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Open Source Computer Vision Library
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405 lines
11 KiB
405 lines
11 KiB
/*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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#ifdef HAVE_CUDA |
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using namespace cvtest; |
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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_QTKIT) || \ |
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defined(HAVE_AVFOUNDATION) || \ |
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defined(HAVE_FFMPEG) || \ |
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defined(WIN32) /* assume that we have ffmpeg */ |
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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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////////////////////////////////////////////////////// |
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// FGDStatModel |
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#if BUILD_WITH_VIDEO_INPUT_SUPPORT |
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namespace cv |
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{ |
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template<> void Ptr<CvBGStatModel>::delete_obj() |
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{ |
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cvReleaseBGStatModel(&obj); |
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} |
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} |
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PARAM_TEST_CASE(FGDStatModel, cv::gpu::DeviceInfo, std::string, Channels) |
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{ |
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cv::gpu::DeviceInfo devInfo; |
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std::string inputFile; |
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int out_cn; |
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virtual void SetUp() |
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{ |
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devInfo = GET_PARAM(0); |
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cv::gpu::setDevice(devInfo.deviceID()); |
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inputFile = std::string(cvtest::TS::ptr()->get_data_path()) + "video/" + GET_PARAM(1); |
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out_cn = GET_PARAM(2); |
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} |
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}; |
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GPU_TEST_P(FGDStatModel, Update) |
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{ |
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cv::VideoCapture cap(inputFile); |
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ASSERT_TRUE(cap.isOpened()); |
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cv::Mat frame; |
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cap >> frame; |
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ASSERT_FALSE(frame.empty()); |
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IplImage ipl_frame = frame; |
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cv::Ptr<CvBGStatModel> model(cvCreateFGDStatModel(&ipl_frame)); |
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cv::gpu::GpuMat d_frame(frame); |
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cv::gpu::FGDStatModel d_model(out_cn); |
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d_model.create(d_frame); |
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cv::Mat h_background; |
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cv::Mat h_foreground; |
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cv::Mat h_background3; |
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cv::Mat backgroundDiff; |
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cv::Mat foregroundDiff; |
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for (int i = 0; i < 5; ++i) |
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{ |
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cap >> frame; |
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ASSERT_FALSE(frame.empty()); |
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ipl_frame = frame; |
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int gold_count = cvUpdateBGStatModel(&ipl_frame, model); |
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d_frame.upload(frame); |
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int count = d_model.update(d_frame); |
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ASSERT_EQ(gold_count, count); |
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cv::Mat gold_background(model->background); |
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cv::Mat gold_foreground(model->foreground); |
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if (out_cn == 3) |
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d_model.background.download(h_background3); |
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else |
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{ |
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d_model.background.download(h_background); |
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cv::cvtColor(h_background, h_background3, cv::COLOR_BGRA2BGR); |
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} |
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d_model.foreground.download(h_foreground); |
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ASSERT_MAT_NEAR(gold_background, h_background3, 1.0); |
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ASSERT_MAT_NEAR(gold_foreground, h_foreground, 0.0); |
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} |
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} |
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INSTANTIATE_TEST_CASE_P(GPU_Video, FGDStatModel, testing::Combine( |
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ALL_DEVICES, |
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testing::Values(std::string("768x576.avi")), |
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testing::Values(Channels(3), Channels(4)))); |
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#endif |
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////////////////////////////////////////////////////// |
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// MOG |
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#if BUILD_WITH_VIDEO_INPUT_SUPPORT |
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namespace |
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{ |
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IMPLEMENT_PARAM_CLASS(UseGray, bool) |
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IMPLEMENT_PARAM_CLASS(LearningRate, double) |
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} |
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PARAM_TEST_CASE(MOG, cv::gpu::DeviceInfo, std::string, UseGray, LearningRate, UseRoi) |
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{ |
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cv::gpu::DeviceInfo devInfo; |
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std::string inputFile; |
