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
153 lines
4.9 KiB
C++
153 lines
4.9 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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// Fangfang Bai, fangfang@multicorewareinc.com
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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 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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#include <iomanip>
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#ifdef HAVE_OPENCL
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using namespace cv;
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using namespace cv::ocl;
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using namespace cvtest;
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using namespace testing;
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using namespace std;
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#ifndef MWC_TEST_UTILITY
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#define MWC_TEST_UTILITY
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// Param class
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#ifndef IMPLEMENT_PARAM_CLASS
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#define IMPLEMENT_PARAM_CLASS(name, type) \
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class name \
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{ \
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public: \
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name ( type arg = type ()) : val_(arg) {} \
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operator type () const {return val_;} \
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private: \
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type val_; \
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}; \
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inline void PrintTo( name param, std::ostream* os) \
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{ \
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*os << #name << "(" << testing::PrintToString(static_cast< type >(param)) << ")"; \
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}
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IMPLEMENT_PARAM_CLASS(Channels, int)
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#endif // IMPLEMENT_PARAM_CLASS
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#endif // MWC_TEST_UTILITY
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////////////////////////////////////////////////////////
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// Canny1
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extern std::string workdir;
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IMPLEMENT_PARAM_CLASS(AppertureSize, int);
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IMPLEMENT_PARAM_CLASS(L2gradient, bool);
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PARAM_TEST_CASE(Canny1, AppertureSize, L2gradient)
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{
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int apperture_size;
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bool useL2gradient;
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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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apperture_size = GET_PARAM(0);
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useL2gradient = GET_PARAM(1);
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//int devnums = getDevice(oclinfo);
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//CV_Assert(devnums > 0);
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}
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};
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TEST_P(Canny1, Performance)
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{
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cv::Mat img = readImage(workdir + "fruits.jpg", cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(img.empty());
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double low_thresh = 100.0;
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double high_thresh = 150.0;
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cv::Mat edges_gold;
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cv::ocl::oclMat edges;
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double totalgputick = 0;
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double totalgputick_kernel = 0;
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double t1 = 0;
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double t2 = 0;
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for(int j = 0; j < LOOP_TIMES + 1; j ++)
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{
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t1 = (double)cvGetTickCount();//gpu start1
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cv::ocl::oclMat ocl_img = cv::ocl::oclMat(img);//upload
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t2 = (double)cvGetTickCount(); //kernel
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cv::ocl::Canny(ocl_img, edges, low_thresh, high_thresh, apperture_size, useL2gradient);
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t2 = (double)cvGetTickCount() - t2;//kernel
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cv::Mat cpu_dst;
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edges.download (cpu_dst);//download
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t1 = (double)cvGetTickCount() - t1;//gpu end1
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if(j == 0)
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continue;
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totalgputick = t1 + totalgputick;
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totalgputick_kernel = t2 + totalgputick_kernel;
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}
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cout << "average gpu runtime is " << totalgputick / ((double)cvGetTickFrequency()* LOOP_TIMES * 1000.) << "ms" << endl;
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cout << "average gpu runtime without data transfer is " << totalgputick_kernel / ((double)cvGetTickFrequency()* LOOP_TIMES * 1000.) << "ms" << endl;
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}
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INSTANTIATE_TEST_CASE_P(GPU_ImgProc, Canny1, testing::Combine(
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testing::Values(AppertureSize(3), AppertureSize(5)),
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testing::Values(L2gradient(false), L2gradient(true))));
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#endif //Have opencl
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