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@ -13,11 +13,12 @@ |
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#define MESSAGE_REPROJ_DIFF_2 "Reprojection error is not optimal." |
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#define MESSAGE_RANSAC_MASK_1 "Sizes of inliers/outliers mask are incorrect." |
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#define MESSAGE_RANSAC_MASK_2 "Mask mustn't have any outliers." |
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#define MESSAGE_RANSAC_MASK_3 "Mask of inliers/outliers is incorrect." |
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#define MESSAGE_RANSAC_MASK_4 "Inlier in original mask shouldn't be outlier in found mask." |
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#define MESSAGE_RANSAC_MASK_3 "All values of mask must be 1 (true) or 0 (false)." |
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#define MESSAGE_RANSAC_MASK_4 "Mask of inliers/outliers is incorrect." |
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#define MESSAGE_RANSAC_MASK_5 "Inlier in original mask shouldn't be outlier in found mask." |
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#define MESSAGE_RANSAC_DIFF "Reprojection error for current pair of points more than required." |
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#define MAX_COUNT_OF_POINTS 500 |
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#define MAX_COUNT_OF_POINTS 303 |
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#define COUNT_NORM_TYPES 3 |
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#define METHODS_COUNT 3 |
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@ -63,17 +64,24 @@ class CV_HomographyTest: public cvtest::ArrayTest |
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bool check_matrix_size(const cv::Mat& H); |
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bool check_matrix_diff(const cv::Mat& original, const cv::Mat& found, const int norm_type, double &diff); |
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// bool check_reproj_error(const cv::Mat& src_3d, const cv::Mat& dst_3d, const int norm_type = NORM_L2);
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bool check_ransac_mask_1(const Mat& src, const Mat& mask); |
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bool check_ransac_mask_2(const Mat& original_mask, const Mat& found_mask); |
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int check_ransac_mask_1(const Mat& src, const Mat& mask); |
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int check_ransac_mask_2(const Mat& original_mask, const Mat& found_mask); |
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void print_information_1(int j, int N, int method, const Mat& H); |
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void print_information_2(int j, int N, int method, const Mat& H, const Mat& H_res, int k, double diff); |
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void print_information_3(int j, int N, const Mat& mask); |
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void print_information_4(int method, int j, int N, int k, int l, double diff); |
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void print_information_5(int method, int j, int N, int l, double diff); |
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void print_information_6(int j, int N, int k, double diff, bool value); |
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void print_information_7(int j, int N, int k, double diff, bool original_value, bool found_value); |
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void print_information_8(int j, int N, int k, int l, double diff); |
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void check_transform_quality(cv::InputArray src_points, cv::InputArray dst_poits, const cv::Mat& H, const int norm_type = NORM_L2); |
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void check_transform_quality(const cv::InputArray src_points, const vector <cv::Point2f> dst_points, const cv::Mat& H, const int norm_type = NORM_L2); |
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void check_transform_quality(const vector <cv::Point2f> src_points, const cv::InputArray dst_points, const cv::Mat& H, const int norm_type = NORM_L2);
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void check_transform_quality(const vector <cv::Point2f> src_points, const vector <cv::Point2f> dst_points, const cv::Mat& H, const int norm_type = NORM_L2); |
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}; |
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/* void CV_HomographyTest::run_func () {} */ |
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CV_HomographyTest::CV_HomographyTest() : max_diff(1e-2), max_2diff(2e-2) |
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{ |
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test_array[INPUT].push_back(NULL); |
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@ -536,28 +544,126 @@ bool CV_HomographyTest::check_matrix_diff(const cv::Mat& original, const cv::Mat |
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return diff <= max_diff; |
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} |
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bool CV_HomographyTest::check_ransac_mask_1(const Mat& src, const Mat& mask) |
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int CV_HomographyTest::check_ransac_mask_1(const Mat& src, const Mat& mask) |
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{ |
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if (!(mask.cols == 1) && (mask.rows == src.cols)) |
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{ |
