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https://github.com/opencv/opencv.git
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4f2b126b7b
Conflicts: modules/core/include/opencv2/core/version.hpp modules/core/src/out.cpp modules/cudaimgproc/test/test_hough.cpp modules/gpu/doc/introduction.rst modules/gpu/perf/perf_imgproc.cpp modules/gpu/src/generalized_hough.cpp modules/nonfree/perf/perf_main.cpp
392 lines
11 KiB
C++
392 lines
11 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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#include "test_precomp.hpp"
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#ifdef HAVE_OPENCV_LEGACY
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# include "opencv2/legacy.hpp"
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#endif
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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 && defined(HAVE_OPENCV_LEGACY)
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namespace cv
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{
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template<> void DefaultDeleter<CvBGStatModel>::operator ()(CvBGStatModel* obj) const
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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::cuda::DeviceInfo, std::string)
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{
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cv::cuda::DeviceInfo devInfo;
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std::string inputFile;
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virtual void SetUp()
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{
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devInfo = GET_PARAM(0);
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cv::cuda::setDevice(devInfo.deviceID());
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inputFile = std::string(cvtest::TS::ptr()->get_data_path()) + "video/" + GET_PARAM(1);
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}
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};
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CUDA_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::cuda::GpuMat d_frame(frame);
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cv::Ptr<cv::cuda::BackgroundSubtractorFGD> d_fgd = cv::cuda::createBackgroundSubtractorFGD();
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cv::cuda::GpuMat d_foreground, d_background;
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std::vector< std::vector<cv::Point> > foreground_regions;
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d_fgd->apply(d_frame, d_foreground);
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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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d_fgd->apply(d_frame, d_foreground);
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d_fgd->getBackgroundImage(d_background);
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d_fgd->getForegroundRegions(foreground_regions);
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int count = (int) foreground_regions.size();
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cv::Mat gold_background = cv::cvarrToMat(model->background);
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cv::Mat gold_foreground = cv::cvarrToMat(model->foreground);
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ASSERT_MAT_NEAR(gold_background, d_background, 1.0);
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ASSERT_MAT_NEAR(gold_foreground, d_foreground, 0.0);
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ASSERT_EQ(gold_count, count);
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}
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}
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INSTANTIATE_TEST_CASE_P(CUDA_BgSegm, FGDStatModel, testing::Combine(
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ALL_DEVICES,
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testing::Values(std::string("768x576.avi"))));
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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::cuda::DeviceInfo, std::string, UseGray, LearningRate, UseRoi)
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{
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cv::cuda::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::cuda::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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CUDA_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::Ptr<cv::BackgroundSubtractorMOG> mog = cv::cuda::createBackgroundSubtractorMOG();
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cv::cuda::GpuMat foreground = createMat(frame.size(), CV_8UC1, useRoi);
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cv::Ptr<cv::BackgroundSubtractorMOG> mog_gold = cv::createBackgroundSubtractorMOG();
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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->apply(loadMat(frame, useRoi), foreground, learningRate);
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mog_gold->apply(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(CUDA_BgSegm, 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::cuda::DeviceInfo, std::string, UseGray, DetectShadow, UseRoi)
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{
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cv::cuda::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::cuda::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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CUDA_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::Ptr<cv::BackgroundSubtractorMOG2> mog2 = cv::cuda::createBackgroundSubtractorMOG2();
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mog2->setDetectShadows(detectShadow);
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cv::cuda::GpuMat foreground = createMat(frame.size(), CV_8UC1, useRoi);
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cv::Ptr<cv::BackgroundSubtractorMOG2> mog2_gold = cv::createBackgroundSubtractorMOG2();
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mog2_gold->setDetectShadows(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->apply(loadMat(frame, useRoi), foreground);
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mog2_gold->apply(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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CUDA_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::Ptr<cv::BackgroundSubtractorMOG2> mog2 = cv::cuda::createBackgroundSubtractorMOG2();
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mog2->setDetectShadows(detectShadow);
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cv::cuda::GpuMat foreground;
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cv::Ptr<cv::BackgroundSubtractorMOG2> mog2_gold = cv::createBackgroundSubtractorMOG2();
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mog2_gold->setDetectShadows(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->apply(loadMat(frame, useRoi), foreground);
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mog2_gold->apply(frame, foreground_gold);
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}
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cv::cuda::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, 1);
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}
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INSTANTIATE_TEST_CASE_P(CUDA_BgSegm, 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::cuda::DeviceInfo, cv::Size, MatDepth, Channels, UseRoi)
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{
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};
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CUDA_TEST_P(GMG, Accuracy)
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{
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const cv::cuda::DeviceInfo devInfo = GET_PARAM(0);
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cv::cuda::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::cuda::GpuMat d_frame = loadMat(frame, useRoi);
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cv::Ptr<cv::BackgroundSubtractorGMG> gmg = cv::cuda::createBackgroundSubtractorGMG();
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gmg->setNumFrames(5);
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gmg->setSmoothingRadius(0);
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cv::cuda::GpuMat d_fgmask = createMat(size, CV_8UC1, useRoi);
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for (int i = 0; i < gmg->getNumFrames(); ++i)
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{
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gmg->apply(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->apply(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(CUDA_BgSegm, 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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