mirror of
https://github.com/opencv/opencv.git
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1ad4592bfc
Conflicts: modules/cudaoptflow/perf/perf_optflow.cpp modules/cudaoptflow/src/tvl1flow.cpp samples/gpu/stereo_multi.cpp
480 lines
15 KiB
C++
480 lines
15 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) 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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#include "opencv2/legacy.hpp"
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using namespace std;
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using namespace testing;
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using namespace perf;
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//////////////////////////////////////////////////////
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// InterpolateFrames
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typedef pair<string, string> pair_string;
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DEF_PARAM_TEST_1(ImagePair, pair_string);
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PERF_TEST_P(ImagePair, InterpolateFrames,
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Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")))
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{
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cv::Mat frame0 = readImage(GetParam().first, cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(frame0.empty());
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cv::Mat frame1 = readImage(GetParam().second, cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(frame1.empty());
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frame0.convertTo(frame0, CV_32FC1, 1.0 / 255.0);
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frame1.convertTo(frame1, CV_32FC1, 1.0 / 255.0);
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if (PERF_RUN_CUDA())
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{
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const cv::cuda::GpuMat d_frame0(frame0);
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const cv::cuda::GpuMat d_frame1(frame1);
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cv::cuda::GpuMat d_fu, d_fv;
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cv::cuda::GpuMat d_bu, d_bv;
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cv::cuda::BroxOpticalFlow d_flow(0.197f /*alpha*/, 50.0f /*gamma*/, 0.8f /*scale_factor*/,
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10 /*inner_iterations*/, 77 /*outer_iterations*/, 10 /*solver_iterations*/);
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d_flow(d_frame0, d_frame1, d_fu, d_fv);
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d_flow(d_frame1, d_frame0, d_bu, d_bv);
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cv::cuda::GpuMat newFrame;
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cv::cuda::GpuMat d_buf;
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TEST_CYCLE() cv::cuda::interpolateFrames(d_frame0, d_frame1, d_fu, d_fv, d_bu, d_bv, 0.5f, newFrame, d_buf);
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CUDA_SANITY_CHECK(newFrame, 1e-4);
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}
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else
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{
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FAIL_NO_CPU();
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}
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}
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//////////////////////////////////////////////////////
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// CreateOpticalFlowNeedleMap
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PERF_TEST_P(ImagePair, CreateOpticalFlowNeedleMap,
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Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")))
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{
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cv::Mat frame0 = readImage(GetParam().first, cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(frame0.empty());
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cv::Mat frame1 = readImage(GetParam().second, cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(frame1.empty());
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frame0.convertTo(frame0, CV_32FC1, 1.0 / 255.0);
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frame1.convertTo(frame1, CV_32FC1, 1.0 / 255.0);
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if (PERF_RUN_CUDA())
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{
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const cv::cuda::GpuMat d_frame0(frame0);
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const cv::cuda::GpuMat d_frame1(frame1);
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cv::cuda::GpuMat u;
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cv::cuda::GpuMat v;
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cv::cuda::BroxOpticalFlow d_flow(0.197f /*alpha*/, 50.0f /*gamma*/, 0.8f /*scale_factor*/,
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10 /*inner_iterations*/, 77 /*outer_iterations*/, 10 /*solver_iterations*/);
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d_flow(d_frame0, d_frame1, u, v);
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cv::cuda::GpuMat vertex, colors;
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TEST_CYCLE() cv::cuda::createOpticalFlowNeedleMap(u, v, vertex, colors);
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CUDA_SANITY_CHECK(vertex, 1e-6);
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CUDA_SANITY_CHECK(colors);
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}
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else
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{
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FAIL_NO_CPU();
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}
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}
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//////////////////////////////////////////////////////
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// BroxOpticalFlow
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PERF_TEST_P(ImagePair, BroxOpticalFlow,
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Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")))
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{
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declare.time(300);
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cv::Mat frame0 = readImage(GetParam().first, cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(frame0.empty());
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cv::Mat frame1 = readImage(GetParam().second, cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(frame1.empty());
