322 lines
8.6 KiB
C++
322 lines
8.6 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 "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 ARITHM_MAT_DEPTH Values(CV_8U, CV_16U, CV_32F, CV_64F)
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//////////////////////////////////////////////////////////////////////
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// Merge
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PERF_TEST_P(Sz_Depth_Cn, Merge,
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Combine(CUDA_TYPICAL_MAT_SIZES,
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ARITHM_MAT_DEPTH,
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Values(2, 3, 4)))
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{
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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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std::vector<cv::Mat> src(channels);
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for (int i = 0; i < channels; ++i)
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{
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src[i].create(size, depth);
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declare.in(src[i], WARMUP_RNG);
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}
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if (PERF_RUN_CUDA())
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{
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std::vector<cv::cuda::GpuMat> d_src(channels);
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for (int i = 0; i < channels; ++i)
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d_src[i].upload(src[i]);
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cv::cuda::GpuMat dst;
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TEST_CYCLE() cv::cuda::merge(d_src, dst);
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CUDA_SANITY_CHECK(dst, 1e-10);
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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::merge(src, dst);
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CPU_SANITY_CHECK(dst);
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}
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}
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//////////////////////////////////////////////////////////////////////
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// Split
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PERF_TEST_P(Sz_Depth_Cn, Split,
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Combine(CUDA_TYPICAL_MAT_SIZES,
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ARITHM_MAT_DEPTH,
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Values(2, 3, 4)))
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{
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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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cv::Mat src(size, CV_MAKE_TYPE(depth, channels));
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declare.in(src, WARMUP_RNG);
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if (PERF_RUN_CUDA())
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{
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const cv::cuda::GpuMat d_src(src);
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std::vector<cv::cuda::GpuMat> dst;
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TEST_CYCLE() cv::cuda::split(d_src, dst);
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const cv::cuda::GpuMat& dst0 = dst[0];
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const cv::cuda::GpuMat& dst1 = dst[1];
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CUDA_SANITY_CHECK(dst0, 1e-10);
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CUDA_SANITY_CHECK(dst1, 1e-10);
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}
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else
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{
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std::vector<cv::Mat> dst;
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TEST_CYCLE() cv::split(src, dst);
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const cv::Mat& dst0 = dst[0];
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const cv::Mat& dst1 = dst[1];
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CPU_SANITY_CHECK(dst0);
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CPU_SANITY_CHECK(dst1);
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}
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}
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//////////////////////////////////////////////////////////////////////
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// Transpose
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PERF_TEST_P(Sz_Type, Transpose,
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Combine(CUDA_TYPICAL_MAT_SIZES,
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Values(CV_8UC1, CV_8UC4, CV_16UC2, CV_16SC2, CV_32SC1, CV_32SC2, CV_64FC1)))
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{
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const cv::Size size = GET_PARAM(0);
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const int type = GET_PARAM(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_CUDA())
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{
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const cv::cuda::GpuMat d_src(src);
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cv::cuda::GpuMat dst;
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TEST_CYCLE() cv::cuda::transpose(d_src, dst);
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CUDA_SANITY_CHECK(dst, 1e-10);
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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::transpose(src, dst);
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CPU_SANITY_CHECK(dst);
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}
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}
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//////////////////////////////////////////////////////////////////////
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// Flip
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enum {FLIP_BOTH = 0, FLIP_X = 1, FLIP_Y = -1};
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CV_ENUM(FlipCode, FLIP_BOTH, FLIP_X, FLIP_Y)
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DEF_PARAM_TEST(Sz_Depth_Cn_Code, cv::Size, MatDepth, MatCn, FlipCode);
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PERF_TEST_P(Sz_Depth_Cn_Code, Flip,
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Combine(CUDA_TYPICAL_MAT_SIZES,
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Values(CV_8U, CV_16U, CV_32F),
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CUDA_CHANNELS_1_3_4,
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FlipCode::all()))
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{
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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 flipCode = GET_PARAM(3);
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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_CUDA())
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{
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const cv::cuda::GpuMat d_src(src);
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cv::cuda::GpuMat dst;
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TEST_CYCLE() cv::cuda::flip(d_src, dst, flipCode);
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CUDA_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::flip(src, dst, flipCode);
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CPU_SANITY_CHECK(dst);
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}
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}
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//////////////////////////////////////////////////////////////////////
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// LutOneChannel
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PERF_TEST_P(Sz_Type, LutOneChannel,
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Combine(CUDA_TYPICAL_MAT_SIZES,
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Values(CV_8UC1, CV_8UC3)))
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{
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const cv::Size size = GET_PARAM(0);
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const int type = GET_PARAM(1);
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cv::Mat src(size, type);
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declare.in(src, WARMUP_RNG);
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cv::Mat lut(1, 256, CV_8UC1);
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declare.in(lut, WARMUP_RNG);
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if (PERF_RUN_CUDA())
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{
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cv::Ptr<cv::cuda::LookUpTable> lutAlg = cv::cuda::createLookUpTable(lut);
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const cv::cuda::GpuMat d_src(src);
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cv::cuda::GpuMat dst;
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TEST_CYCLE() lutAlg->transform(d_src, dst);
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CUDA_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::LUT(src, lut, dst);
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CPU_SANITY_CHECK(dst);
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}
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}
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//////////////////////////////////////////////////////////////////////
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// LutMultiChannel
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PERF_TEST_P(Sz_Type, LutMultiChannel,
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Combine(CUDA_TYPICAL_MAT_SIZES,
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Values<MatType>(CV_8UC3)))
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{
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const cv::Size size = GET_PARAM(0);
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const int type = GET_PARAM(1);
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cv::Mat src(size, type);
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declare.in(src, WARMUP_RNG);
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cv::Mat lut(1, 256, CV_MAKE_TYPE(CV_8U, src.channels()));
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declare.in(lut, WARMUP_RNG);
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if (PERF_RUN_CUDA())
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{
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cv::Ptr<cv::cuda::LookUpTable> lutAlg = cv::cuda::createLookUpTable(lut);
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const cv::cuda::GpuMat d_src(src);
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cv::cuda::GpuMat dst;
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TEST_CYCLE() lutAlg->transform(d_src, dst);
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CUDA_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::LUT(src, lut, dst);
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CPU_SANITY_CHECK(dst);
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}
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}
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//////////////////////////////////////////////////////////////////////
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// CopyMakeBorder
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DEF_PARAM_TEST(Sz_Depth_Cn_Border, cv::Size, MatDepth, MatCn, BorderMode);
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PERF_TEST_P(Sz_Depth_Cn_Border, CopyMakeBorder,
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Combine(CUDA_TYPICAL_MAT_SIZES,
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Values(CV_8U, CV_16U, CV_32F),
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CUDA_CHANNELS_1_3_4,
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ALL_BORDER_MODES))
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{
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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 borderMode = GET_PARAM(3);
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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_CUDA())
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{
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const cv::cuda::GpuMat d_src(src);
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cv::cuda::GpuMat dst;
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TEST_CYCLE() cv::cuda::copyMakeBorder(d_src, dst, 5, 5, 5, 5, borderMode);
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CUDA_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::copyMakeBorder(src, dst, 5, 5, 5, 5, borderMode);
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CPU_SANITY_CHECK(dst);
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}
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}
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