--- /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 "test_precomp.hpp"
+#include "_modelest.h"
+
+using namespace cv;
+
+class BareModelEstimator : public CvModelEstimator2
+{
+public:
+ BareModelEstimator(int modelPoints, CvSize modelSize, int maxBasicSolutions);
+
+ virtual int runKernel( const CvMat*, const CvMat*, CvMat* );
+ virtual void computeReprojError( const CvMat*, const CvMat*,
+ const CvMat*, CvMat* );
+
+ bool checkSubsetPublic( const CvMat* ms1, int count, bool checkPartialSubset );
+};
+
+BareModelEstimator::BareModelEstimator(int _modelPoints, CvSize _modelSize, int _maxBasicSolutions)
+ :CvModelEstimator2(_modelPoints, _modelSize, _maxBasicSolutions)
+{
+}
+
+int BareModelEstimator::runKernel( const CvMat*, const CvMat*, CvMat* )
+{
+ return 0;
+}
+
+void BareModelEstimator::computeReprojError( const CvMat*, const CvMat*,
+ const CvMat*, CvMat* )
+{
+}
+
+bool BareModelEstimator::checkSubsetPublic( const CvMat* ms1, int count, bool checkPartialSubset )
+{
+ checkPartialSubsets = checkPartialSubset;
+ return checkSubset(ms1, count);
+}
+
+class CV_ModelEstimator2_Test : public cvtest::ArrayTest
+{
+public:
+ CV_ModelEstimator2_Test();
+
+protected:
+ void get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types );
+ void fill_array( int test_case_idx, int i, int j, Mat& arr );
+ double get_success_error_level( int test_case_idx, int i, int j );
+ void run_func();
+ void prepare_to_validation( int test_case_idx );
+
+ bool checkPartialSubsets;
+ int usedPointsCount;
+
+ bool checkSubsetResult;
+ int generalPositionsCount;
+ int maxPointsCount;
+};
+
+CV_ModelEstimator2_Test::CV_ModelEstimator2_Test()
+{
+ generalPositionsCount = get_test_case_count() / 2;
+ maxPointsCount = 100;
+
+ test_array[INPUT].push_back(NULL);
+ test_array[OUTPUT].push_back(NULL);
+ test_array[REF_OUTPUT].push_back(NULL);
+}
+
+void CV_ModelEstimator2_Test::get_test_array_types_and_sizes( int /*test_case_idx*/,
+ vector<vector<Size> > &sizes, vector<vector<int> > &types )
+{
+ RNG &rng = ts->get_rng();
+ checkPartialSubsets = (cvtest::randInt(rng) % 2 == 0);
+
+ int pointsCount = cvtest::randInt(rng) % maxPointsCount;
+ usedPointsCount = pointsCount == 0 ? 0 : cvtest::randInt(rng) % pointsCount;
+
+ sizes[INPUT][0] = cvSize(1, pointsCount);
+ types[INPUT][0] = CV_64FC2;
+
+ sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = cvSize(1, 1);
+ types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_8UC1;
+}
+
+void CV_ModelEstimator2_Test::fill_array( int test_case_idx, int i, int j, Mat& arr )
+{
+ if( i != INPUT )
+ {
+ cvtest::ArrayTest::fill_array( test_case_idx, i, j, arr );
+ return;
+ }
+
+ if (test_case_idx < generalPositionsCount)
+ {
+ //generate points in a general position (i.e. no three points can lie on the same line.)
+
+ bool isGeneralPosition;
+ do
+ {
+ ArrayTest::fill_array(test_case_idx, i, j, arr);
+
+ //a simple check that the position is general:
+ // for each line check that all other points don't belong to it
+ isGeneralPosition = true;
+ for (int startPointIndex = 0; startPointIndex < usedPointsCount && isGeneralPosition; startPointIndex++)
+ {
+ for (int endPointIndex = startPointIndex + 1; endPointIndex < usedPointsCount && isGeneralPosition; endPointIndex++)
+ {
+
+ for (int testPointIndex = 0; testPointIndex < usedPointsCount && isGeneralPosition; testPointIndex++)
+ {
+ if (testPointIndex == startPointIndex || testPointIndex == endPointIndex)
+ {
+ continue;
+ }
+
+ CV_Assert(arr.type() == CV_64FC2);
+ Point2d tangentVector_1 = arr.at<Point2d>(endPointIndex) - arr.at<Point2d>(startPointIndex);
+ Point2d tangentVector_2 = arr.at<Point2d>(testPointIndex) - arr.at<Point2d>(startPointIndex);
+
+ const float eps = 1e-4;
+ //TODO: perhaps it is better to normalize the cross product by norms of the tangent vectors
+ if (fabs(tangentVector_1.cross(tangentVector_2)) < eps)
+ {
+ isGeneralPosition = false;
+ }
+ }
+ }
+ }
+ }
+ while(!isGeneralPosition);
+ }
+ else
+ {
+ //create points in a degenerate position (there are at least 3 points belonging to the same line)
+
+ ArrayTest::fill_array(test_case_idx, i, j, arr);
+ if (usedPointsCount <= 2)
+ {
+ return;
+ }
+
+ RNG &rng = ts->get_rng();
+ int startPointIndex, endPointIndex, modifiedPointIndex;
+ do
+ {
+ startPointIndex = cvtest::randInt(rng) % usedPointsCount;
+ endPointIndex = cvtest::randInt(rng) % usedPointsCount;
+ modifiedPointIndex = checkPartialSubsets ? usedPointsCount - 1 : cvtest::randInt(rng) % usedPointsCount;
+ }
+ while (startPointIndex == endPointIndex || startPointIndex == modifiedPointIndex || endPointIndex == modifiedPointIndex);
+
+ double startWeight = cvtest::randReal(rng);
+ CV_Assert(arr.type() == CV_64FC2);
+ arr.at<Point2d>(modifiedPointIndex) = startWeight * arr.at<Point2d>(startPointIndex) + (1.0 - startWeight) * arr.at<Point2d>(endPointIndex);
+ }
+}
+
+
+double CV_ModelEstimator2_Test::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
+{
+ return 0;
+}
+
+void CV_ModelEstimator2_Test::prepare_to_validation( int test_case_idx )
+{
+ test_mat[OUTPUT][0].at<uchar>(0) = checkSubsetResult;
+ test_mat[REF_OUTPUT][0].at<uchar>(0) = test_case_idx < generalPositionsCount || usedPointsCount <= 2;
+}
+
+void CV_ModelEstimator2_Test::run_func()
+{
+ //make the input continuous
+ Mat input = test_mat[INPUT][0].clone();
+ CvMat _input = input;
+
+ RNG &rng = ts->get_rng();
+ int modelPoints = cvtest::randInt(rng);
+ CvSize modelSize = cvSize(2, modelPoints);
+ int maxBasicSolutions = cvtest::randInt(rng);
+ BareModelEstimator modelEstimator(modelPoints, modelSize, maxBasicSolutions);
+ checkSubsetResult = modelEstimator.checkSubsetPublic(&_input, usedPointsCount, checkPartialSubsets);
+}
+
+TEST(Calib3d_ModelEstimator2, accuracy) { CV_ModelEstimator2_Test test; test.safe_run(); }