/*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. // 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 "opencv2/imgproc/imgproc_c.h" namespace opencv_test { namespace { class CV_DefaultNewCameraMatrixTest : public cvtest::ArrayTest { public: CV_DefaultNewCameraMatrixTest(); protected: int prepare_test_case (int test_case_idx); void prepare_to_validation( int test_case_idx ); void get_test_array_types_and_sizes( int test_case_idx, vector >& sizes, vector >& types ); void run_func(); private: cv::Size img_size; cv::Mat camera_mat; cv::Mat new_camera_mat; int matrix_type; bool center_principal_point; static const int MAX_X = 2048; static const int MAX_Y = 2048; //static const int MAX_VAL = 10000; }; CV_DefaultNewCameraMatrixTest::CV_DefaultNewCameraMatrixTest() { test_array[INPUT].push_back(NULL); test_array[OUTPUT].push_back(NULL); test_array[REF_OUTPUT].push_back(NULL); matrix_type = 0; center_principal_point = false; } void CV_DefaultNewCameraMatrixTest::get_test_array_types_and_sizes( int test_case_idx, vector >& sizes, vector >& types ) { cvtest::ArrayTest::get_test_array_types_and_sizes(test_case_idx,sizes,types); RNG& rng = ts->get_rng(); matrix_type = types[INPUT][0] = types[OUTPUT][0]= types[REF_OUTPUT][0] = cvtest::randInt(rng)%2 ? CV_64F : CV_32F; sizes[INPUT][0] = sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = cvSize(3,3); } int CV_DefaultNewCameraMatrixTest::prepare_test_case(int test_case_idx) { int code = cvtest::ArrayTest::prepare_test_case( test_case_idx ); if (code <= 0) return code; RNG& rng = ts->get_rng(); img_size.width = cvtest::randInt(rng) % MAX_X + 1; img_size.height = cvtest::randInt(rng) % MAX_Y + 1; center_principal_point = ((cvtest::randInt(rng) % 2)!=0); // Generating camera_mat matrix double sz = MAX(img_size.width, img_size.height); double aspect_ratio = cvtest::randReal(rng)*0.6 + 0.7; double a[9] = {0,0,0,0,0,0,0,0,1}; Mat _a(3,3,CV_64F,a); a[2] = (img_size.width - 1)*0.5 + cvtest::randReal(rng)*10 - 5; a[5] = (img_size.height - 1)*0.5 + cvtest::randReal(rng)*10 - 5; a[0] = sz/(0.9 - cvtest::randReal(rng)*0.6); a[4] = aspect_ratio*a[0]; Mat& _a0 = test_mat[INPUT][0]; cvtest::convert(_a, _a0, _a0.type()); camera_mat = _a0; return code; } void CV_DefaultNewCameraMatrixTest::run_func() { new_camera_mat = cv::getDefaultNewCameraMatrix(camera_mat,img_size,center_principal_point); } void CV_DefaultNewCameraMatrixTest::prepare_to_validation( int /*test_case_idx*/ ) { const Mat& src = test_mat[INPUT][0]; Mat& dst = test_mat[REF_OUTPUT][0]; Mat& test_output = test_mat[OUTPUT][0]; Mat& output = new_camera_mat; cvtest::convert( output, test_output, test_output.type() ); if (!center_principal_point) { cvtest::copy(src, dst); } else { double a[9] = {0,0,0,0,0,0,0,0,1}; Mat _a(3,3,CV_64F,a); if (matrix_type == CV_64F) { a[0] = src.at(0,0); a[4] = src.at(1,1); } else { a[0] = src.at(0,0); a[4] = src.at(1,1); } a[2] = (img_size.width - 1)*0.5; a[5] = (img_size.height - 