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Merge pull request #1396 from melody-rain:2.4_perf_bgfg_cpp
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282
modules/ocl/perf/perf_bgfg.cpp
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282
modules/ocl/perf/perf_bgfg.cpp
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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) 2010-2012, Multicoreware, Inc., all rights reserved.
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// Copyright (C) 2010-2012, Advanced Micro Devices, 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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// @Authors
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// Fangfang Bai, fangfang@multicorewareinc.com
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// Jin Ma, jin@multicorewareinc.com
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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 oclMaterials 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 "perf_precomp.hpp"
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using namespace perf;
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using namespace std;
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using namespace cv::ocl;
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using namespace cv;
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using std::tr1::tuple;
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using std::tr1::get;
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#if defined(HAVE_XINE) || \
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defined(HAVE_GSTREAMER) || \
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defined(HAVE_QUICKTIME) || \
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defined(HAVE_AVFOUNDATION) || \
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defined(HAVE_FFMPEG) || \
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defined(WIN32)
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# define BUILD_WITH_VIDEO_INPUT_SUPPORT 1
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#else
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# define BUILD_WITH_VIDEO_INPUT_SUPPORT 0
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#endif
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#if BUILD_WITH_VIDEO_INPUT_SUPPORT
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static void cvtFrameFmt(vector<Mat>& input, vector<Mat>& output)
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{
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for(int i = 0; i< (int)(input.size()); i++)
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{
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cvtColor(input[i], output[i], COLOR_RGB2GRAY);
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}
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}
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//prepare data for CPU
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static void prepareData(VideoCapture& cap, int cn, vector<Mat>& frame_buffer)
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{
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cv::Mat frame;
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std::vector<Mat> frame_buffer_init;
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int nFrame = (int)frame_buffer.size();
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for(int i = 0; i < nFrame; i++)
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{
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cap >> frame;
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ASSERT_FALSE(frame.empty());
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frame_buffer_init.push_back(frame);
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}
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if(cn == 1)
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cvtFrameFmt(frame_buffer_init, frame_buffer);
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else
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frame_buffer = frame_buffer_init;
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}
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//copy CPU data to GPU
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static void prepareData(vector<Mat>& frame_buffer, vector<oclMat>& frame_buffer_ocl)
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{
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for(int i = 0; i < (int)frame_buffer.size(); i++)
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frame_buffer_ocl.push_back(cv::ocl::oclMat(frame_buffer[i]));
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}
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#endif
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///////////// MOG ////////////////////////
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#if BUILD_WITH_VIDEO_INPUT_SUPPORT
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typedef tuple<string, int, double> VideoMOGParamType;
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typedef TestBaseWithParam<VideoMOGParamType> VideoMOGFixture;
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PERF_TEST_P(VideoMOGFixture, MOG,
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::testing::Combine(::testing::Values("gpu/video/768x576.avi", "gpu/video/1920x1080.avi"),
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::testing::Values(1, 3),
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::testing::Values(0.0, 0.01)))
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{
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VideoMOGParamType params = GetParam();
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const string inputFile = perf::TestBase::getDataPath(get<0>(params));
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const int cn = get<1>(params);
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const float learningRate = static_cast<float>(get<2>(params));
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const int nFrame = 5;
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Mat foreground_cpu;
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std::vector<Mat> frame_buffer(nFrame);
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std::vector<oclMat> frame_buffer_ocl;
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cv::VideoCapture cap(inputFile);
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ASSERT_TRUE(cap.isOpened());
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prepareData(cap, cn, frame_buffer);
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cv::Mat foreground;
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cv::ocl::oclMat foreground_d;
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if(RUN_PLAIN_IMPL)
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{
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TEST_CYCLE()
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{
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cv::BackgroundSubtractorMOG mog;
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foreground.release();
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for (int i = 0; i < nFrame; i++)
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{
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mog(frame_buffer[i], foreground, learningRate);
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}
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}
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SANITY_CHECK(foreground);
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}else if(RUN_OCL_IMPL)
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{
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prepareData(frame_buffer, frame_buffer_ocl);
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CV_Assert((int)(frame_buffer_ocl.size()) == nFrame);
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OCL_TEST_CYCLE()
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{
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cv::ocl::MOG d_mog;
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foreground_d.release();
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for (int i = 0; i < nFrame; ++i)
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{
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d_mog(frame_buffer_ocl[i], foreground_d, learningRate);
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}
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}
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foreground_d.download(foreground);
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SANITY_CHECK(foreground);
