Merge pull request #1873 from abak:hough_24

pull/1879/merge
Roman Donchenko 11 years ago committed by OpenCV Buildbot
commit 19b88a17bf
  1. 108
      samples/cpp/tutorial_code/ImgTrans/HoughCircle_Demo.cpp

@ -7,49 +7,101 @@
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
#include <stdio.h>
using namespace cv;
/**
* @function main
*/
int main(int, char** argv)
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 = 200;
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, CV_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;
Mat src, src_gray;
if (argc < 2)
{
std::cerr<<"No input image specified\n";
std::cout<<usage;
return -1;
}
/// Read the image
src = imread( argv[1], 1 );
// Read the image
src = imread( argv[1], 1 );
if( !src.data )
{ return -1; }
if( !src.data )
{
std::cerr<<"Invalid input image\n";
std::cout<<usage;
return -1;
}
/// Convert it to gray
// Convert it to gray
cvtColor( src, src_gray, COLOR_BGR2GRAY );
/// Reduce the noise so we avoid false circle detection
// Reduce the noise so we avoid false circle detection
GaussianBlur( src_gray, src_gray, Size(9, 9), 2, 2 );
vector<Vec3f> circles;
//declare and initialize both parameters that are subjects to change
int cannyThreshold = cannyThresholdInitialValue;
int accumulatorThreshold = accumulatorThresholdInitialValue;
/// Apply the Hough Transform to find the circles
HoughCircles( src_gray, circles, CV_HOUGH_GRADIENT, 1, src_gray.rows/8, 200, 100, 0, 0 );
// create the main window, and attach the trackbars
namedWindow( windowName, WINDOW_AUTOSIZE );
createTrackbar(cannyThresholdTrackbarName, windowName, &cannyThreshold,maxCannyThreshold);
createTrackbar(accumulatorThresholdTrackbarName, windowName, &accumulatorThreshold, maxAccumulatorThreshold);
/// Draw the circles detected
for( size_t i = 0; i < circles.size(); i++ )
// infinite loop to display
// and refresh the content of the output image
// until the user presses q or Q
int key = 0;
while(key != 'q' && key != 'Q')
{
Point center(cvRound(circles[i][0]), cvRound(circles[i][1]));
int radius = cvRound(circles[i][2]);
// circle center
circle( src, center, 3, Scalar(0,255,0), -1, 8, 0 );
// circle outline
circle( src, center, radius, Scalar(0,0,255), 3, 8, 0 );
}
// those paramaters cannot be =0
// so we must check here
cannyThreshold = std::max(cannyThreshold, 1);
accumulatorThreshold = std::max(accumulatorThreshold, 1);
/// Show your results
namedWindow( "Hough Circle Transform Demo", WINDOW_AUTOSIZE );
imshow( "Hough Circle Transform Demo", src );
//runs the detection, and update the display
HoughDetection(src_gray, src, cannyThreshold, accumulatorThreshold);
// get user key
key = waitKey(10);
}
waitKey(0);
return 0;
}

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