5df77a841e
remove as much warnings as possible use enum instead of MACRO for ocl.hpp add command line parser in accuracy test and perf test some bug fix for arthim functions
175 lines
6.8 KiB
C++
175 lines
6.8 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) 2010-2012, Multicoreware, Inc., all rights reserved.
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// Copyright (C) 2010-2012, Advanced Micro Devices, 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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// @Authors
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// Peng Xiao, pengxiao@multicorewareinc.com
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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 oclMaterials 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 "precomp.hpp"
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//#define PERF_TEST 0
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#ifdef HAVE_OPENCL
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////////////////////////////////////////////////////////////////////////////////
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// MatchTemplate
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#define ALL_TEMPLATE_METHODS testing::Values(TemplateMethod(cv::TM_SQDIFF), TemplateMethod(cv::TM_CCORR), TemplateMethod(cv::TM_CCOEFF), TemplateMethod(cv::TM_SQDIFF_NORMED), TemplateMethod(cv::TM_CCORR_NORMED), TemplateMethod(cv::TM_CCOEFF_NORMED))
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IMPLEMENT_PARAM_CLASS(TemplateSize, cv::Size);
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const char *TEMPLATE_METHOD_NAMES[6] = {"TM_SQDIFF", "TM_SQDIFF_NORMED", "TM_CCORR", "TM_CCORR_NORMED", "TM_CCOEFF", "TM_CCOEFF_NORMED"};
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#define MTEMP_SIZES testing::Values(cv::Size(128, 256), cv::Size(1024, 768))
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PARAM_TEST_CASE(MatchTemplate8U, cv::Size, TemplateSize, Channels, TemplateMethod)
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{
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cv::Size size;
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cv::Size templ_size;
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int cn;
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int method;
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//std::vector<cv::ocl::Info> oclinfo;
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virtual void SetUp()
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{
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size = GET_PARAM(0);
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templ_size = GET_PARAM(1);
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cn = GET_PARAM(2);
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method = GET_PARAM(3);
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//int devnums = getDevice(oclinfo, OPENCV_DEFAULT_OPENCL_DEVICE);
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//CV_Assert(devnums > 0);
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}
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};
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TEST_P(MatchTemplate8U, Accuracy)
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{
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std::cout << "Method: " << TEMPLATE_METHOD_NAMES[method] << std::endl;
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std::cout << "Image Size: (" << size.width << ", " << size.height << ")" << std::endl;
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std::cout << "Template Size: (" << templ_size.width << ", " << templ_size.height << ")" << std::endl;
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std::cout << "Channels: " << cn << std::endl;
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cv::Mat image = randomMat(size, CV_MAKETYPE(CV_8U, cn));
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cv::Mat templ = randomMat(templ_size, CV_MAKETYPE(CV_8U, cn));
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cv::ocl::oclMat dst, ocl_image(image), ocl_templ(templ);
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cv::ocl::matchTemplate(ocl_image, ocl_templ, dst, method);
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cv::Mat dst_gold;
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cv::matchTemplate(image, templ, dst_gold, method);
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char sss [100] = "";
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cv::Mat mat_dst;
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dst.download(mat_dst);
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EXPECT_MAT_NEAR(dst_gold, mat_dst, templ_size.area() * 1e-1, sss);
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#if PERF_TEST
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{
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P_TEST_FULL( {}, {cv::ocl::matchTemplate(ocl_image, ocl_templ, dst, method);}, {});
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P_TEST_FULL( {}, {cv::matchTemplate(image, templ, dst_gold, method);}, {});
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}
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#endif // PERF_TEST
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}
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PARAM_TEST_CASE(MatchTemplate32F, cv::Size, TemplateSize, Channels, TemplateMethod)
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{
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cv::Size size;
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cv::Size templ_size;
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int cn;
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int method;
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//std::vector<cv::ocl::Info> oclinfo;
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virtual void SetUp()
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{
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size = GET_PARAM(0);
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templ_size = GET_PARAM(1);
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cn = GET_PARAM(2);
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method = GET_PARAM(3);
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//int devnums = getDevice(oclinfo, OPENCV_DEFAULT_OPENCL_DEVICE);
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//CV_Assert(devnums > 0);
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}
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};
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TEST_P(MatchTemplate32F, Accuracy)
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{
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cv::Mat image = randomMat(size, CV_MAKETYPE(CV_32F, cn));
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cv::Mat templ = randomMat(templ_size, CV_MAKETYPE(CV_32F, cn));
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cv::ocl::oclMat dst, ocl_image(image), ocl_templ(templ);
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cv::ocl::matchTemplate(ocl_image, ocl_templ, dst, method);
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cv::Mat dst_gold;
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cv::matchTemplate(image, templ, dst_gold, method);
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char sss [100] = "";
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cv::Mat mat_dst;
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dst.download(mat_dst);
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EXPECT_MAT_NEAR(dst_gold, mat_dst, templ_size.area() * 1e-1, sss);
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#if PERF_TEST
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{
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std::cout << "Method: " << TEMPLATE_METHOD_NAMES[method] << std::endl;
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std::cout << "Image Size: (" << size.width << ", " << size.height << ")" << std::endl;
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std::cout << "Template Size: (" << templ_size.width << ", " << templ_size.height << ")" << std::endl;
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std::cout << "Channels: " << cn << std::endl;
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P_TEST_FULL( {}, {cv::ocl::matchTemplate(ocl_image, ocl_templ, dst, method);}, {});
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P_TEST_FULL( {}, {cv::matchTemplate(image, templ, dst_gold, method);}, {});
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}
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#endif // PERF_TEST
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}
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INSTANTIATE_TEST_CASE_P(GPU_ImgProc, MatchTemplate8U,
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testing::Combine(
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MTEMP_SIZES,
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testing::Values(TemplateSize(cv::Size(5, 5)), TemplateSize(cv::Size(16, 16))/*, TemplateSize(cv::Size(30, 30))*/),
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testing::Values(Channels(1), Channels(3), Channels(4)),
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ALL_TEMPLATE_METHODS
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)
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);
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INSTANTIATE_TEST_CASE_P(GPU_ImgProc, MatchTemplate32F, testing::Combine(
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MTEMP_SIZES,
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testing::Values(TemplateSize(cv::Size(5, 5)), TemplateSize(cv::Size(16, 16))/*, TemplateSize(cv::Size(30, 30))*/),
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testing::Values(Channels(1), Channels(3), Channels(4)),
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testing::Values(TemplateMethod(cv::TM_SQDIFF), TemplateMethod(cv::TM_CCORR))));
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#endif
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