mirror of https://github.com/opencv/opencv.git
Open Source Computer Vision Library
https://opencv.org/
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
426 lines
16 KiB
426 lines
16 KiB
/*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<class T> ostream& operator<<(ostream& out, const Mat_<T>& mat) |
|
//{ |
|
// for(Mat_<T>::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_<double>(mat); } |
|
|
|
Mat calcRvec(const vector<Point3f>& 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<Vec3d>(0) = ex; |
|
*rot.ptr<Vec3d>(1) = ey; |
|
*rot.ptr<Vec3d>(2) = ez * (1.0/cv::norm(ez)); // TODO cvtest |
|
|
|
Mat res; |
|
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_<double>& camMat, const Mat& camMat_est) |
|
{ |
|
if ( camMat_est.at<double>(0, 1) != 0 || camMat_est.at<double>(1, 0) != 0 || |
|
camMat_est.at<double>(2, 0) != 0 || camMat_est.at<double>(2, 1) != 0 || |
|
camMat_est.at<double>(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<double>(0, 0), fy_e = camMat_est.at<double>(1, 1); |
|
double cx_e = camMat_est.at<double>(0, 2), cy_e = camMat_est.at<double>(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_<double>& distCoeffs, const Mat& distCoeffs_est) |
|
{ |
|
const double *dt_e = distCoeffs_est.ptr<double>(); |
|
|
|
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<Mat>& tvecs, const vector<Mat>& 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<Point3d>(); |
|
const Point3d& tvec_est = *tvecs_est[i].ptr<Point3d>(); |
|
|
|
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<Mat>& rvecs, const vector<Mat>& 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) |
|
{ |
|
Rodrigues(rvecs[i], rmat); |
|
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<Point3f>& cb3d, const vector<Mat>& _rvecs_exp, const vector<Mat>& _tvecs_exp, |
|
const vector<Mat>& rvecs_est, const vector<Mat>& 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<Point2f> 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<Point3f> chessboard3D; |
|
vector<Mat> boards, rvecs_exp, tvecs_exp, rvecs_spnp, tvecs_spnp; |
|
vector< vector<Point3f> > objectPoints; |
|
vector< vector<Point2f> > imagePoints_art; |
|
vector< vector<Point2f> > 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<Point2f> 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<Point3d>() = cbg.corners3d[0]; |
|
rvecs_exp[i] = calcRvec(cbg.corners3d, cbg.cornersSize()); |
|
} |
|
|
|
} |
|
|
|
void runTest(const Size& imgSize, const Mat_<double>& camMat, const Mat_<double>& distCoeffs, size_t brdsNum, const Size& cornersSize, int flag = 0) |
|
{ |
|
const TermCriteria tc(TermCriteria::EPS|TermCriteria::MAX_ITER, 30, 0.1); |
|
|
|
vector< vector<Point2f> > 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<Point2f> 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<Point2f> 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<Mat> 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_<double> 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_<double> 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
|
|
|