#include #include #include "opencv2/core.hpp" #include #include "opencv2/imgproc.hpp" #include "opencv2/highgui.hpp" #include "opencv2/video.hpp" #include "opencv2/gpuoptflow.hpp" #include "opencv2/gpuimgproc.hpp" using namespace std; using namespace cv; using namespace cv::cuda; static void download(const GpuMat& d_mat, vector& vec) { vec.resize(d_mat.cols); Mat mat(1, d_mat.cols, CV_32FC2, (void*)&vec[0]); d_mat.download(mat); } static void download(const GpuMat& d_mat, vector& vec) { 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& prevPts, const vector& nextPts, const vector& status, Scalar line_color = Scalar(0, 0, 255)) { 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); } } } template inline T clamp (T x, T a, T b) { return ((x) > (a) ? ((x) < (b) ? (x) : (b)) : (a)); } template inline T mapValue(T x, T a, T b, T c, T d) { x = clamp(x, a, b); return c + (d - c) * (x - a) / (b - a); } static void getFlowField(const Mat& u, const Mat& v, Mat& flowField) { float maxDisplacement = 1.0f; for (int i = 0; i < u.rows; ++i) { const float* ptr_u = u.ptr(i); const float* ptr_v = v.ptr(i); for (int j = 0; j < u.cols; ++j) { float d = max(fabsf(ptr_u[j]), fabsf(ptr_v[j])); if (d > maxDisplacement) maxDisplacement = d; } } flowField.create(u.size(), CV_8UC4); for (int i = 0; i < flowField.rows; ++i) { const float* ptr_u = u.ptr(i); const float* ptr_v = v.ptr(i); Vec4b* row = flowField.ptr(i); for (int j = 0; j < flowField.cols; ++j) { row[j][0] = 0; row[j][1] = static_cast (mapValue (-ptr_v[j], -maxDisplacement, maxDisplacement, 0.0f, 255.0f)); row[j][2] = static_cast (mapValue ( ptr_u[j], -maxDisplacement, maxDisplacement, 0.0f, 255.0f)); row[j][3] = 255; } } } int main(int argc, const char* argv[]) { const char* keys = "{ h help | | print help message }" "{ l left | | specify left image }" "{ r right | | specify right image }" "{ gray | | use grayscale sources [PyrLK Sparse] }" "{ win_size | 21 | specify windows size [PyrLK] }" "{ max_level | 3 | specify max level [PyrLK] }" "{ iters | 30 | specify iterations count [PyrLK] }" "{ points | 4000 | specify points count [GoodFeatureToTrack] }" "{ min_dist | 0 | specify minimal distance between points [GoodFeatureToTrack] }"; CommandLineParser cmd(argc, argv, keys); if (cmd.has("help") || !cmd.check()) { cmd.printMessage(); cmd.printErrors(); return 0; } string fname0 = cmd.get("left"); string fname1 = cmd.get("right"); if (fname0.empty() || fname1.empty()) { cerr << "Missing input file names" << endl; return -1; } bool useGray = cmd.has("gray"); int winSize = cmd.get("win_size"); int maxLevel = cmd.get("max_level"); int iters = cmd.get("iters"); int points = cmd.get("points"); double minDist = cmd.get("min_dist"); Mat frame0 = imread(fname0); Mat frame1 = imread(fname1); if (frame0.empty() || frame1.empty()) { cout << "Can't load input images" << endl; return -1; } namedWindow("PyrLK [Sparse]", WINDOW_NORMAL); namedWindow("PyrLK [Dense] Flow Field", WINDOW_NORMAL); cout << "Image size : " << frame0.cols << " x " << frame0.rows << endl; cout << "Points count : " << points << endl; cout << endl; Mat frame0Gray; cv::cvtColor(frame0, frame0Gray, COLOR_BGR2GRAY); Mat frame1Gray; cv::cvtColor(frame1, frame1Gray, COLOR_BGR2GRAY); // goodFeaturesToTrack GpuMat d_frame0Gray(frame0Gray); GpuMat d_prevPts; Ptr detector = cuda::createGoodFeaturesToTrackDetector(d_frame0Gray.type(), points, 0.01, minDist); detector->detect(d_frame0Gray, d_prevPts); // Sparse PyrLKOpticalFlow d_pyrLK; d_pyrLK.winSize.width = winSize; d_pyrLK.winSize.height = winSize; d_pyrLK.maxLevel = maxLevel; d_pyrLK.iters = iters; GpuMat d_frame0(frame0); GpuMat d_frame1(frame1); GpuMat d_frame1Gray(frame1Gray); GpuMat d_nextPts; GpuMat d_status; d_pyrLK.sparse(useGray ? d_frame0Gray : d_frame0, useGray ? d_frame1Gray : d_frame1, d_prevPts, d_nextPts, d_status); // Draw arrows vector prevPts(d_prevPts.cols); download(d_prevPts, prevPts); vector nextPts(d_nextPts.cols); download(d_nextPts, nextPts); vector status(d_status.cols); download(d_status, status); drawArrows(frame0, prevPts, nextPts, status, Scalar(255, 0, 0)); imshow("PyrLK [Sparse]", frame0); // Dense GpuMat d_u; GpuMat d_v; d_pyrLK.dense(d_frame0Gray, d_frame1Gray, d_u, d_v); // Draw flow field Mat flowField; getFlowField(Mat(d_u), Mat(d_v), flowField); imshow("PyrLK [Dense] Flow Field", flowField); waitKey(); return 0; }