/*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 "test_chessboardgenerator.hpp" namespace opencv_test { namespace { //template ostream& operator<<(ostream& out, const Mat_& mat) //{ // for(Mat_::const_iterator pos = mat.begin(), end = mat.end(); pos != end; ++pos) // out << *pos << " "; // return out; //} //ostream& operator<<(ostream& out, const Mat& mat) { return out << Mat_(mat); } Mat calcRvec(const vector& points, const Size& cornerSize) { Point3f p00 = points[0]; Point3f p10 = points[1]; Point3f p01 = points[cornerSize.width]; Vec3d ex(p10.x - p00.x, p10.y - p00.y, p10.z - p00.z); Vec3d ey(p01.x - p00.x, p01.y - p00.y, p01.z - p00.z); Vec3d ez = ex.cross(ey); Mat rot(3, 3, CV_64F); *rot.ptr(0) = ex; *rot.ptr(1) = ey; *rot.ptr(2) = ez * (1.0/cv::norm(ez)); // TODO cvtest Mat res; cvtest::Rodrigues(rot.t(), res); return res.reshape(1, 1); } class CV_CalibrateCameraArtificialTest : public cvtest::BaseTest { public: CV_CalibrateCameraArtificialTest() : r(0) { } ~CV_CalibrateCameraArtificialTest() {} protected: int r; const static int JUST_FIND_CORNERS = 0; const static int USE_CORNERS_SUBPIX = 1; const static int USE_4QUAD_CORNERS = 2; const static int ARTIFICIAL_CORNERS = 4; bool checkErr(double a, double a0, double eps, double delta) { return fabs(a - a0) > eps * (fabs(a0) + delta); } void compareCameraMatrs(const Mat_& camMat, const Mat& camMat_est) { if ( camMat_est.at(0, 1) != 0 || camMat_est.at(1, 0) != 0 || camMat_est.at(2, 0) != 0 || camMat_est.at(2, 1) != 0 || camMat_est.at(2, 2) != 1) { ts->printf( cvtest::TS::LOG, "Bad shape of camera matrix returned \n"); ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH); } double fx_e = camMat_est.at(0, 0), fy_e = camMat_est.at(1, 1); double cx_e = camMat_est.at(0, 2), cy_e = camMat_est.at(1, 2); double fx = camMat(0, 0), fy = camMat(1, 1), cx = camMat(0, 2), cy = camMat(1, 2); const double eps = 1e-2; const double dlt = 1e-5; bool fail = checkErr(fx_e, fx, eps, dlt) || checkErr(fy_e, fy, eps, dlt) || checkErr(cx_e, cx, eps, dlt) || checkErr(cy_e, cy, eps, dlt); if (fail) { ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY); } ts->printf( cvtest::TS::LOG, "%d) Expected [Fx Fy Cx Cy] = [%.3f %.3f %.3f %.3f]\n", r, fx, fy, cx, cy); ts->printf( cvtest::TS::LOG, "%d) Estimated [Fx Fy Cx Cy] = [%.3f %.3f %.3f %.3f]\n", r, fx_e, fy_e, cx_e, cy_e); } void compareDistCoeffs(const Mat_& distCoeffs, const Mat& distCoeffs_est) { const double *dt_e = distCoeffs_est.ptr(); double k1_e = dt_e[0], k2_e = dt_e[1], k3_e = dt_e[4]; double p1_e = dt_e[2], p2_e = dt_e[3]; double k1 = distCoeffs(0, 0), k2 = distCoeffs(0, 1), k3 = distCoeffs(0, 4); double p1 = distCoeffs(0, 2), p2 = distCoeffs(0, 3); const double eps = 5e-2; const double dlt = 1e-3; const double eps_k3 = 5; const double dlt_k3 = 1e-3; bool fail = checkErr(k1_e, k1, eps, dlt) || checkErr(k2_e, k2, eps, dlt) || checkErr(k3_e, k3, eps_k3, dlt_k3) || checkErr(p1_e, p1, eps, dlt) || checkErr(p2_e, p2, eps, dlt); if (fail) { // commented according to vp123's recommendation. TODO - improve accuracy //ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY); ss } ts->printf( cvtest::TS::LOG, "%d) DistCoeff exp=(%.2f, %.2f, %.4f, %.4f %.2f)\n", r, k1, k2, p1, p2, k3); ts->printf( cvtest::TS::LOG, "%d) DistCoeff est=(%.2f, %.2f, %.4f, %.4f %.2f)\n", r, k1_e, k2_e, p1_e, p2_e, k3_e); ts->printf( cvtest::TS::LOG, "%d) AbsError = [%.5f %.5f %.5f %.5f %.5f]\n", r, fabs(k1-k1_e), fabs(k2-k2_e), fabs(p1-p1_e), fabs(p2-p2_e), fabs(k3-k3_e)); } void compareShiftVecs(const vector& tvecs, const vector& tvecs_est) { const double eps = 1e-2; const double dlt = 1e-4; int err_count = 0; const int errMsgNum = 4; for(size_t i = 0; i < tvecs.size(); ++i) { const Point3d& tvec = *tvecs[i].ptr(); const Point3d& tvec_est = *tvecs_est[i].ptr(); double n1 = cv::norm(tvec_est - tvec); // TODO cvtest double n2 = cv::norm(tvec); // TODO cvtest if (n1 > eps* (n2 + dlt)) { if (err_count++ < errMsgNum) { if (err_count == errMsgNum) ts->printf( cvtest::TS::LOG, "%d) ...\n", r); else { ts->printf( cvtest::TS::LOG, "%d) Bad accuracy in returned tvecs. Index = %d\n", r, i); ts->printf( cvtest::TS::LOG, "%d) norm(tvec_est - tvec) = %f, norm(tvec_exp) = %f \n", r, n1, n2); } } ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY); } } } void compareRotationVecs(const vector& rvecs, const vector& rvecs_est) { const double eps = 2e-2; const double dlt = 1e-4; Mat rmat, rmat_est; int err_count = 0; const int errMsgNum = 4; for(size_t i = 0; i < rvecs.size(); ++i) { cvtest::Rodrigues(rvecs[i], rmat); cvtest::Rodrigues(rvecs_est[i], rmat_est); if (cvtest::norm(rmat_est, rmat, NORM_L2) > eps* (cvtest::norm(rmat, NORM_L2) + dlt)) { if (err_count++ < errMsgNum) { if (err_count == errMsgNum) ts->printf( cvtest::TS::LOG, "%d) ...\n", r); else { ts->printf( cvtest::TS::LOG, "%d) Bad accuracy in returned rvecs (rotation matrs). Index = %d\n", r, i); ts->printf( cvtest::TS::LOG, "%d) norm(rot_mat_est - rot_mat_exp) = %f, norm(rot_mat_exp) = %f \n", r, cvtest::norm(rmat_est, rmat, NORM_L2), cvtest::norm(rmat, NORM_L2)); } } ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY); } } } double reprojectErrorWithoutIntrinsics(const vector& cb3d, const vector& _rvecs_exp, const vector& _tvecs_exp, const vector& rvecs_est, const vector& tvecs_est) { const static Mat eye33 = Mat::eye(3, 3, CV_64F); const static Mat zero15 = Mat::zeros(1, 5, CV_64F); Mat _chessboard3D(cb3d); vector uv_exp, uv_est; double res = 0; for(size_t i = 0; i < rvecs_exp.size(); ++i) { projectPoints(_chessboard3D, _rvecs_exp[i], _tvecs_exp[i], eye33, zero15, uv_exp); projectPoints(_chessboard3D, rvecs_est[i], tvecs_est[i], eye33, zero15, uv_est); for(size_t j = 0; j < cb3d.size(); ++j) res += cv::norm(uv_exp[i] - uv_est[i]); // TODO