/*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 "precomp.hpp" #include "upnp.h" #include "dls.h" #include "epnp.h" #include "p3p.h" #include "ap3p.h" #include "calib3d_c_api.h" #include namespace cv { void drawFrameAxes(InputOutputArray image, InputArray cameraMatrix, InputArray distCoeffs, InputArray rvec, InputArray tvec, float length, int thickness) { CV_INSTRUMENT_REGION(); int type = image.type(); int cn = CV_MAT_CN(type); CV_CheckType(type, cn == 1 || cn == 3 || cn == 4, "Number of channels must be 1, 3 or 4" ); CV_Assert(image.getMat().total() > 0); CV_Assert(length > 0); // project axes points vector axesPoints; axesPoints.push_back(Point3f(0, 0, 0)); axesPoints.push_back(Point3f(length, 0, 0)); axesPoints.push_back(Point3f(0, length, 0)); axesPoints.push_back(Point3f(0, 0, length)); vector imagePoints; projectPoints(axesPoints, rvec, tvec, cameraMatrix, distCoeffs, imagePoints); // draw axes lines line(image, imagePoints[0], imagePoints[1], Scalar(0, 0, 255), thickness); line(image, imagePoints[0], imagePoints[2], Scalar(0, 255, 0), thickness); line(image, imagePoints[0], imagePoints[3], Scalar(255, 0, 0), thickness); } bool solvePnP( InputArray _opoints, InputArray _ipoints, InputArray _cameraMatrix, InputArray _distCoeffs, OutputArray _rvec, OutputArray _tvec, bool useExtrinsicGuess, int flags ) { CV_INSTRUMENT_REGION(); Mat opoints = _opoints.getMat(), ipoints = _ipoints.getMat(); int npoints = std::max(opoints.checkVector(3, CV_32F), opoints.checkVector(3, CV_64F)); CV_Assert( ( (npoints >= 4) || (npoints == 3 && flags == SOLVEPNP_ITERATIVE && useExtrinsicGuess) ) && npoints == std::max(ipoints.checkVector(2, CV_32F), ipoints.checkVector(2, CV_64F)) ); Mat rvec, tvec; if( flags != SOLVEPNP_ITERATIVE ) useExtrinsicGuess = false; if( useExtrinsicGuess ) { int rtype = _rvec.type(), ttype = _tvec.type(); Size rsize = _rvec.size(), tsize = _tvec.size(); CV_Assert( (rtype == CV_32F || rtype == CV_64F) && (ttype == CV_32F || ttype == CV_64F) ); CV_Assert( (rsize == Size(1, 3) || rsize == Size(3, 1)) && (tsize == Size(1, 3) || tsize == Size(3, 1)) ); } else { int mtype = CV_64F; // use CV_32F if all PnP inputs are CV_32F and outputs are empty if (_ipoints.depth() == _cameraMatrix.depth() && _ipoints.depth() == _opoints.depth() && _rvec.empty() && _tvec.empty()) mtype = _opoints.depth(); _rvec.create(3, 1, mtype); _tvec.create(3, 1, mtype); } rvec = _rvec.getMat(); tvec = _tvec.getMat(); Mat cameraMatrix0 = _cameraMatrix.getMat(); Mat distCoeffs0 = _distCoeffs.getMat(); Mat cameraMatrix = Mat_(cameraMatrix0); Mat distCoeffs = Mat_(distCoeffs0); bool result = false; if (flags == SOLVEPNP_EPNP || flags == SOLVEPNP_DLS || flags == SOLVEPNP_UPNP) { Mat undistortedPoints; undistortPoints(ipoints, undistortedPoints, cameraMatrix, distCoeffs); epnp PnP(cameraMatrix, opoints, undistortedPoints); Mat R; PnP.compute_pose(R, tvec); Rodrigues(R, rvec); result = true; } else if (flags == SOLVEPNP_P3P) { CV_Assert( npoints == 4); Mat undistortedPoints; undistortPoints(ipoints, undistortedPoints, cameraMatrix, distCoeffs); p3p P3Psolver(cameraMatrix); Mat R; result = P3Psolver.solve(R, tvec, opoints, undistortedPoints); if (result) Rodrigues(R, rvec); } else if (flags == SOLVEPNP_AP3P) { CV_Assert( npoints == 4); Mat undistortedPoints; undistortPoints(ipoints, undistortedPoints, cameraMatrix, distCoeffs); ap3p P3Psolver(cameraMatrix); Mat R; result = P3Psolver.solve(R, tvec, opoints, undistortedPoints); if (result) Rodrigues(R, rvec); } else if (flags == SOLVEPNP_ITERATIVE) { CvMat c_objectPoints = cvMat(opoints), c_imagePoints = cvMat(ipoints); CvMat c_cameraMatrix = cvMat(cameraMatrix), c_distCoeffs = cvMat(distCoeffs); CvMat c_rvec = cvMat(rvec), c_tvec = cvMat(tvec); cvFindExtrinsicCameraParams2(&c_objectPoints, &c_imagePoints, &c_cameraMatrix, (c_distCoeffs.rows && c_distCoeffs.cols) ? &c_distCoeffs : 0, &c_rvec, &c_tvec, useExtrinsicGuess ); result = true; } /*else if (flags == SOLVEPNP_DLS) { Mat undistortedPoints; undistortPoints(ipoints, undistortedPoints, cameraMatrix, distCoeffs); dls PnP(opoints, undistortedPoints); Mat R, rvec = _rvec.getMat(), tvec = _tvec.getMat(); bool result = PnP.compute_pose(R, tvec); if (result) Rodrigues(R, rvec); return result; } else if (flags == SOLVEPNP_UPNP) { upnp PnP(cameraMatrix, opoints, ipoints); Mat R, rvec = _rvec.getMat(), tvec = _tvec.getMat(); PnP.compute_pose(R, tvec); Rodrigues(R, rvec); return true; }*/ else CV_Error(CV_StsBadArg, "The flags argument must be one of SOLVEPNP_ITERATIVE, SOLVEPNP_P3P, SOLVEPNP_EPNP or SOLVEPNP_DLS"); return result; } class PnPRansacCallback CV_FINAL : public PointSetRegistrator::Callback { public: PnPRansacCallback(Mat _cameraMatrix=Mat(3,3,CV_64F), Mat _distCoeffs=Mat(4,1,CV_64F), int _flags=SOLVEPNP_ITERATIVE, bool _useExtrinsicGuess=false, Mat _rvec=Mat(), Mat _tvec=Mat() ) : cameraMatrix(_cameraMatrix), distCoeffs(_distCoeffs), flags(_flags), useExtrinsicGuess(_useExtrinsicGuess), rvec(_rvec), tvec(_tvec) {} /* Pre: True */ /* Post: compute _model with given points and return number of found models */ int runKernel( InputArray _m1, InputArray _m2, OutputArray _model ) const CV_OVERRIDE { Mat opoints = _m1.getMat(), ipoints = _m2.getMat(); bool correspondence = solvePnP( _m1, _m2, cameraMatrix, distCoeffs, rvec, tvec, useExtrinsicGuess, flags ); Mat _local_model; hconcat(rvec, tvec, _local_model); _local_model.copyTo(_model); return correspondence; } /* Pre: True */ /* Post: fill _err with projection errors */ void computeError( InputArray _m1, InputArray _m2, InputArray _model, OutputArray _err ) const CV_OVERRIDE { Mat opoints = _m1.getMat(), ipoints = _m2.getMat(), model = _model.getMat(); int i, count = opoints.checkVector(3); Mat _rvec = model.col(0); Mat _tvec = model.col(1); Mat projpoints(count, 2, CV_32FC1); projectPoints(opoints, _rvec, _tvec, cameraMatrix, distCoeffs, projpoints); const Point2f* ipoints_ptr = ipoints.ptr(); const Point2f* projpoints_ptr = projpoints.ptr(); _err.create(count, 1, CV_32FC1); float* err = _err.getMat().ptr(); for ( i = 0; i < count; ++i) err[i] = (float)norm( Matx21f(ipoints_ptr[i] - projpoints_ptr[i]), NORM_L2SQR ); } Mat cameraMatrix; Mat distCoeffs; int flags; bool useExtrinsicGuess; Mat rvec; Mat tvec; }; bool solvePnPRansac(InputArray _opoints, InputArray _ipoints, InputArray _cameraMatrix, InputArray _distCoeffs, OutputArray _rvec, OutputArray _tvec, bool useExtrinsicGuess, int iterationsCount, float reprojectionError, double confidence, OutputArray _inliers, int flags) { CV_INSTRUMENT_REGION(); Mat opoints0 = _opoints.getMat(), ipoints0 = _ipoints.getMat(); Mat opoints, ipoints; if( opoints0.depth() == CV_64F || !opoints0.isContinuous() ) opoints0.convertTo(opoints, CV_32F); else opoints = opoints0; if( ipoints0.depth() == CV_64F || !ipoints0.isContinuous() ) ipoints0.convertTo(ipoints, CV_32F); else ipoints = ipoints0; int npoints = std::max(opoints.checkVector(3, CV_32F), opoints.checkVector(3, CV_64F)); CV_Assert( npoints >= 4 && npoints == std::max(ipoints.checkVector(2, CV_32F), ipoints.checkVector(2, CV_64F)) ); CV_Assert(opoints.isContinuous()); CV_Assert(opoints.depth() == CV_32F || opoints.depth() == CV_64F); CV_Assert((opoints.rows == 1 && opoints.channels() == 3) || opoints.cols*opoints.channels() == 3); CV_Assert(ipoints.isContinuous()); CV_Assert(ipoints.depth() == CV_32F || ipoints.depth() == CV_64F); CV_Assert((ipoints.rows == 1 && ipoints.channels() == 2) || ipoints.cols*ipoints.channels() == 2); _rvec.create(3, 1, CV_64FC1); _tvec.create(3, 1, CV_64FC1); Mat rvec = useExtrinsicGuess ? _rvec.getMat() : Mat(3, 1, CV_64FC1); Mat tvec = useExtrinsicGuess ? _tvec.getMat() : Mat(3, 1, CV_64FC1); Mat cameraMatrix = _cameraMatrix.getMat(), distCoeffs = _distCoeffs.getMat(); int model_points = 5; int ransac_kernel_method = SOLVEPNP_EPNP; if( flags == SOLVEPNP_P3P || flags == SOLVEPNP_AP3P) { model_points = 4; ransac_kernel_method = flags; } else if( npoints == 4 ) { model_points = 4; ransac_kernel_method = SOLVEPNP_P3P; } if( model_points == npoints ) { bool result = solvePnP(opoints, ipoints, cameraMatrix, distCoeffs, _rvec, _tvec, useExtrinsicGuess, ransac_kernel_method); if(!result) { if( _inliers.needed() ) _inliers.release(); return false; } if(_inliers.needed()) { _inliers.create(npoints, 1, CV_32S); Mat _local_inliers = _inliers.getMat(); for(int i = 0; i < npoints; i++) { _local_inliers.at(i) = i; } } return true; } Ptr cb; // pointer to callback cb = makePtr( cameraMatrix, distCoeffs, ransac_kernel_method, useExtrinsicGuess, rvec, tvec); double param1 = reprojectionError; // reprojection error double param2 = confidence; // confidence int param3 = iterationsCount; // number maximum iterations Mat _local_model(3, 2, CV_64FC1); Mat _mask_local_inliers(1, opoints.rows, CV_8UC1); // call Ransac int result = createRANSACPointSetRegistrator(cb, model_points, param1, param2, param3)->run(opoints, ipoints, _local_model, _mask_local_inliers); if( result <= 0 || _local_model.rows <= 0) { _rvec.assign(rvec); // output rotation vector _tvec.assign(tvec); // output translation vector if( _inliers.needed() ) _inliers.release(); return false; } vector opoints_inliers; vector ipoints_inliers; opoints = opoints.reshape(3); ipoints = ipoints.reshape(2); opoints.convertTo(opoints_inliers, CV_64F); ipoints.convertTo(ipoints_inliers, CV_64F); const uchar* mask = _mask_local_inliers.ptr(); int npoints1 = compressElems(&opoints_inliers[0], mask, 1, npoints); compressElems(&ipoints_inliers[0], mask, 1, npoints); opoints_inliers.resize(npoints1); ipoints_inliers.resize(npoints1); result = solvePnP(opoints_inliers, ipoints_inliers, cameraMatrix, distCoeffs, rvec, tvec, useExtrinsicGuess, (flags == SOLVEPNP_P3P || flags == SOLVEPNP_AP3P) ? SOLVEPNP_EPNP : flags) ? 1 : -1; if( result <= 0 ) { _rvec.assign(_local_model.col(0)); // output rotation vector _tvec.assign(_local_model.col(1)); // output translation vector if( _inliers.needed() ) _inliers.release(); return false; } else { _rvec.assign(rvec); // output rotation vector _tvec.assign(tvec); // output translation vector } if(_inliers.needed()) { Mat _local_inliers; for (int i = 0; i < npoints; ++i) { if((int)_mask_local_inliers.at(i) != 0) // inliers mask _local_inliers.push_back(i); // output inliers vector } _local_inliers.copyTo(_inliers); } return true; } int solveP3P( InputArray _opoints, InputArray _ipoints, InputArray _cameraMatrix, InputArray _distCoeffs, OutputArrayOfArrays _rvecs, OutputArrayOfArrays _tvecs, int flags) { CV_INSTRUMENT_REGION(); Mat opoints = _opoints.getMat(), ipoints = _ipoints.getMat(); int npoints = std::max(opoints.checkVector(3, CV_32F), opoints.checkVector(3, CV_64F)); CV_Assert( npoints == 3 && npoints == std::max(ipoints.checkVector(2, CV_32F), ipoints.checkVector(2, CV_64F)) ); CV_Assert( flags == SOLVEPNP_P3P || flags == SOLVEPNP_AP3P ); Mat cameraMatrix0 = _cameraMatrix.getMat(); Mat distCoeffs0 = _distCoeffs.getMat(); Mat cameraMatrix = Mat_(cameraMatrix0); Mat distCoeffs = Mat_(distCoeffs0); Mat undistortedPoints; undistortPoints(ipoints, undistortedPoints, cameraMatrix, distCoeffs); std::vector Rs, ts; int solutions = 0; if (flags == SOLVEPNP_P3P) { p3p P3Psolver(cameraMatrix); solutions = P3Psolver.solve(Rs, ts, opoints, undistortedPoints); } else if (flags == SOLVEPNP_AP3P) { ap3p P3Psolver(cameraMatrix); solutions = P3Psolver.solve(Rs, ts, opoints, undistortedPoints); } if (solutions == 0) { return 0; } if (_rvecs.needed()) { _rvecs.create(solutions, 1, CV_64F); } if (_tvecs.needed()) { _tvecs.create(solutions, 1, CV_64F); } for (int i = 0; i < solutions; i++) { Mat rvec; Rodrigues(Rs[i], rvec); _tvecs.getMatRef(i) = ts[i]; _rvecs.getMatRef(i) = rvec; } return solutions; } }