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bool useGray; |
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double learningRate; |
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bool useRoi; |
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virtual void SetUp() |
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{ |
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devInfo = GET_PARAM(0); |
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cv::gpu::setDevice(devInfo.deviceID()); |
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inputFile = std::string(cvtest::TS::ptr()->get_data_path()) + "video/" + GET_PARAM(1); |
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useGray = GET_PARAM(2); |
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learningRate = GET_PARAM(3); |
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useRoi = GET_PARAM(4); |
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} |
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}; |
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GPU_TEST_P(MOG, Update) |
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{ |
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cv::VideoCapture cap(inputFile); |
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ASSERT_TRUE(cap.isOpened()); |
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cv::Mat frame; |
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cap >> frame; |
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ASSERT_FALSE(frame.empty()); |
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cv::gpu::MOG_GPU mog; |
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cv::gpu::GpuMat foreground = createMat(frame.size(), CV_8UC1, useRoi); |
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cv::BackgroundSubtractorMOG mog_gold; |
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cv::Mat foreground_gold; |
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for (int i = 0; i < 10; ++i) |
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{ |
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cap >> frame; |
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ASSERT_FALSE(frame.empty()); |
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if (useGray) |
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{ |
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cv::Mat temp; |
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cv::cvtColor(frame, temp, cv::COLOR_BGR2GRAY); |
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cv::swap(temp, frame); |
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} |
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mog(loadMat(frame, useRoi), foreground, (float)learningRate); |
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mog_gold(frame, foreground_gold, learningRate); |
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ASSERT_MAT_NEAR(foreground_gold, foreground, 0.0); |
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} |
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} |
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INSTANTIATE_TEST_CASE_P(GPU_Video, MOG, testing::Combine( |
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ALL_DEVICES, |
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testing::Values(std::string("768x576.avi")), |
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testing::Values(UseGray(true), UseGray(false)), |
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testing::Values(LearningRate(0.0), LearningRate(0.01)), |
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WHOLE_SUBMAT)); |
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#endif |
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////////////////////////////////////////////////////// |
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// MOG2 |
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#if BUILD_WITH_VIDEO_INPUT_SUPPORT |
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namespace |
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{ |
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IMPLEMENT_PARAM_CLASS(DetectShadow, bool) |
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} |
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PARAM_TEST_CASE(MOG2, cv::gpu::DeviceInfo, std::string, UseGray, DetectShadow, UseRoi) |
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{ |
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cv::gpu::DeviceInfo devInfo; |
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std::string inputFile; |
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bool useGray; |
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bool detectShadow; |
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bool useRoi; |
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virtual void SetUp() |
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{ |
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devInfo = GET_PARAM(0); |
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cv::gpu::setDevice(devInfo.deviceID()); |
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inputFile = std::string(cvtest::TS::ptr()->get_data_path()) + "video/" + GET_PARAM(1); |
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useGray = GET_PARAM(2); |
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detectShadow = GET_PARAM(3); |
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useRoi = GET_PARAM(4); |
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} |
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}; |
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GPU_TEST_P(MOG2, Update) |
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{ |
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cv::VideoCapture cap(inputFile); |
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ASSERT_TRUE(cap.isOpened()); |
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cv::Mat frame; |
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cap >> frame; |
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ASSERT_FALSE(frame.empty()); |
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cv::gpu::MOG2_GPU mog2; |
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mog2.bShadowDetection = detectShadow; |
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cv::gpu::GpuMat foreground = createMat(frame.size(), CV_8UC1, useRoi); |
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cv::BackgroundSubtractorMOG2 mog2_gold; |
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mog2_gold.set("detectShadows", detectShadow); |
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cv::Mat foreground_gold; |
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for (int i = 0; i < 10; ++i) |
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{ |
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cap >> frame; |
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ASSERT_FALSE(frame.empty()); |
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if (useGray) |
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{ |
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cv::Mat temp; |
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cv::cvtColor(frame, temp, cv::COLOR_BGR2GRAY); |
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cv::swap(temp, frame); |
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} |
