r
- validationFN = "slvalidation.xml";\r
-}\r
-\r
-int CV_SLMLTest::run_test_case( int testCaseIdx )\r
-{\r
- int code = CvTS::OK;\r
- code = prepare_test_case( testCaseIdx );\r
-\r
- if( code == CvTS::OK )\r
- {\r
- data.mix_train_and_test_idx();\r
- code = train( testCaseIdx );\r
- if( code == CvTS::OK )\r
- {\r
- get_error( testCaseIdx, CV_TEST_ERROR, &test_resps1 );\r
- tmpnam(fname1);\r
- if(fname1[0] == '\\') fname1[0] = '_';\r
- save( fname1 );\r
- load( fname1);\r
- get_error( testCaseIdx, CV_TEST_ERROR, &test_resps2 );\r
- tmpnam(fname2);\r
- if(fname2[0] == '\\') fname2[0] = '_';\r
- save( fname2 );\r
- }\r
- else\r
- ts->printf( CvTS::LOG, "model can not be trained" );\r
- }\r
- return code;\r
-}\r
-\r
-int CV_SLMLTest::validate_test_results( int testCaseIdx )\r
-{\r
- int code = CvTS::OK;\r
-\r
- // 1. compare files\r
- ifstream f1( fname1 ), f2( fname2 );\r
- string s1, s2;\r
- int lineIdx = 0; \r
- CV_Assert( f1.is_open() && f2.is_open() );\r
- for( ; !f1.eof() && !f2.eof(); lineIdx++ )\r
- {\r
- getline( f1, s1 );\r
- getline( f2, s2 );\r
- if( s1.compare(s2) )\r
- {\r
- ts->printf( CvTS::LOG, "first and second saved files differ in %n-line; first %n line: %s; second %n-line: %s",\r
- lineIdx, lineIdx, s1.c_str(), lineIdx, s2.c_str() );\r
- code = CvTS::FAIL_INVALID_OUTPUT;\r
- }\r
- }\r
- if( !f1.eof() || !f2.eof() )\r
- {\r
- ts->printf( CvTS::LOG, "in test case %d first and second saved files differ in %n-line; first %n line: %s; second %n-line: %s",\r
- testCaseIdx, lineIdx, lineIdx, s1.c_str(), lineIdx, s2.c_str() );\r
- code = CvTS::FAIL_INVALID_OUTPUT;\r
- }\r
- f1.close();\r
- f2.close();\r
- // delete temporary files\r
- remove( fname1 );\r
- remove( fname2 );\r
-\r
- // 2. compare responses\r
- CV_Assert( test_resps1.size() == test_resps2.size() );\r
- vector<float>::const_iterator it1 = test_resps1.begin(), it2 = test_resps2.begin();\r
- for( ; it1 != test_resps1.end(); ++it1, ++it2 )\r
- {\r
- if( fabs(*it1 - *it2) > FLT_EPSILON )\r
- {\r
- ts->printf( CvTS::LOG, "in test case %d responses predicted before saving and after loading is different", testCaseIdx );\r
- code = CvTS::FAIL_INVALID_OUTPUT;\r
- }\r
- }\r
- return code;\r
-}\r
-\r
-CV_SLMLTest lsmlnbayes( CV_NBAYES, "slnbayes" );\r
-//CV_SLMLTest lsmlknearest( CV_KNEAREST, "slknearest" ); // does not support save!\r
-CV_SLMLTest lsmlsvm( CV_SVM, "slsvm" );\r
-//CV_SLMLTest lsmlem( CV_EM, "slem" ); // does not support save!\r
-CV_SLMLTest lsmlann( CV_ANN, "slann" );\r
-CV_SLMLTest slmldtree( CV_DTREE, "sldtree" );\r
-CV_SLMLTest slmlboost( CV_BOOST, "slboost" );\r
-CV_SLMLTest slmlrtrees( CV_RTREES, "slrtrees" );\r
-CV_SLMLTest slmlertrees( CV_ERTREES, "slertrees" );\r
-\r
-/* End of file. */\r
+++ /dev/null
-#!/usr/bin/octave -q
-
-addpath(getenv("OCTAVEPATH"));
-
-highgui;
-cv;
-
-I=cvLoadImage("frame.jpg");
-a=cv2im(I);
-I2=im2cv(a, CV_8UC(1));
-
-imshow(cv2im(I));
-imshow(cv2im(I2));
-
-a=rand(3,3,3);
-b=mat2cv(a,CV_64FC(1));
-c=cv2mat(b);
-assert(all(a==c));
-
-a=eye(3);
-b=mat2cv(a,CV_64FC(1));
-c=cv2mat(b);
-assert(all(a==c));
-
-assert(all(cv2mat(mat2cv(eye(3),6))==eye(3)));
-
-I=cvLoadImage("frame.jpg");
-a=cv2im(I);
-I2=cvCloneImage(I);
-cvSobel(I,I2,2,2);
-imshow(cv2im(I2));
-
-imshow(a);
projects / profile / ivi / opencv.git / commitdiff