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CV_Error(CALIB3D_HOMOGRAPHY_ERROR_RANSAC_MASK, MESSAGE_RANSAC_MASK_1); |
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return false; |
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} |
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if (countNonZero(mask) < mask.rows) |
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{ |
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CV_Error(CALIB3D_HOMOGRAPHY_ERROR_RANSAC_MASK, MESSAGE_RANSAC_MASK_2); |
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return false; |
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} |
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return true; |
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if (!(mask.cols == 1) && (mask.rows == src.cols)) return 1; |
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if (countNonZero(mask) < mask.rows) return 2; |
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for (size_t i = 0; i < mask.rows; ++i) if (mask.at<uchar>(i, 0) > 1) return 3; |
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return 0; |
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} |
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bool CV_HomographyTest::check_ransac_mask_2(const Mat& original_mask, const Mat& found_mask) |
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int CV_HomographyTest::check_ransac_mask_2(const Mat& original_mask, const Mat& found_mask) |
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{ |
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if (!(found_mask.cols == 1) && (found_mask.rows == original_mask.rows)) |
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{ |
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CV_Error(CALIB3D_HOMOGRAPHY_ERROR_RANSAC_MASK, MESSAGE_RANSAC_MASK_1); |
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return false; |
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}
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if (!(found_mask.cols == 1) && (found_mask.rows == original_mask.rows)) return 1; |
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for (size_t i = 0; i < found_mask.rows; ++i) if (found_mask.at<uchar>(i, 0) > 1) return 2; |
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return 0; |
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} |
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void CV_HomographyTest::print_information_1(int j, int N, int method, const Mat& H) |
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{ |
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cout << endl; cout << "Checking for homography matrix sizes..." << endl; cout << endl; |
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cout << "Type of srcPoints: "; if (0 <= j < 2) cout << "Mat of CV_32FC2"; else cout << "vector <Point2f>";
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cout << " Type of dstPoints: "; if (j % 2 == 0) cout << "Mat of CV_32FC2"; else cout << "vector <Point2f>"; cout << endl; |
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cout << "Count of points: " << N << endl; cout << endl; |
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cout << "Method: "; if (method == 0) cout << 0; else if (method == 8) cout << "RANSAC"; else cout << "LMEDS"; cout << endl; |
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cout << "Homography matrix:" << endl; cout << endl; |
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cout << H << endl; cout << endl; |
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cout << "Number of rows: " << H.rows << " Number of cols: " << H.cols << endl; cout << endl; |
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} |
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void CV_HomographyTest::print_information_2(int j, int N, int method, const Mat& H, const Mat& H_res, int k, double diff) |
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{ |
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cout << endl; cout << "Checking for accuracy of homography matrix computing..." << endl; cout << endl; |
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cout << "Type of srcPoints: "; if (0 <= j < 2) cout << "Mat of CV_32FC2"; else cout << "vector <Point2f>";
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cout << " Type of dstPoints: "; if (j % 2 == 0) cout << "Mat of CV_32FC2"; else cout << "vector <Point2f>"; cout << endl; |
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cout << "Count of points: " << N << endl; cout << endl; |
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cout << "Method: "; if (method == 0) cout << 0; else if (method == 8) cout << "RANSAC"; else cout << "LMEDS"; cout << endl; |
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cout << "Original matrix:" << endl; cout << endl; |
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cout << H << endl; cout << endl; |
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cout << "Found matrix:" << endl; cout << endl; |
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cout << H_res << endl; cout << endl; |
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cout << "Norm type using in criteria: "; if (NORM_TYPE[k] == 1) cout << "INF"; else if (NORM_TYPE[k] == 2) cout << "L1"; else cout << "L2"; cout << endl; |
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cout << "Difference between matrix: " << diff << endl; |
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cout << "Maximum allowed difference: " << max_diff << endl; cout << endl; |
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} |
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void CV_HomographyTest::print_information_3(int j, int N, const Mat& mask) |
