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Open Source Computer Vision Library
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520 lines
13 KiB
520 lines
13 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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using namespace std; |
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using namespace testing; |
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using namespace perf; |
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////////////////////////////////////////////////////////////////////// |
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// Norm |
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DEF_PARAM_TEST(Sz_Depth_Norm, cv::Size, MatDepth, NormType); |
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PERF_TEST_P(Sz_Depth_Norm, Norm, |
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Combine(CUDA_TYPICAL_MAT_SIZES, |
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Values(CV_8U, CV_16U, CV_32S, CV_32F), |
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Values(NormType(cv::NORM_INF), NormType(cv::NORM_L1), NormType(cv::NORM_L2)))) |
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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 normType = GET_PARAM(2); |
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cv::Mat src(size, depth); |
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if (depth == CV_8U) |
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cv::randu(src, 0, 254); |
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else |
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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 d_buf; |
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double gpu_dst; |
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TEST_CYCLE() gpu_dst = cv::cuda::norm(d_src, normType, d_buf); |
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SANITY_CHECK(gpu_dst, 1e-6, ERROR_RELATIVE); |
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} |
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else |
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{ |
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double cpu_dst; |
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TEST_CYCLE() cpu_dst = cv::norm(src, normType); |
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SANITY_CHECK(cpu_dst, 1e-6, ERROR_RELATIVE); |
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} |
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} |
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////////////////////////////////////////////////////////////////////// |
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// NormDiff |
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DEF_PARAM_TEST(Sz_Norm, cv::Size, NormType); |
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PERF_TEST_P(Sz_Norm, NormDiff, |
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Combine(CUDA_TYPICAL_MAT_SIZES, |
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Values(NormType(cv::NORM_INF), NormType(cv::NORM_L1), NormType(cv::NORM_L2)))) |
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{ |
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const cv::Size size = GET_PARAM(0); |
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const int normType = GET_PARAM(1); |
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cv::Mat src1(size, CV_8UC1); |
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declare.in(src1, WARMUP_RNG); |
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cv::Mat src2(size, CV_8UC1); |
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declare.in(src2, WARMUP_RNG); |
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if (PERF_RUN_CUDA()) |
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{ |
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const cv::cuda::GpuMat d_src1(src1); |
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const cv::cuda::GpuMat d_src2(src2); |
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double gpu_dst; |
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TEST_CYCLE() gpu_dst = cv::cuda::norm(d_src1, d_src2, normType); |
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SANITY_CHECK(gpu_dst); |
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} |
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else |
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{ |
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double cpu_dst; |
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TEST_CYCLE() cpu_dst = cv::norm(src1, src2, normType); |
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SANITY_CHECK(cpu_dst); |
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} |
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} |
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////////////////////////////////////////////////////////////////////// |
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// Sum |
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DEF_PARAM_TEST(Sz_Depth_Cn, cv::Size, MatDepth, MatCn); |
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PERF_TEST_P(Sz_Depth_Cn, Sum, |
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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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{ |
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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 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::Scalar gpu_dst; |
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TEST_CYCLE() gpu_dst = cv::cuda::sum(d_src); |
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SANITY_CHECK(gpu_dst, 1e-5, ERROR_RELATIVE); |
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} |
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else |
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{ |
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cv::Scalar cpu_dst; |
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TEST_CYCLE() cpu_dst = cv::sum(src); |
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SANITY_CHECK(cpu_dst, 1e-6, ERROR_RELATIVE); |
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} |
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} |
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////////////////////////////////////////////////////////////////////// |
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// SumAbs |
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PERF_TEST_P(Sz_Depth_Cn, SumAbs, |
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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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{ |
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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 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::Scalar gpu_dst; |
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TEST_CYCLE() gpu_dst = cv::cuda::absSum(d_src); |
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SANITY_CHECK(gpu_dst, 1e-6, ERROR_RELATIVE); |
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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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// SumSqr |
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PERF_TEST_P(Sz_Depth_Cn, SumSqr, |
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Combine(CUDA_TYPICAL_MAT_SIZES, |
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Values<MatDepth>(CV_8U, CV_16U, CV_32F), |
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CUDA_CHANNELS_1_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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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::Scalar gpu_dst; |
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TEST_CYCLE() gpu_dst = cv::cuda::sqrSum(d_src); |
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SANITY_CHECK(gpu_dst, 1e-6, ERROR_RELATIVE); |
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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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// MinMax |
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DEF_PARAM_TEST(Sz_Depth, cv::Size, MatDepth); |
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PERF_TEST_P(Sz_Depth, MinMax, |
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Combine(CUDA_TYPICAL_MAT_SIZES, |
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Values(CV_8U, CV_16U, CV_32F, CV_64F))) |
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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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cv::Mat src(size, depth); |
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if (depth == CV_8U) |
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cv::randu(src, 0, 254); |
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else |
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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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double gpu_minVal, gpu_maxVal; |
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TEST_CYCLE() cv::cuda::minMax(d_src, &gpu_minVal, &gpu_maxVal, cv::cuda::GpuMat()); |
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SANITY_CHECK(gpu_minVal, 1e-10); |
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SANITY_CHECK(gpu_maxVal, 1e-10); |
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} |
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else |
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{ |
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double cpu_minVal, cpu_maxVal; |
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TEST_CYCLE() cv::minMaxLoc(src, &cpu_minVal, &cpu_maxVal); |
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SANITY_CHECK(cpu_minVal); |
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SANITY_CHECK(cpu_maxVal); |
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} |
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} |
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////////////////////////////////////////////////////////////////////// |
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// MinMaxLoc |
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PERF_TEST_P(Sz_Depth, MinMaxLoc, |
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Combine(CUDA_TYPICAL_MAT_SIZES, |
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Values(CV_8U, CV_16U, CV_32F, CV_64F))) |
