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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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// Intel License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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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namespace opencv_test { namespace {
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/* ///////////////////// pyrlk_test ///////////////////////// */
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class CV_OptFlowPyrLKTest : public cvtest::BaseTest
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{
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public:
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CV_OptFlowPyrLKTest();
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protected:
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void run(int);
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};
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CV_OptFlowPyrLKTest::CV_OptFlowPyrLKTest() {}
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void CV_OptFlowPyrLKTest::run( int )
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{
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int code = cvtest::TS::OK;
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const double success_error_level = 0.3;
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const int bad_points_max = 8;
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/* test parameters */
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double max_err = 0., sum_err = 0;
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int pt_cmpd = 0;
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int pt_exceed = 0;
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int merr_i = 0, merr_j = 0, merr_k = 0, merr_nan = 0;
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char filename[1000];
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cv::Point2f *v = 0, *v2 = 0;
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cv::Mat _u, _v, _v2;
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cv::Mat imgI, imgJ;
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int n = 0, i = 0;
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for(;;)
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{
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sprintf( filename, "%soptflow/%s", ts->get_data_path().c_str(), "lk_prev.dat" );
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{
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FileStorage fs(filename, FileStorage::READ);
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fs["points"] >> _u;
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if( _u.empty() )
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{
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ts->printf( cvtest::TS::LOG, "could not read %s\n", filename );
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code = cvtest::TS::FAIL_MISSING_TEST_DATA;
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break;
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}
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}
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sprintf( filename, "%soptflow/%s", ts->get_data_path().c_str(), "lk_next.dat" );
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{
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FileStorage fs(filename, FileStorage::READ);
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fs["points"] >> _v;
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if( _v.empty() )
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{
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ts->printf( cvtest::TS::LOG, "could not read %s\n", filename );
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code = cvtest::TS::FAIL_MISSING_TEST_DATA;
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break;
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}
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}
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if( _u.cols != 2 || _u.type() != CV_32F ||
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_v.cols != 2 || _v.type() != CV_32F ||
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_v.rows != _u.rows )
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{
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ts->printf( cvtest::TS::LOG, "the loaded matrices of points are not valid\n" );
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code = cvtest::TS::FAIL_MISSING_TEST_DATA;
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break;
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}
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/* read first image */
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sprintf( filename, "%soptflow/%s", ts->get_data_path().c_str(), "rock_1.bmp" );
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imgI = cv::imread( filename, cv::IMREAD_UNCHANGED );
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if( imgI.empty() )
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{
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ts->printf( cvtest::TS::LOG, "could not read %s\n", filename );
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code = cvtest::TS::FAIL_MISSING_TEST_DATA;
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break;
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}
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/* read second image */
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sprintf( filename, "%soptflow/%s", ts->get_data_path().c_str(), "rock_2.bmp" );
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imgJ = cv::imread( filename, cv::IMREAD_UNCHANGED );
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if( imgJ.empty() )
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{
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ts->printf( cvtest::TS::LOG, "could not read %s\n", filename );
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code = cvtest::TS::FAIL_MISSING_TEST_DATA;
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break;
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}
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n = _u.rows;
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std::vector<uchar> status(n, (uchar)0);
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/* calculate flow */
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calcOpticalFlowPyrLK(imgI, imgJ, _u, _v2, status, cv::noArray(), Size( 41, 41 ), 4,
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TermCriteria( TermCriteria::MAX_ITER + TermCriteria::EPS, 30, 0.01f ), 0 );
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v = (cv::Point2f*)_v.ptr();
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v2 = (cv::Point2f*)_v2.ptr();
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/* compare results */
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for( i = 0; i < n; i++ )
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{
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if( status[i] != 0 )
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{
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double err;
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if( cvIsNaN(v[i].x) || cvIsNaN(v[i].y) )
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{
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merr_j++;
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continue;
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}
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if( cvIsNaN(v2[i].x) || cvIsNaN(v2[i].y) )
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{
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merr_nan++;
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continue;
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}
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err = fabs(v2[i].x - v[i].x) + fabs(v2[i].y - v[i].y);
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if( err > max_err )
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{
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max_err = err;
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merr_i = i;
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}
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pt_exceed += err > success_error_level;
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sum_err += err;
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pt_cmpd++;
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}
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else
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{
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if( !cvIsNaN( v[i].x ))
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{
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merr_i = i;
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merr_k++;
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ts->printf( cvtest::TS::LOG, "The algorithm lost the point #%d\n", i );
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code = cvtest::TS::FAIL_BAD_ACCURACY;
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break;
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}
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}
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}
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if( i < n )
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break;
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if( pt_exceed > bad_points_max )
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{
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ts->printf( cvtest::TS::LOG,
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"The number of poorly tracked points is too big (>=%d)\n", pt_exceed );
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code = cvtest::TS::FAIL_BAD_ACCURACY;
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break;
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}
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if( max_err > 1 )
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{
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ts->printf( cvtest::TS::LOG, "Maximum tracking error is too big (=%g) at %d\n", max_err, merr_i );
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code = cvtest::TS::FAIL_BAD_ACCURACY;
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break;
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}
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if( merr_nan > 0 )
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{
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ts->printf( cvtest::TS::LOG, "NAN tracking result with status != 0 (%d times)\n", merr_nan );
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code = cvtest::TS::FAIL_BAD_ACCURACY;
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}
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break;
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}
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if( code < 0 )
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ts->set_failed_test_info( code );
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}
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TEST(Video_OpticalFlowPyrLK, accuracy) { CV_OptFlowPyrLKTest test; test.safe_run(); }
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TEST(Video_OpticalFlowPyrLK, submat)
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{
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// see bug #2075
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std::string path = cvtest::TS::ptr()->get_data_path() + "../cv/shared/lena.png";
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cv::Mat lenaImg = cv::imread(path);
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ASSERT_FALSE(lenaImg.empty());
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cv::Mat wholeImage;
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cv::resize(lenaImg, wholeImage, cv::Size(1024, 1024), 0, 0, cv::INTER_LINEAR_EXACT);
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cv::Mat img1 = wholeImage(cv::Rect(0, 0, 640, 360)).clone();
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cv::Mat img2 = wholeImage(cv::Rect(40, 60, 640, 360));
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std::vector<uchar> status;
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std::vector<float> error;
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std::vector<cv::Point2f> prev;
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std::vector<cv::Point2f> next;
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cv::RNG rng(123123);
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for(int i = 0; i < 50; ++i)
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{
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int x = rng.uniform(0, 640);
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int y = rng.uniform(0, 360);
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prev.push_back(cv::Point2f((float)x, (float)y));
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}
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ASSERT_NO_THROW(cv::calcOpticalFlowPyrLK(img1, img2, prev, next, status, error));
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}
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}} // namespace
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