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{ |
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cout << endl; cout << "Checking for inliers/outliers mask..." << endl; cout << endl; |
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cout << "Type of srcPoints: "; if (0 <= j < 2) cout << "Mat of CV_32FC2"; else cout << "vector <Point2f>";
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cout << " Type of dstPoints: "; if (j % 2 == 0) cout << "Mat of CV_32FC2"; else cout << "vector <Point2f>"; cout << endl; |
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cout << "Count of points: " << N << endl; cout << endl; |
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cout << "Method: RANSAC" << endl; |
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cout << "Found mask:" << endl; cout << endl; |
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cout << mask << endl; cout << endl; |
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cout << "Number of rows: " << mask.rows << " Number of cols: " << mask.cols << endl; cout << endl; |
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} |
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void CV_HomographyTest::print_information_4(int method, int j, int N, int k, int l, double diff) |
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{ |
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cout << endl; cout << "Checking for accuracy of reprojection error computing..." << endl; cout << endl; |
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cout << "Method: "; if (method == 0) cout << 0 << endl; else cout << "CV_LMEDS" << endl; |
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cout << "Type of srcPoints: "; if (0 <= j < 2) cout << "Mat of CV_32FC2"; else cout << "vector <Point2f>";
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cout << " Type of dstPoints: "; if (j % 2 == 0) cout << "Mat of CV_32FC2"; else cout << "vector <Point2f>"; cout << endl; |
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cout << "Sigma of normal noise: " << sigma << endl; |
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cout << "Count of points: " << N << endl; |
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cout << "Number of point: " << k << endl; |
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cout << "Norm type using in criteria: "; if (NORM_TYPE[l] == 1) cout << "INF"; else if (NORM_TYPE[l] == 2) cout << "L1"; else cout << "L2"; cout << endl; |
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cout << "Difference with noise of point: " << diff << endl;
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cout << "Maxumum allowed difference: " << max_2diff << endl; cout << endl; |
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} |
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void CV_HomographyTest::print_information_5(int method, int j, int N, int l, double diff) |
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{
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cout << endl; cout << "Checking for accuracy of reprojection error computing..." << endl; cout << endl; |
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cout << "Method: "; if (method == 0) cout << 0 << endl; else cout << "CV_LMEDS" << endl; |
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cout << "Type of srcPoints: "; if (0 <= j < 2) cout << "Mat of CV_32FC2"; else cout << "vector <Point2f>";
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cout << " Type of dstPoints: "; if (j % 2 == 0) cout << "Mat of CV_32FC2"; else cout << "vector <Point2f>"; cout << endl; |
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cout << "Sigma of normal noise: " << sigma << endl; |
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cout << "Count of points: " << N << endl; |
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cout << "Norm type using in criteria: "; if (NORM_TYPE[l] == 1) cout << "INF"; else if (NORM_TYPE[l] == 2) cout << "L1"; else cout << "L2"; cout << endl;
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cout << "Difference with noise of points: " << diff << endl;
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cout << "Maxumum allowed difference: " << max_diff << endl; cout << endl;
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} |
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void CV_HomographyTest::print_information_6(int j, int N, int k, double diff, bool value) |
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{ |
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cout << endl; cout << "Checking for inliers/outliers mask..." << endl; cout << endl; |
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cout << "Method: RANSAC" << endl; |
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cout << "Type of srcPoints: "; if (0 <= j < 2) cout << "Mat of CV_32FC2"; else cout << "vector <Point2f>";
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cout << " Type of dstPoints: "; if (j % 2 == 0) cout << "Mat of CV_32FC2"; else cout << "vector <Point2f>"; cout << endl; |
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cout << "Count of points: " << N << " " << endl;
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cout << "Number of point: " << k << " " << endl; |
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cout << "Reprojection error for this point: " << diff << " " << endl; |
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cout << "Reprojection error threshold: " << reproj_threshold << " " << endl; |
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cout << "Value of found mask: "<< value << endl; cout << endl; |
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} |
