/*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; ////////////////////////////////////////////////////////////////////// // Remap enum { HALF_SIZE=0, UPSIDE_DOWN, REFLECTION_X, REFLECTION_BOTH }; CV_ENUM(RemapMode, HALF_SIZE, UPSIDE_DOWN, REFLECTION_X, REFLECTION_BOTH) void generateMap(cv::Mat& map_x, cv::Mat& map_y, int remapMode) { for (int j = 0; j < map_x.rows; ++j) { for (int i = 0; i < map_x.cols; ++i) { switch (remapMode) { case HALF_SIZE: if (i > map_x.cols*0.25 && i < map_x.cols*0.75 && j > map_x.rows*0.25 && j < map_x.rows*0.75) { map_x.at(j,i) = 2.f * (i - map_x.cols * 0.25f) + 0.5f; map_y.at(j,i) = 2.f * (j - map_x.rows * 0.25f) + 0.5f; } else { map_x.at(j,i) = 0.f; map_y.at(j,i) = 0.f; } break; case UPSIDE_DOWN: map_x.at(j,i) = static_cast(i); map_y.at(j,i) = static_cast(map_x.rows - j); break; case REFLECTION_X: map_x.at(j,i) = static_cast(map_x.cols - i); map_y.at(j,i) = static_cast(j); break; case REFLECTION_BOTH: map_x.at(j,i) = static_cast(map_x.cols - i); map_y.at(j,i) = static_cast(map_x.rows - j); break; } // end of switch } } } DEF_PARAM_TEST(Sz_Depth_Cn_Inter_Border_Mode, cv::Size, MatDepth, MatCn, Interpolation, BorderMode, RemapMode); PERF_TEST_P(Sz_Depth_Cn_Inter_Border_Mode, Remap, Combine(CUDA_TYPICAL_MAT_SIZES, Values(CV_8U, CV_16U, CV_32F), CUDA_CHANNELS_1_3_4, Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC)), ALL_BORDER_MODES, RemapMode::all())) { declare.time(20.0); const cv::Size size = GET_PARAM(0); const int depth = GET_PARAM(1); const int channels = GET_PARAM(2); const int interpolation = GET_PARAM(3); const int borderMode = GET_PARAM(4); const int remapMode = GET_PARAM(5); const int type = CV_MAKE_TYPE(depth, channels); cv::Mat src(size, type); declare.in(src, WARMUP_RNG); cv::Mat xmap(size, CV_32FC1); cv::Mat ymap(size, CV_32FC1); generateMap(xmap, ymap, remapMode); if (PERF_RUN_CUDA()) { const cv::cuda::GpuMat d_src(src); const cv::cuda::GpuMat d_xmap(xmap); const cv::cuda::GpuMat d_ymap(ymap); cv::cuda::GpuMat dst; TEST_CYCLE() cv::cuda::remap(d_src, dst, d_xmap, d_ymap, interpolation, borderMode); CUDA_SANITY_CHECK(dst); } else { cv::Mat dst; TEST_CYCLE() cv::remap(src, dst, xmap, ymap, interpolation, borderMode); CPU_SANITY_CHECK(dst); } } ////////////////////////////////////////////////////////////////////// // Resize DEF_PARAM_TEST(Sz_Depth_Cn_Inter_Scale, cv::Size, MatDepth, MatCn, Interpolation, double); PERF_TEST_P(Sz_Depth_Cn_Inter_Scale, Resize, Combine(CUDA_TYPICAL_MAT_SIZES, Values(CV_8U, CV_16U, CV_32F), CUDA_CHANNELS_1_3_4, Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC)), Values(0.5, 0.3, 2.0))) { declare.time(20.0); const cv::Size size = GET_PARAM(0); const int depth = GET_PARAM(1); const int channels = GET_PARAM(2); const int interpolation = GET_PARAM(3); const double f = GET_PARAM(4); const int type = CV_MAKE_TYPE(depth, channels); cv::Mat src(size, type); declare.in(src, WARMUP_RNG); if (PERF_RUN_CUDA()) { const cv::cuda::GpuMat d_src(src); cv::cuda::GpuMat dst; TEST_CYCLE() cv::cuda::resize(d_src, dst, cv::Size(), f, f, interpolation); CUDA_SANITY_CHECK(dst, 1e-3, ERROR_RELATIVE); } else { cv::Mat dst; TEST_CYCLE() cv::resize(src, dst, cv::Size(), f, f, interpolation); CPU_SANITY_CHECK(dst); } } ////////////////////////////////////////////////////////////////////// // ResizeArea DEF_PARAM_TEST(Sz_Depth_Cn_Scale, cv::Size, MatDepth, MatCn, double); PERF_TEST_P(Sz_Depth_Cn_Scale, ResizeArea, Combine(CUDA_TYPICAL_MAT_SIZES, Values(CV_8U, CV_16U, CV_32F), CUDA_CHANNELS_1_3_4, Values(0.2, 0.1, 0.05))) { declare.time(1.0); const cv::Size size = GET_PARAM(0); const int depth = GET_PARAM(1); const int channels = GET_PARAM(2); const int interpolation = cv::INTER_AREA; const double f = GET_PARAM(3); const int type = CV_MAKE_TYPE(depth, channels); cv::Mat src(size, type); declare.in(src, WARMUP_RNG); if (PERF_RUN_CUDA()) { const cv::cuda::GpuMat d_src(src); cv::cuda::GpuMat dst; TEST_CYCLE() cv::cuda::resize(d_src, dst, cv::Size(), f, f, interpolation); CUDA_SANITY_CHECK(dst); } else { cv::Mat dst; TEST_CYCLE() cv::resize(src, dst, cv::Size(), f, f, interpolation); CPU_SANITY_CHECK(dst); } } ////////////////////////////////////////////////////////////////////// // WarpAffine DEF_PARAM_TEST(Sz_Depth_Cn_Inter_Border, cv::Size, MatDepth, MatCn, Interpolation, BorderMode); PERF_TEST_P(Sz_Depth_Cn_Inter_Border, WarpAffine, Combine(CUDA_TYPICAL_MAT_SIZES, Values(CV_8U, CV_16U, CV_32F), CUDA_CHANNELS_1_3_4, Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC)), ALL_BORDER_MODES)) { declare.time(20.0); const cv::Size size = GET_PARAM(0); const int depth = GET_PARAM(1); const int channels = GET_PARAM(2); const int interpolation = GET_PARAM(3); const int borderMode = GET_PARAM(4); const int type = CV_MAKE_TYPE(depth, channels); cv::Mat src(size, type); declare.in(src, WARMUP_RNG); const double aplha = CV_PI / 4; const double mat[2 * 3] = { std::cos(aplha), -std::sin(aplha), src.cols / 2, std::sin(aplha), std::cos(aplha), 0 }; const cv::Mat M(2, 3, CV_64F, (void*) mat); if (PERF_RUN_CUDA()) { const cv::cuda::GpuMat d_src(src); cv::cuda::GpuMat dst; TEST_CYCLE() cv::cuda::warpAffine(d_src, dst, M, size, interpolation, borderMode); CUDA_SANITY_CHECK(dst, 1); } else { cv::Mat dst; TEST_CYCLE() cv::warpAffine(src, dst, M, size, interpolation, borderMode); CPU_SANITY_CHECK(dst); } } ////////////////////////////////////////////////////////////////////// // WarpPerspective