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vendor: OpenCV 5.0.0 snapshot at 755e50675d97db9b7d449d8bd6b09888646f6c6e

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2026-08-22 00:11:13 +08:00
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modules/cudaoptflow/perf/perf_main.cpp
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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "perf_precomp.hpp"
using namespace perf;
CV_PERF_TEST_CUDA_MAIN(cudaoptflow)
modules/cudaoptflow/perf/perf_optflow.cpp
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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "perf_precomp.hpp"
namespace opencv_test { namespace {
typedef pair<string, string> pair_string;
DEF_PARAM_TEST_1(ImagePair, pair_string);
//////////////////////////////////////////////////////
// BroxOpticalFlow
PERF_TEST_P(ImagePair, BroxOpticalFlow,
Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")))
{
declare.time(300);
cv::Mat frame0 = readImage(GetParam().first, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame0.empty());
cv::Mat frame1 = readImage(GetParam().second, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame1.empty());
frame0.convertTo(frame0, CV_32FC1, 1.0 / 255.0);
frame1.convertTo(frame1, CV_32FC1, 1.0 / 255.0);
if (PERF_RUN_CUDA())
{
const cv::cuda::GpuMat d_frame0(frame0);
const cv::cuda::GpuMat d_frame1(frame1);
cv::cuda::GpuMat flow;
cv::Ptr<cv::cuda::BroxOpticalFlow> d_alg =
cv::cuda::BroxOpticalFlow::create(0.197 /*alpha*/, 50.0 /*gamma*/, 0.8 /*scale_factor*/,
10 /*inner_iterations*/, 77 /*outer_iterations*/, 10 /*solver_iterations*/);
TEST_CYCLE() d_alg->calc(d_frame0, d_frame1, flow);
cv::cuda::GpuMat flows[2];
cv::cuda::split(flow, flows);
cv::cuda::GpuMat u = flows[0];
cv::cuda::GpuMat v = flows[1];
CUDA_SANITY_CHECK(u, 1e-1);
CUDA_SANITY_CHECK(v, 1e-1);
}
else
{
FAIL_NO_CPU();
}
}
//////////////////////////////////////////////////////
// PyrLKOpticalFlowSparse
DEF_PARAM_TEST(ImagePair_Gray_NPts_WinSz_Levels_Iters, pair_string, bool, int, int, int, int);
PERF_TEST_P(ImagePair_Gray_NPts_WinSz_Levels_Iters, PyrLKOpticalFlowSparse,
Combine(Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")),
Bool(),
Values(8000),
Values(21),
Values(1, 3),
Values(1, 30)))
{
declare.time(20.0);
const pair_string imagePair = GET_PARAM(0);
const bool useGray = GET_PARAM(1);
const int points = GET_PARAM(2);
const int winSize = GET_PARAM(3);
const int levels = GET_PARAM(4);
const int iters = GET_PARAM(5);
cv::Mat frame0 = readImage(imagePair.first, useGray ? cv::IMREAD_GRAYSCALE : cv::IMREAD_COLOR);
ASSERT_FALSE(frame0.empty());
cv::Mat frame1 = readImage(imagePair.second, useGray ? cv::IMREAD_GRAYSCALE : cv::IMREAD_COLOR);
ASSERT_FALSE(frame1.empty());
cv::Mat gray_frame;
if (useGray)
gray_frame = frame0;
else
cv::cvtColor(frame0, gray_frame, cv::COLOR_BGR2GRAY);
cv::Mat pts;
cv::goodFeaturesToTrack(gray_frame, pts, points, 0.01, 0.0);
frame0.convertTo(frame0, CV_32F);
frame1.convertTo(frame1, CV_32F);
if(!useGray)
{
cv::cvtColor(frame0, frame0, cv::COLOR_BGR2BGRA);
cv::cvtColor(frame1, frame1, cv::COLOR_BGR2BGRA);
}
if (PERF_RUN_CUDA())
{
const cv::cuda::GpuMat d_pts(pts.reshape(2, 1));
cv::Ptr<cv::cuda::SparsePyrLKOpticalFlow> d_pyrLK =
cv::cuda::SparsePyrLKOpticalFlow::create(cv::Size(winSize, winSize),
levels - 1,
iters);
const cv::cuda::GpuMat d_frame0(frame0);
const cv::cuda::GpuMat d_frame1(frame1);
cv::cuda::GpuMat nextPts;
cv::cuda::GpuMat status;
TEST_CYCLE() d_pyrLK->calc(d_frame0, d_frame1, d_pts, nextPts, status);
CUDA_SANITY_CHECK(nextPts);
CUDA_SANITY_CHECK(status);
}
else
{
cv::Mat nextPts;
cv::Mat status;
TEST_CYCLE()
{
cv::calcOpticalFlowPyrLK(frame0, frame1, pts, nextPts, status, cv::noArray(),
cv::Size(winSize, winSize), levels - 1,
