175 lines
		
	
	
		
			5.5 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
			
		
		
	
	
			175 lines
		
	
	
		
			5.5 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_CUDA
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using namespace cvtest;
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////////////////////////////////////////////////////////////////////////////////
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// MeanShift
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struct MeanShift : testing::TestWithParam<cv::cuda::DeviceInfo>
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{
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    cv::cuda::DeviceInfo devInfo;
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    cv::Mat img;
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    int spatialRad;
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    int colorRad;
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    virtual void SetUp()
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    {
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        devInfo = GetParam();
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        cv::cuda::setDevice(devInfo.deviceID());
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        img = readImageType("meanshift/cones.png", CV_8UC4);
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        ASSERT_FALSE(img.empty());
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        spatialRad = 30;
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        colorRad = 30;
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    }
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};
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CUDA_TEST_P(MeanShift, Filtering)
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{
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    cv::Mat img_template;
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    if (supportFeature(devInfo, cv::cuda::FEATURE_SET_COMPUTE_20))
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        img_template = readImage("meanshift/con_result.png");
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    else
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        img_template = readImage("meanshift/con_result_CC1X.png");
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    ASSERT_FALSE(img_template.empty());
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    cv::cuda::GpuMat d_dst;
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    cv::cuda::meanShiftFiltering(loadMat(img), d_dst, spatialRad, colorRad);
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    ASSERT_EQ(CV_8UC4, d_dst.type());
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    cv::Mat dst(d_dst);
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    cv::Mat result;
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    cv::cvtColor(dst, result, cv::COLOR_BGRA2BGR);
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    EXPECT_MAT_NEAR(img_template, result, 0.0);
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}
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CUDA_TEST_P(MeanShift, Proc)
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{
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    cv::FileStorage fs;
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    if (supportFeature(devInfo, cv::cuda::FEATURE_SET_COMPUTE_20))
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        fs.open(std::string(cvtest::TS::ptr()->get_data_path()) + "meanshift/spmap.yaml", cv::FileStorage::READ);
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    else
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        fs.open(std::string(cvtest::TS::ptr()->get_data_path()) + "meanshift/spmap_CC1X.yaml", cv::FileStorage::READ);
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    ASSERT_TRUE(fs.isOpened());
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    cv::Mat spmap_template;
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    fs["spmap"] >> spmap_template;
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    ASSERT_FALSE(spmap_template.empty());
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    cv::cuda::GpuMat rmap_filtered;
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    cv::cuda::meanShiftFiltering(loadMat(img), rmap_filtered, spatialRad, colorRad);
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    cv::cuda::GpuMat rmap;
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    cv::cuda::GpuMat spmap;
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    cv::cuda::meanShiftProc(loadMat(img), rmap, spmap, spatialRad, colorRad);
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    ASSERT_EQ(CV_8UC4, rmap.type());
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    EXPECT_MAT_NEAR(rmap_filtered, rmap, 0.0);
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    EXPECT_MAT_NEAR(spmap_template, spmap, 0.0);
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}
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INSTANTIATE_TEST_CASE_P(CUDA_ImgProc, MeanShift, ALL_DEVICES);
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////////////////////////////////////////////////////////////////////////////////
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// MeanShiftSegmentation
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namespace
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{
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    IMPLEMENT_PARAM_CLASS(MinSize, int);
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}
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PARAM_TEST_CASE(MeanShiftSegmentation, cv::cuda::DeviceInfo, MinSize)
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{
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    cv::cuda::DeviceInfo devInfo;
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    int minsize;
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    virtual void SetUp()
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    {
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        devInfo = GET_PARAM(0);
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        minsize = GET_PARAM(1);
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        cv::cuda::setDevice(devInfo.deviceID());
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    }
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};
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CUDA_TEST_P(MeanShiftSegmentation, Regression)
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{
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    cv::Mat img = readImageType("meanshift/cones.png", CV_8UC4);
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    ASSERT_FALSE(img.empty());
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    std::ostringstream path;
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    path << "meanshift/cones_segmented_sp10_sr10_minsize" << minsize;
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    if (supportFeature(devInfo, cv::cuda::FEATURE_SET_COMPUTE_20))
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        path << ".png";
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    else
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        path << "_CC1X.png";
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    cv::Mat dst_gold = readImage(path.str());
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    ASSERT_FALSE(dst_gold.empty());
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    cv::Mat dst;
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    cv::cuda::meanShiftSegmentation(loadMat(img), dst, 10, 10, minsize);
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    cv::Mat dst_rgb;
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    cv::cvtColor(dst, dst_rgb, cv::COLOR_BGRA2BGR);
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    EXPECT_MAT_SIMILAR(dst_gold, dst_rgb, 1e-3);
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}
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INSTANTIATE_TEST_CASE_P(CUDA_ImgProc, MeanShiftSegmentation, testing::Combine(
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    ALL_DEVICES,
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    testing::Values(MinSize(0), MinSize(4), MinSize(20), MinSize(84), MinSize(340), MinSize(1364))));
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#endif // HAVE_CUDA
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