PERF_TEST_P(Sz_Depth_Cn_Inter_Border, WarpPerspective, Combine(CUDA_TYPICAL_MAT_SIZES, Values(CV_8U, CV_16U, CV_32F), CUDA_CHANNELS_1_3_4, Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC)), ALL_BORDER_MODES)) { declare.time(20.0); const cv::Size size = GET_PARAM(0); const int depth = GET_PARAM(1); const int channels = GET_PARAM(2); const int interpolation = GET_PARAM(3); const int borderMode = GET_PARAM(4); const int type = CV_MAKE_TYPE(depth, channels); cv::Mat src(size, type); declare.in(src, WARMUP_RNG); const double aplha = CV_PI / 4; double mat[3][3] = { {std::cos(aplha), -std::sin(aplha), src.cols / 2}, {std::sin(aplha), std::cos(aplha), 0}, {0.0, 0.0, 1.0}}; const cv::Mat M(3, 3, CV_64F, (void*) mat); if (PERF_RUN_CUDA()) { const cv::cuda::GpuMat d_src(src); cv::cuda::GpuMat dst; TEST_CYCLE() cv::cuda::warpPerspective(d_src, dst, M, size, interpolation, borderMode); CUDA_SANITY_CHECK(dst, 1); } else { cv::Mat dst; TEST_CYCLE() cv::warpPerspective(src, dst, M, size, interpolation, borderMode); CPU_SANITY_CHECK(dst); } } ////////////////////////////////////////////////////////////////////// // BuildWarpPlaneMaps PERF_TEST_P(Sz, BuildWarpPlaneMaps, CUDA_TYPICAL_MAT_SIZES) { const cv::Size size = GetParam(); const cv::Mat K = cv::Mat::eye(3, 3, CV_32FC1); const cv::Mat R = cv::Mat::ones(3, 3, CV_32FC1); const cv::Mat T = cv::Mat::zeros(1, 3, CV_32F); if (PERF_RUN_CUDA()) { cv::cuda::GpuMat map_x; cv::cuda::GpuMat map_y; TEST_CYCLE() cv::cuda::buildWarpPlaneMaps(size, cv::Rect(0, 0, size.width, size.height), K, R, T, 1.0, map_x, map_y); CUDA_SANITY_CHECK(map_x); CUDA_SANITY_CHECK(map_y); } else { FAIL_NO_CPU(); } } ////////////////////////////////////////////////////////////////////// // BuildWarpCylindricalMaps PERF_TEST_P(Sz, BuildWarpCylindricalMaps, CUDA_TYPICAL_MAT_SIZES) { const cv::Size size = GetParam(); const cv::Mat K = cv::Mat::eye(3, 3, CV_32FC1); const cv::Mat R = cv::Mat::ones(3, 3, CV_32FC1); if (PERF_RUN_CUDA()) { cv::cuda::GpuMat map_x; cv::cuda::GpuMat map_y; TEST_CYCLE() cv::cuda::buildWarpCylindricalMaps(size, cv::Rect(0, 0, size.width, size.height), K, R, 1.0, map_x, map_y); CUDA_SANITY_CHECK(map_x); CUDA_SANITY_CHECK(map_y); } else { FAIL_NO_CPU(); } } ////////////////////////////////////////////////////////////////////// // BuildWarpSphericalMaps PERF_TEST_P(Sz, BuildWarpSphericalMaps, CUDA_TYPICAL_MAT_SIZES) { const cv::Size size = GetParam(); const cv::Mat K = cv::Mat::eye(3, 3, CV_32FC1); const cv::Mat R = cv::Mat::ones(3, 3, CV_32FC1); if (PERF_RUN_CUDA()) { cv::cuda::GpuMat map_x; cv::cuda::GpuMat map_y; TEST_CYCLE() cv::cuda::buildWarpSphericalMaps(size, cv::Rect(0, 0, size.width, size.height), K, R, 1.0, map_x, map_y); CUDA_SANITY_CHECK(map_x); CUDA_SANITY_CHECK(map_y); } else { FAIL_NO_CPU(); } } ////////////////////////////////////////////////////////////////////// // Rotate