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/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "precomp.hpp"
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#include "upnp.h"
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#include "dls.h"
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#include "epnp.h"
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#include "p3p.h"
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#include "ap3p.h"
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#include "opencv2/calib3d/calib3d_c.h"
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#include <iostream>
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namespace cv
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{
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bool solvePnP( InputArray _opoints, InputArray _ipoints,
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InputArray _cameraMatrix, InputArray _distCoeffs,
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OutputArray _rvec, OutputArray _tvec, bool useExtrinsicGuess, int flags )
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{
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CV_INSTRUMENT_REGION()
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Mat opoints = _opoints.getMat(), ipoints = _ipoints.getMat();
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int npoints = std::max(opoints.checkVector(3, CV_32F), opoints.checkVector(3, CV_64F));
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CV_Assert( npoints >= 4 && npoints == std::max(ipoints.checkVector(2, CV_32F), ipoints.checkVector(2, CV_64F)) );
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Mat rvec, tvec;
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if( flags != SOLVEPNP_ITERATIVE )
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useExtrinsicGuess = false;
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if( useExtrinsicGuess )
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{
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int rtype = _rvec.type(), ttype = _tvec.type();
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Size rsize = _rvec.size(), tsize = _tvec.size();
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CV_Assert( (rtype == CV_32F || rtype == CV_64F) &&
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(ttype == CV_32F || ttype == CV_64F) );
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CV_Assert( (rsize == Size(1, 3) || rsize == Size(3, 1)) &&
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(tsize == Size(1, 3) || tsize == Size(3, 1)) );
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}
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else
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{
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int mtype = CV_64F;
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// use CV_32F if all PnP inputs are CV_32F and outputs are empty
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if (_ipoints.depth() == _cameraMatrix.depth() && _ipoints.depth() == _opoints.depth() &&
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_rvec.empty() && _tvec.empty())
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mtype = _opoints.depth();
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_rvec.create(3, 1, mtype);
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_tvec.create(3, 1, mtype);
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}
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rvec = _rvec.getMat();
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tvec = _tvec.getMat();
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Mat cameraMatrix0 = _cameraMatrix.getMat();
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Mat distCoeffs0 = _distCoeffs.getMat();
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Mat cameraMatrix = Mat_<double>(cameraMatrix0);
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Mat distCoeffs = Mat_<double>(distCoeffs0);
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bool result = false;
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if (flags == SOLVEPNP_EPNP || flags == SOLVEPNP_DLS || flags == SOLVEPNP_UPNP)
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{
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Mat undistortedPoints;
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undistortPoints(ipoints, undistortedPoints, cameraMatrix, distCoeffs);
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epnp PnP(cameraMatrix, opoints, undistortedPoints);
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Mat R;
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PnP.compute_pose(R, tvec);
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Rodrigues(R, rvec);
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result = true;
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}
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else if (flags == SOLVEPNP_P3P)
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{
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CV_Assert( npoints == 4);
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Mat undistortedPoints;
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undistortPoints(ipoints, undistortedPoints, cameraMatrix, distCoeffs);
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p3p P3Psolver(cameraMatrix);
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Mat R;
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result = P3Psolver.solve(R, tvec, opoints, undistortedPoints);
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if (result)
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Rodrigues(R, rvec);
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}
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else if (flags == SOLVEPNP_AP3P)
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{
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CV_Assert( npoints == 4);
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Mat undistortedPoints;
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undistortPoints(ipoints, undistortedPoints, cameraMatrix, distCoeffs);
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ap3p P3Psolver(cameraMatrix);
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Mat R;
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result = P3Psolver.solve(R, tvec, opoints, undistortedPoints);
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if (result)
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Rodrigues(R, rvec);
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}
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else if (flags == SOLVEPNP_ITERATIVE)
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{
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CvMat c_objectPoints = opoints, c_imagePoints = ipoints;
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CvMat c_cameraMatrix = cameraMatrix, c_distCoeffs = distCoeffs;
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CvMat c_rvec = rvec, c_tvec = tvec;
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cvFindExtrinsicCameraParams2(&c_objectPoints, &c_imagePoints, &c_cameraMatrix,
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c_distCoeffs.rows*c_distCoeffs.cols ? &c_distCoeffs : 0,
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&c_rvec, &c_tvec, useExtrinsicGuess );
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result = true;
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}
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/*else if (flags == SOLVEPNP_DLS)
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{
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Mat undistortedPoints;
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undistortPoints(ipoints, undistortedPoints, cameraMatrix, distCoeffs);
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dls PnP(opoints, undistortedPoints);
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Mat R, rvec = _rvec.getMat(), tvec = _tvec.getMat();
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bool result = PnP.compute_pose(R, tvec);
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if (result)
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Rodrigues(R, rvec);
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return result;
