/*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 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_CannyTest canny_test; /* End of file. */