DEF_PARAM_TEST(Sz_Depth_Cn_Inter, cv::Size, MatDepth, MatCn, Interpolation); PERF_TEST_P(Sz_Depth_Cn_Inter, Rotate, Combine(CUDA_TYPICAL_MAT_SIZES, Values(CV_8U, CV_16U, CV_32F), CUDA_CHANNELS_1_3_4, Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC)))) { const cv::Size size = GET_PARAM(0); const int depth = GET_PARAM(1); const int channels = GET_PARAM(2); const int interpolation = GET_PARAM(3); const int type = CV_MAKE_TYPE(depth, channels); cv::Mat src(size, type); declare.in(src, WARMUP_RNG); if (PERF_RUN_CUDA()) { const cv::cuda::GpuMat d_src(src); cv::cuda::GpuMat dst; TEST_CYCLE() cv::cuda::rotate(d_src, dst, size, 30.0, 0, 0, interpolation); CUDA_SANITY_CHECK(dst, 1e-3, ERROR_RELATIVE); } else { FAIL_NO_CPU(); } } ////////////////////////////////////////////////////////////////////// // PyrDown PERF_TEST_P(Sz_Depth_Cn, PyrDown, Combine(CUDA_TYPICAL_MAT_SIZES, Values(CV_8U, CV_16U, CV_32F), CUDA_CHANNELS_1_3_4)) { const cv::Size size = GET_PARAM(0); const int depth = GET_PARAM(1); const int channels = GET_PARAM(2); const int type = CV_MAKE_TYPE(depth, channels); cv::Mat src(size, type); declare.in(src, WARMUP_RNG); if (PERF_RUN_CUDA()) { const cv::cuda::GpuMat d_src(src); cv::cuda::GpuMat dst; TEST_CYCLE() cv::cuda::pyrDown(d_src, dst); CUDA_SANITY_CHECK(dst); } else { cv::Mat dst; TEST_CYCLE() cv::pyrDown(src, dst); CPU_SANITY_CHECK(dst); } } ////////////////////////////////////////////////////////////////////// // PyrUp PERF_TEST_P(Sz_Depth_Cn, PyrUp, Combine(CUDA_TYPICAL_MAT_SIZES, Values(CV_8U, CV_16U, CV_32F), CUDA_CHANNELS_1_3_4)) { const cv::Size size = GET_PARAM(0); const int depth = GET_PARAM(1); const int channels = GET_PARAM(2); const int type = CV_MAKE_TYPE(depth, channels); cv::Mat src(size, type); declare.in(src, WARMUP_RNG); if (PERF_RUN_CUDA()) { const cv::cuda::GpuMat d_src(src); cv::cuda::GpuMat dst; TEST_CYCLE() cv::cuda::pyrUp(d_src, dst); CUDA_SANITY_CHECK(dst); } else { cv::Mat dst; TEST_CYCLE() cv::pyrUp(src, dst); CPU_SANITY_CHECK(dst); } } ////////////////////////////////////////////////////////////////////// // ImagePyramidGetLayer PERF_TEST_P(Sz_Depth_Cn, ImagePyramidGetLayer, Combine(CUDA_TYPICAL_MAT_SIZES, Values(CV_8U, CV_16U, CV_32F), CUDA_CHANNELS_1_3_4)) { const cv::Size size = GET_PARAM(0); const int depth = GET_PARAM(1); const int channels = GET_PARAM(2); const int type = CV_MAKE_TYPE(depth, channels); cv::Mat src(size, type); declare.in(src, WARMUP_RNG); const int nLayers = 3; const cv::Size dstSize(size.width / 2 + 10, size.height / 2 + 10); if (PERF_RUN_CUDA()) { const cv::cuda::GpuMat d_src(src); cv::cuda::GpuMat dst; cv::Ptr d_pyr = cv::cuda::createImagePyramid(d_src, nLayers); TEST_CYCLE() d_pyr->getLayer(dst, dstSize); CUDA_SANITY_CHECK(dst); } else { FAIL_NO_CPU(); } }