Open Source Computer Vision Library https://opencv.org/
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#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/gpu.hpp"
using namespace std;
using namespace cv;
using namespace cv::gpu;
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);
}
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<float>(i);
const float* ptr_v = v.ptr<float>(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<float>(i);
const float* ptr_v = v.ptr<float>(i);
Vec4b* row = flowField.ptr<Vec4b>(i);
for (int j = 0; j < flowField.cols; ++j)
{
row[j][0] = 0;
row[j][1] = static_cast<unsigned char> (mapValue (-ptr_v[j], -maxDisplacement, maxDisplacement, 0.0f, 255.0f));
row[j][2] = static_cast<unsigned char> (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<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<gpu::CornersDetector> detector = gpu::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<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);
// 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;
}