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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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cv::Mat src(size, depth); |
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if (depth == CV_8U) |
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cv::randu(src, 0, 254); |
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else |
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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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double gpu_minVal, gpu_maxVal; |
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cv::Point gpu_minLoc, gpu_maxLoc; |
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TEST_CYCLE() cv::cuda::minMaxLoc(d_src, &gpu_minVal, &gpu_maxVal, &gpu_minLoc, &gpu_maxLoc); |
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SANITY_CHECK(gpu_minVal, 1e-10); |
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SANITY_CHECK(gpu_maxVal, 1e-10); |
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} |
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else |
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{ |
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double cpu_minVal, cpu_maxVal; |
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cv::Point cpu_minLoc, cpu_maxLoc; |
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TEST_CYCLE() cv::minMaxLoc(src, &cpu_minVal, &cpu_maxVal, &cpu_minLoc, &cpu_maxLoc); |
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SANITY_CHECK(cpu_minVal); |
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SANITY_CHECK(cpu_maxVal); |
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} |
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} |
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////////////////////////////////////////////////////////////////////// |
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// CountNonZero |
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PERF_TEST_P(Sz_Depth, CountNonZero, |
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Combine(CUDA_TYPICAL_MAT_SIZES, |
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Values(CV_8U, CV_16U, CV_32F, CV_64F))) |
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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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cv::Mat src(size, depth); |
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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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int gpu_dst = 0; |
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TEST_CYCLE() gpu_dst = cv::cuda::countNonZero(d_src); |
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SANITY_CHECK(gpu_dst); |
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} |
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else |
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{ |
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int cpu_dst = 0; |
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TEST_CYCLE() cpu_dst = cv::countNonZero(src); |
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SANITY_CHECK(cpu_dst); |
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} |
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} |
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////////////////////////////////////////////////////////////////////// |
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// Reduce |
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CV_ENUM(ReduceCode, REDUCE_SUM, REDUCE_AVG, REDUCE_MAX, REDUCE_MIN) |
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enum {Rows = 0, Cols = 1}; |
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CV_ENUM(ReduceDim, Rows, Cols) |
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DEF_PARAM_TEST(Sz_Depth_Cn_Code_Dim, cv::Size, MatDepth, MatCn, ReduceCode, ReduceDim); |
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PERF_TEST_P(Sz_Depth_Cn_Code_Dim, Reduce, |
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Combine(CUDA_TYPICAL_MAT_SIZES, |
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Values(CV_8U, CV_16U, CV_16S, CV_32F), |
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Values(1, 2, 3, 4), |
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ReduceCode::all(), |
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ReduceDim::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 reduceOp = GET_PARAM(3); |
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const int dim = GET_PARAM(4); |
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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::reduce(d_src, dst, dim, reduceOp, CV_32F); |
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dst = dst.reshape(dst.channels(), 1); |
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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::reduce(src, dst, dim, reduceOp, CV_32F); |
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CPU_SANITY_CHECK(dst); |
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} |
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} |
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////////////////////////////////////////////////////////////////////// |
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// Normalize |
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DEF_PARAM_TEST(Sz_Depth_NormType, cv::Size, MatDepth, NormType); |
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PERF_TEST_P(Sz_Depth_NormType, Normalize, |
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Combine(CUDA_TYPICAL_MAT_SIZES, |
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Values(CV_8U, CV_16U, CV_32F, CV_64F), |
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Values(NormType(cv::NORM_INF), |
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NormType(cv::NORM_L1), |
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NormType(cv::NORM_L2), |
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NormType(cv::NORM_MINMAX)))) |
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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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const int norm_type = GET_PARAM(2); |
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const double alpha = 1; |
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const double beta = 0; |
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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::normalize(d_src, dst, alpha, beta, norm_type, type, cv::cuda::GpuMat()); |
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CUDA_SANITY_CHECK(dst, 1e-6); |
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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::normalize(src, dst, alpha, beta, norm_type, type); |
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CPU_SANITY_CHECK(dst); |
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} |
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} |
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////////////////////////////////////////////////////////////////////// |
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// MeanStdDev |
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PERF_TEST_P(Sz, MeanStdDev, |
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CUDA_TYPICAL_MAT_SIZES) |
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{ |
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const cv::Size size = GetParam(); |
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cv::Mat src(size, CV_8UC1); |
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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::Scalar gpu_mean; |
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cv::Scalar gpu_stddev; |
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TEST_CYCLE() cv::cuda::meanStdDev(d_src, gpu_mean, gpu_stddev); |
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SANITY_CHECK(gpu_mean); |
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SANITY_CHECK(gpu_stddev); |
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} |
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else |
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{ |
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cv::Scalar cpu_mean; |
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cv::Scalar cpu_stddev; |
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TEST_CYCLE() cv::meanStdDev(src, cpu_mean, cpu_stddev); |
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SANITY_CHECK(cpu_mean); |
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SANITY_CHECK(cpu_stddev); |
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} |
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} |
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////////////////////////////////////////////////////////////////////// |
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// Integral |
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PERF_TEST_P(Sz, Integral, |
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CUDA_TYPICAL_MAT_SIZES) |
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{ |
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const cv::Size size = GetParam(); |
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cv::Mat src(size, CV_8UC1); |
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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::integral(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::integral(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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// IntegralSqr |
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PERF_TEST_P(Sz, IntegralSqr, |
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CUDA_TYPICAL_MAT_SIZES) |
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{ |
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const cv::Size size = GetParam(); |
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cv::Mat src(size, CV_8UC1); |
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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::sqrIntegral(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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FAIL_NO_CPU(); |
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} |
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}
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