mirror of
https://github.com/opencv/opencv.git
synced 2024-12-24 17:18:28 +08:00
aa5326c231
Conflicts: modules/core/src/stat.cpp
432 lines
16 KiB
C++
432 lines
16 KiB
C++
/*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 <string>
|
|
#include <limits>
|
|
#include <vector>
|
|
#include <iostream>
|
|
#include <sstream>
|
|
#include <iomanip>
|
|
|
|
#include "test_chessboardgenerator.hpp"
|
|
|
|
using namespace cv;
|
|
using namespace std;
|
|
|
|
//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/norm(ez));
|
|
|
|
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 recomendation. TODO - improve accuaracy
|
|
//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>();
|
|
|
|
if (norm(tvec_est - tvec) > eps* (norm(tvec) + 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, norm(tvec_est - tvec), norm(tvec));
|
|
}
|
|
}
|
|
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 += norm(uv_exp[i] - uv_est[i]);
|
|
}
|
|
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(Mat(objectPoints[i]), Mat(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(); }
|