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void CV_HomographyTest::print_information_7(int j, int N, int k, double diff, bool original_value, bool found_value) |
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{ |
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cout << endl; cout << "Checking for inliers/outliers mask..." << endl; cout << endl; |
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cout << "Method: RANSAC" << endl; |
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cout << "Type of srcPoints: "; if (0 <= j < 2) cout << "Mat of CV_32FC2"; else cout << "vector <Point2f>";
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cout << " Type of dstPoints: "; if (j % 2 == 0) cout << "Mat of CV_32FC2"; else cout << "vector <Point2f>"; cout << endl; |
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cout << "Count of points: " << N << " " << endl;
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cout << "Number of point: " << k << " " << endl; |
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cout << "Reprojection error for this point: " << diff << " " << endl; |
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cout << "Reprojection error threshold: " << reproj_threshold << " " << endl; |
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cout << "Value of original mask: "<< original_value << " Value of found mask: " << found_value << endl; cout << endl; |
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} |
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void CV_HomographyTest::print_information_8(int j, int N, int k, int l, double diff) |
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{ |
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cout << endl; cout << "Checking for reprojection error of inlier..." << endl; cout << endl; |
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cout << "Method: RANSAC" << endl; |
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cout << "Sigma of normal noise: " << sigma << endl; |
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cout << "Type of srcPoints: "; if (0 <= j < 2) cout << "Mat of CV_32FC2"; else cout << "vector <Point2f>";
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cout << " Type of dstPoints: "; if (j % 2 == 0) cout << "Mat of CV_32FC2"; else cout << "vector <Point2f>"; cout << endl; |
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cout << "Count of points: " << N << " " << endl;
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cout << "Number of point: " << k << " " << endl; |
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cout << "Norm type using in criteria: "; if (NORM_TYPE[l] == 1) cout << "INF"; else if (NORM_TYPE[l] == 2) cout << "L1"; else cout << "L2"; cout << endl;
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cout << "Difference with noise of point: " << diff << endl; |
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cout << "Maxumum allowed difference: " << max_2diff << endl; cout << endl; |
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} |
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void CV_HomographyTest::check_transform_quality(cv::InputArray src_points, cv::InputArray dst_points, const cv::Mat& H, const int norm_type) |
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@ -588,18 +694,22 @@ void CV_HomographyTest::run(int) |
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src_data[2*i] = (float)cvtest::randReal(rng)*image_size; |
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src_data[2*i+1] = (float)cvtest::randReal(rng)*image_size; |
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} |
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cv::Mat src_mat_2f(1, N, CV_32FC2, src_data),
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src_mat_2d(2, N, CV_32F, src_data),
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src_mat_3d(3, N, CV_32F); |
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cv::Mat dst_mat_2f, dst_mat_2d, dst_mat_3d; |
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vector <Point2f> src_vec, dst_vec; |
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for (size_t i = 0; i < N; ++i) |
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{ |
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float *tmp = src_mat_2d.ptr<float>()+2*i; |
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src_mat_3d.at<float>(0, i) = tmp[0]; |
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src_mat_3d.at<float>(1, i) = tmp[1]; |
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src_mat_3d.at<float>(2, i) = 1.0f; |
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src_vec.push_back(Point2f(tmp[0], tmp[1])); |
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} |
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double fi = cvtest::randReal(rng)*2*CV_PI; |
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@ -624,6 +734,9 @@ void CV_HomographyTest::run(int) |
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float *tmp_2f = dst_mat_2f.ptr<float>()+2*i; |
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tmp_2f[0] = dst_mat_2d.at<float>(0, i) = dst_mat_3d.at<float>(0, i) /= dst_mat_3d.at<float>(2, i); |
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tmp_2f[1] = dst_mat_2d.at<float>(1, i) = dst_mat_3d.at<float>(1, i) /= dst_mat_3d.at<float>(2, i); |
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dst_mat_3d.at<float>(2, i) = 1.0f; |
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dst_vec.push_back(Point2f(tmp_2f[0], tmp_2f[1])); |
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} |
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for (size_t i = 0; i < METHODS_COUNT; ++i) |
