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333 lines
13 KiB
C++
333 lines
13 KiB
C++
/*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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using namespace cv;
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void cv::solvePnP( const InputArray& _opoints, const InputArray& _ipoints,
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const InputArray& _cameraMatrix, const InputArray& _distCoeffs,
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OutputArray _rvec, OutputArray _tvec, bool useExtrinsicGuess )
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{
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Mat opoints = _opoints.getMat(), ipoints = _ipoints.getMat();
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int npoints = opoints.checkVector(3, CV_32F);
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CV_Assert( npoints >= 0 && npoints == ipoints.checkVector(2, CV_32F) );
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_rvec.create(3, 1, CV_64F);
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_tvec.create(3, 1, CV_64F);
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Mat cameraMatrix = _cameraMatrix.getMat(), distCoeffs = _distCoeffs.getMat();
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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.getMat(), c_tvec = _tvec.getMat();
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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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}
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namespace cv
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{
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namespace pnpransac
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{
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const int MIN_POINTS_COUNT = 4;
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void project3dPoints(const Mat& points, const Mat& rvec, const Mat& tvec, Mat& modif_points)
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{
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modif_points.create(1, points.cols, CV_32FC3);
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Mat R(3, 3, CV_64FC1);
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Rodrigues(rvec, R);
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Mat transformation(3, 4, CV_64F);
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Mat r = transformation.colRange(0, 3);
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R.copyTo(r);
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Mat t = transformation.colRange(3, 4);
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tvec.copyTo(t);
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transform(points, modif_points, transformation);
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}
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class Mutex
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{
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public:
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Mutex() {}
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void lock()
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{
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#ifdef HAVE_TBB
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slock.acquire(resultsMutex);
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#endif
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}
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void unlock()
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{
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#ifdef HAVE_TBB
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slock.release();
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#endif
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}
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private:
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#ifdef HAVE_TBB
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tbb::mutex resultsMutex;
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tbb::mutex::scoped_lock slock;
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#endif
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};
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struct CameraParameters
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{
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void init(Mat _intrinsics, Mat _distCoeffs)
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{
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_intrinsics.copyTo(intrinsics);
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_distCoeffs.copyTo(distortion);
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}
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Mat intrinsics;
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Mat distortion;
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};
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struct Parameters
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{
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int iterationsCount;
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float reprojectionError;
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int minInliersCount;
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bool useExtrinsicGuess;
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CameraParameters camera;
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};
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void pnpTask(const vector<char>& pointsMask, const Mat& objectPoints, const Mat& imagePoints,
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const Parameters& params, vector<int>& inliers, Mat& rvec, Mat& tvec,
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const Mat& rvecInit, const Mat& tvecInit, Mutex& resultsMutex)
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{
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Mat modelObjectPoints(1, MIN_POINTS_COUNT, CV_32FC3), modelImagePoints(1, MIN_POINTS_COUNT, CV_32FC2);
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for (size_t i = 0, colIndex = 0; i < pointsMask.size(); i++)
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{
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if (pointsMask[i])
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{
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Mat colModelImagePoints = modelImagePoints(Rect(colIndex, 0, 1, 1));
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imagePoints.col(i).copyTo(colModelImagePoints);
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Mat colModelObjectPoints = modelObjectPoints(Rect(colIndex, 0, 1, 1));
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objectPoints.col(i).copyTo(colModelObjectPoints);
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colIndex = colIndex+1;
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}
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}
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//filter same 3d points, hang in solvePnP
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double eps = 1e-10;
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int num_same_points = 0;
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for (int i = 0; i < MIN_POINTS_COUNT; i++)
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for (int j = i + 1; j < MIN_POINTS_COUNT; j++)
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{
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if (norm(modelObjectPoints.at<Vec3f>(0, i) - modelObjectPoints.at<Vec3f>(0, j)) < eps)
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num_same_points++;
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}
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if (num_same_points > 0)
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return;
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Mat localRvec, localTvec;
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rvecInit.copyTo(localRvec);
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tvecInit.copyTo(localTvec);
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solvePnP(modelObjectPoints, modelImagePoints, params.camera.intrinsics, params.camera.distortion, localRvec, localTvec, params.useExtrinsicGuess);
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vector<Point2f> projected_points;
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projected_points.resize(objectPoints.cols);
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projectPoints(objectPoints, localRvec, localTvec, params.camera.intrinsics, params.camera.distortion, projected_points);
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Mat rotatedPoints;
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project3dPoints(objectPoints, localRvec, localTvec, rotatedPoints);
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vector<int> localInliers;
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for (int i = 0; i < objectPoints.cols; i++)
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{
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Point2f p(imagePoints.at<Vec2f>(0, i)[0], imagePoints.at<Vec2f>(0, i)[1]);
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if ((norm(p - projected_points[i]) < params.reprojectionError)
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&& (rotatedPoints.at<Vec3f>(0, i)[2] > 0)) //hack
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{
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localInliers.push_back(i);
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}
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}
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if (localInliers.size() > inliers.size())
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{
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resultsMutex.lock();
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inliers.clear();
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inliers.resize(localInliers.size());