1)*0.5; cvtest::convert( _a, dst, dst.type() ); } } //--------- class CV_UndistortPointsTest : public cvtest::ArrayTest { public: CV_UndistortPointsTest(); protected: int prepare_test_case (int test_case_idx); void prepare_to_validation( int test_case_idx ); void get_test_array_types_and_sizes( int test_case_idx, vector >& sizes, vector >& types ); double get_success_error_level( int test_case_idx, int i, int j ); void run_func(); void distortPoints(const CvMat* _src, CvMat* _dst, const CvMat* _cameraMatrix, const CvMat* _distCoeffs, const CvMat* matR, const CvMat* matP); private: bool useCPlus; bool useDstMat; static const int N_POINTS = 10; static const int MAX_X = 2048; static const int MAX_Y = 2048; bool zero_new_cam; bool zero_distortion; bool zero_R; cv::Size img_size; cv::Mat dst_points_mat; cv::Mat camera_mat; cv::Mat R; cv::Mat P; cv::Mat distortion_coeffs; cv::Mat src_points; std::vector dst_points; }; CV_UndistortPointsTest::CV_UndistortPointsTest() { test_array[INPUT].push_back(NULL); // points matrix test_array[INPUT].push_back(NULL); // camera matrix test_array[INPUT].push_back(NULL); // distortion coeffs test_array[INPUT].push_back(NULL); // R matrix test_array[INPUT].push_back(NULL); // P matrix test_array[OUTPUT].push_back(NULL); // distorted dst points test_array[TEMP].push_back(NULL); // dst points test_array[REF_OUTPUT].push_back(NULL); useCPlus = useDstMat = false; zero_new_cam = zero_distortion = zero_R = false; } void CV_UndistortPointsTest::get_test_array_types_and_sizes( int test_case_idx, vector >& sizes, vector >& types ) { cvtest::ArrayTest::get_test_array_types_and_sizes(test_case_idx,sizes,types); RNG& rng = ts->get_rng(); useCPlus = ((cvtest::randInt(rng) % 2)!=0); //useCPlus = 0; if (useCPlus) { types[INPUT][0] = types[OUTPUT][0] = types[REF_OUTPUT][0] = types[TEMP][0]= CV_32FC2; } else { types[INPUT][0] = types[OUTPUT][0] = types[REF_OUTPUT][0] = types[TEMP][0]= cvtest::randInt(rng)%2 ? CV_64FC2 : CV_32FC2; } types[INPUT][1] = cvtest::randInt(rng)%2 ? CV_64F : CV_32F; types[INPUT][2] = cvtest::randInt(rng)%2 ? CV_64F : CV_32F; types[INPUT][3] = cvtest::randInt(rng)%2 ? CV_64F : CV_32F; types[INPUT][4] = cvtest::randInt(rng)%2 ? CV_64F : CV_32F; sizes[INPUT][0] = sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = sizes[TEMP][0]= cvtest::randInt(rng)%2 ? cvSize(1,N_POINTS) : cvSize(N_POINTS,1); sizes[INPUT][1] = sizes[INPUT][3] = cvSize(3,3); sizes[INPUT][4] = cvtest::randInt(rng)%2 ? cvSize(3,3) : cvSize(4,3); if (cvtest::randInt(rng)%2) { if (cvtest::randInt(rng)%2) { sizes[INPUT][2] = cvSize(1,4); } else { sizes[INPUT][2] = cvSize(1,5); } } else { if (cvtest::randInt(rng)%2) { sizes[INPUT][2] = cvSize(4,1); } else { sizes[INPUT][2] = cvSize(5,1); } } } int CV_UndistortPointsTest::prepare_test_case(int test_case_idx) { RNG& rng = ts->get_rng(); int code = cvtest::ArrayTest::prepare_test_case( test_case_idx ); if (code <= 0) return code; useDstMat = (cvtest::randInt(rng) % 2) == 