Revert "Merge pull request #836 from jet47:gpu-modules"
This reverts commitfba72cb60d, reversing changes made to02131ffb62.
This commit is contained in:
Andrey Kamaev
230
modules/gpu/perf/perf_denoising.cpp
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230
modules/gpu/perf/perf_denoising.cpp
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/*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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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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PERF_TEST_P(Sz_Depth_Cn_WinSz_BlockSz, 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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PERF_TEST_P(Sz_Depth_Cn_WinSz_BlockSz, 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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