mirror of
https://github.com/opencv/opencv.git
synced 2024-12-26 18:58:16 +08:00
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///////////////////////////////////////////////////////////////////////////////////////
|
|
//
|
|
// 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"
|
|
#include "opencv2/legacy.hpp"
|
|
|
|
using namespace std;
|
|
using namespace testing;
|
|
using namespace perf;
|
|
|
|
//////////////////////////////////////////////////////
|
|
// InterpolateFrames
|
|
|
|
typedef pair<string, string> pair_string;
|
|
|
|
DEF_PARAM_TEST_1(ImagePair, pair_string);
|
|
|
|
PERF_TEST_P(ImagePair, InterpolateFrames,
|
|
Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")))
|
|
{
|
|
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 d_fu, d_fv;
|
|
cv::cuda::GpuMat d_bu, d_bv;
|
|
|
|
cv::cuda::BroxOpticalFlow d_flow(0.197f /*alpha*/, 50.0f /*gamma*/, 0.8f /*scale_factor*/,
|
|
10 /*inner_iterations*/, 77 /*outer_iterations*/, 10 /*solver_iterations*/);
|
|
|
|
d_flow(d_frame0, d_frame1, d_fu, d_fv);
|
|
d_flow(d_frame1, d_frame0, d_bu, d_bv);
|
|
|
|
cv::cuda::GpuMat newFrame;
|
|
cv::cuda::GpuMat d_buf;
|
|
|
|
TEST_CYCLE() cv::cuda::interpolateFrames(d_frame0, d_frame1, d_fu, d_fv, d_bu, d_bv, 0.5f, newFrame, d_buf);
|
|
|
|
CUDA_SANITY_CHECK(newFrame, 1e-4);
|
|
}
|
|
else
|
|
{
|
|
FAIL_NO_CPU();
|
|
}
|
|
}
|
|
|
|
//////////////////////////////////////////////////////
|
|
// CreateOpticalFlowNeedleMap
|
|
|
|
PERF_TEST_P(ImagePair, CreateOpticalFlowNeedleMap,
|
|
Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")))
|
|
{
|
|
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 u;
|
|
cv::cuda::GpuMat v;
|
|
|
|
cv::cuda::BroxOpticalFlow d_flow(0.197f /*alpha*/, 50.0f /*gamma*/, 0.8f /*scale_factor*/,
|
|
10 /*inner_iterations*/, 77 /*outer_iterations*/, 10 /*solver_iterations*/);
|
|
|
|
d_flow(d_frame0, d_frame1, u, v);
|
|
|
|
cv::cuda::GpuMat vertex, colors;
|
|
|
|
TEST_CYCLE() cv::cuda::createOpticalFlowNeedleMap(u, v, vertex, colors);
|
|
|
|
CUDA_SANITY_CHECK(vertex, 1e-6);
|
|
CUDA_SANITY_CHECK(colors);
|
|
}
|
|
else
|
|
{
|
|
FAIL_NO_CPU();
|
|
}
|
|
}
|
|
|
|
//////////////////////////////////////////////////////
|
|
// 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 u;
|
|
cv::cuda::GpuMat v;
|
|
|
|
cv::cuda::BroxOpticalFlow d_flow(0.197f /*alpha*/, 50.0f /*gamma*/, 0.8f /*scale_factor*/,
|
|
10 /*inner_iterations*/, 77 /*outer_iterations*/, 10 /*solver_iterations*/);
|
|
|
|
TEST_CYCLE() d_flow(d_frame0, d_frame1, u, v);
|
|
|
|
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);
|
|
|
|
const cv::Mat frame0 = readImage(imagePair.first, useGray ? cv::IMREAD_GRAYSCALE : cv::IMREAD_COLOR);
|
|
ASSERT_FALSE(frame0.empty());
|
|
|
|
const 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);
|
|
|
|
if (PERF_RUN_CUDA())
|
|
{
|
|
const cv::cuda::GpuMat d_pts(pts.reshape(2, 1));
|
|
|
|
cv::cuda::PyrLKOpticalFlow d_pyrLK;
|
|
d_pyrLK.winSize = cv::Size(winSize, winSize);
|
|
d_pyrLK.maxLevel = levels - 1;
|
|
d_pyrLK.iters = 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.sparse(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 u;
|
|
cv::cuda::GpuMat v;
|
|
|
|
cv::cuda::PyrLKOpticalFlow d_pyrLK;
|
|
d_pyrLK.winSize = cv::Size(winSize, winSize);
|
|
d_pyrLK.maxLevel = levels - 1;
