Open Source Computer Vision Library https://opencv.org/
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#include "opencv2/imgcodecs.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"
#include <iostream>
using namespace cv;
using namespace std;
static void help()
{
cout << "\nThis program demonstrates circle finding with the Hough transform.\n"
"Usage:\n"
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"./houghcircles <image_name>, Default is ../data/board.jpg\n" << endl;
}
int main(int argc, char** argv)
{
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cv::CommandLineParser parser(argc, argv,
"{help h ||}{@image|../data/board.jpg|}"
);
if (parser.has("help"))
{
help();
return 0;
}
//![load]
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string filename = parser.get<string>("@image");
Mat img = imread(filename, IMREAD_COLOR);
if(img.empty())
{
help();
cout << "can not open " << filename << endl;
return -1;
}
//![load]
//![convert_to_gray]
Mat gray;
cvtColor(img, gray, COLOR_BGR2GRAY);
//![convert_to_gray]
//![reduce_noise]
medianBlur(gray, gray, 5);
//![reduce_noise]
//![houghcircles]
vector<Vec3f> circles;
HoughCircles(gray, circles, HOUGH_GRADIENT, 1,
gray.rows/16, // change this value to detect circles with different distances to each other
100, 30, 1, 30 // change the last two parameters
// (min_radius & max_radius) to detect larger circles
);
//![houghcircles]
//![draw]
for( size_t i = 0; i < circles.size(); i++ )
{
Vec3i c = circles[i];
circle( img, Point(c[0], c[1]), c[2], Scalar(0,0,255), 3, LINE_AA);
circle( img, Point(c[0], c[1]), 2, Scalar(0,255,0), 3, LINE_AA);
}
//![draw]
//![display]
imshow("detected circles", img);
waitKey();
//![display]
return 0;
}