0; img_size.width = cvtest::randInt(rng) % MAX_X + 1; img_size.height = cvtest::randInt(rng) % MAX_Y + 1; int dist_size = test_mat[INPUT][2].cols > test_mat[INPUT][2].rows ? test_mat[INPUT][2].cols : test_mat[INPUT][2].rows; double cam[9] = {0,0,0,0,0,0,0,0,1}; vector dist(dist_size); vector proj(test_mat[INPUT][4].cols * test_mat[INPUT][4].rows); vector points(N_POINTS); Mat _camera(3,3,CV_64F,cam); Mat _distort(test_mat[INPUT][2].rows,test_mat[INPUT][2].cols,CV_64F,&dist[0]); Mat _proj(test_mat[INPUT][4].size(), CV_64F, &proj[0]); Mat _points(test_mat[INPUT][0].size(), CV_64FC2, &points[0]); _proj = Scalar::all(0); //Generating points for( int i = 0; i < N_POINTS; i++ ) { points[i].x = cvtest::randReal(rng)*img_size.width; points[i].y = cvtest::randReal(rng)*img_size.height; } //Generating camera matrix double sz = MAX(img_size.width,img_size.height); double aspect_ratio = cvtest::randReal(rng)*0.6 + 0.7; cam[2] = (img_size.width - 1)*0.5 + cvtest::randReal(rng)*10 - 5; cam[5] = (img_size.height - 1)*0.5 + cvtest::randReal(rng)*10 - 5; cam[0] = sz/(0.9 - cvtest::randReal(rng)*0.6); cam[4] = aspect_ratio*cam[0]; //Generating distortion coeffs dist[0] = cvtest::randReal(rng)*0.06 - 0.03; dist[1] = cvtest::randReal(rng)*0.06 - 0.03; if( dist[0]*dist[1] > 0 ) dist[1] = -dist[1]; if( cvtest::randInt(rng)%4 != 0 ) { dist[2] = cvtest::randReal(rng)*0.004 - 0.002; dist[3] = cvtest::randReal(rng)*0.004 - 0.002; if (dist_size > 4) dist[4] = cvtest::randReal(rng)*0.004 - 0.002; } else { dist[2] = dist[3] = 0; if (dist_size > 4) dist[4] = 0; } //Generating P matrix (projection) if( test_mat[INPUT][4].cols != 4 ) { proj[8] = 1; if (cvtest::randInt(rng)%2 == 0) // use identity new camera matrix { proj[0] = 1; proj[4] = 1; } else { proj[0] = cam[0] + (cvtest::randReal(rng) - (double)0.5)*0.2*cam[0]; //10% proj[4] = cam[4] + (cvtest::randReal(rng) - (double)0.5)*0.2*cam[4]; //10% proj[2] = cam[2] + (cvtest::randReal(rng) - (double)0.5)*0.3*img_size.width; //15% proj[5] = cam[5] + (cvtest::randReal(rng) - (double)0.5)*0.3*img_size.height; //15% } } else { proj[10] = 1; proj[0] = cam[0] + (cvtest::randReal(rng) - (double)0.5)*0.2*cam[0]; //10% proj[5] = cam[4] + (cvtest::randReal(rng) - (double)0.5)*0.2*cam[4]; //10% proj[2] = cam[2] + (cvtest::randReal(rng) - (double)0.5)*0.3*img_size.width; //15% proj[6] = cam[5] + (cvtest::randReal(rng) - (double)0.5)*0.3*img_size.height; //15% proj[3] = (img_size.height + img_size.width - 1)*0.5 + cvtest::randReal(rng)*10 - 5; proj[7] = (img_size.height + img_size.width - 1)*0.5 + cvtest::randReal(rng)*10 - 5; proj[11] = (img_size.height + img_size.width - 1)*0.5 + cvtest::randReal(rng)*10 - 5; } //Generating R matrix Mat _rot(3,3,CV_64F); Mat rotation(1,3,CV_64F); rotation.at(0) = CV_PI*(cvtest::randReal(rng) - (double)0.5); // phi rotation.at(1) = CV_PI*(cvtest::randReal(rng) - (double)0.5); // ksi rotation.at(2) = CV_PI*(cvtest::randReal(rng) - (double)0.5); //khi cvtest::Rodrigues(rotation, _rot); //copying