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@ -634,67 +747,81 @@ void CV_HomographyTest::run(int) |
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case 0: |
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case CV_LMEDS: |
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{ |
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Mat H_res_64 = cv::findHomography(src_mat_2f, dst_mat_2f, method); |
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if (!check_matrix_size(H_res_64)) |
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Mat H_res_64 [4] = { cv::findHomography(src_mat_2f, dst_mat_2f, method), |
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cv::findHomography(src_mat_2f, dst_vec, method),
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cv::findHomography(src_vec, dst_mat_2f, method), |
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cv::findHomography(src_vec, dst_vec, method) }; |
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for (size_t j = 0; j < 4; ++j) |
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{ |
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cout << endl; cout << "Checking for homography matrix sizes..." << endl; cout << endl; |
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cout << "Count of points: " << N << endl; cout << endl; |
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cout << "Homography matrix:" << endl; cout << endl; |
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cout << H_res_64 << endl; cout << endl; |
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cout << "Number of rows: " << H_res_64.rows << " Number of cols: " << H_res_64.cols << endl; cout << endl; |
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CV_Error(CALIB3D_HOMOGRAPHY_ERROR_MATRIX_SIZE, MESSAGE_MATRIX_SIZE); |
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return; |
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|
|
|
if (!check_matrix_size(H_res_64[j])) |
|
|
|
|
{ |
|
|
|
|
print_information_1(j, N, method, H_res_64[j]); |
|
|
|
|
CV_Error(CALIB3D_HOMOGRAPHY_ERROR_MATRIX_SIZE, MESSAGE_MATRIX_SIZE); |
|
|
|
|
return; |
|
|
|
|
} |
|
|
|
|
|
|
|
|
|
double diff; |
|
|
|
|
|
|
|
|
|
for (size_t k = 0; k < COUNT_NORM_TYPES; ++k) |
|
|
|
|
if (!check_matrix_diff(H_64, H_res_64[j], NORM_TYPE[k], diff))
|
|
|
|
|
{ |
|
|
|
|
print_information_2(j, N, method, H_64, H_res_64[j], k, diff); |
|
|
|
|
CV_Error(CALIB3D_HOMOGRAPHY_ERROR_MATRIX_DIFF, MESSAGE_MATRIX_DIFF); |
|
|
|
|
return; |
|
|
|
|
} |
|
|
|
|
} |
|
|
|
|
|
|
|
|
|
double diff; |
|
|
|
|
|
|
|
|
|
for (size_t j = 0; j < COUNT_NORM_TYPES; ++j) |
|
|
|
|
if (!check_matrix_diff(H_64, H_res_64, NORM_TYPE[j], diff))
|
|
|
|
|
{ |
|
|
|
|
cout << endl; cout << "Checking for accuracy of homography matrix computing..." << endl; cout << endl; |
|
|
|
|
cout << "Count of points: " << N << endl; cout << endl; |
|
|
|
|
cout << "Original matrix:" << endl; cout << endl; |
|
|
|
|
cout << H_64 << endl; cout << endl; |
|
|
|
|
cout << "Found matrix:" << endl; cout << endl; |
|
|
|
|
cout << H_res_64 << endl; cout << endl; |
|
|
|
|
cout << "Norm type using in criteria: "; if (NORM_TYPE[j] == 1) cout << "INF"; else if (NORM_TYPE[j] == 2) cout << "L1"; else cout << "L2"; cout << endl; |
|
|
|
|
cout << "Difference between matrix: " << diff << endl; |
|
|
|
|
cout << "Maximum allowed difference: " << max_diff << endl; cout << endl; |
|
|
|
|
CV_Error(CALIB3D_HOMOGRAPHY_ERROR_MATRIX_DIFF, MESSAGE_MATRIX_DIFF); |
|
|
|
|
return; |
|
|
|
|
} |
|
|
|
|
continue; |
|
|
|
|
} |
|
|
|
|
case CV_RANSAC: |
|
|
|
|
{ |
|
|
|
|
cv::Mat mask; double diff;
|
|
|
|
|
Mat H_res_64 = cv::findHomography(src_mat_2f, dst_mat_2f, CV_RANSAC, reproj_threshold, mask); |
|
|
|
|
if (!check_matrix_size(H_res_64))
|
|
|
|
|
{ |
|
|
|
|
cout << endl; cout << "Checking for homography matrix sizes..." << endl; cout << endl; |
|
|
|
|
cout << "Count of points: " << N << endl; cout << endl; |
|
|
|
|
cout << "Homography matrix:" << endl; cout << endl; |
|
|
|
|
cout << H_res_64 << endl; cout << endl; |
|
|
|
|
cout << "Number of rows: " << H_res_64.rows << " Number of cols: " << H_res_64.cols << endl; cout << endl; |
|
|
|
|
CV_Error(CALIB3D_HOMOGRAPHY_ERROR_MATRIX_SIZE, MESSAGE_MATRIX_SIZE); |
|
|
|
|
return; |
|
|
|
|
} |
|
|
|
|
for (size_t j = 0; j < COUNT_NORM_TYPES; ++j) |
|
|
|
|
if (!check_matrix_diff(H_64, H_res_64, NORM_TYPE[j], diff))
|
|
|
|
|
cv::Mat mask [4]; double diff;
|
|
|
|
|
|
|
|
|
|
Mat H_res_64 [4] = { cv::findHomography(src_mat_2f, dst_mat_2f, CV_RANSAC, reproj_threshold, mask[0]), |
|
|
|
|
cv::findHomography(src_mat_2f, dst_vec, CV_RANSAC, reproj_threshold, mask[1]), |
|
|
|
|
cv::findHomography(src_vec, dst_mat_2f, CV_RANSAC, reproj_threshold, mask[2]), |
|
|
|
|
cv::findHomography(src_vec, dst_vec, CV_RANSAC, reproj_threshold, mask[3]) }; |
|
|
|
|
|
|
|
|
|
for (size_t j = 0; j < 4; ++j) |
|
|
|
|
{ |
|
|
|
|
cout << endl; cout << "Checking for accuracy of homography matrix computing..." << endl; cout << endl; |
|
|
|
|
cout << "Count of points: " << N << endl; cout << endl; |
|
|
|
|
cout << "Original matrix:" << endl; cout << endl; |
|
|
|
|
cout << H_64 << endl; cout << endl; |
|
|
|
|
cout << "Found matrix:" << endl; cout << endl; |
|
|
|
|
cout << H_res_64 << endl; cout << endl; |
|
|
|
|
cout << "Norm type using in criteria: "; if (NORM_TYPE[j] == 1) cout << "INF"; else if (NORM_TYPE[j] == 2) cout << "L1"; else cout << "L2"; cout << endl; |
|
|
|
|
cout << "Difference between matrix: " << diff << endl; |
|
|
|
|
cout << "Maximum allowed difference: " << max_diff << endl; cout << endl; |
|
|
|
|
CV_Error(CALIB3D_HOMOGRAPHY_ERROR_MATRIX_DIFF, MESSAGE_MATRIX_DIFF); |
|
|
|
|
return; |
|
|
|
|
|
|
|
|
|
if (!check_matrix_size(H_res_64[j]))
|
|
|
|
|
{ |
|
|
|
|
