Open Source Computer Vision Library https://opencv.org/
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#include <iostream>
#include <vector>
#include <iomanip>
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/ocl/ocl.hpp"
#include "opencv2/video/video.hpp"
using namespace std;
using namespace cv;
using namespace cv::ocl;
typedef unsigned char uchar;
#define LOOP_NUM 10
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int64 work_begin = 0;
int64 work_end = 0;
static void workBegin()
{
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work_begin = getTickCount();
}
static void workEnd()
{
work_end += (getTickCount() - work_begin);
}
static double getTime()
{
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return work_end * 1000. / getTickFrequency();
}
static void download(const oclMat& d_mat, vector<Point2f>& vec)
{
vec.clear();
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vec.resize(d_mat.cols);
Mat mat(1, d_mat.cols, CV_32FC2, (void*)&vec[0]);
d_mat.download(mat);
}
static void download(const oclMat& d_mat, vector<uchar>& vec)
{
vec.clear();
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vec.resize(d_mat.cols);
Mat mat(1, d_mat.cols, CV_8UC1, (void*)&vec[0]);
d_mat.download(mat);
}
static void drawArrows(Mat& frame, const vector<Point2f>& prevPts, const vector<Point2f>& nextPts, const vector<uchar>& status,
Scalar line_color = Scalar(0, 0, 255))
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{
for (size_t i = 0; i < prevPts.size(); ++i)
{
if (status[i])
{
int line_thickness = 1;
Point p = prevPts[i];
Point q = nextPts[i];
double angle = atan2((double) p.y - q.y, (double) p.x - q.x);
double hypotenuse = sqrt( (double)(p.y - q.y)*(p.y - q.y) + (double)(p.x - q.x)*(p.x - q.x) );
if (hypotenuse < 1.0)
continue;
// Here we lengthen the arrow by a factor of three.
q.x = (int) (p.x - 3 * hypotenuse * cos(angle));
q.y = (int) (p.y - 3 * hypotenuse * sin(angle));
// Now we draw the main line of the arrow.
line(frame, p, q, line_color, line_thickness);
// Now draw the tips of the arrow. I do some scaling so that the
// tips look proportional to the main line of the arrow.
p.x = (int) (q.x + 9 * cos(angle + CV_PI / 4));
p.y = (int) (q.y + 9 * sin(angle + CV_PI / 4));
line(frame, p, q, line_color, line_thickness);
p.x = (int) (q.x + 9 * cos(angle - CV_PI / 4));
p.y = (int) (q.y + 9 * sin(angle - CV_PI / 4));
line(frame, p, q, line_color, line_thickness);
}
}
}
int main(int argc, const char* argv[])
{
const char* keys =
"{ h | help | false | print help message }"
"{ l | left | | specify left image }"
"{ r | right | | specify right image }"
"{ c | camera | 0 | specify camera id }"
"{ s | use_cpu | false | use cpu or gpu to process the image }"
"{ v | video | | use video as input }"
"{ o | output | pyrlk_output.jpg| specify output save path when input is images }"
"{ p | points | 1000 | specify points count [GoodFeatureToTrack] }"
"{ m | min_dist | 0 | specify minimal distance between points [GoodFeatureToTrack] }";
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CommandLineParser cmd(argc, argv, keys);
if (cmd.get<bool>("help"))
{
cout << "Usage: pyrlk_optical_flow [options]" << endl;
cout << "Available options:" << endl;
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cmd.printParams();
return EXIT_SUCCESS;
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}
bool defaultPicturesFail = false;
string fname0 = cmd.get<string>("l");
string fname1 = cmd.get<string>("r");
string vdofile = cmd.get<string>("v");
string outfile = cmd.get<string>("o");
int points = cmd.get<int>("p");
double minDist = cmd.get<double>("m");
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bool useCPU = cmd.get<bool>("s");
