/*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. // // // License Agreement // For Open Source Computer Vision Library // // Copyright (C) 2000-2008, Intel Corporation, all rights reserved. // Copyright (C) 2009, Willow Garage Inc., all rights reserved. // Copyright (C) 2015, Itseez Inc., 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 the copyright holders 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" #include #define CALIB3D_HOMOGRAPHY_ERROR_MATRIX_SIZE 1 #define CALIB3D_HOMOGRAPHY_ERROR_MATRIX_DIFF 2 #define CALIB3D_HOMOGRAPHY_ERROR_REPROJ_DIFF 3 #define CALIB3D_HOMOGRAPHY_ERROR_RANSAC_MASK 4 #define CALIB3D_HOMOGRAPHY_ERROR_RANSAC_DIFF 5 #define MESSAGE_MATRIX_SIZE "Homography matrix must have 3*3 sizes." #define MESSAGE_MATRIX_DIFF "Accuracy of homography transformation matrix less than required." #define MESSAGE_REPROJ_DIFF_1 "Reprojection error for current pair of points more than required." #define MESSAGE_REPROJ_DIFF_2 "Reprojection error is not optimal." #define MESSAGE_RANSAC_MASK_1 "Sizes of inliers/outliers mask are incorrect." #define MESSAGE_RANSAC_MASK_2 "Mask mustn't have any outliers." #define MESSAGE_RANSAC_MASK_3 "All values of mask must be 1 (true) or 0 (false)." #define MESSAGE_RANSAC_MASK_4 "Mask of inliers/outliers is incorrect." #define MESSAGE_RANSAC_MASK_5 "Inlier in original mask shouldn't be outlier in found mask." #define MESSAGE_RANSAC_DIFF "Reprojection error for current pair of points more than required." #define MAX_COUNT_OF_POINTS 303 #define COUNT_NORM_TYPES 3 #define METHODS_COUNT 3 int NORM_TYPE[COUNT_NORM_TYPES] = {cv::NORM_L1, cv::NORM_L2, cv::NORM_INF}; int METHOD[METHODS_COUNT] = {0, CV_RANSAC, CV_LMEDS}; using namespace cv; using namespace std; class CV_HomographyTest: public cvtest::ArrayTest { public: CV_HomographyTest(); ~CV_HomographyTest(); void run (int); protected: int method; int image_size; double reproj_threshold; double sigma; private: float max_diff, max_2diff; bool check_matrix_size(const cv::Mat& H); bool check_matrix_diff(const cv::Mat& original, const cv::Mat& found, const int norm_type, double &diff); int check_ransac_mask_1(const Mat& src, const Mat& mask); int check_ransac_mask_2(const Mat& original_mask, const Mat& found_mask); void print_information_1(int j, int N, int method, const Mat& H); void print_information_2(int j, int N, int method, const Mat& H, const Mat& H_res, int k, double diff); void print_information_3(int j, int N, const Mat& mask); void print_information_4(int method, int j, int N, int k, int l, double diff); void print_information_5(int method, int j, int N, int l, double diff); void print_information_6(int j, int N, int k, double diff, bool value); void print_information_7(int j, int N, int k, double diff, bool original_value, bool found_value); void print_information_8(int j, int N, int k, int l, double diff); }; CV_HomographyTest::CV_HomographyTest() : max_diff(1e-2f), max_2diff(2e-2f) { method = 0; image_size = 100; reproj_threshold = 3.0; sigma = 0.01; } CV_HomographyTest::~CV_HomographyTest() {} bool CV_HomographyTest::check_matrix_size(const cv::Mat& H) { return (H.rows == 3) && (H.cols == 3); } bool CV_HomographyTest::check_matrix_diff(const cv::Mat& original, const cv::Mat& found, const int norm_type, double &diff) { diff = cv::norm(original, found, norm_type); return diff <= max_diff; } int CV_HomographyTest::check_ransac_mask_1(const Mat& src, const Mat& mask) { if (!(mask.cols == 1) && (mask.rows == src.cols)) return 1; if (countNonZero(mask) < mask.rows) return 2; for (int i = 0; i < mask.rows; ++i) if (mask.at(i, 0) > 1) return 3; return 0; } int CV_HomographyTest::check_ransac_mask_2(const Mat& original_mask, const Mat& found_mask) { if (!