print_information_1(j, N, method, H_res_64[j]); |
|
|
|
|
CV_Error(CALIB3D_HOMOGRAPHY_ERROR_MATRIX_SIZE, MESSAGE_MATRIX_SIZE); |
|
|
|
|
return; |
|
|
|
|
} |
|
|
|
|
|
|
|
|
|
for (size_t k = 0; k < COUNT_NORM_TYPES; ++k) |
|
|
|
|
if (!check_matrix_diff(H_64, H_res_64[j], NORM_TYPE[k], diff))
|
|
|
|
|
{ |
|
|
|
|
print_information_2(j, N, method, H_64, H_res_64[j], k, diff); |
|
|
|
|
CV_Error(CALIB3D_HOMOGRAPHY_ERROR_MATRIX_DIFF, MESSAGE_MATRIX_DIFF); |
|
|
|
|
return; |
|
|
|
|
} |
|
|
|
|
|
|
|
|
|
int code = check_ransac_mask_1(src_mat_2f, mask[j]); |
|
|
|
|
|
|
|
|
|
if (code) |
|
|
|
|
{ |
|
|
|
|
print_information_3(j, N, mask[j]); |
|
|
|
|
|
|
|
|
|
switch (code) |
|
|
|
|
{ |
|
|
|
|
case 1: { CV_Error(CALIB3D_HOMOGRAPHY_ERROR_RANSAC_MASK, MESSAGE_RANSAC_MASK_1); break; } |
|
|
|
|
case 2: { CV_Error(CALIB3D_HOMOGRAPHY_ERROR_RANSAC_MASK, MESSAGE_RANSAC_MASK_2); break; } |
|
|
|
|
case 3: { CV_Error(CALIB3D_HOMOGRAPHY_ERROR_RANSAC_MASK, MESSAGE_RANSAC_MASK_3); break; } |
|
|
|
|
|
|
|
|
|
default: break; |
|
|
|
|
} |
|
|
|
|
|
|
|
|
|
return; |
|
|
|
|
} |
|
|
|
|
|
|
|
|
|
} |
|
|
|
|
if (!check_ransac_mask_1(src_mat_2f, mask)) return; |
|
|
|
|
|
|
|
|
|
continue; |
|
|
|
|
} |
|
|
|
|
|
|
|
|
@ -712,7 +839,7 @@ void CV_HomographyTest::run(int) |
|
|
|
|
float *a = noise_2f.ptr<float>()+2*i, *_2f = dst_mat_2f.ptr<float>()+2*i; |
|
|
|
|
_2f[0] /* = dst_mat_2d.at<float>(0, i) = dst_mat_3d.at<float>(0, i) */ += a[0]; |
|
|
|
|
_2f[1] /* = dst_mat_2d.at<float>(1, i) = dst_mat_3d.at<float>(1, i) */ += a[1]; |
|
|
|
|
mask.at<uchar>(i, 0) = sqrt(a[0]*a[0]+a[1]*a[1]) > reproj_threshold ? 0 : 1; |
|
|
|
|
mask.at<bool>(i, 0) = !(sqrt(a[0]*a[0]+a[1]*a[1]) > reproj_threshold); |
|
|
|
|
} |
|
|
|
|
|
|
|
|
|
for (size_t i = 0; i < METHODS_COUNT; ++i) |
|
|
|
@ -723,161 +850,152 @@ void CV_HomographyTest::run(int) |
|
|
|
|
case 0: |
|
|
|
|
case CV_LMEDS: |
|
|
|
|
{ |
|
|
|
|
Mat H_res_64 = cv::findHomography(src_mat_2f, dst_mat_2f, mask); |
|
|
|
|
|
|
|
|
|
if (!check_matrix_size(H_res_64)) |
|
|
|
|
Mat H_res_64 [4] = { cv::findHomography(src_mat_2f, dst_mat_2f), |
|
|
|
|
cv::findHomography(src_mat_2f, dst_vec), |
|
|
|
|
cv::findHomography(src_vec, dst_mat_2f), |
|
|
|
|
cv::findHomography(src_vec, dst_vec) }; |
|
|
|
|
|
|
|
|
|
for (size_t j = 0; j < 4; ++j) |
|
|
|
|
{ |
|
|
|
|
cout << endl; cout << "Checking for homography matrix sizes..." << endl; cout << endl; |
|
|
|
|
cout << "Count of points: " << N << endl; cout << endl; |
|
|
|
|
cout << "Homography matrix:" << endl; cout << endl; |
|
|
|
|
cout << H_res_64 << endl; cout << endl; |
|
|
|
|
cout << "Number of rows: " << H_res_64.rows << " Number of cols: " << H_res_64.cols << endl; cout << endl; |
|
|
|
|
CV_Error(CALIB3D_HOMOGRAPHY_ERROR_MATRIX_SIZE, MESSAGE_MATRIX_SIZE); |
|
|
|
|
return; |
|
|
|
|
} |
|
|
|
|
|
|
|
|
|
if (!check_matrix_size(H_res_64[j])) |
|
|
|
|
{ |
|
|
|
|
print_information_1(j, N, method, H_res_64[j]); |
|
|
|
|
CV_Error(CALIB3D_HOMOGRAPHY_ERROR_MATRIX_SIZE, MESSAGE_MATRIX_SIZE); |
|
|
|
|
return; |
|
|
|
|
} |
|
|
|
|
|
|
|
|
|
Mat H_res_32; H_res_64.convertTo(H_res_32, CV_32F); |
|
|
|
|
Mat H_res_32; H_res_64[j].convertTo(H_res_32, CV_32F); |
|
|
|
|
|
|
|
|
|
cv::Mat dst_res_3d(3, N, CV_32F), noise_2d(2, N, CV_32F); |
|
|
|
|
cv::Mat dst_res_3d(3, N, CV_32F), noise_2d(2, N, CV_32F); |
|
|
|
|
|
|
|
|
|
for (size_t k = 0; k < N; ++k) |
|
|
|
|
{ |
|
|
|
|
for (size_t k = 0; k < N; ++k) |
|
|
|
|
{ |
|
|
|
|
|
|
|
|
|
Mat tmp_mat_3d = H_res_32*src_mat_3d.col(k); |
|
|
|
|
Mat tmp_mat_3d = H_res_32*src_mat_3d.col(k); |
|
|
|
|
|
|
|
|
|
dst_res_3d.at<float>(0, k) = tmp_mat_3d.at<float>(0, 0) /= tmp_mat_3d.at<float>(2, 0); |
|
|
|
|
dst_res_3d.at<float>(1, k) = tmp_mat_3d.at<float>(1, 0) /= tmp_mat_3d.at<float>(2, 0); |
|
|
|
|
dst_res_3d.at<float>(2, k) = tmp_mat_3d.at<float>(2, 0) = 1.0f; |
|
|
|
|
dst_res_3d.at<float>(0, k) = tmp_mat_3d.at<float>(0, 0) /= tmp_mat_3d.at<float>(2, 0); |
|
|
|
|
dst_res_3d.at<float>(1, k) = tmp_mat_3d.at<float>(1, 0) /= tmp_mat_3d.at<float>(2, 0); |
|
|
|
|
dst_res_3d.at<float>(2, k) = tmp_mat_3d.at<float>(2, 0) = 1.0f; |
|
|
|
|
|
|
|
|
|
float *a = noise_2f.ptr<float>()+2*k; |
|
|
|
|
noise_2d.at<float>(0, k) = a[0]; noise_2d.at<float>(1, k) = a[1]; |
|
|
|
|
float *a = noise_2f.ptr<float>()+2*k; |
|
|
|
|
noise_2d.at<float>(0, k) = a[0]; noise_2d.at<float>(1, k) = a[1]; |
|
|
|
|
|
|
|
|
|
for (size_t j = 0; j < METHODS_COUNT; ++j)
|
|
|
|
|
if (cv::norm(tmp_mat_3d, dst_mat_3d.col(k), NORM_TYPE[j]) - cv::norm(noise_2d.col(k), NORM_TYPE[j]) > max_2diff)
|
|
|
|
|
{ |
|
|
|
|
cout << endl; cout << "Checking for accuracy of reprojection error computing..." << endl; cout << endl; |
|
|
|
|
cout << "Method: "; if (method == 0) cout << 0 << endl; else cout << "CV_LMEDS" << endl; |
|
|
|
|
cout << "Sigma of normal noise: " << sigma << endl; |
|
|
|
|
cout << "Count of points: " << N << endl; |
|
|
|
|
cout << "Number of point: " << k << endl; |
|
|
|
|
cout << "Norm type using in criteria: "; if (NORM_TYPE[j] == 1) cout << "INF"; else if (NORM_TYPE[j] == 2) cout << "L1"; else cout << "L2"; cout << endl; |
|
|
|
|
cout << "Difference with noise of point: " << cv::norm(tmp_mat_3d, dst_mat_3d.col(k), NORM_TYPE[j]) - cv::norm(noise_2d.col(k), NORM_TYPE[j]) << endl;
|
|
|
|
|
cout << "Maxumum allowed difference: " << max_2diff << endl; cout << endl; |
|
|
|
|
CV_Error(CALIB3D_HOMOGRAPHY_ERROR_REPROJ_DIFF, MESSAGE_REPROJ_DIFF_1); |
|
|
|
|
return; |
|
|
|
|
}
|
|
|
|
|
for (size_t l = 0; l < COUNT_NORM_TYPES; ++l)
|
|
|
|
|
if (cv::norm(tmp_mat_3d, dst_mat_3d.col(k), NORM_TYPE[l]) - cv::norm(noise_2d.col(k), NORM_TYPE[l]) > max_2diff)
|
|
|
|
|
{ |
|
|
|
|
print_information_4(method, j, N, k, l, cv::norm(tmp_mat_3d, dst_mat_3d.col(k), NORM_TYPE[l]) - cv::norm(noise_2d.col(k), NORM_TYPE[l])); |