data //src_points = &_points; _points.convertTo(test_mat[INPUT][0], test_mat[INPUT][0].type()); _camera.convertTo(test_mat[INPUT][1], test_mat[INPUT][1].type()); _distort.convertTo(test_mat[INPUT][2], test_mat[INPUT][2].type()); _rot.convertTo(test_mat[INPUT][3], test_mat[INPUT][3].type()); _proj.convertTo(test_mat[INPUT][4], test_mat[INPUT][4].type()); zero_distortion = (cvtest::randInt(rng)%2) == 0 ? false : true; zero_new_cam = (cvtest::randInt(rng)%2) == 0 ? false : true; zero_R = (cvtest::randInt(rng)%2) == 0 ? false : true; if (useCPlus) { _points.convertTo(src_points, CV_32F); camera_mat = test_mat[INPUT][1]; distortion_coeffs = test_mat[INPUT][2]; R = test_mat[INPUT][3]; P = test_mat[INPUT][4]; } return code; } void CV_UndistortPointsTest::prepare_to_validation(int /*test_case_idx*/) { int dist_size = test_mat[INPUT][2].cols > test_mat[INPUT][2].rows ? test_mat[INPUT][2].cols : test_mat[INPUT][2].rows; double cam[9] = {0,0,0,0,0,0,0,0,1}; double rot[9] = {1,0,0,0,1,0,0,0,1}; double* dist = new double[dist_size ]; double* proj = new double[test_mat[INPUT][4].cols * test_mat[INPUT][4].rows]; double* points = new double[N_POINTS*2]; double* r_points = new double[N_POINTS*2]; //Run reference calculations CvMat ref_points= cvMat(test_mat[INPUT][0].rows,test_mat[INPUT][0].cols,CV_64FC2,r_points); CvMat _camera = cvMat(3,3,CV_64F,cam); CvMat _rot = cvMat(3,3,CV_64F,rot); CvMat _distort = cvMat(test_mat[INPUT][2].rows,test_mat[INPUT][2].cols,CV_64F,dist); CvMat _proj = cvMat(test_mat[INPUT][4].rows,test_mat[INPUT][4].cols,CV_64F,proj); CvMat _points= cvMat(test_mat[TEMP][0].rows,test_mat[TEMP][0].cols,CV_64FC2,points); Mat __camera = cvarrToMat(&_camera); Mat __distort = cvarrToMat(&_distort); Mat __rot = cvarrToMat(&_rot); Mat __proj = cvarrToMat(&_proj); Mat __points = cvarrToMat(&_points); Mat _ref_points = cvarrToMat(&ref_points); cvtest::convert(test_mat[INPUT][1], __camera, __camera.type()); cvtest::convert(test_mat[INPUT][2], __distort, __distort.type()); cvtest::convert(test_mat[INPUT][3], __rot, __rot.type()); cvtest::convert(test_mat[INPUT][4], __proj, __proj.type()); if (useCPlus) { if (useDstMat) { CvMat temp = cvMat(dst_points_mat); for (int i=0;icols == 3)) __P = cvCreateMat(3,3,CV_64F); else __P = cvCreateMat(3,4,CV_64F); if (matP) { cvtest::convert(cvarrToMat(matP), cvarrToMat(__P), -1); } else { cvZero(__P); __P->data.db[0] = 1; __P->data.db[4] = 1; __P->data.db[8] = 1; } CvMat* __R = cvCreateMat(3,3,CV_64F); if (matR) { cvCopy(matR,__R); } else { cvZero(__R); __R->data.db[0] = 1; __R->data.db[4] = 1; __R->data.db[8] = 1; } for (int i=0;icols > 3 ? 