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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 "test_precomp.hpp"
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#include "opencv2/video/tracking.hpp"
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#include <string>
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#include <iostream>
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#include <fstream>
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#include <iterator>
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#include <limits>
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using namespace cv;
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using namespace std;
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class CV_OptFlowTest : public cvtest::BaseTest
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{
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public:
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CV_OptFlowTest();
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~CV_OptFlowTest();
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protected:
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void run(int);
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bool runDense(const Point& shift = Point(3, 0));
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bool runSparse();
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};
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CV_OptFlowTest::CV_OptFlowTest() {}
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CV_OptFlowTest::~CV_OptFlowTest() {}
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Mat copnvert2flow(const Mat& velx, const Mat& vely)
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{
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Mat flow(velx.size(), CV_32FC2);
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for(int y = 0 ; y < flow.rows; ++y)
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for(int x = 0 ; x < flow.cols; ++x)
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flow.at<Point2f>(y, x) = Point2f(velx.at<float>(y, x), vely.at<float>(y, x));
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return flow;
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}
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void calcOpticalFlowLK( const Mat& prev, const Mat& curr, Size winSize, Mat& flow )
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{
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Mat velx(prev.size(), CV_32F), vely(prev.size(), CV_32F);
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CvMat cvvelx = velx; CvMat cvvely = vely;
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CvMat cvprev = prev; CvMat cvcurr = curr;
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cvCalcOpticalFlowLK( &cvprev, &cvcurr, winSize, &cvvelx, &cvvely );
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flow = copnvert2flow(velx, vely);
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}
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void calcOpticalFlowBM( const Mat& prev, const Mat& curr, Size bSize, Size shiftSize, Size maxRange, int usePrevious, Mat& flow )
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{
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Size sz((curr.cols - bSize.width + shiftSize.width)/shiftSize.width, (curr.rows - bSize.height + shiftSize.height)/shiftSize.height);
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Mat velx(sz, CV_32F), vely(sz, CV_32F);
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CvMat cvvelx = velx; CvMat cvvely = vely;
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CvMat cvprev = prev; CvMat cvcurr = curr;
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cvCalcOpticalFlowBM( &cvprev, &cvcurr, bSize, shiftSize, maxRange, usePrevious, &cvvelx, &cvvely);
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flow = copnvert2flow(velx, vely);
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}
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void calcOpticalFlowHS( const Mat& prev, const Mat& curr, int usePrevious, double lambda, TermCriteria criteria, Mat& flow)
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{
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Mat velx(prev.size(), CV_32F), vely(prev.size(), CV_32F);
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CvMat cvvelx = velx; CvMat cvvely = vely;
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CvMat cvprev = prev; CvMat cvcurr = curr;
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cvCalcOpticalFlowHS( &cvprev, &cvcurr, usePrevious, &cvvelx, &cvvely, lambda, criteria );
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flow = copnvert2flow(velx, vely);
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}
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void calcAffineFlowPyrLK( const Mat& prev, const Mat& curr,
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const vector<Point2f>& prev_features, vector<Point2f>& curr_features,
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vector<uchar>& status, vector<float>& track_error, vector<float>& matrices,
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TermCriteria criteria = TermCriteria(TermCriteria::COUNT+TermCriteria::EPS,30, 0.01),
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Size win_size = Size(15, 15), int level = 3, int flags = 0)
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{
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CvMat cvprev = prev;
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CvMat cvcurr = curr;
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size_t count = prev_features.size();
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curr_features.resize(count);
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status.resize(count);
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track_error.resize(count);
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matrices.resize(count * 6);
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cvCalcAffineFlowPyrLK( &cvprev, &cvcurr, 0, 0,
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(const CvPoint2D32f*)&prev_features[0], (CvPoint2D32f*)&curr_features[0], &matrices[0],
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(int)count, win_size, level, (char*)&status[0], &track_error[0], criteria, flags );
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}
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double showFlowAndCalcError(const string& name, const Mat& gray, const Mat& flow,
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const Rect& where, const Point& d,
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bool showImages = false, bool writeError = false)
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{
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const int mult = 16;
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if (showImages)
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{
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Mat tmp, cflow;
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resize(gray, tmp, gray.size() * mult, 0, 0, INTER_NEAREST);