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}
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else if (flags == SOLVEPNP_UPNP)
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{
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upnp PnP(cameraMatrix, opoints, ipoints);
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Mat R, rvec = _rvec.getMat(), tvec = _tvec.getMat();
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PnP.compute_pose(R, tvec);
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Rodrigues(R, rvec);
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return true;
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}*/
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else
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CV_Error(CV_StsBadArg, "The flags argument must be one of SOLVEPNP_ITERATIVE, SOLVEPNP_P3P, SOLVEPNP_EPNP or SOLVEPNP_DLS");
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return result;
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}
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class PnPRansacCallback : public PointSetRegistrator::Callback
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{
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public:
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PnPRansacCallback(Mat _cameraMatrix=Mat(3,3,CV_64F), Mat _distCoeffs=Mat(4,1,CV_64F), int _flags=SOLVEPNP_ITERATIVE,
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bool _useExtrinsicGuess=false, Mat _rvec=Mat(), Mat _tvec=Mat() )
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: cameraMatrix(_cameraMatrix), distCoeffs(_distCoeffs), flags(_flags), useExtrinsicGuess(_useExtrinsicGuess),
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rvec(_rvec), tvec(_tvec) {}
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/* Pre: True */
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/* Post: compute _model with given points and return number of found models */
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int runKernel( InputArray _m1, InputArray _m2, OutputArray _model ) const
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{
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Mat opoints = _m1.getMat(), ipoints = _m2.getMat();
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bool correspondence = solvePnP( _m1, _m2, cameraMatrix, distCoeffs,
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rvec, tvec, useExtrinsicGuess, flags );
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Mat _local_model;
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hconcat(rvec, tvec, _local_model);
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_local_model.copyTo(_model);
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return correspondence;
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}
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/* Pre: True */
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/* Post: fill _err with projection errors */
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void computeError( InputArray _m1, InputArray _m2, InputArray _model, OutputArray _err ) const
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{
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Mat opoints = _m1.getMat(), ipoints = _m2.getMat(), model = _model.getMat();
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int i, count = opoints.checkVector(3);
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Mat _rvec = model.col(0);
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Mat _tvec = model.col(1);
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Mat projpoints(count, 2, CV_32FC1);
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projectPoints(opoints, _rvec, _tvec, cameraMatrix, distCoeffs, projpoints);
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const Point2f* ipoints_ptr = ipoints.ptr<Point2f>();
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const Point2f* projpoints_ptr = projpoints.ptr<Point2f>();
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_err.create(count, 1, CV_32FC1);
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float* err = _err.getMat().ptr<float>();
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for ( i = 0; i < count; ++i)
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err[i] = (float)norm( Matx21f(ipoints_ptr[i] - projpoints_ptr[i]), NORM_L2SQR );
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}
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Mat cameraMatrix;
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Mat distCoeffs;
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int flags;
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bool useExtrinsicGuess;
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Mat rvec;
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Mat tvec;
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};
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bool solvePnPRansac(InputArray _opoints, InputArray _ipoints,
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InputArray _cameraMatrix, InputArray _distCoeffs,
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OutputArray _rvec, OutputArray _tvec, bool useExtrinsicGuess,
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int iterationsCount, float reprojectionError, double confidence,
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OutputArray _inliers, int flags)
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{
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CV_INSTRUMENT_REGION()
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Mat opoints0 = _opoints.getMat(), ipoints0 = _ipoints.getMat();
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Mat opoints, ipoints;
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if( opoints0.depth() == CV_64F || !opoints0.isContinuous() )
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opoints0.convertTo(opoints, CV_32F);
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else
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opoints = opoints0;
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if( ipoints0.depth() == CV_64F || !ipoints0.isContinuous() )
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ipoints0.convertTo(ipoints, CV_32F);
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else
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ipoints = ipoints0;
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int npoints = std::max(opoints.checkVector(3, CV_32F), opoints.checkVector(3, CV_64F));
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CV_Assert( npoints >= 4 && npoints == std::max(ipoints.checkVector(2, CV_32F), ipoints.checkVector(2, CV_64F)) );
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CV_Assert(opoints.isContinuous());
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CV_Assert(opoints.depth() == CV_32F || opoints.depth() == CV_64F);
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CV_Assert((opoints.rows == 1 && opoints.channels() == 3) || opoints.cols*opoints.channels() == 3);
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CV_Assert(ipoints.isContinuous());
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CV_Assert(ipoints.depth() == CV_32F || ipoints.depth() == CV_64F);
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CV_Assert((ipoints.rows == 1 && ipoints.channels() == 2) || ipoints.cols*ipoints.channels() == 2);
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_rvec.create(3, 1, CV_64FC1);
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_tvec.create(3, 1, CV_64FC1);
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Mat rvec = useExtrinsicGuess ? _rvec.getMat() : Mat(3, 1, CV_64FC1);
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Mat tvec = useExtrinsicGuess ? _tvec.getMat() : Mat(3, 1, CV_64FC1);
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Mat cameraMatrix = _cameraMatrix.getMat(), distCoeffs = _distCoeffs.getMat();
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int model_points = 5;
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int ransac_kernel_method = SOLVEPNP_EPNP;
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if( flags == SOLVEPNP_P3P || flags == SOLVEPNP_AP3P)
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{