1 : 0; double x = (_src->data.db[2*i]-__P->data.db[2])/__P->data.db[0]; double y = (_src->data.db[2*i+1]-__P->data.db[5+movement])/__P->data.db[4+movement]; CvMat inverse = cvMat(3,3,CV_64F,a); cvInvert(__R,&inverse); double w1 = x*inverse.data.db[6]+y*inverse.data.db[7]+inverse.data.db[8]; double _x = (x*inverse.data.db[0]+y*inverse.data.db[1]+inverse.data.db[2])/w1; double _y = (x*inverse.data.db[3]+y*inverse.data.db[4]+inverse.data.db[5])/w1; //Distortions double __x = _x; double __y = _y; if (_distCoeffs) { double r2 = _x*_x+_y*_y; __x = _x*(1+_distCoeffs->data.db[0]*r2+_distCoeffs->data.db[1]*r2*r2)+ 2*_distCoeffs->data.db[2]*_x*_y+_distCoeffs->data.db[3]*(r2+2*_x*_x); __y = _y*(1+_distCoeffs->data.db[0]*r2+_distCoeffs->data.db[1]*r2*r2)+ 2*_distCoeffs->data.db[3]*_x*_y+_distCoeffs->data.db[2]*(r2+2*_y*_y); if ((_distCoeffs->cols > 4) || (_distCoeffs->rows > 4)) { __x+=_x*_distCoeffs->data.db[4]*r2*r2*r2; __y+=_y*_distCoeffs->data.db[4]*r2*r2*r2; } } _dst->data.db[2*i] = __x*_cameraMatrix->data.db[0]+_cameraMatrix->data.db[2]; _dst->data.db[2*i+1] = __y*_cameraMatrix->data.db[4]+_cameraMatrix->data.db[5]; } cvReleaseMat(&__R); cvReleaseMat(&__P); } double CV_UndistortPointsTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ ) { return 5e-2; } //------------------------------------------------------ class CV_InitUndistortRectifyMapTest : public cvtest::ArrayTest { public: CV_InitUndistortRectifyMapTest(); protected: int prepare_test_case (int test_case_idx); void prepare_to_validation( int test_case_idx ); void get_test_array_types_and_sizes( int test_case_idx, vector >& sizes, vector >& types ); double get_success_error_level( int test_case_idx, int i, int j ); void run_func(); private: bool useCPlus; static const int N_POINTS = 100; static const int MAX_X = 2048; static const int MAX_Y = 2048; bool zero_new_cam; bool zero_distortion; bool zero_R; cv::Size img_size; cv::Mat camera_mat; cv::Mat R; cv::Mat new_camera_mat; cv::Mat distortion_coeffs; cv::Mat mapx; cv::Mat mapy; CvMat* _mapx; CvMat* _mapy; int mat_type; }; CV_InitUndistortRectifyMapTest::CV_InitUndistortRectifyMapTest() { test_array[INPUT].push_back(NULL); // test points matrix test_array[INPUT].push_back(NULL); // camera matrix test_array[INPUT].push_back(NULL); // distortion coeffs test_array[INPUT].push_back(NULL); // R matrix test_array[INPUT].push_back(NULL); // new camera matrix test_array[OUTPUT].push_back(NULL); // distorted dst points test_array[REF_OUTPUT].push_back(NULL); useCPlus = false; zero_distortion = zero_new_cam = zero_R = false; _mapx = _mapy = NULL; mat_type = 0; } void CV_InitUndistortRectifyMapTest::get_test_array_types_and_sizes( int test_case_idx, vector >& sizes, vector >& types ) { cvtest::ArrayTest::get_test_array_types_and_sizes(test_case_idx,sizes,types); RNG& rng = ts->get_rng(); useCPlus = ((cvtest::randInt(rng) % 2)!