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cvtColor(tmp, cflow, CV_GRAY2BGR);
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const float m2 = 0.3f;
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const float minVel = 0.1f;
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for(int y = 0; y < flow.rows; ++y)
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for(int x = 0; x < flow.cols; ++x)
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{
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Point2f f = flow.at<Point2f>(y, x);
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if (f.x * f.x + f.y * f.y > minVel * minVel)
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{
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Point p1 = Point(x, y) * mult;
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Point p2 = Point(cvRound((x + f.x*m2) * mult), cvRound((y + f.y*m2) * mult));
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line(cflow, p1, p2, CV_RGB(0, 255, 0));
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circle(cflow, Point(x, y) * mult, 2, CV_RGB(255, 0, 0));
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}
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}
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rectangle(cflow, (where.tl() + d) * mult, (where.br() + d - Point(1,1)) * mult, CV_RGB(0, 0, 255));
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namedWindow(name, 1); imshow(name, cflow);
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}
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double angle = atan2((float)d.y, (float)d.x);
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double error = 0;
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bool all = true;
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Mat inner = flow(where);
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for(int y = 0; y < inner.rows; ++y)
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for(int x = 0; x < inner.cols; ++x)
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{
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const Point2f f = inner.at<Point2f>(y, x);
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if (f.x == 0 && f.y == 0)
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continue;
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all = false;
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double a = atan2(f.y, f.x);
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error += fabs(angle - a);
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}
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double res = all ? numeric_limits<double>::max() : error / (inner.cols * inner.rows);
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if (writeError)
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cout << "Error " + name << " = " << res << endl;
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return res;
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}
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Mat generateImage(const Size& sz, bool doBlur = true)
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{
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RNG rng;
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Mat mat(sz, CV_8U);
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mat = Scalar(0);
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for(int y = 0; y < mat.rows; ++y)
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for(int x = 0; x < mat.cols; ++x)
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mat.at<uchar>(y, x) = (uchar)rng;
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if (doBlur)
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blur(mat, mat, Size(3, 3));
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return mat;
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}
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Mat generateSample(const Size& sz)
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{
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Mat smpl(sz, CV_8U);
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smpl = Scalar(0);
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Point sc(smpl.cols/2, smpl.rows/2);
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rectangle(smpl, Point(0,0), sc - Point(1,1), Scalar(255), CV_FILLED);
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rectangle(smpl, sc, Point(smpl.cols, smpl.rows), Scalar(255), CV_FILLED);
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return smpl;
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}
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bool CV_OptFlowTest::runDense(const Point& d)
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{
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Size matSize(40, 40);
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Size movSize(8, 8);
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Mat smpl = generateSample(movSize);
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Mat prev = generateImage(matSize);
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Mat curr = prev.clone();
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Rect rect(Point(prev.cols/2, prev.rows/2) - Point(movSize.width/2, movSize.height/2), movSize);
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Mat flowLK, flowBM, flowHS, flowFB, flowFB_G, flowBM_received, m1;
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m1 = prev(rect); smpl.copyTo(m1);
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m1 = curr(Rect(rect.tl() + d, rect.br() + d)); smpl.copyTo(m1);
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calcOpticalFlowLK( prev, curr, Size(15, 15), flowLK);
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calcOpticalFlowBM( prev, curr, Size(15, 15), Size(1, 1), Size(15, 15), 0, flowBM_received);
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calcOpticalFlowHS( prev, curr, 0, 5, TermCriteria(TermCriteria::MAX_ITER, 400, 0), flowHS);
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calcOpticalFlowFarneback( prev, curr, flowFB, 0.5, 3, std::max(d.x, d.y) + 10, 100, 6, 2, 0);
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calcOpticalFlowFarneback( prev, curr, flowFB_G, 0.5, 3, std::max(d.x, d.y) + 10, 100, 6, 2, OPTFLOW_FARNEBACK_GAUSSIAN);
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flowBM.create(prev.size(), CV_32FC2);
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flowBM = Scalar(0);
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Point origin((flowBM.cols - flowBM_received.cols)/2, (flowBM.rows - flowBM_received.rows)/2);
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Mat wcp = flowBM(Rect(origin, flowBM_received.size()));
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flowBM_received.copyTo(wcp);
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double errorLK = showFlowAndCalcError("LK", prev, flowLK, rect, d);
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double errorBM = showFlowAndCalcError("BM", prev, flowBM, rect, d);