cv::TermCriteria(cv::TermCriteria::COUNT + cv::TermCriteria::EPS, iters, 0.01));
}
CPU_SANITY_CHECK(nextPts);
CPU_SANITY_CHECK(status);
}
}
//////////////////////////////////////////////////////
// PyrLKOpticalFlowDense
DEF_PARAM_TEST(ImagePair_WinSz_Levels_Iters, pair_string, int, int, int);
PERF_TEST_P(ImagePair_WinSz_Levels_Iters, PyrLKOpticalFlowDense,
Combine(Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")),
Values(3, 5, 7, 9, 13, 17, 21),
Values(1, 3),
Values(1, 10)))
{
declare.time(30);
const pair_string imagePair = GET_PARAM(0);
const int winSize = GET_PARAM(1);
const int levels = GET_PARAM(2);
const int iters = GET_PARAM(3);
const cv::Mat frame0 = readImage(imagePair.first, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame0.empty());
const cv::Mat frame1 = readImage(imagePair.second, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame1.empty());
if (PERF_RUN_CUDA())
{
const cv::cuda::GpuMat d_frame0(frame0);
const cv::cuda::GpuMat d_frame1(frame1);
cv::cuda::GpuMat flow;
cv::Ptr<cv::cuda::DensePyrLKOpticalFlow> d_pyrLK =
cv::cuda::DensePyrLKOpticalFlow::create(cv::Size(winSize, winSize),
levels - 1,
iters);
TEST_CYCLE() d_pyrLK->calc(d_frame0, d_frame1, flow);
cv::cuda::GpuMat flows[2];
cv::cuda::split(flow, flows);
cv::cuda::GpuMat u = flows[0];
cv::cuda::GpuMat v = flows[1];
// Sanity test fails on Maxwell and CUDA 7.0
SANITY_CHECK_NOTHING();
}
else
{
FAIL_NO_CPU();
}
}
//////////////////////////////////////////////////////
// FarnebackOpticalFlow
PERF_TEST_P(ImagePair, FarnebackOpticalFlow,
Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")))
{
declare.time(10);
const cv::Mat frame0 = readImage(GetParam().first, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame0.empty());
const cv::Mat frame1 = readImage(GetParam().second, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame1.empty());
const int numLevels = 5;
const double pyrScale = 0.5;
const int winSize = 13;
const int numIters = 10;
const int polyN = 5;
const double polySigma = 1.1;
const int flags = 0;
if (PERF_RUN_CUDA())
{
const cv::cuda::GpuMat d_frame0(frame0);
const cv::cuda::GpuMat d_frame1(frame1);
cv::cuda::GpuMat flow;
cv::Ptr<cv::cuda::FarnebackOpticalFlow> d_farneback =
cv::cuda::FarnebackOpticalFlow::create(numLevels, pyrScale, false, winSize,
numIters, polyN, polySigma, flags);
TEST_CYCLE() d_farneback->calc(d_frame0, d_frame1, flow);
cv::cuda::GpuMat flows[2];
cv::cuda::split(flow, flows);
cv::cuda::GpuMat u = flows[0];
cv::cuda::GpuMat v = flows[1];
CUDA_SANITY_CHECK(u, 1e-4);
CUDA_SANITY_CHECK(v, 1e-4);
}
else
{
cv::Mat flow;
TEST_CYCLE() cv::calcOpticalFlowFarneback(frame0, frame1, flow, pyrScale, numLevels, winSize, numIters, polyN, polySigma, flags);
CPU_SANITY_CHECK(flow);
}
}
//////////////////////////////////////////////////////
// OpticalFlowDual_TVL1
PERF_TEST_P(ImagePair, OpticalFlowDual_TVL1,
Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")))
{
declare.time(20);
const cv::Mat frame0 = readImage(GetParam().first, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame0.empty());
const cv::Mat frame1 = readImage(GetParam().second, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame1.empty());
if (PERF_RUN_CUDA())
{
const cv::cuda::GpuMat d_frame0(frame0);
const cv::cuda::GpuMat d_frame1(frame1);
cv::cuda::GpuMat flow;
cv::Ptr<cv::cuda::OpticalFlowDual_TVL1> d_alg =
cv::cuda::OpticalFlowDual_TVL1::create();
TEST_CYCLE() d_alg->calc(d_frame0, d_frame1, flow);
cv::cuda::GpuMat flows[2];
cv::cuda::split(flow, flows);
cv::cuda::GpuMat u = flows[0];
cv::cuda::GpuMat v = flows[1];
CUDA_SANITY_CHECK(u, 1e-1);
CUDA_SANITY_CHECK(v, 1e-1);
}
else
{
cv::Mat flow;
cv::Ptr<cv::optflow::DualTVL1OpticalFlow> alg = cv::optflow::createOptFlow_DualTVL1();