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memcpy(&inliers[0], &localInliers[0], sizeof(int) * localInliers.size());
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localRvec.copyTo(rvec);
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localTvec.copyTo(tvec);
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resultsMutex.unlock();
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}
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}
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class PnPSolver
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{
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public:
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void operator()( const BlockedRange& r ) const
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{
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vector<char> pointsMask(objectPoints.cols, 0);
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memset(&pointsMask[0], 1, MIN_POINTS_COUNT );
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for( int i=r.begin(); i!=r.end(); ++i )
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{
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generateVar(pointsMask);
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pnpTask(pointsMask, objectPoints, imagePoints, parameters,
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inliers, rvec, tvec, initRvec, initTvec, syncMutex);
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if ((int)inliers.size() > parameters.minInliersCount)
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{
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#ifdef HAVE_TBB
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tbb::task::self().cancel_group_execution();
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#else
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break;
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#endif
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}
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}
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}
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PnPSolver(const Mat& objectPoints, const Mat& imagePoints, const Parameters& parameters,
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Mat& rvec, Mat& tvec, vector<int>& inliers):
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objectPoints(objectPoints), imagePoints(imagePoints), parameters(parameters),
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rvec(rvec), tvec(tvec), inliers(inliers)
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{
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rvec.copyTo(initRvec);
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tvec.copyTo(initTvec);
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}
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private:
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PnPSolver& operator=(const PnPSolver&);
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const Mat& objectPoints;
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const Mat& imagePoints;
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const Parameters& parameters;
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Mat &rvec, &tvec;
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vector<int>& inliers;
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Mat initRvec, initTvec;
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static RNG generator;
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static Mutex syncMutex;
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void generateVar(vector<char>& mask) const
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{
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size_t size = mask.size();
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for (size_t i = 0; i < size; i++)
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{
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int i1 = generator.uniform(0, size);
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int i2 = generator.uniform(0, size);
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char curr = mask[i1];
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mask[i1] = mask[i2];
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mask[i2] = curr;
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}
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}
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};
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Mutex PnPSolver::syncMutex;
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RNG PnPSolver::generator;
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}
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}
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void cv::solvePnPRansac(const InputArray& _opoints, const InputArray& _ipoints,
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const InputArray& _cameraMatrix, const InputArray& _distCoeffs,
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OutputArray _rvec, OutputArray _tvec, bool useExtrinsicGuess,
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int iterationsCount, float reprojectionError, int minInliersCount,
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OutputArray _inliers)
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{
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Mat opoints = _opoints.getMat(), ipoints = _ipoints.getMat();
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Mat cameraMatrix = _cameraMatrix.getMat(), distCoeffs = _distCoeffs.getMat();
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CV_Assert(opoints.isContinuous());
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CV_Assert(opoints.depth() == CV_32F);
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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);
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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 = _rvec.getMat();
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Mat tvec = _tvec.getMat();
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Mat objectPoints = opoints.reshape(3, 1), imagePoints = ipoints.reshape(2, 1);
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if (minInliersCount <= 0)
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minInliersCount = objectPoints.cols;
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cv::pnpransac::Parameters params;
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params.iterationsCount = iterationsCount;
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params.minInliersCount = minInliersCount;
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params.reprojectionError = reprojectionError;
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params.useExtrinsicGuess = useExtrinsicGuess;
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params.camera.init(cameraMatrix, distCoeffs);
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vector<int> localInliers;
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Mat localRvec, localTvec;
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rvec.copyTo(localRvec);
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tvec.copyTo(localTvec);
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if (objectPoints.cols >= pnpransac::MIN_POINTS_COUNT)
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{
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parallel_for(BlockedRange(0,iterationsCount), cv::pnpransac::PnPSolver(objectPoints, imagePoints, params,
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localRvec, localTvec, localInliers));
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}
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if (localInliers.size() >= (size_t)pnpransac::MIN_POINTS_COUNT)
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{
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size_t pointsCount = localInliers.size();
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Mat inlierObjectPoints(1, pointsCount, CV_32FC3), inlierImagePoints(1, pointsCount, CV_32FC2);
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int index;
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for (size_t i = 0; i < localInliers.size(); i++)
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{
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index = localInliers[i];
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Mat colInlierImagePoints = inlierImagePoints(Rect(i, 0, 1, 1));
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imagePoints.col(index).copyTo(colInlierImagePoints);
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Mat colInlierObjectPoints = inlierObjectPoints(Rect(i, 0, 1, 1));
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objectPoints.col(index).copyTo(colInlierObjectPoints);
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}
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solvePnP(inlierObjectPoints, inlierImagePoints, params.camera.intrinsics, params.camera.distortion, localRvec, localTvec, true);
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localRvec.copyTo(rvec);
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localTvec.copyTo(tvec);
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if (_inliers.needed())
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Mat(localInliers).copyTo(_inliers);
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}
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else
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{
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tvec.setTo(Scalar(0));
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Mat R = Mat::eye(3, 3, CV_64F);
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Rodrigues(R, rvec);
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if( _inliers.needed() )
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_inliers.release();
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}
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return;
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}
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