int inputName = cmd.get<int>("c");
oclMat d_nextPts, d_status;
GoodFeaturesToTrackDetector_OCL d_features(points);
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Mat frame0 = imread(fname0, cv::IMREAD_GRAYSCALE);
Mat frame1 = imread(fname1, cv::IMREAD_GRAYSCALE);
PyrLKOpticalFlow d_pyrLK;
vector<cv::Point2f> pts(points);
vector<cv::Point2f> nextPts(points);
vector<unsigned char> status(points);
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vector<float> err;
cout << "Points count : " << points << endl << endl;
if (frame0.empty() || frame1.empty())
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{
CvCapture* capture = 0;
Mat frame, frameCopy;
Mat frame0Gray, frame1Gray;
Mat ptr0, ptr1;
if(vdofile.empty())
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capture = cvCaptureFromCAM( inputName );
else
capture = cvCreateFileCapture(vdofile.c_str());
int c = inputName ;
if(!capture)
{
if(vdofile.empty())
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cout << "Capture from CAM " << c << " didn't work" << endl;
else
cout << "Capture from file " << vdofile << " failed" <<endl;
if (defaultPicturesFail)
return EXIT_FAILURE;
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goto nocamera;
}
cout << "In capture ..." << endl;
for(int i = 0;; i++)
{
frame = cvQueryFrame( capture );
if( frame.empty() )
break;
if (i == 0)
{
frame.copyTo( frame0 );
cvtColor(frame0, frame0Gray, COLOR_BGR2GRAY);
}
else
{
if (i%2 == 1)
{
frame.copyTo(frame1);
cvtColor(frame1, frame1Gray, COLOR_BGR2GRAY);
ptr0 = frame0Gray;
ptr1 = frame1Gray;
}
else
{
frame.copyTo(frame0);
cvtColor(frame0, frame0Gray, COLOR_BGR2GRAY);
ptr0 = frame1Gray;
ptr1 = frame0Gray;
}
if (useCPU)
{
pts.clear();
goodFeaturesToTrack(ptr0, pts, points, 0.01, 0.0);
if(pts.size() == 0)
continue;
calcOpticalFlowPyrLK(ptr0, ptr1, pts, nextPts, status, err);
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}
else
{
oclMat d_img(ptr0), d_prevPts;
d_features(d_img, d_prevPts);
if(!d_prevPts.rows || !d_prevPts.cols)
continue;
d_pyrLK.sparse(d_img, oclMat(ptr1), d_prevPts, d_nextPts, d_status);
d_features.downloadPoints(d_prevPts,pts);
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download(d_nextPts, nextPts);
download(d_status, status);
}
if (i%2 == 1)
frame1.copyTo(frameCopy);
else
frame0.copyTo(frameCopy);
drawArrows(frameCopy, pts, nextPts, status, Scalar(255, 0, 0));
imshow("PyrLK [Sparse]", frameCopy);
}
if( waitKey( 10 ) >= 0 )
break;
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}
cvReleaseCapture( &capture );
}
else
{
nocamera:
for(int i = 0; i <= LOOP_NUM; i ++)
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{
cout << "loop" << i << endl;
if (i > 0) workBegin();
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if (useCPU)
{
goodFeaturesToTrack(frame0, pts, points, 0.01, minDist);
calcOpticalFlowPyrLK(frame0, frame1, pts, nextPts, status, err);
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}
else
{
oclMat d_img(frame0), d_prevPts;
d_features(d_img, d_prevPts);
d_pyrLK.sparse(d_img, oclMat(frame1), d_prevPts, d_nextPts, d_status);
d_features.downloadPoints(d_prevPts, pts);
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download(d_nextPts, nextPts);
download(d_status, status);
}
if (i > 0 && i <= LOOP_NUM)
workEnd();
if (i == LOOP_NUM)
{
if (useCPU)
cout << "average CPU time (noCamera) : ";
else
cout << "average GPU time (noCamera) : ";
cout << getTime() / LOOP_NUM << " ms" << endl;
drawArrows(frame0, pts, nextPts, status, Scalar(255, 0, 0));
imshow("PyrLK [Sparse]", frame0);
imwrite(outfile, frame0);
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}
}
}
waitKey();
return EXIT_SUCCESS;
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}