alg->setMedianFiltering(1);
alg->setInnerIterations(1);
alg->setOuterIterations(300);
TEST_CYCLE() alg->calc(frame0, frame1, flow);
CPU_SANITY_CHECK(flow);
}
}
//////////////////////////////////////////////////////
// NvidiaOpticalFlow_1_0
PERF_TEST_P(ImagePair, NvidiaOpticalFlow_1_0,
Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")))
{
declare.time(10);
const cv::Mat frame0 = readImage(GetParam().first, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame0.empty());
const cv::Mat frame1 = readImage(GetParam().second, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame1.empty());
Stream inputStream;
Stream outputStream;
if (PERF_RUN_CUDA())
{
const cv::cuda::GpuMat d_frame0(frame0);
const cv::cuda::GpuMat d_frame1(frame1);
cv::cuda::GpuMat d_flow;
cv::Ptr<cv::cuda::NvidiaOpticalFlow_1_0> d_nvof;
try
{
d_nvof = cv::cuda::NvidiaOpticalFlow_1_0::create(frame0.size(),
cv::cuda::NvidiaOpticalFlow_1_0::NVIDIA_OF_PERF_LEVEL::NV_OF_PERF_LEVEL_FAST,
false, false, false, 0, inputStream, outputStream);
}
catch (const cv::Exception& e)
{
if(e.code == Error::StsBadFunc || e.code == Error::StsBadArg || e.code == Error::StsNullPtr)
throw SkipTestException("Current configuration is not supported");
throw;
}
TEST_CYCLE() d_nvof->calc(d_frame0, d_frame1, d_flow);
cv::cuda::GpuMat flow[2];
cv::cuda::split(d_flow, flow);
cv::cuda::GpuMat u = flow[0];
cv::cuda::GpuMat v = flow[1];
CUDA_SANITY_CHECK(u, 1e-10);
CUDA_SANITY_CHECK(v, 1e-10);
d_nvof->collectGarbage();
}
}
//////////////////////////////////////////////////////
// NvidiaOpticalFlow_2_0
PERF_TEST_P(ImagePair, NvidiaOpticalFlow_2_0,
Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")))
{
declare.time(10);
const cv::Mat frame0 = readImage(GetParam().first, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame0.empty());
const cv::Mat frame1 = readImage(GetParam().second, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame1.empty());
const cv::cuda::NvidiaOpticalFlow_2_0::NVIDIA_OF_OUTPUT_VECTOR_GRID_SIZE outGridSize
= cv::cuda::NvidiaOpticalFlow_2_0::NVIDIA_OF_OUTPUT_VECTOR_GRID_SIZE::NV_OF_OUTPUT_VECTOR_GRID_SIZE_1;
const cv::cuda::NvidiaOpticalFlow_2_0::NVIDIA_OF_HINT_VECTOR_GRID_SIZE hintGridSize
= cv::cuda::NvidiaOpticalFlow_2_0::NVIDIA_OF_HINT_VECTOR_GRID_SIZE::NV_OF_HINT_VECTOR_GRID_SIZE_1;
Stream inputStream;
Stream outputStream;
if (PERF_RUN_CUDA())
{
const cv::cuda::GpuMat d_frame0(frame0);
const cv::cuda::GpuMat d_frame1(frame1);
cv::cuda::GpuMat d_flow;
cv::Ptr<cv::cuda::NvidiaOpticalFlow_2_0> d_nvof;
try
{
d_nvof = cv::cuda::NvidiaOpticalFlow_2_0::create(frame0.size(),
cv::cuda::NvidiaOpticalFlow_2_0::NVIDIA_OF_PERF_LEVEL::NV_OF_PERF_LEVEL_FAST, outGridSize, hintGridSize,
false, false, false, 0, inputStream, outputStream);
}
catch (const cv::Exception& e)
{
if (e.code == Error::StsBadFunc || e.code == Error::StsBadArg || e.code == Error::StsNullPtr)
throw SkipTestException("Current configuration is not supported");
throw;
}
TEST_CYCLE() d_nvof->calc(d_frame0, d_frame1, d_flow);
cv::cuda::GpuMat flow[2];
cv::cuda::split(d_flow, flow);
cv::cuda::GpuMat u = flow[0];
cv::cuda::GpuMat v = flow[1];
CUDA_SANITY_CHECK(u, 1e-10);
CUDA_SANITY_CHECK(v, 1e-10);
d_nvof->collectGarbage();
}
}
}} // namespace
modules/cudaoptflow/perf/perf_precomp.hpp
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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_PERF_PRECOMP_HPP__
#define __OPENCV_PERF_PRECOMP_HPP__
#include "opencv2/ts.hpp"
#include "opencv2/ts/cuda_perf.hpp"
#include "opencv2/cudaoptflow.hpp"
#include "opencv2/cudaarithm.hpp"
#include "opencv2/cudafeatures2d.hpp"
#include "opencv2/video.hpp"
#include "opencv2/optflow.hpp"
namespace opencv_test {
using namespace perf;
using namespace testing;
}
#endif