/*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" using namespace cv; using namespace std; ///////////////////// base MHI class /////////////////////// class CV_MHIBaseTest : public cvtest::ArrayTest { public: CV_MHIBaseTest(); protected: void get_test_array_types_and_sizes( int test_case_idx, vector >& sizes, vector >& types ); void get_minmax_bounds( int i, int j, int type, Scalar& low, Scalar& 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() { timestamp = duration = 0; max_log_duration = 9; mhi_i = mhi_ref_i = -1; silh_ratio = 0.25; } void CV_MHIBaseTest::get_minmax_bounds( int i, int j, int type, Scalar& low, Scalar& high ) { cvtest::ArrayTest::get_minmax_bounds( i, j, type, low, high ); if( i == INPUT && CV_MAT_DEPTH(type) == CV_8U ) { low = Scalar::all(cvRound(-1./silh_ratio)+2.); high = Scalar::all(2); } else if( i == mhi_i || i == mhi_ref_i ) { low = Scalar::all(-exp(max_log_duration)); high = Scalar::all(0.); } } void CV_MHIBaseTest::get_test_array_types_and_sizes( int test_case_idx, vector >& sizes, vector >& types ) { RNG& rng = ts->get_rng(); cvtest::ArrayTest::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(cvtest::randReal(rng)*max_log_duration); timestamp = duration + cvtest::randReal(rng)*30.-10.; } int CV_MHIBaseTest::prepare_test_case( int test_case_idx ) { int code = cvtest::ArrayTest::prepare_test_case( test_case_idx ); if( code > 0 ) { Mat& mat = test_mat[mhi_i][0]; mat += Scalar::all(duration); cv::max(mat, 0, mat); if( mhi_i != mhi_ref_i ) { Mat& mat0 = test_mat[mhi_ref_i][0]; cvtest::copy( mat, mat0 ); } } return code; } ///////////////////// update motion history //////////////////////////// static void test_updateMHI( const Mat& silh, Mat& 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.ptr(i); float* mhi_row = mhi.ptr(i); 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() { test_array[INPUT].push_back(NULL); test_array[INPUT_OUTPUT].push_back(NULL); test_array[REF_INPUT_OUTPUT].push_back(NULL); mhi_i = INPUT_OUTPUT; mhi_ref_i = REF_INPUT_OUTPUT; } double CV_UpdateMHITest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ ) { return 0; } void CV_UpdateMHITest::run_func() { CvMat m = test_mat[INPUT_OUTPUT][0]; cv::updateMotionHistory( test_mat[INPUT][0], test_mat[INPUT_OUTPUT][0], timestamp, duration); m = test_mat[INPUT_OUTPUT][0]; } void CV_UpdateMHITest::prepare_to_validation( int /*test_case_idx*/ ) { //CvMat m0 = test_mat[REF_INPUT_OUTPUT][0]; test_updateMHI( test_mat[INPUT][0], test_mat[REF_INPUT_OUTPUT][0], timestamp, duration ); } ///////////////////// calc motion gradient //////////////////////////// static void test_MHIGradient( const Mat& mhi, Mat& mask, Mat& orientation, double delta1, double delta2, int aperture_size ) { Point anchor( aperture_size/2, aperture_size/2 ); double limit = 1e-4*aperture_size*aperture_size; Mat dx, dy, min_mhi, max_mhi; Mat kernel = cvtest::calcSobelKernel2D( 1, 0, aperture_size ); cvtest::filter2D( mhi, dx, CV_32F, kernel, anchor, 0, BORDER_REPLICATE ); kernel = cvtest::calcSobelKernel2D( 0, 1, aperture_size ); cvtest::filter2D( mhi, dy, CV_32F, kernel, anchor, 0, BORDER_REPLICATE ); kernel = Mat::ones(aperture_size, aperture_size, CV_8U); cvtest::erode(mhi, min_mhi, kernel, anchor, 0, BORDER_REPLICATE); cvtest::dilate(mhi, max_mhi, kernel, anchor, 0, BORDER_REPLICATE); if( delta1 > delta2 ) { double t; CV_SWAP( delta1, delta2, t ); } for( int i = 0; i < mhi.rows; i++ ) { uchar* mask_row = mask.ptr(i); float* orient_row = orientation.ptr(i); const float* dx_row = dx.ptr(i); const float* dy_row = dy.ptr(i); const float* min_row = min_mhi.ptr(i); const float* max_row = max_mhi.ptr(i); for( int 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; } } } } class CV_MHIGradientTest : public CV_MHIBaseTest { public: CV_MHIGradientTest(); protected: void get_test_array_types_and_sizes( int test_case_idx, vector >& sizes, vector >& types ); double get_success_error_level( int