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Open Source Computer Vision Library
https://opencv.org/
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180 lines
5.4 KiB
180 lines
5.4 KiB
#include <iostream> |
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#include <vector> |
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#include "opencv2/core.hpp" |
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#include <opencv2/core/utility.hpp> |
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#include "opencv2/imgproc.hpp" |
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#include "opencv2/highgui.hpp" |
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#include "opencv2/video.hpp" |
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#include "opencv2/cudaoptflow.hpp" |
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#include "opencv2/cudaimgproc.hpp" |
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using namespace std; |
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using namespace cv; |
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using namespace cv::cuda; |
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static void download(const GpuMat& d_mat, vector<Point2f>& vec) |
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{ |
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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 GpuMat& d_mat, vector<uchar>& vec) |
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{ |
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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, 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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template <typename T> inline T clamp (T x, T a, T b) |
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{ |
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return ((x) > (a) ? ((x) < (b) ? (x) : (b)) : (a)); |
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} |
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template <typename T> inline T mapValue(T x, T a, T b, T c, T d) |
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{ |
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x = clamp(x, a, b); |
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return c + (d - c) * (x - a) / (b - a); |
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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 | | print help message }" |
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"{ l left | ../data/pic1.png | specify left image }" |
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"{ r right | ../data/pic2.png | specify right image }" |
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"{ gray | | use grayscale sources [PyrLK Sparse] }" |
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"{ win_size | 21 | specify windows size [PyrLK] }" |
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"{ max_level | 3 | specify max level [PyrLK] }" |
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"{ iters | 30 | specify iterations count [PyrLK] }" |
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"{ points | 4000 | specify points count [GoodFeatureToTrack] }" |
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"{ min_dist | 0 | specify minimal distance between points [GoodFeatureToTrack] }"; |
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CommandLineParser cmd(argc, argv, keys); |
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if (cmd.has("help") || !cmd.check()) |
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{ |
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cmd.printMessage(); |
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cmd.printErrors(); |
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return 0; |
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} |
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string fname0 = cmd.get<string>("left"); |
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string fname1 = cmd.get<string>("right"); |
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if (fname0.empty() || fname1.empty()) |
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{ |
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cerr << "Missing input file names" << endl; |
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return -1; |
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} |
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bool useGray = cmd.has("gray"); |
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int winSize = cmd.get<int>("win_size"); |
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int maxLevel = cmd.get<int>("max_level"); |
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int iters = cmd.get<int>("iters"); |
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int points = cmd.get<int>("points"); |
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double minDist = cmd.get<double>("min_dist"); |
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Mat frame0 = imread(fname0); |
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Mat frame1 = imread(fname1); |
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if (frame0.empty() || frame1.empty()) |
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{ |
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cout << "Can't load input images" << endl; |
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return -1; |
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} |
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namedWindow("PyrLK [Sparse]", WINDOW_NORMAL); |
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namedWindow("PyrLK [Dense] Flow Field", WINDOW_NORMAL); |
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cout << "Image size : " << frame0.cols << " x " << frame0.rows << endl; |
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cout << "Points count : " << points << endl; |
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cout << endl; |
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Mat frame0Gray; |
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cv::cvtColor(frame0, frame0Gray, COLOR_BGR2GRAY); |
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Mat frame1Gray; |
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cv::cvtColor(frame1, frame1Gray, COLOR_BGR2GRAY); |
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// goodFeaturesToTrack |
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GpuMat d_frame0Gray(frame0Gray); |
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GpuMat d_prevPts; |
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Ptr<cuda::CornersDetector> detector = cuda::createGoodFeaturesToTrackDetector(d_frame0Gray.type(), points, 0.01, minDist); |
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detector->detect(d_frame0Gray, d_prevPts); |
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// Sparse |
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Ptr<cuda::SparsePyrLKOpticalFlow> d_pyrLK = cuda::SparsePyrLKOpticalFlow::create( |
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Size(winSize, winSize), maxLevel, iters); |
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GpuMat d_frame0(frame0); |
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GpuMat d_frame1(frame1); |
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GpuMat d_frame1Gray(frame1Gray); |
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GpuMat d_nextPts; |
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GpuMat d_status; |
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d_pyrLK->calc(useGray ? d_frame0Gray : d_frame0, useGray ? d_frame1Gray : d_frame1, d_prevPts, d_nextPts, d_status); |
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// Draw arrows |
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vector<Point2f> prevPts(d_prevPts.cols); |
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download(d_prevPts, prevPts); |
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vector<Point2f> nextPts(d_nextPts.cols); |
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download(d_nextPts, nextPts); |
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vector<uchar> status(d_status.cols); |
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download(d_status, status); |
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drawArrows(frame0, prevPts, nextPts, status, Scalar(255, 0, 0)); |
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imshow("PyrLK [Sparse]", frame0); |
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waitKey(); |
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return 0; |
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}
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