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459 lines
16 KiB
459 lines
16 KiB
/*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 "calib3d_c_api.h" |
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#include <iostream> |
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namespace cv |
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{ |
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void drawFrameAxes(InputOutputArray image, InputArray cameraMatrix, InputArray distCoeffs, |
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InputArray rvec, InputArray tvec, float length, int thickness) |
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{ |
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CV_INSTRUMENT_REGION(); |
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int type = image.type(); |
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int cn = CV_MAT_CN(type); |
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CV_CheckType(type, cn == 1 || cn == 3 || cn == 4, |
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"Number of channels must be 1, 3 or 4" ); |
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CV_Assert(image.getMat().total() > 0); |
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CV_Assert(length > 0); |
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// project axes points |
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vector<Point3f> axesPoints; |
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axesPoints.push_back(Point3f(0, 0, 0)); |
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axesPoints.push_back(Point3f(length, 0, 0)); |
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axesPoints.push_back(Point3f(0, length, 0)); |
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axesPoints.push_back(Point3f(0, 0, length)); |
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vector<Point2f> imagePoints; |
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projectPoints(axesPoints, rvec, tvec, cameraMatrix, distCoeffs, imagePoints); |
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// draw axes lines |
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line(image, imagePoints[0], imagePoints[1], Scalar(0, 0, 255), thickness); |
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line(image, imagePoints[0], imagePoints[2], Scalar(0, 255, 0), thickness); |
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line(image, imagePoints[0], imagePoints[3], Scalar(255, 0, 0), thickness); |
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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 == 3 && flags == SOLVEPNP_ITERATIVE && useExtrinsicGuess) ) |
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&& 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 = cvMat(opoints), c_imagePoints = cvMat(ipoints); |
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CvMat c_cameraMatrix = cvMat(cameraMatrix), c_distCoeffs = cvMat(distCoeffs); |
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CvMat c_rvec = cvMat(rvec), c_tvec = cvMat(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 CV_FINAL : 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 CV_OVERRIDE |
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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 CV_OVERRIDE |
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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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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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int solveP3P( InputArray _opoints, InputArray _ipoints, |
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InputArray _cameraMatrix, InputArray _distCoeffs, |
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OutputArrayOfArrays _rvecs, OutputArrayOfArrays _tvecs, int flags) { |
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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 == 3 && npoints == std::max(ipoints.checkVector(2, CV_32F), ipoints.checkVector(2, CV_64F)) ); |
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CV_Assert( flags == SOLVEPNP_P3P || flags == SOLVEPNP_AP3P ); |
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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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Mat undistortedPoints; |
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undistortPoints(ipoints, undistortedPoints, cameraMatrix, distCoeffs); |
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std::vector<Mat> Rs, ts; |
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int solutions = 0; |
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if (flags == SOLVEPNP_P3P) |
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{ |
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p3p P3Psolver(cameraMatrix); |
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solutions = P3Psolver.solve(Rs, ts, opoints, undistortedPoints); |
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} |
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else if (flags == SOLVEPNP_AP3P) |
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{ |
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ap3p P3Psolver(cameraMatrix); |
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solutions = P3Psolver.solve(Rs, ts, opoints, undistortedPoints); |
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} |
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if (solutions == 0) { |
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return 0; |
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} |
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if (_rvecs.needed()) { |
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_rvecs.create(solutions, 1, CV_64F); |
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} |
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if (_tvecs.needed()) { |
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_tvecs.create(solutions, 1, CV_64F); |
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} |
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for (int i = 0; i < solutions; i++) { |
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Mat rvec; |
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Rodrigues(Rs[i], rvec); |
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_tvecs.getMatRef(i) = ts[i]; |
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_rvecs.getMatRef(i) = rvec; |
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} |
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return solutions; |
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} |
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}
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