=0); //useCPlus = 0; types[INPUT][0] = types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_64FC2; types[INPUT][1] = cvtest::randInt(rng)%2 ? CV_64F : CV_32F; types[INPUT][2] = cvtest::randInt(rng)%2 ? CV_64F : CV_32F; types[INPUT][3] = cvtest::randInt(rng)%2 ? CV_64F : CV_32F; types[INPUT][4] = cvtest::randInt(rng)%2 ? CV_64F : CV_32F; sizes[INPUT][0] = sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = cvSize(N_POINTS,1); sizes[INPUT][1] = sizes[INPUT][3] = cvSize(3,3); sizes[INPUT][4] = cvSize(3,3); if (cvtest::randInt(rng)%2) { if (cvtest::randInt(rng)%2) { sizes[INPUT][2] = cvSize(1,4); } else { sizes[INPUT][2] = cvSize(1,5); } } else { if (cvtest::randInt(rng)%2) { sizes[INPUT][2] = cvSize(4,1); } else { sizes[INPUT][2] = cvSize(5,1); } } } int CV_InitUndistortRectifyMapTest::prepare_test_case(int test_case_idx) { RNG& rng = ts->get_rng(); int code = cvtest::ArrayTest::prepare_test_case( test_case_idx ); if (code <= 0) return code; img_size.width = cvtest::randInt(rng) % MAX_X + 1; img_size.height = cvtest::randInt(rng) % MAX_Y + 1; if (useCPlus) { mat_type = (cvtest::randInt(rng) % 2) == 0 ? CV_32FC1 : CV_16SC2; if ((cvtest::randInt(rng) % 4) == 0) mat_type = -1; if ((cvtest::randInt(rng) % 4) == 0) mat_type = CV_32FC2; _mapx = 0; _mapy = 0; } else { int typex = (cvtest::randInt(rng) % 2) == 0 ? CV_32FC1 : CV_16SC2; //typex = CV_32FC1; ///!!!!!!!!!!!!!!!! int typey = (typex == CV_32FC1) ? CV_32FC1 : CV_16UC1; _mapx = cvCreateMat(img_size.height,img_size.width,typex); _mapy = cvCreateMat(img_size.height,img_size.width,typey); } int dist_size = test_mat[INPUT][2].cols > test_mat[INPUT][2].rows ? test_mat[INPUT][2].cols : test_mat[INPUT][2].rows; double cam[9] = {0,0,0,0,0,0,0,0,1}; vector dist(dist_size); vector new_cam(test_mat[INPUT][4].cols * test_mat[INPUT][4].rows); vector points(N_POINTS); Mat _camera(3,3,CV_64F,cam); Mat _distort(test_mat[INPUT][2].size(),CV_64F,&dist[0]); Mat _new_cam(test_mat[INPUT][4].size(),CV_64F,&new_cam[0]); Mat _points(test_mat[INPUT][0].size(),CV_64FC2, &points[0]); //Generating points for (int i=0;i 0 ) dist[1] = -dist[1]; if( cvtest::randInt(rng)%4 != 0 ) { dist[2] = cvtest::randReal(rng)*0.004 - 0.002; dist[3] = cvtest::randReal(rng)*0.004 - 0.002; if (dist_size > 4) dist[4] = cvtest::randReal(rng)*0.004 - 0.002; } else { dist[2] = dist[3] = 0; if (dist_size > 4) dist[4] = 0; } //Generating new camera matrix _new_cam = Scalar::all(0); new_cam[8] = 1; //new_cam[0] = cam[0]; //new_cam[4] = cam[4]; //new_cam[2] = cam[2]; //new_cam[5] = cam[5]; new_cam[0] = cam[0] + (cvtest::randReal(rng) - (double)0.5)*0.2*cam[0]; //10% new_cam[4] = cam[4] + (cvtest::randReal(rng) - (double)0.5)*0.2*cam[4]; //10% new_cam[2] = cam[2] + (cvtest::randReal(rng) - (double)0.5)*0.3*img_size.width; //15% new_cam[5] = cam[5] + (cvtest::randReal(rng) - (double)0.5)*0.3*img_size.height; //15% //Generating R matrix Mat _rot(3,3,CV_64F); Mat rotation(1,3,CV_64F); rotation.at(0) = CV_PI/8*(cvtest::randReal(rng) - (double)0.5); // phi rotation.at(1) = CV_PI/8*(cvtest::randReal(rng) - (double)0.5); // ksi rotation.at(2) = CV_PI/3*(cvtest::randReal(rng) - (double)0.5); //khi cvtest::Rodrigues(rotation, _rot); //cvSetIdentity(_rot); //copying data