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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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// Fangfang Bai, fangfang@multicorewareinc.com
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// Jin Ma, jin@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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///////////// PyrLKOpticalFlow ////////////////////////
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PERFTEST(PyrLKOpticalFlow)
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{
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std::string images1[] = {"rubberwhale1.png", "basketball1.png"};
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std::string images2[] = {"rubberwhale2.png", "basketball2.png"};
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for (size_t i = 0; i < sizeof(images1) / sizeof(std::string); i++)
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{
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Mat frame0 = imread(abspath(images1[i]), i == 0 ? IMREAD_COLOR : IMREAD_GRAYSCALE);
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if (frame0.empty())
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{
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std::string errstr = "can't open " + images1[i];
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throw runtime_error(errstr);
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}
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Mat frame1 = imread(abspath(images2[i]), i == 0 ? IMREAD_COLOR : IMREAD_GRAYSCALE);
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if (frame1.empty())
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{
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std::string errstr = "can't open " + images2[i];
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throw runtime_error(errstr);
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}
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Mat gray_frame;
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if (i == 0)
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{
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cvtColor(frame0, gray_frame, COLOR_BGR2GRAY);
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}
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for (int points = Min_Size; points <= Max_Size; points *= Multiple)
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{
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if (i == 0)
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SUBTEST << frame0.cols << "x" << frame0.rows << "; color; " << points << " points";
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else
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SUBTEST << frame0.cols << "x" << frame0.rows << "; gray; " << points << " points";
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Mat ocl_nextPts;
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Mat ocl_status;
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vector<Point2f> pts;
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goodFeaturesToTrack(i == 0 ? gray_frame : frame0, pts, points, 0.01, 0.0);
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vector<Point2f> nextPts;
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vector<unsigned char> status;
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vector<float> err;
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calcOpticalFlowPyrLK(frame0, frame1, pts, nextPts, status, err);
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CPU_ON;
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calcOpticalFlowPyrLK(frame0, frame1, pts, nextPts, status, err);
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CPU_OFF;
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ocl::PyrLKOpticalFlow d_pyrLK;
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ocl::oclMat d_frame0(frame0);
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ocl::oclMat d_frame1(frame1);
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ocl::oclMat d_pts;
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Mat pts_mat(1, (int)pts.size(), CV_32FC2, (void *)&pts[0]);
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d_pts.upload(pts_mat);
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ocl::oclMat d_nextPts;
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ocl::oclMat d_status;
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ocl::oclMat d_err;
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WARMUP_ON;
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d_pyrLK.sparse(d_frame0, d_frame1, d_pts, d_nextPts, d_status, &d_err);
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WARMUP_OFF;
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GPU_ON;
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d_pyrLK.sparse(d_frame0, d_frame1, d_pts, d_nextPts, d_status, &d_err);
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GPU_OFF;
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GPU_FULL_ON;
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d_frame0.upload(frame0);
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d_frame1.upload(frame1);
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d_pts.upload(pts_mat);
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d_pyrLK.sparse(d_frame0, d_frame1, d_pts, d_nextPts, d_status, &d_err);
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if (!d_nextPts.empty())
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d_nextPts.download(ocl_nextPts);
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if (!d_status.empty())
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d_status.download(ocl_status);
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GPU_FULL_OFF;
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size_t mismatch = 0;
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for (int i = 0; i < (int)nextPts.size(); ++i)
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{
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if(status[i] != ocl_status.at<unsigned char>(0, i)){
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mismatch++;
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continue;
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}
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if(status[i]){
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Point2f gpu_rst = ocl_nextPts.at<Point2f>(0, i);
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Point2f cpu_rst = nextPts[i];
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if(fabs(gpu_rst.x - cpu_rst.x) >= 1. || fabs(gpu_rst.y - cpu_rst.y) >= 1.)
