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 #include "opencv2/imgproc/imgproc_c.h" 44 #include <limits> 45 #include "test_chessboardgenerator.hpp" 46 47 using namespace std; 48 using namespace cv; 49 50 class CV_ChessboardSubpixelTest : public cvtest::BaseTest 51 { 52 public: 53 CV_ChessboardSubpixelTest(); 54 55 protected: 56 Mat intrinsic_matrix_; 57 Mat distortion_coeffs_; 58 Size image_size_; 59 60 void run(int); 61 void generateIntrinsicParams(); 62 }; 63 64 65 int calcDistance(const vector<Point2f>& set1, const vector<Point2f>& set2, double& mean_dist) 66 { 67 if(set1.size() != set2.size()) 68 { 69 return 0; 70 } 71 72 std::vector<int> indices; 73 double sum_dist = 0.0; 74 for(size_t i = 0; i < set1.size(); i++) 75 { 76 double min_dist = std::numeric_limits<double>::max(); 77 int min_idx = -1; 78 79 for(int j = 0; j < (int)set2.size(); j++) 80 { 81 double dist = norm(set1[i] - set2[j]); 82 if(dist < min_dist) 83 { 84 min_idx = j; 85 min_dist = dist; 86 } 87 } 88 89 // check validity of min_idx 90 if(min_idx == -1) 91 { 92 return 0; 93 } 94 std::vector<int>::iterator it = std::find(indices.begin(), indices.end(), min_idx); 95 if(it != indices.end()) 96 { 97 // there are two points in set1 corresponding to the same point in set2 98 return 0; 99 } 100 indices.push_back(min_idx); 101 102 // printf("dist %d = %f\n", (int)i, min_dist); 103 104 sum_dist += min_dist*min_dist; 105 } 106 107 mean_dist = sqrt(sum_dist/set1.size()); 108 // printf("sum_dist = %f, set1.size() = %d, mean_dist = %f\n", sum_dist, (int)set1.size(), mean_dist); 109 110 return 1; 111 } 112 113 CV_ChessboardSubpixelTest::CV_ChessboardSubpixelTest() : 114 intrinsic_matrix_(Size(3, 3), CV_64FC1), distortion_coeffs_(Size(1, 4), CV_64FC1), 115 image_size_(640, 480) 116 { 117 } 118 119 /* ///////////////////// chess_corner_test ///////////////////////// */ 120 void CV_ChessboardSubpixelTest::run( int ) 121 { 122 int code = cvtest::TS::OK; 123 int progress = 0; 124 125 RNG& rng = ts->get_rng(); 126 127 const int runs_count = 20; 128 const int max_pattern_size = 8; 129 const int min_pattern_size = 5; 130 Mat bg(image_size_, CV_8UC1); 131 bg = Scalar(0); 132 133 double sum_dist = 0.0; 134 int count = 0; 135 for(int i = 0; i < runs_count; i++) 136 { 137 const int pattern_width = min_pattern_size + cvtest::randInt(rng) % (max_pattern_size - min_pattern_size); 138 const int pattern_height = min_pattern_size + cvtest::randInt(rng) % (max_pattern_size - min_pattern_size); 139 Size pattern_size; 140 if(pattern_width > pattern_height) 141 { 142 pattern_size = Size(pattern_height, pattern_width); 143 } 144 else 145 { 146 pattern_size = Size(pattern_width, pattern_height); 147 } 148 ChessBoardGenerator gen_chessboard(Size(pattern_size.width + 1, pattern_size.height + 1)); 149 150 // generates intrinsic camera and distortion matrices 151 generateIntrinsicParams(); 152 153 vector<Point2f> corners; 154 Mat chessboard_image = gen_chessboard(bg, intrinsic_matrix_, distortion_coeffs_, corners); 155 156 vector<Point2f> test_corners; 157 bool result = findChessboardCorners(chessboard_image, pattern_size, test_corners, 15); 158 if(!result) 159 { 160 #if 0 161 