mirror of
https://github.com/opencv/opencv.git
synced 2024-12-30 13:08:18 +08:00
181 lines
5.4 KiB
C++
181 lines
5.4 KiB
C++
#include <iostream>
|
|
#include <vector>
|
|
|
|
#include "opencv2/core.hpp"
|
|
#include <opencv2/core/utility.hpp>
|
|
#include "opencv2/imgproc.hpp"
|
|
#include "opencv2/highgui.hpp"
|
|
#include "opencv2/video.hpp"
|
|
#include "opencv2/cudaoptflow.hpp"
|
|
#include "opencv2/cudaimgproc.hpp"
|
|
|
|
using namespace std;
|
|
using namespace cv;
|
|
using namespace cv::cuda;
|
|
|
|
static void download(const GpuMat& d_mat, vector<Point2f>& 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<uchar>& 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<Point2f>& prevPts, const vector<Point2f>& nextPts, const vector<uchar>& 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 <typename T> inline T clamp (T x, T a, T b)
|
|
{
|
|
return ((x) > (a) ? ((x) < (b) ? (x) : (b)) : (a));
|
|
}
|
|
|
|
template <typename T> 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);
|
|
}
|
|
|
|
int main(int argc, const char* argv[])
|
|
{
|
|
const char* keys =
|
|
"{ h help | | print help message }"
|
|
"{ l left | ../data/pic1.png | specify left image }"
|
|
"{ r right | ../data/pic2.png | 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<string>("left");
|
|
string fname1 = cmd.get<string>("right");
|
|
|
|
if (fname0.empty() || fname1.empty())
|
|
{
|
|
cerr << "Missing input file names" << endl;
|
|
return -1;
|
|
}
|
|
|
|
bool useGray = cmd.has("gray");
|
|
int winSize = cmd.get<int>("win_size");
|
|
int maxLevel = cmd.get<int>("max_level");
|
|
int iters = cmd.get<int>("iters");
|
|
int points = cmd.get<int>("points");
|
|
double minDist = cmd.get<double>("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<cuda::CornersDetector> detector = cuda::createGoodFeaturesToTrackDetector(d_frame0Gray.type(), points, 0.01, minDist);
|
|
|
|
detector->detect(d_frame0Gray, d_prevPts);
|
|
|
|
// Sparse
|
|
|
|
Ptr<cuda::SparsePyrLKOpticalFlow> d_pyrLK = cuda::SparsePyrLKOpticalFlow::create(
|
|
Size(winSize, winSize), maxLevel, iters);
|
|
|
|
GpuMat d_frame0(frame0);
|
|
GpuMat d_frame1(frame1);
|
|
GpuMat d_frame1Gray(frame1Gray);
|
|
GpuMat d_nextPts;
|
|
GpuMat d_status;
|
|
|
|
d_pyrLK->calc(useGray ? d_frame0Gray : d_frame0, useGray ? d_frame1Gray : d_frame1, d_prevPts, d_nextPts, d_status);
|
|
|
|
// Draw arrows
|
|
|
|
vector<Point2f> prevPts(d_prevPts.cols);
|
|
download(d_prevPts, prevPts);
|
|
|
|
vector<Point2f> nextPts(d_nextPts.cols);
|
|
download(d_nextPts, nextPts);
|
|
|
|
vector<uchar> status(d_status.cols);
|
|
download(d_status, status);
|
|
|
|
drawArrows(frame0, prevPts, nextPts, status, Scalar(255, 0, 0));
|
|
|
|
imshow("PyrLK [Sparse]", frame0);
|
|
|
|
waitKey();
|
|
|
|
return 0;
|
|
}
|