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