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Open Source Computer Vision Library
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56 lines
1.3 KiB
56 lines
1.3 KiB
/** |
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* @file HoughCircle_Demo.cpp |
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* @brief Demo code for Hough Transform |
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* @author OpenCV team |
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*/ |
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#include "opencv2/highgui/highgui.hpp" |
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#include "opencv2/imgproc/imgproc.hpp" |
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#include <iostream> |
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#include <stdio.h> |
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using namespace std; |
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using namespace cv; |
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/** |
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* @function main |
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*/ |
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int main(int, char** argv) |
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{ |
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Mat src, src_gray; |
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/// Read the image |
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src = imread( argv[1], 1 ); |
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if( !src.data ) |
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{ return -1; } |
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/// Convert it to gray |
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cvtColor( src, src_gray, COLOR_BGR2GRAY ); |
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/// Reduce the noise so we avoid false circle detection |
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GaussianBlur( src_gray, src_gray, Size(9, 9), 2, 2 ); |
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vector<Vec3f> circles; |
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/// Apply the Hough Transform to find the circles |
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HoughCircles( src_gray, circles, HOUGH_GRADIENT, 1, src_gray.rows/8, 200, 100, 0, 0 ); |
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/// Draw the circles detected |
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for( size_t i = 0; i < circles.size(); i++ ) |
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{ |
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Point center(cvRound(circles[i][0]), cvRound(circles[i][1])); |
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int radius = cvRound(circles[i][2]); |
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// circle center |
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circle( src, center, 3, Scalar(0,255,0), -1, 8, 0 ); |
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// circle outline |
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circle( src, center, radius, Scalar(0,0,255), 3, 8, 0 ); |
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} |
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/// Show your results |
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namedWindow( "Hough Circle Transform Demo", WINDOW_AUTOSIZE ); |
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imshow( "Hough Circle Transform Demo", src ); |
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waitKey(0); |
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return 0; |
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}
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