189 lines
		
	
	
		
			6.1 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
			
		
		
	
	
			189 lines
		
	
	
		
			6.1 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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| 
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| #include "test_precomp.hpp"
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| 
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| #ifdef HAVE_CUDA
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| 
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| using namespace cvtest;
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| 
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| ////////////////////////////////////////////////////////
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| // BilateralFilter
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| 
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| PARAM_TEST_CASE(BilateralFilter, cv::gpu::DeviceInfo, cv::Size, MatType)
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| {
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|     cv::gpu::DeviceInfo devInfo;
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|     cv::Size size;
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|     int type;
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|     int kernel_size;
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|     float sigma_color;
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|     float sigma_spatial;
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| 
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|     virtual void SetUp()
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|     {
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|         devInfo = GET_PARAM(0);
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|         size = GET_PARAM(1);
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|         type = GET_PARAM(2);
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| 
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|         kernel_size = 5;
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|         sigma_color = 10.f;
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|         sigma_spatial = 3.5f;
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| 
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|         cv::gpu::setDevice(devInfo.deviceID());
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|     }
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| };
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| 
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| GPU_TEST_P(BilateralFilter, Accuracy)
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| {
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|     cv::Mat src = randomMat(size, type);
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| 
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|     src.convertTo(src, type);
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|     cv::gpu::GpuMat dst;
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| 
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|     cv::gpu::bilateralFilter(loadMat(src), dst, kernel_size, sigma_color, sigma_spatial);
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| 
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|     cv::Mat dst_gold;
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|     cv::bilateralFilter(src, dst_gold, kernel_size, sigma_color, sigma_spatial);
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| 
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|     EXPECT_MAT_NEAR(dst_gold, dst, src.depth() == CV_32F ? 1e-3 : 1.0);
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| }
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| 
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| INSTANTIATE_TEST_CASE_P(GPU_Denoising, BilateralFilter, testing::Combine(
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|     ALL_DEVICES,
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|     testing::Values(cv::Size(128, 128), cv::Size(113, 113), cv::Size(639, 481)),
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|     testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_32FC1), MatType(CV_32FC3))
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|     ));
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| 
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| 
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| ////////////////////////////////////////////////////////
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| // Brute Force Non local means
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| 
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| struct BruteForceNonLocalMeans: testing::TestWithParam<cv::gpu::DeviceInfo>
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| {
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|     cv::gpu::DeviceInfo devInfo;
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| 
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|     virtual void SetUp()
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|     {
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|         devInfo = GetParam();
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|         cv::gpu::setDevice(devInfo.deviceID());
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|     }
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| };
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| 
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| GPU_TEST_P(BruteForceNonLocalMeans, Regression)
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| {
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|     using cv::gpu::GpuMat;
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| 
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|     cv::Mat bgr  = readImage("denoising/lena_noised_gaussian_sigma=20_multi_0.png", cv::IMREAD_COLOR);
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|     ASSERT_FALSE(bgr.empty());
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|     cv::resize(bgr, bgr, cv::Size(256, 256));
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| 
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|     cv::Mat gray;
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|     cv::cvtColor(bgr, gray, CV_BGR2GRAY);
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| 
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|     GpuMat dbgr, dgray;
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|     cv::gpu::nonLocalMeans(GpuMat(bgr),  dbgr, 20);
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|     cv::gpu::nonLocalMeans(GpuMat(gray), dgray, 20);
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| 
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| #if 0
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|     dumpImage("denoising/nlm_denoised_lena_bgr.png", cv::Mat(dbgr));
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|     dumpImage("denoising/nlm_denoised_lena_gray.png", cv::Mat(dgray));
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| #endif
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| 
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|     cv::Mat bgr_gold  = readImage("denoising/nlm_denoised_lena_bgr.png", cv::IMREAD_COLOR);
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|     cv::Mat gray_gold  = readImage("denoising/nlm_denoised_lena_gray.png", cv::IMREAD_GRAYSCALE);
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|     ASSERT_FALSE(bgr_gold.empty() || gray_gold.empty());
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|     cv::resize(bgr_gold, bgr_gold, cv::Size(256, 256));
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|     cv::resize(gray_gold, gray_gold, cv::Size(256, 256));
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| 
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|     EXPECT_MAT_NEAR(bgr_gold, dbgr, 1);
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|     EXPECT_MAT_NEAR(gray_gold, dgray, 1);
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| }
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| 
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| INSTANTIATE_TEST_CASE_P(GPU_Denoising, BruteForceNonLocalMeans, ALL_DEVICES);
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| 
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| ////////////////////////////////////////////////////////
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| // Fast Force Non local means
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| 
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| struct FastNonLocalMeans: testing::TestWithParam<cv::gpu::DeviceInfo>
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| {
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|     cv::gpu::DeviceInfo devInfo;
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| 
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|     virtual void SetUp()
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|     {
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|         devInfo = GetParam();
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|         cv::gpu::setDevice(devInfo.deviceID());
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|     }
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| };
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| 
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| GPU_TEST_P(FastNonLocalMeans, Regression)
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| {
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|     using cv::gpu::GpuMat;
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| 
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|     cv::Mat bgr  = readImage("denoising/lena_noised_gaussian_sigma=20_multi_0.png", cv::IMREAD_COLOR);
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|     ASSERT_FALSE(bgr.empty());
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| 
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|     cv::Mat gray;
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|     cv::cvtColor(bgr, gray, CV_BGR2GRAY);
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| 
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|     GpuMat dbgr, dgray;
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|     cv::gpu::FastNonLocalMeansDenoising fnlmd;
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| 
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|     fnlmd.simpleMethod(GpuMat(gray),  dgray, 20);
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|     fnlmd.labMethod(GpuMat(bgr),  dbgr, 20, 10);
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| 
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| #if 0
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|     dumpImage("denoising/fnlm_denoised_lena_bgr.png", cv::Mat(dbgr));
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|     dumpImage("denoising/fnlm_denoised_lena_gray.png", cv::Mat(dgray));
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| #endif
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| 
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|     cv::Mat bgr_gold  = readImage("denoising/fnlm_denoised_lena_bgr.png", cv::IMREAD_COLOR);
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|     cv::Mat gray_gold  = readImage("denoising/fnlm_denoised_lena_gray.png", cv::IMREAD_GRAYSCALE);
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|     ASSERT_FALSE(bgr_gold.empty() || gray_gold.empty());
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| 
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|     EXPECT_MAT_NEAR(bgr_gold, dbgr, 1);
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|     EXPECT_MAT_NEAR(gray_gold, dgray, 1);
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| }
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| 
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| INSTANTIATE_TEST_CASE_P(GPU_Denoising, FastNonLocalMeans, ALL_DEVICES);
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| 
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| #endif // HAVE_CUDA
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