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mismatch++;
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}
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}
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double ratio = (double)mismatch / (double)nextPts.size();
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if(ratio < .02)
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TestSystem::instance().setAccurate(1, ratio);
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else
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TestSystem::instance().setAccurate(0, ratio);
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}
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}
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}
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PERFTEST(tvl1flow)
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{
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cv::Mat frame0 = imread("rubberwhale1.png", cv::IMREAD_GRAYSCALE);
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assert(!frame0.empty());
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cv::Mat frame1 = imread("rubberwhale2.png", cv::IMREAD_GRAYSCALE);
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assert(!frame1.empty());
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cv::ocl::OpticalFlowDual_TVL1_OCL d_alg;
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cv::ocl::oclMat d_flowx(frame0.size(), CV_32FC1);
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cv::ocl::oclMat d_flowy(frame1.size(), CV_32FC1);
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cv::Ptr<cv::DenseOpticalFlow> alg = cv::createOptFlow_DualTVL1();
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cv::Mat flow;
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SUBTEST << frame0.cols << 'x' << frame0.rows << "; rubberwhale1.png; "<<frame1.cols<<'x'<<frame1.rows<<"; rubberwhale2.png";
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alg->calc(frame0, frame1, flow);
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CPU_ON;
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alg->calc(frame0, frame1, flow);
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CPU_OFF;
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cv::Mat gold[2];
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cv::split(flow, gold);
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cv::ocl::oclMat d0(frame0.size(), CV_32FC1);
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d0.upload(frame0);
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cv::ocl::oclMat d1(frame1.size(), CV_32FC1);
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d1.upload(frame1);
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WARMUP_ON;
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d_alg(d0, d1, d_flowx, d_flowy);
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WARMUP_OFF;
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/*
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double diff1 = 0.0, diff2 = 0.0;
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if(ExceptedMatSimilar(gold[0], cv::Mat(d_flowx), 3e-3, diff1) == 1
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&&ExceptedMatSimilar(gold[1], cv::Mat(d_flowy), 3e-3, diff2) == 1)
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TestSystem::instance().setAccurate(1);
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else
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TestSystem::instance().setAccurate(0);
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TestSystem::instance().setDiff(diff1);
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TestSystem::instance().setDiff(diff2);
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*/
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GPU_ON;
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d_alg(d0, d1, d_flowx, d_flowy);
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d_alg.collectGarbage();
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GPU_OFF;
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cv::Mat flowx, flowy;
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GPU_FULL_ON;
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d0.upload(frame0);
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d1.upload(frame1);
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d_alg(d0, d1, d_flowx, d_flowy);
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d_alg.collectGarbage();
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d_flowx.download(flowx);
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d_flowy.download(flowy);
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GPU_FULL_OFF;
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TestSystem::instance().ExceptedMatSimilar(gold[0], flowx, 3e-3);
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TestSystem::instance().ExceptedMatSimilar(gold[1], flowy, 3e-3);
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}
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///////////// FarnebackOpticalFlow ////////////////////////
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PERFTEST(FarnebackOpticalFlow)
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{
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cv::Mat frame0 = imread("rubberwhale1.png", cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(frame0.empty());
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cv::Mat frame1 = imread("rubberwhale2.png", cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(frame1.empty());
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cv::ocl::oclMat d_frame0(frame0), d_frame1(frame1);
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int polyNs[2] = { 5, 7 };
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double polySigmas[2] = { 1.1, 1.5 };
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int farneFlags[2] = { 0, cv::OPTFLOW_FARNEBACK_GAUSSIAN };
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bool UseInitFlows[2] = { false, true };
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double pyrScale = 0.5;
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string farneFlagStrs[2] = { "BoxFilter", "GaussianBlur" };
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string useInitFlowStrs[2] = { "", "UseInitFlow" };
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for ( int i = 0; i < 2; ++i)
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{
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int polyN = polyNs[i];
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double polySigma = polySigmas[i];
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for ( int j = 0; j < 2; ++j)
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{