|
|
|
|
CV_Error(CALIB3D_HOMOGRAPHY_ERROR_REPROJ_DIFF, MESSAGE_REPROJ_DIFF_1); |
|
|
|
|
return; |
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
} |
|
|
|
|
} |
|
|
|
|
|
|
|
|
|
Mat tmp_mat_3d = H_res_32*src_mat_3d; |
|
|
|
|
Mat tmp_mat_3d = H_res_32*src_mat_3d; |
|
|
|
|
|
|
|
|
|
for (size_t j = 0; j < METHODS_COUNT; ++j) |
|
|
|
|
if (cv::norm(dst_res_3d, dst_mat_3d, NORM_TYPE[j]) - cv::norm(noise_2d, NORM_TYPE[j]) > max_diff)
|
|
|
|
|
{ |
|
|
|
|
cout << endl; cout << "Checking for accuracy of reprojection error computing..." << endl; cout << endl; |
|
|
|
|
cout << "Method: "; if (method == 0) cout << 0 << endl; else cout << "CV_LMEDS" << endl; |
|
|
|
|
cout << "Sigma of normal noise: " << sigma << endl; |
|
|
|
|
cout << "Count of points: " << N << endl; |
|
|
|
|
cout << "Norm type using in criteria: "; if (NORM_TYPE[j] == 1) cout << "INF"; else if (NORM_TYPE[j] == 2) cout << "L1"; else cout << "L2"; cout << endl;
|
|
|
|
|
cout << "Difference with noise of points: " << cv::norm(dst_res_3d, dst_mat_3d, NORM_TYPE[j]) - cv::norm(noise_2d, NORM_TYPE[j]) << endl;
|
|
|
|
|
cout << "Maxumum allowed difference: " << max_diff << endl; cout << endl;
|
|
|
|
|
CV_Error(CALIB3D_HOMOGRAPHY_ERROR_REPROJ_DIFF, MESSAGE_REPROJ_DIFF_2); |
|
|
|
|
return; |
|
|
|
|
}
|
|
|
|
|
for (size_t l = 0; l < COUNT_NORM_TYPES; ++l) |
|
|
|
|
if (cv::norm(dst_res_3d, dst_mat_3d, NORM_TYPE[l]) - cv::norm(noise_2d, NORM_TYPE[l]) > max_diff)
|
|
|
|
|
{ |
|
|
|
|
print_information_5(method, j, N, l, cv::norm(dst_res_3d, dst_mat_3d, NORM_TYPE[l]) - cv::norm(noise_2d, NORM_TYPE[l])); |
|
|
|
|
CV_Error(CALIB3D_HOMOGRAPHY_ERROR_REPROJ_DIFF, MESSAGE_REPROJ_DIFF_2); |
|
|
|
|
return; |
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
} |
|
|
|
|
|
|
|
|
|
continue; |
|
|
|
|
} |
|
|
|
|
case CV_RANSAC: |
|
|
|
|
{ |
|
|
|
|
cv::Mat mask_res;
|
|
|
|
|
Mat H_res_64 = cv::findHomography(src_mat_2f, dst_mat_2f, CV_RANSAC, reproj_threshold, mask_res); |
|
|
|
|
cv::Mat mask_res [4];
|
|
|
|
|
|
|
|
|
|
if (!check_matrix_size(H_res_64))
|
|
|
|
|
{ |
|
|
|
|
cout << endl; cout << "Checking for homography matrix sizes..." << endl; cout << endl; |
|
|
|
|
cout << "Count of points: " << N << endl; cout << endl; |
|
|
|
|
cout << "Homography matrix:" << endl; cout << endl; |
|
|
|
|
cout << H_res_64 << endl; cout << endl; |
|
|
|
|
cout << "Number of rows: " << H_res_64.rows << " Number of cols: " << H_res_64.cols << endl; cout << endl; |
|
|
|
|
CV_Error(CALIB3D_HOMOGRAPHY_ERROR_MATRIX_SIZE, MESSAGE_MATRIX_SIZE); |
|
|
|
|
return; |
|
|
|
|
} |
|
|
|
|
|
|
|
|
|
if (!check_ransac_mask_2(mask, mask_res)) return; |
|
|
|
|
Mat H_res_64 [4] = { cv::findHomography(src_mat_2f, dst_mat_2f, CV_RANSAC, reproj_threshold, mask_res[0]), |
|
|
|
|
cv::findHomography(src_mat_2f, dst_vec, CV_RANSAC, reproj_threshold, mask_res[1]), |
|
|
|
|
cv::findHomography(src_vec, dst_mat_2f, CV_RANSAC, reproj_threshold, mask_res[2]), |
|
|
|
|
cv::findHomography(src_vec, dst_vec, CV_RANSAC, reproj_threshold, mask_res[3]) }; |
|
|
|
|
|
|
|
|
|
cv::Mat H_res_32; H_res_64.convertTo(H_res_32, CV_32F); |
|
|
|
|
for (size_t j = 0; j < 4; ++j) |
|
|
|
|
{ |
|
|
|
|
|
|
|
|
|
cv::Mat dst_res_3d = H_res_32*src_mat_3d; |
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if (!check_matrix_size(H_res_64[j]))
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{ |
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print_information_1(j, N, method, H_res_64[j]); |
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CV_Error(CALIB3D_HOMOGRAPHY_ERROR_MATRIX_SIZE, MESSAGE_MATRIX_SIZE); |
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return; |
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} |
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int code = check_ransac_mask_2(mask, mask_res[j]); |
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for (size_t k = 0; k < N; ++k) |
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{ |
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dst_res_3d.at<float>(0, k) /= dst_res_3d.at<float>(2, k); |
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dst_res_3d.at<float>(1, k) /= dst_res_3d.at<float>(2, k); |
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dst_res_3d.at<float>(2, k) = 1.0f; |
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if (code) |
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{ |
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print_information_3(j, N, mask_res[j]); |
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float *p = dst_mat_2f.ptr<float>()+2*k; |
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switch (code) |
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{ |
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case 1: { CV_Error(CALIB3D_HOMOGRAPHY_ERROR_RANSAC_MASK, MESSAGE_RANSAC_MASK_1); break; } |
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case 2: { CV_Error(CALIB3D_HOMOGRAPHY_ERROR_RANSAC_MASK, MESSAGE_RANSAC_MASK_3); break; } |
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default: break; |
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} |
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dst_mat_3d.at<float>(0, k) = p[0]; |
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dst_mat_3d.at<float>(1, k) = p[1]; |
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return; |
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} |
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double diff = cv::norm(dst_res_3d.col(k), dst_mat_3d.col(k), NORM_L2);
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cv::Mat H_res_32; H_res_64[j].convertTo(H_res_32, CV_32F); |