cvtest::convert( _points, test_mat[INPUT][0], test_mat[INPUT][0].type()); cvtest::convert( _camera, test_mat[INPUT][1], test_mat[INPUT][1].type()); cvtest::convert( _distort, test_mat[INPUT][2], test_mat[INPUT][2].type()); cvtest::convert( _rot, test_mat[INPUT][3], test_mat[INPUT][3].type()); cvtest::convert( _new_cam, test_mat[INPUT][4], test_mat[INPUT][4].type()); zero_distortion = (cvtest::randInt(rng)%2) == 0 ? false : true; zero_new_cam = (cvtest::randInt(rng)%2) == 0 ? false : true; zero_R = (cvtest::randInt(rng)%2) == 0 ? false : true; if (useCPlus) { camera_mat = test_mat[INPUT][1]; distortion_coeffs = test_mat[INPUT][2]; R = test_mat[INPUT][3]; new_camera_mat = test_mat[INPUT][4]; } return code; } void CV_InitUndistortRectifyMapTest::prepare_to_validation(int/* test_case_idx*/) { #if 0 int dist_size = test_mat[INPUT][2].cols > test_mat[INPUT][2].rows ? test_mat[INPUT][2].cols : test_mat[INPUT][2].rows; double cam[9] = {0,0,0,0,0,0,0,0,1}; double rot[9] = {1,0,0,0,1,0,0,0,1}; vector dist(dist_size); vector new_cam(test_mat[INPUT][4].cols * test_mat[INPUT][4].rows); vector points(N_POINTS); vector r_points(N_POINTS); //Run reference calculations Mat ref_points(test_mat[INPUT][0].size(),CV_64FC2,&r_points[0]); Mat _camera(3,3,CV_64F,cam); Mat _rot(3,3,CV_64F,rot); Mat _distort(test_mat[INPUT][2].size(),CV_64F,&dist[0]); Mat _new_cam(test_mat[INPUT][4].size(),CV_64F,&new_cam[0]); Mat _points(test_mat[INPUT][0].size(),CV_64FC2,&points[0]); cvtest::convert(test_mat[INPUT][1],_camera,_camera.type()); cvtest::convert(test_mat[INPUT][2],_distort,_distort.type()); cvtest::convert(test_mat[INPUT][3],_rot,_rot.type()); cvtest::convert(test_mat[INPUT][4],_new_cam,_new_cam.type()); //Applying precalculated undistort rectify map if (!useCPlus) { mapx = cv::Mat(_mapx); mapy = cv::Mat(_mapy); } cv::Mat map1,map2; cv::convertMaps(mapx,mapy,map1,map2,CV_32FC1); CvMat _map1 = map1; CvMat _map2 = map2; const Point2d* sptr = (const Point2d*)test_mat[INPUT][0].data; for( int i = 0;i < N_POINTS; i++ ) { int u = saturate_cast(sptr[i].x); int v = saturate_cast(sptr[i].y); points[i].x = _map1.data.fl[v*_map1.cols + u]; points[i].y = _map2.data.fl[v*_map2.cols + u]; } //--- cv::undistortPoints(_points, ref_points, _camera, zero_distortion ? Mat() : _distort, zero_R ? Mat::eye(3,3,CV_64F) : _rot, zero_new_cam ? _camera : _new_cam); //cvTsDistortPoints(&_points,&ref_points,&_camera,&_distort,&_rot,&_new_cam); cvtest::convert(ref_points, test_mat[REF_OUTPUT][0], test_mat[REF_OUTPUT][0].type()); cvtest::copy(test_mat[INPUT][0],test_mat[OUTPUT][0]); cvReleaseMat(&_mapx); cvReleaseMat(&_mapy); #else int dist_size = test_mat[INPUT][2].cols > test_mat[INPUT][2].rows ? test_mat[INPUT][2].cols : test_mat[INPUT][2].rows; double cam[9] = {0,0,0,0,0,0,0,0,1}; double rot[9] = {1,0,0,0,1,0,0,0,1}; double* dist = new double[dist_size ]; double* new_cam = new double[test_mat[INPUT][4].cols * test_mat[INPUT][4].rows]; double* points = new double[N_POINTS*2]; double* r_points = new double[N_POINTS*2]; //Run reference calculations CvMat ref_points= cvMat(test_mat[INPUT][0].rows,test_mat[INPUT][0].cols,CV_64FC2,r_points); CvMat _camera = cvMat(3,3,CV_64F,cam); CvMat _rot = cvMat(3,3,CV_64F,rot); CvMat _distort = cvMat(test_mat[INPUT][2].rows,test_mat[INPUT][2].cols,CV_64F,dist); CvMat _new_cam = cvMat(test_mat[INPUT][4].rows,test_mat[INPUT][4].cols,CV_64F,new_cam); CvMat _points= cvMat(test_mat[INPUT][0].rows,test_mat[INPUT][0].cols,CV_64FC2,points); CvMat _input1 = cvMat(test_mat[INPUT][1]); CvMat _input2 = cvMat(test_mat[INPUT][2]); CvMat _input3 = cvMat(test_mat[INPUT][3]); CvMat _input4 = cvMat(test_mat[INPUT][4]); cvtest::convert(cvarrToMat(&_input1), cvarrToMat(&_camera), -1); cvtest::convert(cvarrToMat(&_input2), cvarrToMat(&_distort), -1); cvtest::convert(cvarrToMat(&_input3), cvarrToMat(&_rot), -1); cvtest::convert(cvarrToMat(&_input4), cvarrToMat(&_new_cam), -1); //Applying precalculated undistort rectify map if (!useCPlus) { mapx = cv::cvarrToMat(_mapx); mapy = cv::cvarrToMat(_mapy); } cv::Mat map1,map2; cv::convertMaps(mapx,mapy,map1,map2,CV_32FC1); CvMat _map1 = cvMat(map1); CvMat _map2 = cvMat(map2); for (int i=0;i()[2*i]; double v = test_mat[INPUT][0].ptr()[2*i+1]; _points.data.db[2*i] = (double)_map1.data.fl[(int)v*_map1.cols+(int)u]; _points.data.db[2*i+1] = (double)_map2.data.fl[(int)v*_map2.cols+(int)u]; } //--- cvUndistortPoints(&_points,&ref_points,&_camera, zero_distortion ? 0 : &_distort, zero_R ? 0 : &_rot, zero_new_cam ? &_camera : &_new_cam); //cvTsDistortPoints(&_points,&ref_points,&_camera,&_distort,&_rot,&_new_cam); CvMat dst = cvMat(test_mat[REF_OUTPUT][0]); cvtest::convert(cvarrToMat(&ref_points), cvarrToMat(&dst), -1); cvtest::copy(test_mat[INPUT][0],test_mat[OUTPUT][0]); delete[] dist; delete[] new_cam; delete[] points; delete[] r_points; cvReleaseMat(&_mapx); cvReleaseMat(&_mapy); #endif } void CV_InitUndistortRectifyMapTest::run_func() { if (useCPlus) { cv::Mat input2,input3,input4; input2 = zero_distortion ? cv::Mat() : test_mat[INPUT][2]; input3 = zero_R ? cv::Mat() : test_mat[INPUT][3]; input4 = zero_new_cam ? cv::Mat() : test_mat[INPUT][4]; cv::initUndistortRectifyMap(camera_mat,input2,input3,input4,img_size,mat_type,mapx,mapy); } else { CvMat input1 = cvMat(test_mat[INPUT][1]), input2, input3, input4; if( !zero_distortion ) input2 = cvMat(test_mat[INPUT][2]); if( !zero_R ) input3 = cvMat(test_mat[INPUT][3]); if( !zero_new_cam ) input4 = cvMat(test_mat[INPUT][4]); cvInitUndistortRectifyMap(&input1, zero_distortion ? 0 : &input2, zero_R ? 0 : &input3, zero_new_cam ? 0 : &input4, _mapx,_mapy); } } double CV_InitUndistortRectifyMapTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ ) { return 8; } ////////////////////////////////////////////////////////////////////////////////////////////////////// TEST(Calib3d_DefaultNewCameraMatrix, accuracy) { CV_DefaultNewCameraMatrixTest test; test.safe_run(); } TEST(Calib3d_UndistortPoints, accuracy) { CV_UndistortPointsTest test; test.safe_run(); } TEST(Calib3d_InitUndistortRectifyMap, accuracy) { CV_InitUndistortRectifyMapTest test; test.safe_run(); } }} // namespace