cvtest } return res; } Size2f sqSile; vector chessboard3D; vector boards, rvecs_exp, tvecs_exp, rvecs_spnp, tvecs_spnp; vector< vector > objectPoints; vector< vector > imagePoints_art; vector< vector > imagePoints_findCb; void prepareForTest(const Mat& bg, const Mat& camMat, const Mat& distCoeffs, size_t brdsNum, const ChessBoardGenerator& cbg) { sqSile = Size2f(1.f, 1.f); Size cornersSize = cbg.cornersSize(); chessboard3D.clear(); for(int j = 0; j < cornersSize.height; ++j) for(int i = 0; i < cornersSize.width; ++i) chessboard3D.push_back(Point3f(sqSile.width * i, sqSile.height * j, 0)); boards.resize(brdsNum); rvecs_exp.resize(brdsNum); tvecs_exp.resize(brdsNum); objectPoints.clear(); objectPoints.resize(brdsNum, chessboard3D); imagePoints_art.clear(); imagePoints_findCb.clear(); vector corners_art, corners_fcb; for(size_t i = 0; i < brdsNum; ++i) { for(;;) { boards[i] = cbg(bg, camMat, distCoeffs, sqSile, corners_art); if(findChessboardCorners(boards[i], cornersSize, corners_fcb)) break; } //cv::namedWindow("CB"); imshow("CB", boards[i]); cv::waitKey(); imagePoints_art.push_back(corners_art); imagePoints_findCb.push_back(corners_fcb); tvecs_exp[i].create(1, 3, CV_64F); *tvecs_exp[i].ptr() = cbg.corners3d[0]; rvecs_exp[i] = calcRvec(cbg.corners3d, cbg.cornersSize()); } } void runTest(const Size& imgSize, const Mat_& camMat, const Mat_& distCoeffs, size_t brdsNum, const Size& cornersSize, int flag = 0) { const TermCriteria tc(TermCriteria::EPS|TermCriteria::MAX_ITER, 30, 0.1); vector< vector > imagePoints; switch(flag) { case JUST_FIND_CORNERS: imagePoints = imagePoints_findCb; break; case ARTIFICIAL_CORNERS: imagePoints = imagePoints_art; break; case USE_CORNERS_SUBPIX: for(size_t i = 0; i < brdsNum; ++i) { Mat gray; cvtColor(boards[i], gray, COLOR_BGR2GRAY); vector tmp = imagePoints_findCb[i]; cornerSubPix(gray, tmp, Size(5, 5), Size(-1,-1), tc); imagePoints.push_back(tmp); } break; case USE_4QUAD_CORNERS: for(size_t i = 0; i < brdsNum; ++i) { Mat gray; cvtColor(boards[i], gray, COLOR_BGR2GRAY); vector tmp = imagePoints_findCb[i]; find4QuadCornerSubpix(gray, tmp, Size(5, 5)); imagePoints.push_back(tmp); } break; default: throw std::exception(); } Mat camMat_est = Mat::eye(3, 3, CV_64F), distCoeffs_est = Mat::zeros(1, 5, CV_64F); vector rvecs_est, tvecs_est; int flags = /*CALIB_FIX_K3|*/CALIB_FIX_K4|CALIB_FIX_K5|CALIB_FIX_K6; //CALIB_FIX_K3; //CALIB_FIX_ASPECT_RATIO | | CALIB_ZERO_TANGENT_DIST; TermCriteria criteria = TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 100, DBL_EPSILON); double rep_error = calibrateCamera(objectPoints, imagePoints, imgSize, camMat_est, distCoeffs_est, rvecs_est, tvecs_est, flags, criteria); rep_error /= brdsNum * cornersSize.area(); const double thres = 1; if (rep_error > thres) { ts->printf( cvtest::TS::LOG, "%d) Too big reproject error = %f\n", r, rep_error); ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY); } compareCameraMatrs(camMat, camMat_est); compareDistCoeffs(distCoeffs, distCoeffs_est); compareShiftVecs(tvecs_exp, tvecs_est); compareRotationVecs(rvecs_exp, rvecs_est); double rep_errorWOI = reprojectErrorWithoutIntrinsics(chessboard3D, rvecs_exp, tvecs_exp, rvecs_est, tvecs_est); rep_errorWOI /= brdsNum * cornersSize.area(); const double thres2 = 0.01; if (rep_errorWOI > thres2) { ts->printf( cvtest::TS::LOG, "%d) Too big reproject error without intrinsics = %f\n", r, rep_errorWOI); ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY); } ts->printf( cvtest::TS::LOG, "%d) Testing solvePnP...\n", r); rvecs_spnp.resize(brdsNum); tvecs_spnp.resize(brdsNum); for(size_t i = 0; i < brdsNum; ++i) solvePnP(objectPoints[i], imagePoints[i], camMat, distCoeffs, rvecs_spnp[i], tvecs_spnp[i]); compareShiftVecs(tvecs_exp, tvecs_spnp); compareRotationVecs(rvecs_exp, rvecs_spnp); } void run(int) { ts->set_failed_test_info(cvtest::TS::OK); RNG& rng = theRNG(); int progress = 0; int repeat_num = 3; for(r = 0; r < repeat_num; ++r) { const int brds_num = 20; Mat bg(Size(640, 480), CV_8UC3); randu(bg, Scalar::all(32), Scalar::all(255)); GaussianBlur(bg, bg, Size(5, 5), 2); double fx = 300 + (20 * (double)rng - 10); double fy = 300 + (20 * (double)rng - 10); double cx = bg.cols/2 + (40 * (double)rng - 20); double cy = bg.rows/2 + (40 * (double)rng - 20); Mat_ camMat(3, 3); camMat << fx, 0., cx, 0, fy, cy, 0., 0., 1.; double k1 = 0.5 + (double)rng/5; double k2 = (double)rng/5; double k3 = (double)rng/5; double p1 = 0.001 + (double)rng/10; double p2 = 0.001 + (double)rng/10; Mat_ distCoeffs(1, 5, 0.0); distCoeffs << k1, k2, p1, p2, k3; ChessBoardGenerator cbg(Size(9, 8)); cbg.min_cos = 0.9; cbg.cov = 0.8; progress = update_progress(progress, r, repeat_num, 0); ts->printf( cvtest::TS::LOG, "\n"); prepareForTest(bg, camMat, distCoeffs, brds_num, cbg); ts->printf( cvtest::TS::LOG, "artificial corners\n"); runTest(bg.size(), camMat, distCoeffs, brds_num, cbg.cornersSize(), ARTIFICIAL_CORNERS); progress = update_progress(progress, r, repeat_num, 0); ts->printf( cvtest::TS::LOG, "findChessboard corners\n"); runTest(bg.size(), camMat, distCoeffs, brds_num, cbg.cornersSize(), JUST_FIND_CORNERS); progress = update_progress(progress, r, repeat_num, 0); ts->printf( cvtest::TS::LOG, "cornersSubPix corners\n"); runTest(bg.size(), camMat, distCoeffs, brds_num, cbg.cornersSize(), USE_CORNERS_SUBPIX); progress = update_progress(progress, r, repeat_num, 0); ts->printf( cvtest::TS::LOG, "4quad corners\n"); runTest(bg.size(), camMat, distCoeffs, brds_num, cbg.cornersSize(), USE_4QUAD_CORNERS); progress = update_progress(progress, r, repeat_num, 0); } } }; TEST(Calib3d_CalibrateCamera_CPP, DISABLED_accuracy_on_artificial_data) { CV_CalibrateCameraArtificialTest test; test.safe_run(); } }} // namespace