355 lines
		
	
	
		
			12 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
			
		
		
	
	
			355 lines
		
	
	
		
			12 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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| 
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| #include "test_precomp.hpp"
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| #include "opencv2/video/tracking.hpp"
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| 
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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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| 
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| using namespace cv;
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| using namespace std;
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| 
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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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| 
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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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| 
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| CV_OptFlowTest::CV_OptFlowTest() {}
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| CV_OptFlowTest::~CV_OptFlowTest() {}
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| 
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| 
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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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| 
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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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| 
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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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| 
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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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| 
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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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| 
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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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| 
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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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| 
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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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| 
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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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| 
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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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| 
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|         const float m2 = 0.3f;
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|         const float minVel = 0.1f;
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| 
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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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| 
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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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| 
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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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| 
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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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| 
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|     double angle = atan2((float)d.y, (float)d.x);
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|     double error = 0;
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| 
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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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| 
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|             if (f.x == 0 && f.y == 0)
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|                 continue;
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| 
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|             all = false;
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| 
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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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| 
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|         if (writeError)
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|             cout << "Error " + name << " = " << res << endl;
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| 
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|         return res;
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| }
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| 
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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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| 
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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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| 
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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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| 
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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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| 
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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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| 
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|     Mat flowLK, flowBM, flowHS, flowFB, flowFB_G, flowBM_received, m1;
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| 
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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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| 
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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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| 
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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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| 
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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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| 
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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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| 
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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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| 
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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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| 
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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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| 
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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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| 
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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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| 
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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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| 
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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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| 
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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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| 
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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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| 
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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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|         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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| 
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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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|     }
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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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| 
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|     return true;
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| }
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| 
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| 
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| void CV_OptFlowTest::run( int /* start_from */)
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| {
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| 
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|     if (!runDense(Point(3, 0)))
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|         return;
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| 
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|     if (!runDense(Point(0, 3)))
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|         return;
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| 
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|     //if (!runDense(Point(3, 3))) return;  //probably LK works incorrectly in this case.
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| 
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|     if (!runSparse())
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|         return;
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| 
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|     ts->set_failed_test_info(cvtest::TS::OK);
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| }
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| 
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| 
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| TEST(Legacy_OpticalFlow, accuracy) { CV_OptFlowTest test; test.safe_run(); }
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