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double errorFB = showFlowAndCalcError("FB", prev, flowFB, rect, d);
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double errorFBG = showFlowAndCalcError("FBG", prev, flowFB_G, rect, d);
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double errorHS = showFlowAndCalcError("HS", prev, flowHS, rect, d); (void)errorHS;
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//waitKey();
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const double thres = 0.2;
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if (errorLK > thres || errorBM > thres || errorFB > thres || errorFBG > thres /*|| errorHS > thres */)
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{
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ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
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return false;
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}
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return true;
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}
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bool CV_OptFlowTest::runSparse()
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{
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Mat prev = imread(string(ts->get_data_path()) + "optflow/rock_1.bmp", 0);
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Mat next = imread(string(ts->get_data_path()) + "optflow/rock_2.bmp", 0);
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if (prev.empty() || next.empty())
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{
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ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_TEST_DATA );
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return false;
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}
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Mat cprev, cnext;
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cvtColor(prev, cprev, CV_GRAY2BGR);
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cvtColor(next, cnext, CV_GRAY2BGR);
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vector<Point2f> prev_pts;
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vector<Point2f> next_ptsOpt;
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vector<Point2f> next_ptsAff;
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vector<uchar> status_Opt;
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vector<uchar> status_Aff;
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vector<float> error;
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vector<float> matrices;
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Size netSize(10, 10);
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Point2f center = Point(prev.cols/2, prev.rows/2);
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for(int i = 0 ; i < netSize.width; ++i)
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for(int j = 0 ; j < netSize.width; ++j)
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{
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Point2f p(i * float(prev.cols)/netSize.width, j * float(prev.rows)/netSize.height);
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prev_pts.push_back((p - center) * 0.5f + center);
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}
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calcOpticalFlowPyrLK( prev, next, prev_pts, next_ptsOpt, status_Opt, error );
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calcAffineFlowPyrLK ( prev, next, prev_pts, next_ptsAff, status_Aff, error, matrices);
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const double expected_shift = 25;
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const double thres = 1;
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for(size_t i = 0; i < prev_pts.size(); ++i)
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{
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circle(cprev, prev_pts[i], 2, CV_RGB(255, 0, 0));
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if (status_Opt[i])
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{
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circle(cnext, next_ptsOpt[i], 2, CV_RGB(0, 0, 255));
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Point2f shift = prev_pts[i] - next_ptsOpt[i];
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double n = sqrt(shift.ddot(shift));
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if (fabs(n - expected_shift) > thres)
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{
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ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
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return false;
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}
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}
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if (status_Aff[i])
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{
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circle(cnext, next_ptsAff[i], 4, CV_RGB(0, 255, 0));
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Point2f shift = prev_pts[i] - next_ptsAff[i];
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double n = sqrt(shift.ddot(shift));
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if (fabs(n - expected_shift) > thres)
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{
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ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
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return false;
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}
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}
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}
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/*namedWindow("P"); imshow("P", cprev);
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namedWindow("N"); imshow("N", cnext);
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waitKey();*/
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return true;
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}
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void CV_OptFlowTest::run( int /* start_from */)
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{
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if (!runDense(Point(3, 0)))
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return;
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if (!runDense(Point(0, 3)))
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return;
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//if (!runDense(Point(3, 3))) return; //probably LK works incorrectly in this case.
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if (!runSparse())
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return;
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ts->set_failed_test_info(cvtest::TS::OK);
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}
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TEST(Legacy_OpticalFlow, accuracy) { CV_OptFlowTest test; test.safe_run(); }
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