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int flags = farneFlags[j];
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for ( int k = 0; k < 2; ++k)
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{
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bool useInitFlow = UseInitFlows[k];
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SUBTEST << "polyN(" << polyN << "); " << farneFlagStrs[j] << "; " << useInitFlowStrs[k];
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cv::ocl::FarnebackOpticalFlow farn;
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farn.pyrScale = pyrScale;
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farn.polyN = polyN;
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farn.polySigma = polySigma;
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farn.flags = flags;
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cv::ocl::oclMat d_flowx, d_flowy;
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cv::Mat flow, flowBuf, flowxBuf, flowyBuf;
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WARMUP_ON;
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farn(d_frame0, d_frame1, d_flowx, d_flowy);
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if (useInitFlow)
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{
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cv::Mat flowxy[] = {cv::Mat(d_flowx), cv::Mat(d_flowy)};
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cv::merge(flowxy, 2, flow);
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flow.copyTo(flowBuf);
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flowxy[0].copyTo(flowxBuf);
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flowxy[1].copyTo(flowyBuf);
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farn.flags |= cv::OPTFLOW_USE_INITIAL_FLOW;
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farn(d_frame0, d_frame1, d_flowx, d_flowy);
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}
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WARMUP_OFF;
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cv::calcOpticalFlowFarneback(
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frame0, frame1, flow, farn.pyrScale, farn.numLevels, farn.winSize,
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farn.numIters, farn.polyN, farn.polySigma, farn.flags);
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std::vector<cv::Mat> flowxy;
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cv::split(flow, flowxy);
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double diff0 = 0.0;
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TestSystem::instance().setAccurate(ExceptedMatSimilar(flowxy[0], cv::Mat(d_flowx), 0.1, diff0));
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TestSystem::instance().setDiff(diff0);
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double diff1 = 0.0;
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TestSystem::instance().setAccurate(ExceptedMatSimilar(flowxy[1], cv::Mat(d_flowy), 0.1, diff1));
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TestSystem::instance().setDiff(diff1);
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if (useInitFlow)
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{
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cv::Mat flowx, flowy;
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farn.flags = (flags | cv::OPTFLOW_USE_INITIAL_FLOW);
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CPU_ON;
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cv::calcOpticalFlowFarneback(
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frame0, frame1, flowBuf, farn.pyrScale, farn.numLevels, farn.winSize,
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farn.numIters, farn.polyN, farn.polySigma, farn.flags);
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CPU_OFF;
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GPU_ON;
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farn(d_frame0, d_frame1, d_flowx, d_flowy);
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GPU_OFF;
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GPU_FULL_ON;
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d_frame0.upload(frame0);
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d_frame1.upload(frame1);
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d_flowx.upload(flowxBuf);
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d_flowy.upload(flowyBuf);
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farn(d_frame0, d_frame1, d_flowx, d_flowy);
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d_flowx.download(flowx);
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d_flowy.download(flowy);
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GPU_FULL_OFF;
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}
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else
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{
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cv::Mat flow, flowx, flowy;
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cv::ocl::oclMat d_flowx, d_flowy;
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farn.flags = flags;
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CPU_ON;
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cv::calcOpticalFlowFarneback(
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frame0, frame1, flow, farn.pyrScale, farn.numLevels, farn.winSize,
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farn.numIters, farn.polyN, farn.polySigma, farn.flags);
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CPU_OFF;
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GPU_ON;
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farn(d_frame0, d_frame1, d_flowx, d_flowy);
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GPU_OFF;
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GPU_FULL_ON;
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d_frame0.upload(frame0);
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d_frame1.upload(frame1);
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farn(d_frame0, d_frame1, d_flowx, d_flowy);
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d_flowx.download(flowx);
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d_flowy.download(flowy);
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GPU_FULL_OFF;
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}
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}
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}
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}
|
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|
|
}
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|
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|