/*M/////////////////////////////////////////////////////////////////////////////////////// // // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. // // By downloading, copying, installing or using the software you agree to this license. // If you do not agree to this license, do not download, install, // copy or use the software. // // // License Agreement // For Open Source Computer Vision Library // // Copyright (C) 2000-2008, Intel Corporation, all rights reserved. // Copyright (C) 2009, Willow Garage Inc., all rights reserved. // Third party copyrights are property of their respective owners. // // Redistribution and use in source and binary forms, with or without modification, // are permitted provided that the following conditions are met: // // * Redistribution's of source code must retain the above copyright notice, // this list of conditions and the following disclaimer. // // * Redistribution's in binary form must reproduce the above copyright notice, // this list of conditions and the following disclaimer in the documentation // and/or other materials provided with the distribution. // // * The name of the copyright holders may not be used to endorse or promote products // derived from this software without specific prior written permission. // // This software is provided by the copyright holders and contributors "as is" and // any express or implied warranties, including, but not limited to, the implied // warranties of merchantability and fitness for a particular purpose are disclaimed. // In no event shall the Intel Corporation or contributors be liable for any direct, // indirect, incidental, special, exemplary, or consequential damages // (including, but not limited to, procurement of substitute goods or services; // loss of use, data, or profits; or business interruption) however caused // and on any theory of liability, whether in contract, strict liability, // or tort (including negligence or otherwise) arising in any way out of // the use of this software, even if advised of the possibility of such damage. // //M*/ #include "perf_precomp.hpp" using namespace std; using namespace testing; using namespace perf; ////////////////////////////////////////////////////////////////////// // GEMM CV_FLAGS(GemmFlags, 0, cv::GEMM_1_T, cv::GEMM_2_T, cv::GEMM_3_T) #define ALL_GEMM_FLAGS Values(GemmFlags(0), GemmFlags(cv::GEMM_1_T), GemmFlags(cv::GEMM_2_T), GemmFlags(cv::GEMM_3_T), \ GemmFlags(cv::GEMM_1_T | cv::GEMM_2_T), GemmFlags(cv::GEMM_1_T | cv::GEMM_3_T), GemmFlags(cv::GEMM_1_T | cv::GEMM_2_T | cv::GEMM_3_T)) DEF_PARAM_TEST(Sz_Type_Flags, cv::Size, MatType, GemmFlags); PERF_TEST_P(Sz_Type_Flags, GEMM, Combine(Values(cv::Size(512, 512), cv::Size(1024, 1024)), Values(CV_32FC1, CV_32FC2, CV_64FC1), ALL_GEMM_FLAGS)) { const cv::Size size = GET_PARAM(0); const int type = GET_PARAM(1); const int flags = GET_PARAM(2); cv::Mat src1(size, type); declare.in(src1, WARMUP_RNG); cv::Mat src2(size, type); declare.in(src2, WARMUP_RNG); cv::Mat src3(size, type); declare.in(src3, WARMUP_RNG); if (PERF_RUN_GPU()) { declare.time(5.0); const cv::gpu::GpuMat d_src1(src1); const cv::gpu::GpuMat d_src2(src2); const cv::gpu::GpuMat d_src3(src3); cv::gpu::GpuMat dst; TEST_CYCLE() cv::gpu::gemm(d_src1, d_src2, 1.0, d_src3, 1.0, dst, flags); GPU_SANITY_CHECK(dst, 1e-6); } else { declare.time(50.0); cv::Mat dst; TEST_CYCLE() cv::gemm(src1, src2, 1.0, src3, 1.0, dst, flags); CPU_SANITY_CHECK(dst); } } ////////////////////////////////////////////////////////////////////// // MulSpectrums CV_FLAGS(DftFlags, 