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}else
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OCL_PERF_ELSE
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}
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#endif
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///////////// MOG2 ////////////////////////
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#if BUILD_WITH_VIDEO_INPUT_SUPPORT
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typedef tuple<string, int> VideoMOG2ParamType;
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typedef TestBaseWithParam<VideoMOG2ParamType> VideoMOG2Fixture;
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PERF_TEST_P(VideoMOG2Fixture, MOG2,
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::testing::Combine(::testing::Values("gpu/video/768x576.avi", "gpu/video/1920x1080.avi"),
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::testing::Values(1, 3)))
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{
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VideoMOG2ParamType params = GetParam();
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const string inputFile = perf::TestBase::getDataPath(get<0>(params));
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const int cn = get<1>(params);
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int nFrame = 5;
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std::vector<cv::Mat> frame_buffer(nFrame);
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std::vector<cv::ocl::oclMat> frame_buffer_ocl;
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cv::VideoCapture cap(inputFile);
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ASSERT_TRUE(cap.isOpened());
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prepareData(cap, cn, frame_buffer);
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cv::Mat foreground;
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cv::ocl::oclMat foreground_d;
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if(RUN_PLAIN_IMPL)
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{
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TEST_CYCLE()
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{
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cv::BackgroundSubtractorMOG2 mog2;
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mog2.set("detectShadows", false);
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foreground.release();
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for (int i = 0; i < nFrame; i++)
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{
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mog2(frame_buffer[i], foreground);
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}
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}
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SANITY_CHECK(foreground);
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}else if(RUN_OCL_IMPL)
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{
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prepareData(frame_buffer, frame_buffer_ocl);
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CV_Assert((int)(frame_buffer_ocl.size()) == nFrame);
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OCL_TEST_CYCLE()
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{
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cv::ocl::MOG2 d_mog2;
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foreground_d.release();
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for (int i = 0; i < nFrame; i++)
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{
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d_mog2(frame_buffer_ocl[i], foreground_d);
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}
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}
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foreground_d.download(foreground);
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SANITY_CHECK(foreground);
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}else
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OCL_PERF_ELSE
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}
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#endif
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///////////// MOG2_GetBackgroundImage //////////////////
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#if BUILD_WITH_VIDEO_INPUT_SUPPORT
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typedef TestBaseWithParam<VideoMOG2ParamType> Video_MOG2GetBackgroundImage;
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PERF_TEST_P(Video_MOG2GetBackgroundImage, MOG2,
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::testing::Combine(::testing::Values("gpu/video/768x576.avi", "gpu/video/1920x1080.avi"),
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::testing::Values(3)))
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{
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VideoMOG2ParamType params = GetParam();
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const string inputFile = perf::TestBase::getDataPath(get<0>(params));
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const int cn = get<1>(params);
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int nFrame = 5;
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std::vector<cv::Mat> frame_buffer(nFrame);
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std::vector<cv::ocl::oclMat> frame_buffer_ocl;
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cv::VideoCapture cap(inputFile);
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ASSERT_TRUE(cap.isOpened());
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prepareData(cap, cn, frame_buffer);
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cv::Mat foreground;
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cv::Mat background;
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cv::ocl::oclMat foreground_d;
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cv::ocl::oclMat background_d;
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if(RUN_PLAIN_IMPL)
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{
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TEST_CYCLE()
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{
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cv::BackgroundSubtractorMOG2 mog2;
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mog2.set("detectShadows", false);
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foreground.release();
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background.release();
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for (int i = 0; i < nFrame; i++)
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{
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mog2(frame_buffer[i], foreground);
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}
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mog2.getBackgroundImage(background);
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}
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SANITY_CHECK(background);
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}else if(RUN_OCL_IMPL)
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{
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prepareData(frame_buffer, frame_buffer_ocl);
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CV_Assert((int)(frame_buffer_ocl.size()) == nFrame);
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OCL_TEST_CYCLE()
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{
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cv::ocl::MOG2 d_mog2;
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foreground_d.release();
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background_d.release();
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for (int i = 0; i < nFrame; i++)
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{
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d_mog2(frame_buffer_ocl[i], foreground_d);
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}
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d_mog2.getBackgroundImage(background_d);
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}
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background_d.download(background);
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SANITY_CHECK(background);
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}else
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OCL_PERF_ELSE
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}
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#endif
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