437 lines
13 KiB
C++
437 lines
13 KiB
C++
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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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namespace opencv_test { namespace {
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//////////////////////////////////////////////////////////////////////
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// Remap
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enum { HALF_SIZE=0, UPSIDE_DOWN, REFLECTION_X, REFLECTION_BOTH };
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CV_ENUM(RemapMode, HALF_SIZE, UPSIDE_DOWN, REFLECTION_X, REFLECTION_BOTH)
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void generateMap(cv::Mat& map_x, cv::Mat& map_y, int remapMode)
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{
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for (int j = 0; j < map_x.rows; ++j)
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{
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for (int i = 0; i < map_x.cols; ++i)
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{
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switch (remapMode)
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{
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case HALF_SIZE:
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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)
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{
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map_x.at<float>(j,i) = 2.f * (i - map_x.cols * 0.25f) + 0.5f;
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map_y.at<float>(j,i) = 2.f * (j - map_x.rows * 0.25f) + 0.5f;
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}
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else
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{
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map_x.at<float>(j,i) = 0.f;
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map_y.at<float>(j,i) = 0.f;
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}
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break;
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case UPSIDE_DOWN:
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map_x.at<float>(j,i) = static_cast<float>(i);
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map_y.at<float>(j,i) = static_cast<float>(map_x.rows - j);
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break;
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case REFLECTION_X:
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map_x.at<float>(j,i) = static_cast<float>(map_x.cols - i);
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map_y.at<float>(j,i) = static_cast<float>(j);
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break;
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case REFLECTION_BOTH:
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map_x.at<float>(j,i) = static_cast<float>(map_x.cols - i);
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map_y.at<float>(j,i) = static_cast<float>(map_x.rows - j);
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break;
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} // end of switch
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}
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}
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}
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DEF_PARAM_TEST(Sz_Depth_Cn_Inter_Border_Mode, cv::Size, MatDepth, MatCn, Interpolation, BorderMode, RemapMode);
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PERF_TEST_P(Sz_Depth_Cn_Inter_Border_Mode, Remap,
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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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Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC)),
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ALL_BORDER_MODES,
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RemapMode::all()))
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{
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declare.time(20.0);
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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 interpolation = GET_PARAM(3);
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const int borderMode = GET_PARAM(4);
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const int remapMode = GET_PARAM(5);
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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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cv::Mat xmap(size, CV_32FC1);
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cv::Mat ymap(size, CV_32FC1);
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generateMap(xmap, ymap, remapMode);
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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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const cv::cuda::GpuMat d_xmap(xmap);
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const cv::cuda::GpuMat d_ymap(ymap);
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cv::cuda::GpuMat dst;
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TEST_CYCLE() cv::cuda::remap(d_src, dst, d_xmap, d_ymap, interpolation, 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::remap(src, dst, xmap, ymap, interpolation, 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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// Resize
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DEF_PARAM_TEST(Sz_Depth_Cn_Inter_Scale, cv::Size, MatDepth, MatCn, Interpolation, double);
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PERF_TEST_P(Sz_Depth_Cn_Inter_Scale, Resize,
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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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Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC)),
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Values(0.5, 0.3, 2.0)))
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{
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declare.time(20.0);
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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 interpolation = GET_PARAM(3);
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const double f = 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::resize(d_src, dst, cv::Size(), f, f, interpolation);
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CUDA_SANITY_CHECK(dst, 1e-3, ERROR_RELATIVE);
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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::resize(src, dst, cv::Size(), f, f, interpolation);
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CPU_SANITY_CHECK(dst);
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}
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}
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//////////////////////////////////////////////////////////////////////
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// ResizeArea
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DEF_PARAM_TEST(Sz_Depth_Cn_Scale, cv::Size, MatDepth, MatCn, double);
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PERF_TEST_P(Sz_Depth_Cn_Scale, ResizeArea,
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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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Values(0.2, 0.1, 0.05)))
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{
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declare.time(1.0);
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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 interpolation = cv::INTER_AREA;
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const double f = 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::resize(d_src, dst, cv::Size(), f, f, interpolation);
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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::resize(src, dst, cv::Size(), f, f, interpolation);
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CPU_SANITY_CHECK(dst);
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}
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}
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//////////////////////////////////////////////////////////////////////
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// WarpAffine
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DEF_PARAM_TEST(Sz_Depth_Cn_Inter_Border, cv::Size, MatDepth, MatCn, Interpolation, BorderMode);
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PERF_TEST_P(Sz_Depth_Cn_Inter_Border, WarpAffine,
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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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Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC)),
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ALL_BORDER_MODES))
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{
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declare.time(20.0);
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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 interpolation = GET_PARAM(3);
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const int borderMode = 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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const double aplha = CV_PI / 4;
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const double mat[2 * 3] =
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{
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std::cos(aplha), -std::sin(aplha), static_cast<double>(src.cols) / 2.0,
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std::sin(aplha), std::cos(aplha), 0
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};
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const cv::Mat M(2, 3, CV_64F, (void*) mat);
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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::warpAffine(d_src, dst, M, size, interpolation, borderMode);
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CUDA_SANITY_CHECK(dst, 1);
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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::warpAffine(src, dst, M, size, interpolation, 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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// WarpPerspective
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PERF_TEST_P(Sz_Depth_Cn_Inter_Border, WarpPerspective,
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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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Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC)),
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ALL_BORDER_MODES))
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{
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declare.time(20.0);
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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 interpolation = GET_PARAM(3);
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const int borderMode = 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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const double aplha = CV_PI / 4;
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double mat[3][3] = { {std::cos(aplha), -std::sin(aplha), static_cast<double>(src.cols) / 2.0},
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{std::sin(aplha), std::cos(aplha), 0},
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{0.0, 0.0, 1.0}};
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const cv::Mat M(3, 3, CV_64F, (void*) mat);
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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::warpPerspective(d_src, dst, M, size, interpolation, borderMode);
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CUDA_SANITY_CHECK(dst, 1);
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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::warpPerspective(src, dst, M, size, interpolation, 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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// Rotate
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DEF_PARAM_TEST(Sz_Depth_Cn_Inter, cv::Size, MatDepth, MatCn, Interpolation);
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PERF_TEST_P(Sz_Depth_Cn_Inter, Rotate,
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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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Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC))))
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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 interpolation = 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::rotate(d_src, dst, size, 30.0, 0, 0, interpolation);
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CUDA_SANITY_CHECK(dst, 1e-3, ERROR_RELATIVE);
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}
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||
|
|
else
|
||
|
|
{
|
||
|
|
FAIL_NO_CPU();
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
//////////////////////////////////////////////////////////////////////
|
||
|
|
// PyrDown
|
||
|
|
|
||
|
|
DEF_PARAM_TEST(Sz_Depth_Cn, cv::Size, MatDepth, MatCn);
|
||
|
|
|
||
|
|
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);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
}} // namespace
|