1 /*M/////////////////////////////////////////////////////////////////////////////////////// 2 // 3 // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. 4 // 5 // By downloading, copying, installing or using the software you agree to this license. 6 // If you do not agree to this license, do not download, install, 7 // copy or use the software. 8 // 9 // 10 // Intel License Agreement 11 // For Open Source Computer Vision Library 12 // 13 // Copyright (C) 2000, Intel Corporation, all rights reserved. 14 // Third party copyrights are property of their respective owners. 15 // 16 // Redistribution and use in source and binary forms, with or without modification, 17 // are permitted provided that the following conditions are met: 18 // 19 // * Redistribution's of source code must retain the above copyright notice, 20 // this list of conditions and the following disclaimer. 21 // 22 // * Redistribution's in binary form must reproduce the above copyright notice, 23 // this list of conditions and the following disclaimer in the documentation 24 // and/or other materials provided with the distribution. 25 // 26 // * The name of Intel Corporation may not be used to endorse or promote products 27 // derived from this software without specific prior written permission. 28 // 29 // This software is provided by the copyright holders and contributors "as is" and 30 // any express or implied warranties, including, but not limited to, the implied 31 // warranties of merchantability and fitness for a particular purpose are disclaimed. 32 // In no event shall the Intel Corporation or contributors be liable for any direct, 33 // indirect, incidental, special, exemplary, or consequential damages 34 // (including, but not limited to, procurement of substitute goods or services; 35 // loss of use, data, or profits; or business interruption) however caused 36 // and on any theory of liability, whether in contract, strict liability, 37 // or tort (including negligence or otherwise) arising in any way out of 38 // the use of this software, even if advised of the possibility of such damage. 39 // 40 //M*/ 41 42 #include "test_precomp.hpp" 43 44 using namespace cv; 45 using namespace std; 46 47 class CV_CannyTest : public cvtest::ArrayTest 48 { 49 public: 50 CV_CannyTest(); 51 52 protected: 53 void get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types ); 54 double get_success_error_level( int test_case_idx, int i, int j ); 55 int prepare_test_case( int test_case_idx ); 56 void run_func(); 57 void prepare_to_validation( int ); 58 int validate_test_results( int /*test_case_idx*/ ); 59 60 int aperture_size; 61 bool use_true_gradient; 62 double threshold1, threshold2; 63 bool test_cpp; 64 }; 65 66 67 CV_CannyTest::CV_CannyTest() 68 { 69 test_array[INPUT].push_back(NULL); 70 test_array[OUTPUT].push_back(NULL); 71 test_array[REF_OUTPUT].push_back(NULL); 72 element_wise_relative_error = true; 73 aperture_size = 0; 74 use_true_gradient = false; 75 threshold1 = threshold2 = 0; 76 77 test_cpp = false; 78 } 79 80 81 void CV_CannyTest::get_test_array_types_and_sizes( int test_case_idx, 82 vector<vector<Size> >& sizes, 83 vector<vector<int> >& types ) 84 { 85 RNG& rng = ts->get_rng(); 86 double thresh_range; 87 88 cvtest::ArrayTest::get_test_array_types_and_sizes( test_case_idx, sizes, types ); 89 types[INPUT][0] = types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_8U; 90 91 aperture_size = cvtest::randInt(rng) % 2 ? 5 : 3; 92 thresh_range = aperture_size == 3 ? 300 : 1000; 93 94 threshold1 = cvtest::randReal(rng)*thresh_range; 95 threshold2 = cvtest::randReal(rng)*thresh_range*0.3; 96 97 if( cvtest::randInt(rng) % 2 ) 98 CV_SWAP( threshold1, threshold2, thresh_range ); 99 100 use_true_gradient = cvtest::randInt(rng) % 2 != 0; 101 test_cpp = (cvtest::randInt(rng) & 256) == 0; 102 } 103 104 105 int CV_CannyTest::prepare_test_case( int test_case_idx ) 106 { 107 int code = cvtest::ArrayTest::prepare_test_case( test_case_idx ); 108 if( code > 0 ) 109 { 110 Mat& src = test_mat[INPUT][0]; 111 GaussianBlur(src, src, Size(11, 11), 5, 5); 112 } 113 114 return code; 115 } 116 117 118 double CV_CannyTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ ) 119 { 120 return 0; 121 } 122 123 124 void CV_CannyTest::run_func() 125 { 126 if(!test_cpp) 127 cvCanny( test_array[INPUT][0], test_array[OUTPUT][0], threshold1, threshold2, 128 aperture_size + (use_true_gradient ? CV_CANNY_L2_GRADIENT : 0)); 129 else 130 { 131 cv::Mat _out = cv::cvarrToMat(test_array[OUTPUT][0]); 132 cv::Canny(cv::cvarrToMat(test_array[INPUT][0]), _out, threshold1, threshold2, 