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if (mask_res.at<bool>(k, 0) != (diff <= reproj_threshold)) |
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{ |
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cout << endl; cout << "Checking for inliers/outliers mask..." << endl; cout << endl; |
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cout << "Count of points: " << N << " " << endl;
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cout << "Number of point: " << k << " " << endl; |
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cout << "Reprojection error for this point: " << diff << " " << endl; |
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cout << "Reprojection error threshold: " << reproj_threshold << " " << endl; |
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cout << "Value of found mask: "<< mask_res.at<bool>(k, 0) << endl; cout << endl; |
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CV_Error(CALIB3D_HOMOGRAPHY_ERROR_RANSAC_MASK, MESSAGE_RANSAC_MASK_3); |
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return;
|
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}
|
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if (mask.at<bool>(k, 0) && !mask_res.at<bool>(k, 0)) |
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{ |
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cout << endl; cout << "Checking for inliers/outliers mask..." << endl; cout << endl; |
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cout << "Count of points: " << N << " " << endl;
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cout << "Number of point: " << k << " " << endl; |
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cout << "Reprojection error for this point: " << diff << " " << endl; |
|
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cout << "Reprojection error threshold: " << reproj_threshold << " " << endl; |
|
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cout << "Value of original mask: "<< mask.at<bool>(k, 0) << " Value of found mask: " << mask_res.at<bool>(k, 0) << endl; cout << endl; |
|
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CV_Error(CALIB3D_HOMOGRAPHY_ERROR_RANSAC_MASK, MESSAGE_RANSAC_MASK_4); |
|
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|
|
return; |
|
|
|
|
} |
|
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|
cv::Mat dst_res_3d = H_res_32*src_mat_3d; |
|
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|
|
|
|
|
|
|
if (mask_res.at<bool>(k, 0)) |
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for (size_t k = 0; k < N; ++k) |
|
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|
{ |
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|
float *a = noise_2f.ptr<float>()+2*k; |
|
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|
dst_mat_3d.at<float>(0, k) -= a[0]; |
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|
dst_mat_3d.at<float>(1, k) -= a[1]; |
|
|
|
|
dst_res_3d.at<float>(0, k) /= dst_res_3d.at<float>(2, k); |
|
|
|
|
dst_res_3d.at<float>(1, k) /= dst_res_3d.at<float>(2, k); |
|
|
|
|
dst_res_3d.at<float>(2, k) = 1.0f; |
|
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|
|
|
|
|
|
|
float *p = dst_mat_2f.ptr<float>()+2*k; |
|
|
|
|
|
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|
|
|
dst_mat_3d.at<float>(0, k) = p[0]; |
|
|
|
|
dst_mat_3d.at<float>(1, k) = p[1]; |
|
|
|
|
|
|
|
|
|
cv::Mat noise_2d(2, 1, CV_32F); |
|
|
|
|
noise_2d.at<float>(0, 0) = a[0]; noise_2d.at<float>(1, 0) = a[1]; |
|
|
|
|
double diff = cv::norm(dst_res_3d.col(k), dst_mat_3d.col(k), NORM_L2);
|
|
|
|
|
|
|
|
|
|
for (size_t j = 0; j < METHODS_COUNT; ++j) |
|
|
|
|
if (mask_res[j].at<bool>(k, 0) != (diff <= reproj_threshold)) |
|
|
|
|
{ |
|
|
|
|
diff = cv::norm(dst_res_3d.col(k), dst_mat_3d.col(k), NORM_TYPE[j]); |
|
|
|
|
|
|
|
|
|
if (diff - cv::norm(noise_2d, NORM_TYPE[j]) > max_2diff) |
|
|
|
|
print_information_6(j, N, k, diff, mask_res[j].at<bool>(k, 0)); |
|
|
|
|
CV_Error(CALIB3D_HOMOGRAPHY_ERROR_RANSAC_MASK, MESSAGE_RANSAC_MASK_4); |
|
|
|
|
return;
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
if (mask.at<bool>(k, 0) && !mask_res[j].at<bool>(k, 0)) |
|
|
|
|
{ |
|
|
|
|
print_information_7(j, N, k, diff, mask.at<bool>(k, 0), mask_res[j].at<bool>(k, 0)); |
|
|
|
|
CV_Error(CALIB3D_HOMOGRAPHY_ERROR_RANSAC_MASK, MESSAGE_RANSAC_MASK_5); |
|
|
|
|
return; |
|
|
|
|
} |
|
|
|
|
|
|
|
|
|
if (mask_res[j].at<bool>(k, 0)) |
|
|
|
|
{ |
|
|
|
|
float *a = noise_2f.ptr<float>()+2*k; |
|
|
|
|
dst_mat_3d.at<float>(0, k) -= a[0]; |
|
|
|
|
dst_mat_3d.at<float>(1, k) -= a[1]; |
|
|
|
|
|
|
|
|
|
cv::Mat noise_2d(2, 1, CV_32F); |
|
|
|
|
noise_2d.at<float>(0, 0) = a[0]; noise_2d.at<float>(1, 0) = a[1]; |
|
|
|
|
|
|
|
|
|
for (size_t l = 0; l < COUNT_NORM_TYPES; ++l) |
|
|
|
|
{ |
|
|
|
|
|
|
|
|
|
cout << endl; cout << "Checking for reprojection error of inlier..." << endl; cout << endl; |
|
|
|
|
cout << "Count of points: " << N << " " << endl;
|
|
|
|
|
cout << "Number of point: " << k << " " << endl; |
|
|
|
|
cout << "Reprojection error for this point: " << diff << " " << endl; |
|
|
|
|
CV_Error(CALIB3D_HOMOGRAPHY_ERROR_RANSAC_DIFF, MESSAGE_RANSAC_DIFF); |
|
|
|
|
return;
|
|
|
|
|
diff = cv::norm(dst_res_3d.col(k), dst_mat_3d.col(k), NORM_TYPE[l]); |
|
|
|
|
|
|
|
|
|
if (diff - cv::norm(noise_2d, NORM_TYPE[l]) > max_2diff) |
|
|
|
|
{ |
|
|
|
|
print_information_8(j, N, k, l, diff - cv::norm(noise_2d, NORM_TYPE[l]));
|
|
|
|
|
CV_Error(CALIB3D_HOMOGRAPHY_ERROR_RANSAC_DIFF, MESSAGE_RANSAC_DIFF); |
|
|
|
|
return;
|
|
|
|
|
} |
|
|
|
|
} |
|
|
|
|
} |
|
|
|
|
} |
|
|
|
|
} |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
// Checking of reprojection error for any points pair.
|
|
|
|
|
|
|
|
|
|
continue; |
|
|
|
|
} |
|
|
|
|
|
|
|
|
|