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/**
* @file HoughCircle_Demo.cpp
* @brief Demo code for Hough Transform
* @author OpenCV team
*/
#include "opencv2/imgcodecs.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"
#include <iostream>
using namespace std;
using namespace cv;
namespace
{
// windows and trackbars name
const std::string windowName = "Hough Circle Detection Demo";
const std::string cannyThresholdTrackbarName = "Canny threshold";
const std::string accumulatorThresholdTrackbarName = "Accumulator Threshold";
const std::string usage = "Usage : tutorial_HoughCircle_Demo <path_to_input_image>\n";
// initial and max values of the parameters of interests.
const int cannyThresholdInitialValue = 100;
const int accumulatorThresholdInitialValue = 50;
const int maxAccumulatorThreshold = 200;
const int maxCannyThreshold = 255;
void HoughDetection(const Mat& src_gray, const Mat& src_display, int cannyThreshold, int accumulatorThreshold)
{
// will hold the results of the detection
std::vector<Vec3f> circles;
// runs the actual detection
HoughCircles( src_gray, circles, HOUGH_GRADIENT, 1, src_gray.rows/8, cannyThreshold, accumulatorThreshold, 0, 0 );
// clone the colour, input image for displaying purposes
Mat display = src_display.clone();
for( size_t i = 0; i < circles.size(); i++ )
{
Point center(cvRound(circles[i][0]), cvRound(circles[i][1]));
int radius = cvRound(circles[i][2]);
// circle center
circle( display, center, 3, Scalar(0,255,0), -1, 8, 0 );
// circle outline
circle( display, center, radius, Scalar(0,0,255), 3, 8, 0 );
}
// shows the results
imshow( windowName, display);
}
}
int main(int argc, char** argv)
{
Mat src, src_gray;
// Read the image
String imageName("../data/stuff.jpg"); // by default
if (argc > 1)
{
imageName = argv[1];
}
src = imread( imageName, IMREAD_COLOR );
if( src.empty() )
{
std::cerr<<"Invalid input image\n";
std::cout<<usage;
return -1;
}
// Convert it to gray
cvtColor( src, src_gray, COLOR_BGR2GRAY );
// Reduce the noise so we avoid false circle detection
GaussianBlur( src_gray, src_gray, Size(9, 9), 2, 2 );
//declare and initialize both parameters that are subjects to change
int cannyThreshold = cannyThresholdInitialValue;
int accumulatorThreshold = accumulatorThresholdInitialValue;
// create the main window, and attach the trackbars
namedWindow( windowName, WINDOW_AUTOSIZE );
createTrackbar(cannyThresholdTrackbarName, windowName, &cannyThreshold,maxCannyThreshold);
createTrackbar(accumulatorThresholdTrackbarName, windowName, &accumulatorThreshold, maxAccumulatorThreshold);
// infinite loop to display
// and refresh the content of the output image
// until the user presses q or Q
char key = 0;
while(key != 'q' && key != 'Q')
{
// those parameters cannot be =0
// so we must check here
cannyThreshold = std::max(cannyThreshold, 1);
accumulatorThreshold = std::max(accumulatorThreshold, 1);
//runs the detection, and update the display
HoughDetection(src_gray, src, cannyThreshold, accumulatorThreshold);
// get user key
key = (char)waitKey(10);
}
return 0;
}