(found_mask.cols == 1) && (found_mask.rows == original_mask.rows)) return 1; for (int i = 0; i < found_mask.rows; ++i) if (found_mask.at(i, 0) > 1) return 2; return 0; } void CV_HomographyTest::print_information_1(int j, int N, int _method, const Mat& H) { cout << endl; cout << "Checking for homography matrix sizes..." << endl; cout << endl; cout << "Type of srcPoints: "; if ((j>-1) && (j<2)) cout << "Mat of CV_32FC2"; else cout << "vector "; cout << " Type of dstPoints: "; if (j % 2 == 0) cout << "Mat of CV_32FC2"; else cout << "vector "; cout << endl; cout << "Count of points: " << N << endl; cout << endl; cout << "Method: "; if (_method == 0) cout << 0; else if (_method == 8) cout << "RANSAC"; else cout << "LMEDS"; cout << endl; cout << "Homography matrix:" << endl; cout << endl; cout << H << endl; cout << endl; cout << "Number of rows: " << H.rows << " Number of cols: " << H.cols << endl; cout << endl; } void CV_HomographyTest::print_information_2(int j, int N, int _method, const Mat& H, const Mat& H_res, int k, double diff) { cout << endl; cout << "Checking for accuracy of homography matrix computing..." << endl; cout << endl; cout << "Type of srcPoints: "; if ((j>-1) && (j<2)) cout << "Mat of CV_32FC2"; else cout << "vector "; cout << " Type of dstPoints: "; if (j % 2 == 0) cout << "Mat of CV_32FC2"; else cout << "vector "; cout << endl; cout << "Count of points: " << N << endl; cout << endl; cout << "Method: "; if (_method == 0) cout << 0; else if (_method == 8) cout << "RANSAC"; else cout << "LMEDS"; cout << endl; cout << "Original matrix:" << endl; cout << endl; cout << H << endl; cout << endl; cout << "Found matrix:" << endl; cout << endl; cout << H_res << endl; cout << endl; 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; cout << "Difference between matrices: " << diff << endl; cout << "Maximum allowed difference: " << max_diff << endl; cout << endl; } void CV_HomographyTest::print_information_3(int j, int N, const Mat& mask) { cout << endl; cout << "Checking for inliers/outliers mask..." << endl; cout << endl; cout << "Type of srcPoints: "; if ((j>-1) && (j<2)) cout << "Mat of CV_32FC2"; else cout << "vector "; cout << " Type of dstPoints: "; if (j % 2 == 0) cout << "Mat of CV_32FC2"; else cout << "vector "; cout << endl; cout << "Count of points: " << N << endl; cout << endl; cout << "Method: RANSAC" << endl; cout << "Found mask:" << endl; cout << endl; cout << mask << endl; cout << endl; cout << "Number of rows: " << mask.rows << " Number of cols: " << mask.cols << endl; cout << endl; } void CV_HomographyTest::print_information_4(int _method, int j, int N, int k, int l, double 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 << "Type of srcPoints: "; if ((j>-1) && (j<2)) cout << "Mat of CV_32FC2"; else cout << "vector "; cout << " Type of dstPoints: "; if (j % 2 == 0) cout << "Mat of CV_32FC2"; else cout << "vector "; cout << 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[l] == 1) cout << "INF"; else if (NORM_TYPE[l] == 2) cout << "L1"; else cout << "L2"; cout << endl; cout << "Difference with noise of point: " << diff << endl; cout << "Maxumum allowed difference: " << max_2diff << endl; cout << endl; } void CV_HomographyTest::print_information_5(int _method, int j, int N, int l, double 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 << "Type of srcPoints: "; if ((j>-1) && (j<2)) cout << "Mat of CV_32FC2"; else cout << "vector "; cout << " Type of dstPoints: "; if (j % 2 == 0) cout << "Mat of CV_32FC2"; else cout << "vector "; cout << endl; cout << "Sigma of normal noise: " << sigma << endl; cout << "Count of points: " << N << endl; 