Open Source Computer Vision Library https://opencv.org/
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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) 2010-2012, Multicoreware, Inc., all rights reserved.
// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// @Authors
// Fangfang Bai, fangfang@multicorewareinc.com
// Jin Ma, jin@multicorewareinc.com
//
// 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 oclMaterials 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 "precomp.hpp"
///////////// PyrLKOpticalFlow ////////////////////////
PERFTEST(PyrLKOpticalFlow)
{
std::string images1[] = {"rubberwhale1.png", "basketball1.png"};
std::string images2[] = {"rubberwhale2.png", "basketball2.png"};
for (size_t i = 0; i < sizeof(images1) / sizeof(std::string); i++)
{
Mat frame0 = imread(abspath(images1[i]), i == 0 ? IMREAD_COLOR : IMREAD_GRAYSCALE);
if (frame0.empty())
{
std::string errstr = "can't open " + images1[i];
throw runtime_error(errstr);
}
Mat frame1 = imread(abspath(images2[i]), i == 0 ? IMREAD_COLOR : IMREAD_GRAYSCALE);
if (frame1.empty())
{
std::string errstr = "can't open " + images2[i];
throw runtime_error(errstr);
}
Mat gray_frame;
if (i == 0)
{
cvtColor(frame0, gray_frame, COLOR_BGR2GRAY);
}
for (int points = Min_Size; points <= Max_Size; points *= Multiple)
{
if (i == 0)
SUBTEST << frame0.cols << "x" << frame0.rows << "; color; " << points << " points";
else
SUBTEST << frame0.cols << "x" << frame0.rows << "; gray; " << points << " points";
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Mat ocl_nextPts;
Mat ocl_status;
vector<Point2f> pts;
goodFeaturesToTrack(i == 0 ? gray_frame : frame0, pts, points, 0.01, 0.0);
vector<Point2f> nextPts;
vector<unsigned char> status;
vector<float> err;
calcOpticalFlowPyrLK(frame0, frame1, pts, nextPts, status, err);
CPU_ON;
calcOpticalFlowPyrLK(frame0, frame1, pts, nextPts, status, err);
CPU_OFF;
ocl::PyrLKOpticalFlow d_pyrLK;
ocl::oclMat d_frame0(frame0);
ocl::oclMat d_frame1(frame1);
ocl::oclMat d_pts;
Mat pts_mat(1, (int)pts.size(), CV_32FC2, (void *)&pts[0]);
d_pts.upload(pts_mat);
ocl::oclMat d_nextPts;
ocl::oclMat d_status;
ocl::oclMat d_err;
WARMUP_ON;
d_pyrLK.sparse(d_frame0, d_frame1, d_pts, d_nextPts, d_status, &d_err);
WARMUP_OFF;
GPU_ON;
d_pyrLK.sparse(d_frame0, d_frame1, d_pts, d_nextPts, d_status, &d_err);
GPU_OFF;
GPU_FULL_ON;
d_frame0.upload(frame0);
d_frame1.upload(frame1);
d_pts.upload(pts_mat);
d_pyrLK.sparse(d_frame0, d_frame1, d_pts, d_nextPts, d_status, &d_err);
if (!d_nextPts.empty())
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d_nextPts.download(ocl_nextPts);
if (!d_status.empty())
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d_status.download(ocl_status);
GPU_FULL_OFF;
size_t mismatch = 0;
for (int i = 0; i < (int)nextPts.size(); ++i)
{
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if(status[i] != ocl_status.at<unsigned char>(0, i)){
mismatch++;
continue;
}
if(status[i]){
Point2f gpu_rst = ocl_nextPts.at<Point2f>(0, i);
Point2f cpu_rst = nextPts[i];
if(fabs(gpu_rst.x - cpu_rst.x) >= 1. || fabs(gpu_rst.y - cpu_rst.y) >= 1.)
mismatch++;
}
}
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double ratio = (double)mismatch / (double)nextPts.size();
if(ratio < .02)
TestSystem::instance().setAccurate(1, ratio);
else
TestSystem::instance().setAccurate(0, ratio);
}
}
}
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PERFTEST(tvl1flow)
{
cv::Mat frame0 = imread("rubberwhale1.png", cv::IMREAD_GRAYSCALE);
assert(!frame0.empty());
cv::Mat frame1 = imread("rubberwhale2.png", cv::IMREAD_GRAYSCALE);
assert(!frame1.empty());
cv::ocl::OpticalFlowDual_TVL1_OCL d_alg;
cv::ocl::oclMat d_flowx(frame0.size(), CV_32FC1);
cv::ocl::oclMat d_flowy(frame1.size(), CV_32FC1);
cv::Ptr<cv::DenseOpticalFlow> alg = cv::createOptFlow_DualTVL1();
cv::Mat flow;
SUBTEST << frame0.cols << 'x' << frame0.rows << "; rubberwhale1.png; "<<frame1.cols<<'x'<<frame1.rows<<"; rubberwhale2.png";
alg->calc(frame0, frame1, flow);
CPU_ON;
alg->calc(frame0, frame1, flow);
CPU_OFF;