|
|
d_pyrLK.iters = iters;
|
|
|
|
TEST_CYCLE() d_pyrLK.dense(d_frame0, d_frame1, u, v);
|
|
|
|
CUDA_SANITY_CHECK(u);
|
|
CUDA_SANITY_CHECK(v);
|
|
}
|
|
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 u;
|
|
cv::cuda::GpuMat v;
|
|
|
|
cv::cuda::FarnebackOpticalFlow d_farneback;
|
|
d_farneback.numLevels = numLevels;
|
|
d_farneback.pyrScale = pyrScale;
|
|
d_farneback.winSize = winSize;
|
|
d_farneback.numIters = numIters;
|
|
d_farneback.polyN = polyN;
|
|
d_farneback.polySigma = polySigma;
|
|
d_farneback.flags = flags;
|
|
|
|
TEST_CYCLE() d_farneback(d_frame0, d_frame1, u, v);
|
|
|
|
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 u;
|
|
cv::cuda::GpuMat v;
|
|
|
|
cv::cuda::OpticalFlowDual_TVL1_CUDA d_alg;
|
|
|
|
TEST_CYCLE() d_alg(d_frame0, d_frame1, u, v);
|
|
|
|
CUDA_SANITY_CHECK(u, 1e-1);
|
|
CUDA_SANITY_CHECK(v, 1e-1);
|
|
}
|
|
else
|
|
{
|
|
cv::Mat flow;
|
|
|
|
cv::Ptr<cv::DenseOpticalFlow> alg = cv::createOptFlow_DualTVL1();
|
|
alg->set("medianFiltering", 1);
|
|
alg->set("innerIterations", 1);
|
|
alg->set("outerIterations", 300);
|
|
|
|
TEST_CYCLE() alg->calc(frame0, frame1, flow);
|
|
|
|
CPU_SANITY_CHECK(flow);
|
|
}
|
|
}
|
|
|
|
//////////////////////////////////////////////////////
|
|
// OpticalFlowBM
|
|
|
|
void calcOpticalFlowBM(const cv::Mat& prev, const cv::Mat& curr,
|
|
cv::Size bSize, cv::Size shiftSize, cv::Size maxRange, int usePrevious,
|
|
cv::Mat& velx, cv::Mat& vely)
|
|
{
|
|
cv::Size sz((curr.cols - bSize.width + shiftSize.width)/shiftSize.width, (curr.rows - bSize.height + shiftSize.height)/shiftSize.height);
|
|
|
|
velx.create(sz, CV_32FC1);
|
|
vely.create(sz, CV_32FC1);
|
|
|
|
CvMat cvprev = prev;
|
|
CvMat cvcurr = curr;
|
|
|
|
CvMat cvvelx = velx;
|
|
CvMat cvvely = vely;
|
|
|
|
cvCalcOpticalFlowBM(&cvprev, &cvcurr, bSize, shiftSize, maxRange, usePrevious, &cvvelx, &cvvely);
|
|
}
|
|
|
|
PERF_TEST_P(ImagePair, OpticalFlowBM,
|
|
Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")))
|
|
{
|
|
declare.time(400);
|
|
|
|
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::Size block_size(16, 16);
|
|
const cv::Size shift_size(1, 1);
|
|
const cv::Size max_range(16, 16);
|
|
|
|
if (PERF_RUN_CUDA())
|
|
{
|
|
const cv::cuda::GpuMat d_frame0(frame0);
|
|
const cv::cuda::GpuMat d_frame1(frame1);
|
|
cv::cuda::GpuMat u, v, buf;
|
|
|
|
TEST_CYCLE() cv::cuda::calcOpticalFlowBM(d_frame0, d_frame1, block_size, shift_size, max_range, false, u, v, buf);
|
|
|
|
CUDA_SANITY_CHECK(u);
|
|
CUDA_SANITY_CHECK(v);
|
|
}
|
|
else
|
|
{
|
|
cv::Mat u, v;
|
|
|
|
TEST_CYCLE() calcOpticalFlowBM(frame0, frame1, block_size, shift_size, max_range, false, u, v);
|
|
|
|
CPU_SANITY_CHECK(u);
|
|
CPU_SANITY_CHECK(v);
|
|
}
|
|
}
|
|
|
|
PERF_TEST_P(ImagePair, FastOpticalFlowBM,
|
|
Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")))
|
|
{
|
|
declare.time(400);
|
|
|
|
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::Size block_size(16, 16);
|
|
const cv::Size shift_size(1, 1);
|
|
const cv::Size max_range(16, 16);
|
|
|
|
if (PERF_RUN_CUDA())
|
|
{
|
|
const cv::cuda::GpuMat d_frame0(frame0);
|
|
const cv::cuda::GpuMat d_frame1(frame1);
|
|
cv::cuda::GpuMat u, v;
|
|
|
|
cv::cuda::FastOpticalFlowBM fastBM;
|
|
|
|
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();
|
|
}
|
|
}
|