133 aperture_size + (use_true_gradient ? CV_CANNY_L2_GRADIENT : 0)); 134 } 135 } 136 137 138 static void 139 cannyFollow( int x, int y, float lowThreshold, const Mat& mag, Mat& dst ) 140 { 141 static const int ofs[][2] = {{1,0},{1,-1},{0,-1},{-1,-1},{-1,0},{-1,1},{0,1},{1,1}}; 142 int i; 143 144 dst.at<uchar>(y, x) = (uchar)255; 145 146 for( i = 0; i < 8; i++ ) 147 { 148 int x1 = x + ofs[i][0]; 149 int y1 = y + ofs[i][1]; 150 if( (unsigned)x1 < (unsigned)mag.cols && 151 (unsigned)y1 < (unsigned)mag.rows && 152 mag.at<float>(y1, x1) > lowThreshold && 153 !dst.at<uchar>(y1, x1) ) 154 cannyFollow( x1, y1, lowThreshold, mag, dst ); 155 } 156 } 157 158 159 static void 160 test_Canny( const Mat& src, Mat& dst, 161 double threshold1, double threshold2, 162 int aperture_size, bool use_true_gradient ) 163 { 164 int m = aperture_size; 165 Point anchor(m/2, m/2); 166 const double tan_pi_8 = tan(CV_PI/8.); 167 const double tan_3pi_8 = tan(CV_PI*3/8); 168 float lowThreshold = (float)MIN(threshold1, threshold2); 169 float highThreshold = (float)MAX(threshold1, threshold2); 170 171 int x, y, width = src.cols, height = src.rows; 172 173 Mat dxkernel = cvtest::calcSobelKernel2D( 1, 0, m, 0 ); 174 Mat dykernel = cvtest::calcSobelKernel2D( 0, 1, m, 0 ); 175 Mat dx, dy, mag(height, width, CV_32F); 176 cvtest::filter2D(src, dx, CV_16S, dxkernel, anchor, 0, BORDER_REPLICATE); 177 cvtest::filter2D(src, dy, CV_16S, dykernel, anchor, 0, BORDER_REPLICATE); 178 179 // calc gradient magnitude 180 for( y = 0; y < height; y++ ) 181 { 182 for( x = 0; x < width; x++ ) 183 { 184 int dxval = dx.at<short>(y, x), dyval = dy.at<short>(y, x); 185 mag.at<float>(y, x) = use_true_gradient ? 186 (float)sqrt((double)(dxval*dxval + dyval*dyval)) : 187 (float)(fabs((double)dxval) + fabs((double)dyval)); 188 } 189 } 190 191 // calc gradient direction, do nonmaxima suppression 192 for( y = 0; y < height; y++ ) 193 { 194 for( x = 0; x < width; x++ ) 195 { 196 197 float a = mag.at<float>(y, x), b = 0, c = 0; 198 int y1 = 0, y2 = 0, x1 = 0, x2 = 0; 199 200 if( a <= lowThreshold ) 201 continue; 202 203 int dxval = dx.at<short>(y, x); 204 int dyval = dy.at<short>(y, x); 205 206 double tg = dxval ? (double)dyval/dxval : DBL_MAX*CV_SIGN(dyval); 207 208 if( fabs(tg) < tan_pi_8 ) 209 { 210 y1 = y2 = y; x1 = x + 1; x2 = x - 1; 211 } 212 else if( tan_pi_8 <= tg && tg <= tan_3pi_8 ) 213 { 214 y1 = y + 1; y2 = y - 1; x1 = x + 1; x2 = x - 1; 215 } 216 else if( -tan_3pi_8 <= tg && tg <= -tan_pi_8 ) 217 { 218 y1 = y - 1; y2 = y + 1; x1 = x + 1; x2 = x - 1; 219 } 220 else 221 { 222 assert( fabs(tg) > tan_3pi_8 ); 223 x1 = x2 = x; y1 = y + 1; y2 = y - 1; 224 } 225 226 if( (unsigned)y1 < (unsigned)height && (unsigned)x1 < (unsigned)width ) 227 b = (float)fabs(mag.at<float>(y1, x1)); 228 229 if( (unsigned)y2 < (unsigned)height && (unsigned)x2 < (unsigned)width ) 230 c = (float)fabs(mag.at<float>(y2, x2)); 231 232 if( (a > b || (a == b && ((x1 == x+1 && y1 == y) || (x1 == x && y1 == y+1)))) && a > c ) 233 ; 234 else 235 mag.at<float>(y, x) = -a; 236 } 237 } 238 239 dst = Scalar::all(0); 240 241 // hysteresis threshold 242 for( y = 0; y < height; y++ ) 243 { 244 for( x = 0; x < width; x++ ) 245 if( mag.at<float>(y, x) > highThreshold && !dst.at<uchar>(y, x) ) 246 cannyFollow( x, y, lowThreshold, mag, dst ); 247 } 248 } 249 250 251 void CV_CannyTest::prepare_to_validation( int ) 252 { 253 Mat src = test_mat[INPUT][0], dst = test_mat[REF_OUTPUT][0]; 254 test_Canny( src, dst, threshold1, threshold2, aperture_size, use_true_gradient ); 255 } 256 257 258 int CV_CannyTest::validate_test_results( int test_case_idx ) 259 { 260 int code = cvtest::TS::OK, nz0; 261 prepare_to_validation(test_case_idx); 262 263 double err = cvtest::norm(test_mat[OUTPUT][0], test_mat[REF_OUTPUT][0], CV_L1); 264 if( err == 0 ) 265 return code; 266 267 if( err != cvRound(err) || cvRound(err)%255 != 0 ) 268 { 269 ts->printf( cvtest::TS::LOG, "Some of the pixels, produced by Canny, are not 0's or 255's; the difference is %g\n", err ); 270 ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT ); 271 return code; 272 } 273 274 nz0 = cvRound(cvtest::norm(test_mat[REF_OUTPUT][0], CV_L1)/255); 275 err = (err/255/MAX(nz0,100))*100; 276 if( err > 1 ) 277 { 278 ts->printf( cvtest::TS::LOG, "Too high percentage of non-matching edge pixels = %g%%\n", err); 279 ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY ); 280 } 281 282 return code; 283 } 284 285 TEST(Imgproc_Canny, accuracy) { CV_CannyTest test; test.safe_run(); } 286 287 /* End of file. */ 288