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frame0.convertTo(frame0, CV_32FC1, 1.0 / 255.0);
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frame1.convertTo(frame1, CV_32FC1, 1.0 / 255.0);
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if (PERF_RUN_CUDA())
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{
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const cv::cuda::GpuMat d_frame0(frame0);
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const cv::cuda::GpuMat d_frame1(frame1);
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cv::cuda::GpuMat u;
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cv::cuda::GpuMat v;
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cv::cuda::BroxOpticalFlow d_flow(0.197f /*alpha*/, 50.0f /*gamma*/, 0.8f /*scale_factor*/,
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10 /*inner_iterations*/, 77 /*outer_iterations*/, 10 /*solver_iterations*/);
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TEST_CYCLE() d_flow(d_frame0, d_frame1, u, v);
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CUDA_SANITY_CHECK(u, 1e-1);
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CUDA_SANITY_CHECK(v, 1e-1);
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}
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else
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{
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FAIL_NO_CPU();
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}
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}
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//////////////////////////////////////////////////////
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// PyrLKOpticalFlowSparse
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DEF_PARAM_TEST(ImagePair_Gray_NPts_WinSz_Levels_Iters, pair_string, bool, int, int, int, int);
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PERF_TEST_P(ImagePair_Gray_NPts_WinSz_Levels_Iters, PyrLKOpticalFlowSparse,
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Combine(Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")),
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Bool(),
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Values(8000),
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Values(21),
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Values(1, 3),
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Values(1, 30)))
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{
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declare.time(20.0);
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const pair_string imagePair = GET_PARAM(0);
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const bool useGray = GET_PARAM(1);
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const int points = GET_PARAM(2);
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const int winSize = GET_PARAM(3);
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const int levels = GET_PARAM(4);
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const int iters = GET_PARAM(5);
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const cv::Mat frame0 = readImage(imagePair.first, useGray ? cv::IMREAD_GRAYSCALE : cv::IMREAD_COLOR);
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ASSERT_FALSE(frame0.empty());
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const cv::Mat frame1 = readImage(imagePair.second, useGray ? cv::IMREAD_GRAYSCALE : cv::IMREAD_COLOR);
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ASSERT_FALSE(frame1.empty());
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cv::Mat gray_frame;
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if (useGray)
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gray_frame = frame0;
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else
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cv::cvtColor(frame0, gray_frame, cv::COLOR_BGR2GRAY);
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cv::Mat pts;
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cv::goodFeaturesToTrack(gray_frame, pts, points, 0.01, 0.0);
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if (PERF_RUN_CUDA())
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{
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const cv::cuda::GpuMat d_pts(pts.reshape(2, 1));
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cv::cuda::PyrLKOpticalFlow d_pyrLK;
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d_pyrLK.winSize = cv::Size(winSize, winSize);
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d_pyrLK.maxLevel = levels - 1;
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d_pyrLK.iters = iters;
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const cv::cuda::GpuMat d_frame0(frame0);
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const cv::cuda::GpuMat d_frame1(frame1);
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cv::cuda::GpuMat nextPts;
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cv::cuda::GpuMat status;
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TEST_CYCLE() d_pyrLK.sparse(d_frame0, d_frame1, d_pts, nextPts, status);
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CUDA_SANITY_CHECK(nextPts);
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CUDA_SANITY_CHECK(status);
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}
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else
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{
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cv::Mat nextPts;
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cv::Mat status;
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TEST_CYCLE()
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{
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cv::calcOpticalFlowPyrLK(frame0, frame1, pts, nextPts, status, cv::noArray(),
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cv::Size(winSize, winSize), levels - 1,
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cv::TermCriteria(cv::TermCriteria::COUNT + cv::TermCriteria::EPS, iters, 0.01));
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}
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CPU_SANITY_CHECK(nextPts);
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CPU_SANITY_CHECK(status);
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}
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}
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//////////////////////////////////////////////////////
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// PyrLKOpticalFlowDense
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DEF_PARAM_TEST(ImagePair_WinSz_Levels_Iters, pair_string, int, int, int);
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PERF_TEST_P(ImagePair_WinSz_Levels_Iters, PyrLKOpticalFlowDense,
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Combine(Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")),