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mog2(loadMat(frame, useRoi), foreground); |
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mog2_gold(frame, foreground_gold); |
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if (detectShadow) |
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{ |
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ASSERT_MAT_SIMILAR(foreground_gold, foreground, 1e-2); |
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} |
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else |
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{ |
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ASSERT_MAT_NEAR(foreground_gold, foreground, 0); |
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} |
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} |
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} |
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GPU_TEST_P(MOG2, getBackgroundImage) |
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{ |
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if (useGray) |
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return; |
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cv::VideoCapture cap(inputFile); |
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ASSERT_TRUE(cap.isOpened()); |
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cv::Mat frame; |
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cv::gpu::MOG2_GPU mog2; |
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mog2.bShadowDetection = detectShadow; |
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cv::gpu::GpuMat foreground; |
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cv::BackgroundSubtractorMOG2 mog2_gold; |
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mog2_gold.set("detectShadows", detectShadow); |
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cv::Mat foreground_gold; |
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for (int i = 0; i < 10; ++i) |
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{ |
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cap >> frame; |
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ASSERT_FALSE(frame.empty()); |
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mog2(loadMat(frame, useRoi), foreground); |
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mog2_gold(frame, foreground_gold); |
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} |
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cv::gpu::GpuMat background = createMat(frame.size(), frame.type(), useRoi); |
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mog2.getBackgroundImage(background); |
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cv::Mat background_gold; |
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mog2_gold.getBackgroundImage(background_gold); |
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ASSERT_MAT_NEAR(background_gold, background, 0); |
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} |
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INSTANTIATE_TEST_CASE_P(GPU_Video, MOG2, testing::Combine( |
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ALL_DEVICES, |
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testing::Values(std::string("768x576.avi")), |
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testing::Values(UseGray(true), UseGray(false)), |
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testing::Values(DetectShadow(true), DetectShadow(false)), |
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WHOLE_SUBMAT)); |
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#endif |
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////////////////////////////////////////////////////// |
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// GMG |
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PARAM_TEST_CASE(GMG, cv::gpu::DeviceInfo, cv::Size, MatDepth, Channels, UseRoi) |
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{ |
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}; |
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GPU_TEST_P(GMG, Accuracy) |
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{ |
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const cv::gpu::DeviceInfo devInfo = GET_PARAM(0); |
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cv::gpu::setDevice(devInfo.deviceID()); |
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const cv::Size size = GET_PARAM(1); |
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const int depth = GET_PARAM(2); |
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const int channels = GET_PARAM(3); |
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const bool useRoi = GET_PARAM(4); |
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const int type = CV_MAKE_TYPE(depth, channels); |
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const cv::Mat zeros(size, CV_8UC1, cv::Scalar::all(0)); |
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const cv::Mat fullfg(size, CV_8UC1, cv::Scalar::all(255)); |
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cv::Mat frame = randomMat(size, type, 0, 100); |
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cv::gpu::GpuMat d_frame = loadMat(frame, useRoi); |
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cv::gpu::GMG_GPU gmg; |
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gmg.numInitializationFrames = 5; |
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gmg.smoothingRadius = 0; |
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gmg.initialize(d_frame.size(), 0, 255); |
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cv::gpu::GpuMat d_fgmask = createMat(size, CV_8UC1, useRoi); |
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for (int i = 0; i < gmg.numInitializationFrames; ++i) |
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{ |
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gmg(d_frame, d_fgmask); |
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// fgmask should be entirely background during training |
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ASSERT_MAT_NEAR(zeros, d_fgmask, 0); |
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} |
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frame = randomMat(size, type, 160, 255); |
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d_frame = loadMat(frame, useRoi); |
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gmg(d_frame, d_fgmask); |
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// now fgmask should be entirely foreground |
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ASSERT_MAT_NEAR(fullfg, d_fgmask, 0); |
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} |
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INSTANTIATE_TEST_CASE_P(GPU_Video, GMG, testing::Combine( |
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ALL_DEVICES, |
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DIFFERENT_SIZES, |
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testing::Values(MatType(CV_8U), MatType(CV_16U), MatType(CV_32F)), |
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testing::Values(Channels(1), Channels(3), Channels(4)), |
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WHOLE_SUBMAT)); |
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#endif // HAVE_CUDA
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