cv::Mat gold[2];
cv::split(flow, gold);
cv::ocl::oclMat d0(frame0.size(), CV_32FC1);
d0.upload(frame0);
cv::ocl::oclMat d1(frame1.size(), CV_32FC1);
d1.upload(frame1);
WARMUP_ON;
d_alg(d0, d1, d_flowx, d_flowy);
WARMUP_OFF;
/*
double diff1 = 0.0, diff2 = 0.0;
if(ExceptedMatSimilar(gold[0], cv::Mat(d_flowx), 3e-3, diff1) == 1
&&ExceptedMatSimilar(gold[1], cv::Mat(d_flowy), 3e-3, diff2) == 1)
TestSystem::instance().setAccurate(1);
else
TestSystem::instance().setAccurate(0);
TestSystem::instance().setDiff(diff1);
TestSystem::instance().setDiff(diff2);
*/
GPU_ON;
d_alg(d0, d1, d_flowx, d_flowy);
d_alg.collectGarbage();
GPU_OFF;
cv::Mat flowx, flowy;
GPU_FULL_ON;
d0.upload(frame0);
d1.upload(frame1);
d_alg(d0, d1, d_flowx, d_flowy);
d_alg.collectGarbage();
d_flowx.download(flowx);
d_flowy.download(flowy);
GPU_FULL_OFF;
TestSystem::instance().ExceptedMatSimilar(gold[0], flowx, 3e-3);
TestSystem::instance().ExceptedMatSimilar(gold[1], flowy, 3e-3);
}
///////////// FarnebackOpticalFlow ////////////////////////
PERFTEST(FarnebackOpticalFlow)
{
cv::Mat frame0 = imread("rubberwhale1.png", cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame0.empty());
cv::Mat frame1 = imread("rubberwhale2.png", cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame1.empty());
cv::ocl::oclMat d_frame0(frame0), d_frame1(frame1);
int polyNs[2] = { 5, 7 };
double polySigmas[2] = { 1.1, 1.5 };
int farneFlags[2] = { 0, cv::OPTFLOW_FARNEBACK_GAUSSIAN };
bool UseInitFlows[2] = { false, true };
double pyrScale = 0.5;
string farneFlagStrs[2] = { "BoxFilter", "GaussianBlur" };
string useInitFlowStrs[2] = { "", "UseInitFlow" };
for ( int i = 0; i < 2; ++i)
{
int polyN = polyNs[i];
double polySigma = polySigmas[i];
for ( int j = 0; j < 2; ++j)
{
int flags = farneFlags[j];
for ( int k = 0; k < 2; ++k)
{
bool useInitFlow = UseInitFlows[k];
SUBTEST << "polyN(" << polyN << "); " << farneFlagStrs[j] << "; " << useInitFlowStrs[k];
cv::ocl::FarnebackOpticalFlow farn;
farn.pyrScale = pyrScale;
farn.polyN = polyN;
farn.polySigma = polySigma;
farn.flags = flags;
cv::ocl::oclMat d_flowx, d_flowy;
cv::Mat flow, flowBuf, flowxBuf, flowyBuf;
WARMUP_ON;
farn(d_frame0, d_frame1, d_flowx, d_flowy);
if (useInitFlow)
{
cv::Mat flowxy[] = {cv::Mat(d_flowx), cv::Mat(d_flowy)};
cv::merge(flowxy, 2, flow);
flow.copyTo(flowBuf);
flowxy[0].copyTo(flowxBuf);
flowxy[1].copyTo(flowyBuf);
farn.flags |= cv::OPTFLOW_USE_INITIAL_FLOW;
farn(d_frame0, d_frame1, d_flowx, d_flowy);
}
WARMUP_OFF;
cv::calcOpticalFlowFarneback(
frame0, frame1, flow, farn.pyrScale, farn.numLevels, farn.winSize,
farn.numIters, farn.polyN, farn.polySigma, farn.flags);
std::vector<cv::Mat> flowxy;
cv::split(flow, flowxy);
double diff0 = 0.0;
TestSystem::instance().setAccurate(ExceptedMatSimilar(flowxy[0], cv::Mat(d_flowx), 0.1, diff0));
TestSystem::instance().setDiff(diff0);
double diff1 = 0.0;
TestSystem::instance().setAccurate(ExceptedMatSimilar(flowxy[1], cv::Mat(d_flowy), 0.1, diff1));
TestSystem::instance().setDiff(diff1);
if (useInitFlow)
{
cv::Mat flowx, flowy;
farn.flags = (flags | cv::OPTFLOW_USE_INITIAL_FLOW);
CPU_ON;
cv::calcOpticalFlowFarneback(
frame0, frame1, flowBuf, farn.pyrScale, farn.numLevels, farn.winSize,
farn.numIters, farn.polyN, farn.polySigma, farn.flags);
CPU_OFF;
GPU_ON;
farn(d_frame0, d_frame1, d_flowx, d_flowy);
GPU_OFF;
GPU_FULL_ON;
d_frame0.upload(frame0);
d_frame1.upload(frame1);
d_flowx.upload(flowxBuf);
d_flowy.upload(flowyBuf);
farn(d_frame0, d_frame1, d_flowx, d_flowy);
d_flowx.download(flowx);
d_flowy.download(flowy);
GPU_FULL_OFF;
}
else
{
cv::Mat flow, flowx, flowy;
cv::ocl::oclMat d_flowx, d_flowy;
farn.flags = flags;
CPU_ON;
cv::calcOpticalFlowFarneback(
frame0, frame1, flow, farn.pyrScale, farn.numLevels, farn.winSize,
farn.numIters, farn.polyN, farn.polySigma, farn.flags);
CPU_OFF;
GPU_ON;
farn(d_frame0, d_frame1, d_flowx, d_flowy);
GPU_OFF;
GPU_FULL_ON;
d_frame0.upload(frame0);
d_frame1.upload(frame1);
farn(d_frame0, d_frame1, d_flowx, d_flowy);
d_flowx.download(flowx);
d_flowy.download(flowy);
GPU_FULL_OFF;
}
}
}
}
}