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model_points = 4;
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ransac_kernel_method = flags;
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}
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else if( npoints == 4 )
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{
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model_points = 4;
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ransac_kernel_method = SOLVEPNP_P3P;
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}
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if( model_points == npoints )
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{
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bool result = solvePnP(opoints, ipoints, cameraMatrix, distCoeffs, _rvec, _tvec, useExtrinsicGuess, ransac_kernel_method);
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if(!result)
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{
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if( _inliers.needed() )
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_inliers.release();
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return false;
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}
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if(_inliers.needed())
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{
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_inliers.create(npoints, 1, CV_32S);
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Mat _local_inliers = _inliers.getMat();
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for(int i = 0; i < npoints; i++)
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{
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_local_inliers.at<int>(i) = i;
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}
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}
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return true;
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}
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Ptr<PointSetRegistrator::Callback> cb; // pointer to callback
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cb = makePtr<PnPRansacCallback>( cameraMatrix, distCoeffs, ransac_kernel_method, useExtrinsicGuess, rvec, tvec);
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double param1 = reprojectionError; // reprojection error
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double param2 = confidence; // confidence
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int param3 = iterationsCount; // number maximum iterations
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Mat _local_model(3, 2, CV_64FC1);
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Mat _mask_local_inliers(1, opoints.rows, CV_8UC1);
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// call Ransac
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int result = createRANSACPointSetRegistrator(cb, model_points,
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param1, param2, param3)->run(opoints, ipoints, _local_model, _mask_local_inliers);
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if( result <= 0 || _local_model.rows <= 0)
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{
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_rvec.assign(rvec); // output rotation vector
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_tvec.assign(tvec); // output translation vector
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if( _inliers.needed() )
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_inliers.release();
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return false;
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}
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vector<Point3d> opoints_inliers;
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vector<Point2d> ipoints_inliers;
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opoints = opoints.reshape(3);
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ipoints = ipoints.reshape(2);
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opoints.convertTo(opoints_inliers, CV_64F);
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ipoints.convertTo(ipoints_inliers, CV_64F);
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const uchar* mask = _mask_local_inliers.ptr<uchar>();
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int npoints1 = compressElems(&opoints_inliers[0], mask, 1, npoints);
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compressElems(&ipoints_inliers[0], mask, 1, npoints);
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opoints_inliers.resize(npoints1);
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ipoints_inliers.resize(npoints1);
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result = solvePnP(opoints_inliers, ipoints_inliers, cameraMatrix,
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distCoeffs, rvec, tvec, useExtrinsicGuess,
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(flags == SOLVEPNP_P3P || flags == SOLVEPNP_AP3P) ? SOLVEPNP_EPNP : flags) ? 1 : -1;
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if( result <= 0 )
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{
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_rvec.assign(_local_model.col(0)); // output rotation vector
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_tvec.assign(_local_model.col(1)); // output translation vector
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if( _inliers.needed() )
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_inliers.release();
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return false;
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}
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else
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{
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_rvec.assign(rvec); // output rotation vector
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_tvec.assign(tvec); // output translation vector
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}
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if(_inliers.needed())
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|
|
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{
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|
Mat _local_inliers;
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for (int i = 0; i < npoints; ++i)
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{
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if((int)_mask_local_inliers.at<uchar>(i) != 0) // inliers mask
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_local_inliers.push_back(i); // output inliers vector
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}
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_local_inliers.copyTo(_inliers);
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}
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return true;
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|
|
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}
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|
|
|
|
|
|
int solveP3P( InputArray _opoints, InputArray _ipoints,
|
|
|
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InputArray _cameraMatrix, InputArray _distCoeffs,
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|
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OutputArrayOfArrays _rvecs, OutputArrayOfArrays _tvecs, int flags) {
|
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|
|
CV_INSTRUMENT_REGION()
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|
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Mat opoints = _opoints.getMat(), ipoints = _ipoints.getMat();
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|
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int npoints = std::max(opoints.checkVector(3, CV_32F), opoints.checkVector(3, CV_64F));
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|
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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_<double>(cameraMatrix0);
|
|
|
|
Mat distCoeffs = Mat_<double>(distCoeffs0);
|
|
|
|
|
|
|
|
Mat undistortedPoints;
|
|
|
|
undistortPoints(ipoints, undistortedPoints, cameraMatrix, distCoeffs);
|
|
|
|
std::vector<Mat> 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;
|
|
|
|
}
|
|
|
|
|
|
|
|
}
|