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Merge pull request #1121 from pengx17:2.4_gftt_perf_test
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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) 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@outlook.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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// 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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///////////// GoodFeaturesToTrack ////////////////////////
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PERFTEST(GoodFeaturesToTrack) |
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{ |
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using namespace cv; |
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int maxCorners = 2000; |
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double qualityLevel = 0.01; |
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std::string images[] = { "rubberwhale1.png", "aloeL.jpg" }; |
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std::vector<cv::Point2f> pts_gold, pts_ocl; |
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for(size_t imgIdx = 0; imgIdx < (sizeof(images)/sizeof(std::string)); ++imgIdx) |
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{ |
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Mat frame = imread(abspath(images[imgIdx]), IMREAD_GRAYSCALE); |
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CV_Assert(!frame.empty()); |
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for(float minDistance = 0; minDistance < 4; minDistance += 3.0) |
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{ |
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SUBTEST << "image = " << images[imgIdx] << "; "; |
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SUBTEST << "minDistance = " << minDistance << "; "; |
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cv::goodFeaturesToTrack(frame, pts_gold, maxCorners, qualityLevel, minDistance); |
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CPU_ON; |
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cv::goodFeaturesToTrack(frame, pts_gold, maxCorners, qualityLevel, minDistance); |
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CPU_OFF; |
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cv::ocl::GoodFeaturesToTrackDetector_OCL detector(maxCorners, qualityLevel, minDistance); |
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ocl::oclMat frame_ocl(frame), pts_oclmat; |
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WARMUP_ON; |
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detector(frame_ocl, pts_oclmat); |
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WARMUP_OFF; |
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detector.downloadPoints(pts_oclmat, pts_ocl); |
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double diff = abs(static_cast<float>(pts_gold.size() - pts_ocl.size())); |
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TestSystem::instance().setAccurate(diff == 0.0, diff); |
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GPU_ON; |
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detector(frame_ocl, pts_oclmat); |
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GPU_OFF; |
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GPU_FULL_ON; |
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frame_ocl.upload(frame); |
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detector(frame_ocl, pts_oclmat); |
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detector.downloadPoints(pts_oclmat, pts_ocl); |
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GPU_FULL_OFF; |
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} |
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} |
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} |
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