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Open Source Computer Vision Library
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233 lines
7.1 KiB
233 lines
7.1 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 "perf_precomp.hpp" |
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#include "opencv2/ts/gpu_perf.hpp" |
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using namespace std; |
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using namespace testing; |
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using namespace perf; |
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#define GPU_DENOISING_IMAGE_SIZES testing::Values(perf::szVGA, perf::sz720p) |
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////////////////////////////////////////////////////////////////////// |
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// BilateralFilter |
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DEF_PARAM_TEST(Sz_Depth_Cn_KernelSz, cv::Size, MatDepth, MatCn, int); |
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PERF_TEST_P(Sz_Depth_Cn_KernelSz, Denoising_BilateralFilter, |
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Combine(GPU_DENOISING_IMAGE_SIZES, |
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Values(CV_8U, CV_32F), |
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GPU_CHANNELS_1_3, |
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Values(3, 5, 9))) |
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{ |
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declare.time(60.0); |
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const cv::Size size = GET_PARAM(0); |
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const int depth = GET_PARAM(1); |
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const int channels = GET_PARAM(2); |
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const int kernel_size = GET_PARAM(3); |
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const float sigma_color = 7; |
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const float sigma_spatial = 5; |
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const int borderMode = cv::BORDER_REFLECT101; |
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const int type = CV_MAKE_TYPE(depth, channels); |
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cv::Mat src(size, type); |
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declare.in(src, WARMUP_RNG); |
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if (PERF_RUN_GPU()) |
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{ |
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const cv::gpu::GpuMat d_src(src); |
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cv::gpu::GpuMat dst; |
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TEST_CYCLE() cv::gpu::bilateralFilter(d_src, dst, kernel_size, sigma_color, sigma_spatial, borderMode); |
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GPU_SANITY_CHECK(dst); |
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} |
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else |
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{ |
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cv::Mat dst; |
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TEST_CYCLE() cv::bilateralFilter(src, dst, kernel_size, sigma_color, sigma_spatial, borderMode); |
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CPU_SANITY_CHECK(dst); |
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} |
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} |
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////////////////////////////////////////////////////////////////////// |
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// nonLocalMeans |
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DEF_PARAM_TEST(Sz_Depth_Cn_WinSz_BlockSz, cv::Size, MatDepth, MatCn, int, int); |
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// disabled, since it takes too much time |
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PERF_TEST_P(Sz_Depth_Cn_WinSz_BlockSz, DISABLED_Denoising_NonLocalMeans, |
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Combine(GPU_DENOISING_IMAGE_SIZES, |
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Values<MatDepth>(CV_8U), |
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GPU_CHANNELS_1_3, |
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Values(21), |
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Values(5))) |
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{ |
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declare.time(600.0); |
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const cv::Size size = GET_PARAM(0); |
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const int depth = GET_PARAM(1); |
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const int channels = GET_PARAM(2); |
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const int search_widow_size = GET_PARAM(3); |
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const int block_size = GET_PARAM(4); |
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const float h = 10; |
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const int borderMode = cv::BORDER_REFLECT101; |
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const int type = CV_MAKE_TYPE(depth, channels); |
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cv::Mat src(size, type); |
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declare.in(src, WARMUP_RNG); |
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if (PERF_RUN_GPU()) |
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{ |
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const cv::gpu::GpuMat d_src(src); |
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cv::gpu::GpuMat dst; |
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TEST_CYCLE() cv::gpu::nonLocalMeans(d_src, dst, h, search_widow_size, block_size, borderMode); |
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GPU_SANITY_CHECK(dst); |
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} |
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else |
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{ |
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FAIL_NO_CPU(); |
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} |
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} |
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////////////////////////////////////////////////////////////////////// |
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// fastNonLocalMeans |
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DEF_PARAM_TEST(Sz_Depth_Cn_WinSz_BlockSz, cv::Size, MatDepth, MatCn, int, int); |
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// disabled, since it takes too much time |
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PERF_TEST_P(Sz_Depth_Cn_WinSz_BlockSz, DISABLED_Denoising_FastNonLocalMeans, |
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Combine(GPU_DENOISING_IMAGE_SIZES, |
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Values<MatDepth>(CV_8U), |
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GPU_CHANNELS_1_3, |
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Values(21), |
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Values(7))) |
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{ |
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declare.time(60.0); |
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const cv::Size size = GET_PARAM(0); |
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const int depth = GET_PARAM(1); |
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const int search_widow_size = GET_PARAM(2); |
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const int block_size = GET_PARAM(3); |
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const float h = 10; |
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const int type = CV_MAKE_TYPE(depth, 1); |
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cv::Mat src(size, type); |
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declare.in(src, WARMUP_RNG); |
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if (PERF_RUN_GPU()) |
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{ |
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cv::gpu::FastNonLocalMeansDenoising fnlmd; |
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const cv::gpu::GpuMat d_src(src); |
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cv::gpu::GpuMat dst; |
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TEST_CYCLE() fnlmd.simpleMethod(d_src, dst, h, search_widow_size, block_size); |
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GPU_SANITY_CHECK(dst); |
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} |
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else |
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{ |
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cv::Mat dst; |
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TEST_CYCLE() cv::fastNlMeansDenoising(src, dst, h, block_size, search_widow_size); |
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CPU_SANITY_CHECK(dst); |
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} |
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} |
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////////////////////////////////////////////////////////////////////// |
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// fastNonLocalMeans (colored) |
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DEF_PARAM_TEST(Sz_Depth_WinSz_BlockSz, cv::Size, MatDepth, int, int); |
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PERF_TEST_P(Sz_Depth_WinSz_BlockSz, Denoising_FastNonLocalMeansColored, |
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Combine(GPU_DENOISING_IMAGE_SIZES, |
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Values<MatDepth>(CV_8U), |
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Values(21), |
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Values(7))) |
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{ |
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declare.time(60.0); |
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const cv::Size size = GET_PARAM(0); |
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const int depth = GET_PARAM(1); |
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const int search_widow_size = GET_PARAM(2); |
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const int block_size = GET_PARAM(3); |
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const float h = 10; |
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const int type = CV_MAKE_TYPE(depth, 3); |
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cv::Mat src(size, type); |
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declare.in(src, WARMUP_RNG); |
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if (PERF_RUN_GPU()) |
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{ |
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cv::gpu::FastNonLocalMeansDenoising fnlmd; |
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const cv::gpu::GpuMat d_src(src); |
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cv::gpu::GpuMat dst; |
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TEST_CYCLE() fnlmd.labMethod(d_src, dst, h, h, search_widow_size, block_size); |
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GPU_SANITY_CHECK(dst); |
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} |
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else |
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{ |
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cv::Mat dst; |
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TEST_CYCLE() cv::fastNlMeansDenoisingColored(src, dst, h, h, block_size, search_widow_size); |
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CPU_SANITY_CHECK(dst); |
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} |
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}
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