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Values(3, 5, 7, 9, 13, 17, 21),
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Values(1, 3),
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Values(1, 10)))
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{
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declare.time(30);
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const pair_string imagePair = GET_PARAM(0);
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const int winSize = GET_PARAM(1);
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const int levels = GET_PARAM(2);
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const int iters = GET_PARAM(3);
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const cv::Mat frame0 = readImage(imagePair.first, cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(frame0.empty());
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const cv::Mat frame1 = readImage(imagePair.second, cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(frame1.empty());
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if (PERF_RUN_CUDA())
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{
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const cv::cuda::GpuMat d_frame0(frame0);
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const cv::cuda::GpuMat d_frame1(frame1);
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cv::cuda::GpuMat u;
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cv::cuda::GpuMat v;
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cv::cuda::PyrLKOpticalFlow d_pyrLK;
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d_pyrLK.winSize = cv::Size(winSize, winSize);
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d_pyrLK.maxLevel = levels - 1;
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d_pyrLK.iters = iters;
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TEST_CYCLE() d_pyrLK.dense(d_frame0, d_frame1, u, v);
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CUDA_SANITY_CHECK(u);
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CUDA_SANITY_CHECK(v);
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}
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else
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{
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FAIL_NO_CPU();
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}
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}
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//////////////////////////////////////////////////////
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// FarnebackOpticalFlow
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PERF_TEST_P(ImagePair, FarnebackOpticalFlow,
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Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")))
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{
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declare.time(10);
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const cv::Mat frame0 = readImage(GetParam().first, cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(frame0.empty());
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const cv::Mat frame1 = readImage(GetParam().second, cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(frame1.empty());
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const int numLevels = 5;
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const double pyrScale = 0.5;
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const int winSize = 13;
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const int numIters = 10;
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const int polyN = 5;
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const double polySigma = 1.1;
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const int flags = 0;
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if (PERF_RUN_CUDA())
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{
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const cv::cuda::GpuMat d_frame0(frame0);
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const cv::cuda::GpuMat d_frame1(frame1);
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cv::cuda::GpuMat u;
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cv::cuda::GpuMat v;
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cv::cuda::FarnebackOpticalFlow d_farneback;
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d_farneback.numLevels = numLevels;
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d_farneback.pyrScale = pyrScale;
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d_farneback.winSize = winSize;
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d_farneback.numIters = numIters;
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d_farneback.polyN = polyN;
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d_farneback.polySigma = polySigma;
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d_farneback.flags = flags;
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TEST_CYCLE() d_farneback(d_frame0, d_frame1, u, v);
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CUDA_SANITY_CHECK(u, 1e-4);
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CUDA_SANITY_CHECK(v, 1e-4);
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}
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else
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{
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cv::Mat flow;
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TEST_CYCLE() cv::calcOpticalFlowFarneback(frame0, frame1, flow, pyrScale, numLevels, winSize, numIters, polyN, polySigma, flags);
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CPU_SANITY_CHECK(flow);
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}
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}
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//////////////////////////////////////////////////////
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// OpticalFlowDual_TVL1
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PERF_TEST_P(ImagePair, OpticalFlowDual_TVL1,
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Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")))
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{
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declare.time(20);
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const cv::Mat frame0 = readImage(GetParam().first, cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(frame0.empty());
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const cv::Mat frame1 = readImage(GetParam().second, cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(frame1.empty());
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if (PERF_RUN_CUDA())
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{