0, cv::DFT_INVERSE, cv::DFT_SCALE, cv::DFT_ROWS, cv::DFT_COMPLEX_OUTPUT, cv::DFT_REAL_OUTPUT) DEF_PARAM_TEST(Sz_Flags, cv::Size, DftFlags); PERF_TEST_P(Sz_Flags, MulSpectrums, Combine(GPU_TYPICAL_MAT_SIZES, Values(0, DftFlags(cv::DFT_ROWS)))) { const cv::Size size = GET_PARAM(0); const int flag = GET_PARAM(1); cv::Mat a(size, CV_32FC2); cv::Mat b(size, CV_32FC2); declare.in(a, b, WARMUP_RNG); if (PERF_RUN_GPU()) { const cv::gpu::GpuMat d_a(a); const cv::gpu::GpuMat d_b(b); cv::gpu::GpuMat dst; TEST_CYCLE() cv::gpu::mulSpectrums(d_a, d_b, dst, flag); GPU_SANITY_CHECK(dst); } else { cv::Mat dst; TEST_CYCLE() cv::mulSpectrums(a, b, dst, flag); CPU_SANITY_CHECK(dst); } } ////////////////////////////////////////////////////////////////////// // MulAndScaleSpectrums PERF_TEST_P(Sz, MulAndScaleSpectrums, GPU_TYPICAL_MAT_SIZES) { const cv::Size size = GetParam(); const float scale = 1.f / size.area(); cv::Mat src1(size, CV_32FC2); cv::Mat src2(size, CV_32FC2); declare.in(src1,src2, WARMUP_RNG); if (PERF_RUN_GPU()) { const cv::gpu::GpuMat d_src1(src1); const cv::gpu::GpuMat d_src2(src2); cv::gpu::GpuMat dst; TEST_CYCLE() cv::gpu::mulAndScaleSpectrums(d_src1, d_src2, dst, cv::DFT_ROWS, scale, false); GPU_SANITY_CHECK(dst); } else { FAIL_NO_CPU(); } } ////////////////////////////////////////////////////////////////////// // Dft PERF_TEST_P(Sz_Flags, Dft, Combine(GPU_TYPICAL_MAT_SIZES, Values(0, DftFlags(cv::DFT_ROWS), DftFlags(cv::DFT_INVERSE)))) { declare.time(10.0); const cv::Size size = GET_PARAM(0); const int flag = GET_PARAM(1); cv::Mat src(size, CV_32FC2); declare.in(src, WARMUP_RNG); if (PERF_RUN_GPU()) { const cv::gpu::GpuMat d_src(src); cv::gpu::GpuMat dst; TEST_CYCLE() cv::gpu::dft(d_src, dst, size, flag); GPU_SANITY_CHECK(dst, 1e-6, ERROR_RELATIVE); } else { cv::Mat dst; TEST_CYCLE() cv::dft(src, dst, flag); CPU_SANITY_CHECK(dst); } } ////////////////////////////////////////////////////////////////////// // Convolve DEF_PARAM_TEST(Sz_KernelSz_Ccorr, cv::Size, int, bool); PERF_TEST_P(Sz_KernelSz_Ccorr, Convolve, Combine(GPU_TYPICAL_MAT_SIZES, Values(17, 27, 32, 64), Bool())) { declare.time(10.0); const cv::Size size = GET_PARAM(0); const int templ_size = GET_PARAM(1); const bool ccorr = GET_PARAM(2); const cv::Mat image(size, CV_32FC1); const cv::Mat templ(templ_size, templ_size, CV_32FC1); declare.in(image, templ, WARMUP_RNG); if (PERF_RUN_GPU()) { cv::gpu::GpuMat d_image = cv::gpu::createContinuous(size, CV_32FC1); d_image.upload(image); cv::gpu::GpuMat d_templ = cv::gpu::createContinuous(templ_size, templ_size, CV_32FC1); d_templ.upload(templ); cv::Ptr convolution = cv::gpu::createConvolution(); cv::gpu::GpuMat dst; TEST_CYCLE() convolution->convolve(d_image, d_templ, dst, ccorr); GPU_SANITY_CHECK(dst); } else { if (ccorr) FAIL_NO_CPU(); cv::Mat dst; TEST_CYCLE() cv::filter2D(image, dst, image.depth(), templ); CPU_SANITY_CHECK(dst); } } ////////////////////////////////////////////////////////////////////// // Integral PERF_TEST_P(Sz, Integral, GPU_TYPICAL_MAT_SIZES) { const cv::Size size = GetParam(); cv::Mat src(size, CV_8UC1); declare.in(src, WARMUP_RNG); if (PERF_RUN_GPU()) { const cv::gpu::GpuMat d_src(src); cv::gpu::GpuMat dst; cv::gpu::GpuMat d_buf; TEST_CYCLE() cv::gpu::integral(d_src, dst, d_buf); GPU_SANITY_CHECK(dst); } else { cv::Mat dst; TEST_CYCLE() cv::integral(src, dst); CPU_SANITY_CHECK(dst); } } ////////////////////////////////////////////////////////////////////// // IntegralSqr PERF_TEST_P(Sz, IntegralSqr, GPU_TYPICAL_MAT_SIZES) { const cv::Size size = GetParam(); cv::Mat src(size, CV_8UC1); declare.in(src, WARMUP_RNG); if (PERF_RUN_GPU()) { const cv::gpu::GpuMat d_src(src); cv::gpu::GpuMat dst, buf; TEST_CYCLE() cv::gpu::sqrIntegral(d_src, dst, buf); GPU_SANITY_CHECK(dst); } else { FAIL_NO_CPU(); } }