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; cout << "Difference with noise of points: " << diff << endl; cout << "Maxumum allowed difference: " << max_diff << endl; cout << endl; } void CV_HomographyTest::print_information_6(int j, int N, int k, double diff, bool value) { cout << endl; cout << "Checking for inliers/outliers mask..." << endl; cout << endl; cout << "Method: RANSAC" << endl; cout << "Type of srcPoints: "; if ((j>-1) && (j<2)) cout << "Mat of CV_32FC2"; else cout << "vector "; cout << " Type of dstPoints: "; if (j % 2 == 0) cout << "Mat of CV_32FC2"; else cout << "vector "; cout << endl; cout << "Count of points: " << N << " " << endl; cout << "Number of point: " << k << " " << endl; cout << "Reprojection error for this point: " << diff << " " << endl; cout << "Reprojection error threshold: " << reproj_threshold << " " << endl; cout << "Value of found mask: "<< value << endl; cout << endl; } void CV_HomographyTest::print_information_7(int j, int N, int k, double diff, bool original_value, bool found_value) { cout << endl; cout << "Checking for inliers/outliers mask..." << endl; cout << endl; cout << "Method: RANSAC" << endl; cout << "Type of srcPoints: "; if ((j>-1) && (j<2)) cout << "Mat of CV_32FC2"; else cout << "vector "; cout << " Type of dstPoints: "; if (j % 2 == 0) cout << "Mat of CV_32FC2"; else cout << "vector "; cout << endl; cout << "Count of points: " << N << " " << endl; cout << "Number of point: " << k << " " << endl; cout << "Reprojection error for this point: " << diff << " " << endl; cout << "Reprojection error threshold: " << reproj_threshold << " " << endl; cout << "Value of original mask: "<< original_value << " Value of found mask: " << found_value << endl; cout << endl; } void CV_HomographyTest::print_information_8(int j, int N, int k, int l, double diff) { cout << endl; cout << "Checking for reprojection error of inlier..." << endl; cout << endl; cout << "Method: RANSAC" << endl; cout << "Sigma of normal noise: " << sigma << endl; cout << "Type of srcPoints: "; if ((j>-1) && (j<2)) cout << "Mat of CV_32FC2"; else cout << "vector "; cout << " Type of dstPoints: "; if (j % 2 == 0) cout << "Mat of CV_32FC2"; else cout << "vector "; cout << endl; cout << "Count of points: " << N << " " << endl; cout << "Number of point: " << k << " " << endl; 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; cout << "Difference with noise of point: " << diff << endl; cout << "Maxumum allowed difference: " << max_2diff << endl; cout << endl; } void CV_HomographyTest::run(int) { for (int N = 4; N <= MAX_COUNT_OF_POINTS; ++N) { RNG& rng = ts->get_rng(); float *src_data = new float [2*N]; for (int i = 0; i < N; ++i) { src_data[2*i] = (float)cvtest::randReal(rng)*image_size; src_data[2*i+1] = (float)cvtest::randReal(rng)*image_size; } cv::Mat src_mat_2f(1, N, CV_32FC2, src_data), src_mat_2d(2, N, CV_32F, src_data), src_mat_3d(3, N, CV_32F); cv::Mat dst_mat_2f, dst_mat_2d, dst_mat_3d; vector src_vec, dst_vec; for (int i = 0; i < N; ++i) { float *tmp = src_mat_2d.ptr()+2*i; src_mat_3d.at(0, i) = tmp[0]; src_mat_3d.at(1, i) = tmp[1]; src_mat_3d.at(2, i) = 1.0f; src_vec.push_back(Point2f(tmp[0], tmp[1])); } double fi = cvtest::randReal(rng)*2*CV_PI; double t_x = cvtest::randReal(rng)*sqrt(image_size*1.0), t_y = cvtest::randReal(rng)*sqrt(image_size*1.0); double Hdata[9] = { cos(fi), -sin(fi), t_x, sin(fi), cos(fi), t_y, 0.0f, 0.0f, 1.0f }; cv::Mat H_64(3, 3, CV_64F, Hdata), H_32; H_64.convertTo(H_32, CV_32F); dst_mat_3d = H_32*src_mat_3d; dst_mat_2d.create(2, N, CV_32F); dst_mat_2f.create(1, N, CV_32FC2); for (int i = 0; i < N; ++i) { float *tmp_2f = dst_mat_2f.ptr()+2*i; tmp_2f[0] = dst_mat_2d.at(0, i) = dst_mat_3d.at(0, i) /= dst_mat_3d.at(2, i); tmp_2f[1] = dst_mat_2d.at(1, i) = dst_mat_3d.at(1, i) /= dst_mat_3d.at(2, i); dst_mat_3d.at(2, i) = 1.0f; dst_vec.push_back(Point2f(tmp_2f[0], tmp_2f[1])); } for (int i = 0; i < METHODS_COUNT; ++i) { method = METHOD[i]; switch (method) { case 0: case CV_LMEDS: { Mat H_res_64 [4] = { cv::findHomography(src_mat_2f, dst_mat_2f, method), cv::findHomography(src_mat_2f, dst_vec, method), cv::findHomography(src_vec, dst_mat_2f, method), cv::findHomography(src_vec, dst_vec, method) }; for (int j = 0; j < 4; ++j) { 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 (int 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; } } continue; } case CV_RANSAC: { 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 (int j = 0; j < 4; ++j) { 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 (int 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; } } continue; } default: continue; } } Mat noise_2f(1, N, CV_32FC2); rng.fill(noise_2f, RNG::NORMAL, Scalar::all(0), Scalar::all(sigma)); cv::Mat mask(N, 1, CV_8UC1); for (int i = 0; i < N; ++i) { float *a = noise_2f.ptr()+2*i, *_2f = dst_mat_2f.ptr()+2*i; _2f[0] += a[0]; _2f[1] += a[1]; mask.at(i, 0) = !(sqrt(a[0]*a[0]+a[1]*a[1]) > reproj_threshold); } for (int i = 0; i < METHODS_COUNT; ++i) { method = METHOD[i]; switch (method) { case 0: case CV_LMEDS: { 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 (int j = 0; j < 4; ++j) { 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[j].convertTo(H_res_32, CV_32F); cv::Mat dst_res_3d(3, N, CV_32F), noise_2d(2, N, CV_32F); for (int k = 0; k < N; ++k) { Mat tmp_mat_3d = H_res_32*src_mat_3d.col(k); dst_res_3d.at(0, k) = tmp_mat_3d.at(0, 0) /= tmp_mat_3d.at(2, 0); dst_res_3d.at(1, k) = tmp_mat_3d.at(1, 0) /= tmp_mat_3d.at(2, 0); dst_res_3d.at(2, k) = tmp_mat_3d.at(2, 0) = 1.0f; float *a = noise_2f.ptr()+2*k; noise_2d.at(0, k) = a[0]; noise_2d.at(1, k) = a[1]; for (int 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; } } for (int 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 [4]; 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]) }; for (int j = 0; j < 4; ++j) { 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; } int code = check_ransac_mask_2(mask, mask_res[j]); if (code) { print_information_3(j, N, mask_res[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_3); break; } default: break; } return; } cv::Mat H_res_32; H_res_64[j].convertTo(H_res_32, CV_32F); cv::Mat dst_res_3d = H_res_32*src_mat_3d; for (int k = 0; k < N; ++k) { dst_res_3d.at(0, k) /= dst_res_3d.at(2, k); dst_res_3d.at(1, k) /= dst_res_3d.at(2, k); dst_res_3d.at(2, k) = 1.0f; float *p = dst_mat_2f.ptr()+2*k; dst_mat_3d.at(0, k) = p[0]; dst_mat_3d.at(1, k) = p[1]; double diff = cv::norm(dst_res_3d.col(k), dst_mat_3d.col(k), NORM_L2); if (mask_res[j].at(k, 0) != (diff <= reproj_threshold)) { print_information_6(j, N, k, diff, mask_res[j].at(k, 0)); CV_Error(CALIB3D_HOMOGRAPHY_ERROR_RANSAC_MASK, MESSAGE_RANSAC_MASK_4); return; } if (mask.at(k, 0) && !mask_res[j].at(k, 0)) { print_information_7(j, N, k, diff, mask.at(k, 0), mask_res[j].at(k, 0)); CV_Error(CALIB3D_HOMOGRAPHY_ERROR_RANSAC_MASK, MESSAGE_RANSAC_MASK_5); return; } if (mask_res[j].at(k, 0)) { float *a = noise_2f.ptr()+2*k; dst_mat_3d.at(0, k) -= a[0]; dst_mat_3d.at(1, k) -= a[1]; cv::Mat noise_2d(2, 1, CV_32F); noise_2d.at(0, 0) = a[0]; noise_2d.at(1, 0) = a[1]; for (int l = 0; l < COUNT_NORM_TYPES; ++l) { 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; } } } } } continue; } default: continue; } } delete[]src_data; src_data = NULL; } } TEST(Calib3d_Homography, accuracy) { CV_HomographyTest test; test.safe_run(); }