ts->printf(cvtest::TS::LOG, "Warning: chessboard was not detected! Writing image to test.png\n"); 162 ts->printf(cvtest::TS::LOG, "Size = %d, %d\n", pattern_size.width, pattern_size.height); 163 ts->printf(cvtest::TS::LOG, "Intrinsic params: fx = %f, fy = %f, cx = %f, cy = %f\n", 164 intrinsic_matrix_.at<double>(0, 0), intrinsic_matrix_.at<double>(1, 1), 165 intrinsic_matrix_.at<double>(0, 2), intrinsic_matrix_.at<double>(1, 2)); 166 ts->printf(cvtest::TS::LOG, "Distortion matrix: %f, %f, %f, %f, %f\n", 167 distortion_coeffs_.at<double>(0, 0), distortion_coeffs_.at<double>(0, 1), 168 distortion_coeffs_.at<double>(0, 2), distortion_coeffs_.at<double>(0, 3), 169 distortion_coeffs_.at<double>(0, 4)); 170 171 imwrite("test.png", chessboard_image); 172 #endif 173 continue; 174 } 175 176 double dist1 = 0.0; 177 int ret = calcDistance(corners, test_corners, dist1); 178 if(ret == 0) 179 { 180 ts->printf(cvtest::TS::LOG, "findChessboardCorners returns invalid corner coordinates!\n"); 181 code = cvtest::TS::FAIL_INVALID_OUTPUT; 182 break; 183 } 184 185 IplImage chessboard_image_header = chessboard_image; 186 cvFindCornerSubPix(&chessboard_image_header, (CvPoint2D32f*)&test_corners[0], 187 (int)test_corners.size(), cvSize(3, 3), cvSize(1, 1), cvTermCriteria(CV_TERMCRIT_EPS|CV_TERMCRIT_ITER,300,0.1)); 188 find4QuadCornerSubpix(chessboard_image, test_corners, Size(5, 5)); 189 190 double dist2 = 0.0; 191 ret = calcDistance(corners, test_corners, dist2); 192 if(ret == 0) 193 { 194 ts->printf(cvtest::TS::LOG, "findCornerSubpix returns invalid corner coordinates!\n"); 195 code = cvtest::TS::FAIL_INVALID_OUTPUT; 196 break; 197 } 198 199 ts->printf(cvtest::TS::LOG, "Error after findChessboardCorners: %f, after findCornerSubPix: %f\n", 200 dist1, dist2); 201 sum_dist += dist2; 202 count++; 203 204 const double max_reduce_factor = 0.8; 205 if(dist1 < dist2*max_reduce_factor) 206 { 207 ts->printf(cvtest::TS::LOG, "findCornerSubPix increases average error!\n"); 208 code = cvtest::TS::FAIL_INVALID_OUTPUT; 209 break; 210 } 211 212 progress = update_progress( progress, i-1, runs_count, 0 ); 213 } 214 ASSERT_NE(0, count); 215 sum_dist /= count; 216 ts->printf(cvtest::TS::LOG, "Average error after findCornerSubpix: %f\n", sum_dist); 217 218 if( code < 0 ) 219 ts->set_failed_test_info( code ); 220 } 221 222 void CV_ChessboardSubpixelTest::generateIntrinsicParams() 223 { 224 RNG& rng = ts->get_rng(); 225 const double max_focus_length = 1000.0; 226 const double max_focus_diff = 5.0; 227 228 double fx = cvtest::randReal(rng)*max_focus_length; 229 double fy = fx + cvtest::randReal(rng)*max_focus_diff; 230 double cx = image_size_.width/2; 231 double cy = image_size_.height/2; 232 233 double k1 = 0.5*cvtest::randReal(rng); 234 double k2 = 0.05*cvtest::randReal(rng); 235 double p1 = 0.05*cvtest::randReal(rng); 236 double p2 = 0.05*cvtest::randReal(rng); 237 double k3 = 0.0; 238 239 intrinsic_matrix_ = (Mat_<double>(3, 3) << fx, 0.0, cx, 0.0, fy, cy, 0.0, 0.0, 1.0); 240 distortion_coeffs_ = (Mat_<double>(1, 5) << k1, k2, p1, p2, k3); 241 } 242 243 TEST(Calib3d_ChessboardSubPixDetector, accuracy) { CV_ChessboardSubpixelTest test; test.safe_run(); } 244 245 /* End of file. */ 246