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const cv::cuda::GpuMat d_frame0(frame0);
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const cv::cuda::GpuMat d_frame1(frame1);
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cv::cuda::GpuMat u;
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cv::cuda::GpuMat v;
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cv::cuda::OpticalFlowDual_TVL1_CUDA d_alg;
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TEST_CYCLE() d_alg(d_frame0, d_frame1, u, v);
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CUDA_SANITY_CHECK(u, 1e-1);
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CUDA_SANITY_CHECK(v, 1e-1);
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}
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else
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{
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cv::Mat flow;
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cv::Ptr<cv::DenseOpticalFlow> alg = cv::createOptFlow_DualTVL1();
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alg->set("medianFiltering", 1);
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alg->set("innerIterations", 1);
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alg->set("outerIterations", 300);
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TEST_CYCLE() alg->calc(frame0, frame1, flow);
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CPU_SANITY_CHECK(flow);
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}
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}
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//////////////////////////////////////////////////////
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// OpticalFlowBM
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void calcOpticalFlowBM(const cv::Mat& prev, const cv::Mat& curr,
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cv::Size bSize, cv::Size shiftSize, cv::Size maxRange, int usePrevious,
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cv::Mat& velx, cv::Mat& vely)
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{
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cv::Size sz((curr.cols - bSize.width + shiftSize.width)/shiftSize.width, (curr.rows - bSize.height + shiftSize.height)/shiftSize.height);
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velx.create(sz, CV_32FC1);
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vely.create(sz, CV_32FC1);
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CvMat cvprev = prev;
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CvMat cvcurr = curr;
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CvMat cvvelx = velx;
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CvMat cvvely = vely;
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cvCalcOpticalFlowBM(&cvprev, &cvcurr, bSize, shiftSize, maxRange, usePrevious, &cvvelx, &cvvely);
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}
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PERF_TEST_P(ImagePair, OpticalFlowBM,
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Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")))
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{
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declare.time(400);
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const cv::Mat frame0 = readImage(GetParam().first, cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(frame0.empty());
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const cv::Mat frame1 = readImage(GetParam().second, cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(frame1.empty());
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const cv::Size block_size(16, 16);
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const cv::Size shift_size(1, 1);
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const cv::Size max_range(16, 16);
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if (PERF_RUN_CUDA())
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{
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const cv::cuda::GpuMat d_frame0(frame0);
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const cv::cuda::GpuMat d_frame1(frame1);
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cv::cuda::GpuMat u, v, buf;
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TEST_CYCLE() cv::cuda::calcOpticalFlowBM(d_frame0, d_frame1, block_size, shift_size, max_range, false, u, v, buf);
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CUDA_SANITY_CHECK(u);
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CUDA_SANITY_CHECK(v);
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}
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else
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{
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cv::Mat u, v;
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TEST_CYCLE() calcOpticalFlowBM(frame0, frame1, block_size, shift_size, max_range, false, u, v);
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CPU_SANITY_CHECK(u);
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CPU_SANITY_CHECK(v);
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}
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}
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PERF_TEST_P(ImagePair, FastOpticalFlowBM,
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Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")))
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{
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declare.time(400);
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const cv::Mat frame0 = readImage(GetParam().first, cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(frame0.empty());
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const cv::Mat frame1 = readImage(GetParam().second, cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(frame1.empty());
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const cv::Size block_size(16, 16);
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const cv::Size shift_size(1, 1);
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const cv::Size max_range(16, 16);
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if (PERF_RUN_CUDA())
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{
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const cv::cuda::GpuMat d_frame0(frame0);
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const cv::cuda::GpuMat d_frame1(frame1);
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cv::cuda::GpuMat u, v;
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cv::cuda::FastOpticalFlowBM fastBM;
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TEST_CYCLE() fastBM(d_frame0, d_frame1, u, v, max_range.width, block_size.width);
|
|
|
|
CUDA_SANITY_CHECK(u, 2);
|
|
CUDA_SANITY_CHECK(v, 2);
|
|
}
|
|
else
|
|
{
|
|
FAIL_NO_CPU();
|
|
}
|
|
}
|