161 lines
6.3 KiB
C++
161 lines
6.3 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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// 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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typedef tuple<Size> OFParams;
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typedef TestWithParam<OFParams> DenseOpticalFlow_DIS;
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typedef TestWithParam<OFParams> DenseOpticalFlow_VariationalRefinement;
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TEST_P(DenseOpticalFlow_DIS, MultithreadReproducibility)
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{
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double MAX_DIF = 0.01;
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double MAX_MEAN_DIF = 0.001;
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int loopsCount = 2;
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RNG rng(0);
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OFParams params = GetParam();
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Size size = get<0>(params);
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int nThreads = cv::getNumThreads();
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if (nThreads == 1)
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throw SkipTestException("Single thread environment");
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for (int iter = 0; iter <= loopsCount; iter++)
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{
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Mat frame1(size, CV_8U);
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randu(frame1, 0, 255);
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Mat frame2(size, CV_8U);
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randu(frame2, 0, 255);
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Ptr<DISOpticalFlow> algo = DISOpticalFlow::create();
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int psz = rng.uniform(4, 16);
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int pstr = rng.uniform(1, psz - 1);
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int grad_iter = rng.uniform(1, 64);
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int var_iter = rng.uniform(0, 10);
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bool use_mean_normalization = !!rng.uniform(0, 2);
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bool use_spatial_propagation = !!rng.uniform(0, 2);
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algo->setFinestScale(0);
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algo->setPatchSize(psz);
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algo->setPatchStride(pstr);
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algo->setGradientDescentIterations(grad_iter);
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algo->setVariationalRefinementIterations(var_iter);
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algo->setUseMeanNormalization(use_mean_normalization);
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algo->setUseSpatialPropagation(use_spatial_propagation);
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cv::setNumThreads(nThreads);
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Mat resMultiThread;
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algo->calc(frame1, frame2, resMultiThread);
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cv::setNumThreads(1);
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Mat resSingleThread;
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algo->calc(frame1, frame2, resSingleThread);
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EXPECT_LE(cv::norm(resSingleThread, resMultiThread, NORM_INF), MAX_DIF);
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EXPECT_LE(cv::norm(resSingleThread, resMultiThread, NORM_L1), MAX_MEAN_DIF * frame1.total());
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// resulting flow should be within the frame bounds:
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double min_val, max_val;
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minMaxLoc(resMultiThread, &min_val, &max_val);
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EXPECT_LE(abs(min_val), sqrt( static_cast<double>(size.height * size.height + size.width * size.width)) );
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EXPECT_LE(abs(max_val), sqrt( static_cast<double>(size.height * size.height + size.width * size.width)) );
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}
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}
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INSTANTIATE_TEST_CASE_P(FullSet, DenseOpticalFlow_DIS, Values(szODD, szQVGA));
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TEST_P(DenseOpticalFlow_VariationalRefinement, MultithreadReproducibility)
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{
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double MAX_DIF = 0.01;
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double MAX_MEAN_DIF = 0.001;
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float input_flow_rad = 5.0;
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int loopsCount = 2;
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RNG rng(0);
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OFParams params = GetParam();
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Size size = get<0>(params);
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int nThreads = cv::getNumThreads();
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if (nThreads == 1)
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throw SkipTestException("Single thread environment");
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for (int iter = 0; iter <= loopsCount; iter++)
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{
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Mat frame1(size, CV_8U);
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randu(frame1, 0, 255);
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Mat frame2(size, CV_8U);
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randu(frame2, 0, 255);
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Mat flow(size, CV_32FC2);
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randu(flow, -input_flow_rad, input_flow_rad);
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Ptr<VariationalRefinement> var = VariationalRefinement::create();
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var->setAlpha(rng.uniform(1.0f, 100.0f));
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var->setGamma(rng.uniform(0.1f, 10.0f));
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var->setDelta(rng.uniform(0.1f, 10.0f));
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var->setSorIterations(rng.uniform(1, 20));
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var->setFixedPointIterations(rng.uniform(1, 20));
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var->setOmega(rng.uniform(1.01f, 1.99f));
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cv::setNumThreads(nThreads);
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Mat resMultiThread;
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flow.copyTo(resMultiThread);
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var->calc(frame1, frame2, resMultiThread);
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cv::setNumThreads(1);
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Mat resSingleThread;
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flow.copyTo(resSingleThread);
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var->calc(frame1, frame2, resSingleThread);
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EXPECT_LE(cv::norm(resSingleThread, resMultiThread, NORM_INF), MAX_DIF);
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EXPECT_LE(cv::norm(resSingleThread, resMultiThread, NORM_L1), MAX_MEAN_DIF * frame1.total());
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// resulting flow should be within the frame bounds:
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double min_val, max_val;
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minMaxLoc(resMultiThread, &min_val, &max_val);
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EXPECT_LE(abs(min_val), sqrt( static_cast<double>(size.height * size.height + size.width * size.width)) );
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EXPECT_LE(abs(max_val), sqrt( static_cast<double>(size.height * size.height + size.width * size.width)) );
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}
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}
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INSTANTIATE_TEST_CASE_P(FullSet, DenseOpticalFlow_VariationalRefinement, Values(szODD, szQVGA));
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}} // namespace
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