test_case_idx, int i, int j ); void run_func(); void prepare_to_validation( int ); double delta1, delta2, delta_range_log; int aperture_size; }; CV_MHIGradientTest::CV_MHIGradientTest() { mhi_i = mhi_ref_i = INPUT; test_array[INPUT].push_back(NULL); test_array[OUTPUT].push_back(NULL); test_array[OUTPUT].push_back(NULL); test_array[REF_OUTPUT].push_back(NULL); test_array[REF_OUTPUT].push_back(NULL); delta1 = delta2 = 0; aperture_size = 0; delta_range_log = 4; } void CV_MHIGradientTest::get_test_array_types_and_sizes( int test_case_idx, vector >& sizes, vector >& types ) { RNG& 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(cvtest::randReal(rng)*delta_range_log + 1.); delta2 = exp(cvtest::randReal(rng)*delta_range_log + 1.); aperture_size = (cvtest::randInt(rng)%3)*2+3; //duration = exp(cvtest::randReal(rng)*max_log_duration); //timestamp = duration + cvtest::randReal(rng)*30.-10.; } 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() { cv::calcMotionGradient(test_mat[INPUT][0], test_mat[OUTPUT][0], test_mat[OUTPUT][1], delta1, delta2, aperture_size ); //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*/ ) { test_MHIGradient( test_mat[INPUT][0], test_mat[REF_OUTPUT][0], test_mat[REF_OUTPUT][1], delta1, delta2, aperture_size ); test_mat[REF_OUTPUT][0] += Scalar::all(1); test_mat[OUTPUT][0] += Scalar::all(1); } ////////////////////// calc global orientation ///////////////////////// static double test_calcGlobalOrientation( const Mat& orient, const Mat& mask, const Mat& 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 = orient.ptr(y); const uchar* mask_data = mask.ptr(y); const float* mhi_data = mhi.ptr(y); 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 = orient.ptr(y); const float* mhi_data = mhi.ptr(y); const uchar* mask_data = mask.ptr(y); 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, vector >& sizes, vector >& types ); void get_minmax_bounds( int i, int j, int type, Scalar& low, Scalar& 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() { mhi_i = mhi_ref_i = INPUT; test_array[INPUT].push_back(NULL); test_array[INPUT].push_back(NULL); test_array[INPUT].push_back(NULL); min_angle = max_angle = 0; } void CV_MHIGlobalOrientTest::get_test_array_types_and_sizes( int test_case_idx, vector >& sizes, vector >& types ) { RNG& 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 = cvtest::randReal(rng)*359.9; max_angle = cvtest::randReal(rng)*359.9; if( min_angle >= max_angle ) { double t; CV_SWAP( min_angle, max_angle, t ); } max_angle += 0.1; duration = exp(cvtest::randReal(rng)*max_log_duration); timestamp = duration + cvtest::randReal(rng)*30.-10.; } void CV_MHIGlobalOrientTest::get_minmax_bounds( int i, int j, int type, Scalar& low, Scalar& high ) { CV_MHIBaseTest::get_minmax_bounds( i, j, type, low, high ); if( i == INPUT && j == 2 ) { low = Scalar::all(min_angle); high = Scalar::all(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 ); angle = cv::calcGlobalOrientation(test_mat[INPUT][2], test_mat[INPUT][1], test_mat[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 = test_calcGlobalOrientation( 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 = cvtest::TS::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( cvtest::TS::LOG, "The angle=%g is outside (%g,%g) range\n", angle, min_angle - err_level, max_angle + err_level ); code = cvtest::TS::FAIL_BAD_ACCURACY; } else if( fabs(angle - ref_angle) > err_level && fabs(360 - fabs(angle - ref_angle)) > err_level ) { ts->printf( cvtest::TS::LOG, "The angle=%g differs too much from reference value=%g\n", angle, ref_angle ); code = cvtest::TS::FAIL_BAD_ACCURACY; } if( code < 0 ) ts->set_failed_test_info( code ); return code; } TEST(Video_MHIUpdate, accuracy) { CV_UpdateMHITest test; test.safe_run(); } TEST(Video_MHIGradient, accuracy) { CV_MHIGradientTest test; test.safe_run(); } TEST(Video_MHIGlobalOrient, accuracy) { CV_MHIGlobalOrientTest test; test.safe_run(); }