--- /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:
+ virtual void run( int start_from )
+ {
+ const float maxPtDif = 1.f;
+ const float maxSizeDif = 1.f;
+ const float maxAngleDif = 2.f;
+ const float maxResponseDif = 0.1f;
+
+ string imgFilename = string(ts->get_data_path()) + FEATURES2D_DIR + "/" + IMAGE_FILENAME;
+ string resFilename = string(ts->get_data_path()) + DETECTOR_DIR + "/" + string(name) + "_res.xml.gz";
+
+ if( fdetector.empty() )
+ {
+ ts->printf( CvTS::LOG, "Feature detector is empty" );
+ ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA );
+ return;
+ }
+
+ Mat image = imread( imgFilename, 0 );
+ 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 );
+
+ vector<KeyPoint> calcKeypoints;
+ fdetector->detect( image, calcKeypoints );
+
+ if( fs.isOpened() ) // compare computed and valid keypoints
+ {
+ // TODO compare saved feature detector params with current ones
+ vector<KeyPoint> validKeypoints;
+ read( fs["keypoints"], validKeypoints );
+ if( validKeypoints.empty() )
+ {
+ ts->printf( CvTS::LOG, "Keypoints can nod be read\n" );
+ ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA );
+ 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 = norm( calcKeypoints[c].pt - validKeypoints[v].pt );
+ if( curDist < minDist )
+ {
+ minDist = curDist;
+ nearestIdx = c;
+ }
+ }
+
+ if( minDist > maxPtDif ||
+ fabs(calcKeypoints[nearestIdx].size - validKeypoints[v].size) > maxSizeDif ||
+ abs(calcKeypoints[nearestIdx].angle - validKeypoints[v].angle) > maxAngleDif ||
+ abs(calcKeypoints[nearestIdx].response - validKeypoints[v].response) > maxResponseDif ||
+ calcKeypoints[nearestIdx].octave != validKeypoints[v].octave
+
+ // TODO !!!!!!!
+ /*||
+ calcKeypoints[nearestIdx].class_id != validKeypoints[v].class_id*/ )
+ {
+ 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;
+ }
+ }
+ else // write
+ {
+ 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 );
+ }
+ }
+ ts->set_failed_test_info( CvTS::OK );
+ }
+
+ Ptr<FeatureDetector> fdetector;
+};
+
+CV_FeatureDetectorTest fastTest( "detector_fast", createFeatureDetector("FAST") );
+CV_FeatureDetectorTest gfttTest( "detector_gftt", createFeatureDetector("GFTT") );
+CV_FeatureDetectorTest harrisTest( "detector_harris", createFeatureDetector("HARRIS") );
+CV_FeatureDetectorTest mserTest( "detector_mser", createFeatureDetector("MSER") );
+CV_FeatureDetectorTest siftTest( "detector_sift", createFeatureDetector("SIFT") );
+CV_FeatureDetectorTest starTest( "detector_star", createFeatureDetector("STAR") );
+CV_FeatureDetectorTest surfTest( "detector_surf", createFeatureDetector("SURF") );
+
+/****************************************************************************************\
+* 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 );
+ fwrite( (void*)&mat.step, sizeof(int), 1, f );
+ fwrite( (void*)mat.data, 1, mat.step*mat.rows, f );
+ fclose(f);
+ }
+}
+
+static Mat readMatFromBin( const string& filename )
+{
+ FILE* f = fopen( filename.c_str(), "rb" );
+ if( f )
+ {
+ int rows, cols, type, step;
+ fread( (void*)&rows, sizeof(int), 1, f );
+ fread( (void*)&cols, sizeof(int), 1, f );
+ fread( (void*)&type, sizeof(int), 1, f );
+ fread( (void*)&step, sizeof(int), 1, f );
+
+ uchar* data = (uchar*)cvAlloc(step*rows);
+ fread( (void*)data, 1, step*rows, f );
+ fclose(f);
+
+ return Mat( rows, cols, type, data );
+ }
+ return Mat();
+}
+
+class CV_DescriptorExtractorTest : public CvTest
+{
+public:
+ CV_DescriptorExtractorTest( const char* testName, float _normDif, const Ptr<DescriptorExtractor>& _dextractor, float _prevTime ) :
+ CvTest( testName, "cv::DescriptorExtractor::compute" ), normDif(_normDif), prevTime(_prevTime), dextractor(_dextractor) {}
+protected:
+ virtual void createDescriptorExtractor() {}
+
+ void run(int)
+ {
+ createDescriptorExtractor();
+
+ if( dextractor.empty() )
+ {
+ ts->printf(CvTS::LOG, "Descriptor extractor is empty\n");
+ ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA );
+ return;
+ }
+
+ string imgFilename = string(ts->get_data_path()) + FEATURES2D_DIR + "/" + IMAGE_FILENAME;
+ Mat img = imread( imgFilename, 0 );
+ 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 );
+ 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;
+ }
+ }
+
+ 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 );
+
+ // TODO read and write descriptor extractor parameters and check them
+ Mat validDescriptors = readDescriptors();
+ if( !validDescriptors.empty() )
+ {
+ double normVal = norm( calcDescriptors, validDescriptors, NORM_INF );
+ ts->printf( CvTS::LOG, "nofm (inf) BTW valid and calculated float descriptors = %f\n", normVal );
+ if( normVal > normDif )
+ ts->set_failed_test_info( CvTS::FAIL_BAD_ACCURACY );
+ }
+ 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;
+ }
+ }
+ }
+
+ 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 float normDif;
+ const float prevTime;
+
+ Ptr<DescriptorExtractor> dextractor;
+};
+
+template<typename T>
+class CV_CalonderDescriptorExtractorTest : public CV_DescriptorExtractorTest
+{
+public:
+ CV_CalonderDescriptorExtractorTest( const char* testName, float _normDif, float _prevTime ) :
+ CV_DescriptorExtractorTest( testName, _normDif, Ptr<DescriptorExtractor>(), _prevTime )
+ {}
+
+ virtual void createDescriptorExtractor()
+ {
+ dextractor = new CalonderDescriptorExtractor<T>( string(ts->get_data_path()) + FEATURES2D_DIR + "/calonder_classifier.rtc");
+ }
+};
+
+CV_DescriptorExtractorTest siftDescriptorTest( "descriptor_sift", std::numeric_limits<float>::epsilon(),
+ createDescriptorExtractor("SIFT"), 8.06652f );
+CV_DescriptorExtractorTest surfDescriptorTest( "descriptor_surf", std::numeric_limits<float>::epsilon(),
+ createDescriptorExtractor("SURF"), 0.147372f );
+#if CV_SSE2
+CV_CalonderDescriptorExtractorTest<uchar> ucharCalonderTest( "descriptor_calonder_uchar",
+ std::numeric_limits<float>::epsilon() + 1,
+ 0.0132175f );
+CV_CalonderDescriptorExtractorTest<float> floatCalonderTest( "descriptor_calonder_float",
+ std::numeric_limits<float>::epsilon(),
+ 0.0221308f );
+#endif // CV_SSE2
projects / platform / upstream / opencv.git / commitdiff