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Tutorial Hough Circles
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@@ -1,71 +0,0 @@
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#include "opencv2/imgcodecs.hpp"
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#include "opencv2/highgui.hpp"
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#include "opencv2/imgproc.hpp"
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#include <iostream>
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using namespace cv;
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using namespace std;
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static void help()
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{
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cout << "\nThis program demonstrates circle finding with the Hough transform.\n"
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"Usage:\n"
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"./houghcircles <image_name>, Default is ../data/board.jpg\n" << endl;
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}
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int main(int argc, char** argv)
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{
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cv::CommandLineParser parser(argc, argv,
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"{help h ||}{@image|../data/board.jpg|}"
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);
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if (parser.has("help"))
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{
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help();
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return 0;
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}
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//![load]
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string filename = parser.get<string>("@image");
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Mat img = imread(filename, IMREAD_COLOR);
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if(img.empty())
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{
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help();
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cout << "can not open " << filename << endl;
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return -1;
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}
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//![load]
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//![convert_to_gray]
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Mat gray;
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cvtColor(img, gray, COLOR_BGR2GRAY);
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//![convert_to_gray]
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//![reduce_noise]
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medianBlur(gray, gray, 5);
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//![reduce_noise]
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//![houghcircles]
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vector<Vec3f> circles;
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HoughCircles(gray, circles, HOUGH_GRADIENT, 1,
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gray.rows/16, // change this value to detect circles with different distances to each other
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100, 30, 1, 30 // change the last two parameters
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// (min_radius & max_radius) to detect larger circles
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);
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//![houghcircles]
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//![draw]
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for( size_t i = 0; i < circles.size(); i++ )
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{
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Vec3i c = circles[i];
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circle( img, Point(c[0], c[1]), c[2], Scalar(0,0,255), 3, LINE_AA);
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circle( img, Point(c[0], c[1]), 2, Scalar(0,255,0), 3, LINE_AA);
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}
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//![draw]
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//![display]
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imshow("detected circles", img);
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waitKey();
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//![display]
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return 0;
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}
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@@ -0,0 +1,65 @@
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/**
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* @file houghcircles.cpp
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* @brief This program demonstrates circle finding with the Hough transform
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*/
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#include "opencv2/imgcodecs.hpp"
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#include "opencv2/highgui.hpp"
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#include "opencv2/imgproc.hpp"
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using namespace cv;
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using namespace std;
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int main(int argc, char** argv)
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{
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//![load]
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const char* filename = argc >=2 ? argv[1] : "../../../data/smarties.png";
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// Loads an image
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Mat src = imread( filename, IMREAD_COLOR );
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// Check if image is loaded fine
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if(src.empty()){
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printf(" Error opening image\n");
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printf(" Program Arguments: [image_name -- default %s] \n", filename);
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return -1;
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}
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//![load]
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//![convert_to_gray]
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Mat gray;
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cvtColor(src, gray, COLOR_BGR2GRAY);
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//![convert_to_gray]
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//![reduce_noise]
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medianBlur(gray, gray, 5);
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//![reduce_noise]
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//![houghcircles]
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vector<Vec3f> circles;
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HoughCircles(gray, circles, HOUGH_GRADIENT, 1,
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gray.rows/16, // change this value to detect circles with different distances to each other
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100, 30, 1, 30 // change the last two parameters
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// (min_radius & max_radius) to detect larger circles
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);
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//![houghcircles]
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//![draw]
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for( size_t i = 0; i < circles.size(); i++ )
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{
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Vec3i c = circles[i];
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Point center = Point(c[0], c[1]);
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// circle center
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circle( src, center, 1, Scalar(0,100,100), 3, LINE_AA);
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// circle outline
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int radius = c[2];
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circle( src, center, radius, Scalar(255,0,255), 3, LINE_AA);
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}
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//![draw]
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//![display]
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imshow("detected circles", src);
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waitKey();
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//![display]
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return 0;
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}
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package sample;
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/**
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* @file HoughCircles.java
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* @brief This program demonstrates circle finding with the Hough transform
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*/
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import org.opencv.core.*;
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import org.opencv.core.Point;
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import org.opencv.highgui.HighGui;
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import org.opencv.imgcodecs.Imgcodecs;
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import org.opencv.imgproc.Imgproc;
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class HoughCirclesRun {
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public void run(String[] args) {
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//! [load]
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String default_file = "../../../../data/smarties.png";
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String filename = ((args.length > 0) ? args[0] : default_file);
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// Load an image
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Mat src = Imgcodecs.imread(filename, Imgcodecs.IMREAD_COLOR);
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// Check if image is loaded fine
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if( src.empty() ) {
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System.out.println("Error opening image!");
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System.out.println("Program Arguments: [image_name -- default "
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+ default_file +"] \n");
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System.exit(-1);
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}
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//! [load]
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//! [convert_to_gray]
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Mat gray = new Mat();
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Imgproc.cvtColor(src, gray, Imgproc.COLOR_BGR2GRAY);
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//! [convert_to_gray]
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//![reduce_noise]
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Imgproc.medianBlur(gray, gray, 5);
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//![reduce_noise]
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//! [houghcircles]
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Mat circles = new Mat();
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Imgproc.HoughCircles(gray, circles, Imgproc.HOUGH_GRADIENT, 1.0,
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(double)gray.rows()/16, // change this value to detect circles with different distances to each other
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100.0, 30.0, 1, 30); // change the last two parameters
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// (min_radius & max_radius) to detect larger circles
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//! [houghcircles]
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//! [draw]
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for (int x = 0; x < circles.cols(); x++) {
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double[] c = circles.get(0, x);
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Point center = new Point(Math.round(c[0]), Math.round(c[1]));
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// circle center
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Imgproc.circle(src, center, 1, new Scalar(0,100,100), 3, 8, 0 );
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// circle outline
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int radius = (int) Math.round(c[2]);
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Imgproc.circle(src, center, radius, new Scalar(255,0,255), 3, 8, 0 );
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}
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//! [draw]
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//! [display]
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HighGui.imshow("detected circles", src);
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HighGui.waitKey();
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//! [display]
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System.exit(0);
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}
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}
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public class HoughCircles {
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public static void main(String[] args) {
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// Load the native library.
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System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
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new HoughCirclesRun().run(args);
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}
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}
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@@ -0,0 +1,59 @@
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import sys
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import cv2
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import numpy as np
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def main(argv):
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## [load]
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default_file = "../../../../data/smarties.png"
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filename = argv[0] if len(argv) > 0 else default_file
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# Loads an image
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src = cv2.imread(filename, cv2.IMREAD_COLOR)
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# Check if image is loaded fine
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if src is None:
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print ('Error opening image!')
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print ('Usage: hough_circle.py [image_name -- default ' + default_file + '] \n')
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return -1
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## [load]
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## [convert_to_gray]
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# Convert it to gray
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gray = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY)
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## [convert_to_gray]
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## [reduce_noise]
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# Reduce the noise to avoid false circle detection
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gray = cv2.medianBlur(gray, 5)
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## [reduce_noise]
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## [houghcircles]
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rows = gray.shape[0]
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circles = cv2.HoughCircles(gray, cv2.HOUGH_GRADIENT, 1, rows / 8,
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param1=100, param2=30,
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minRadius=1, maxRadius=30)
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## [houghcircles]
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## [draw]
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if circles is not None:
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circles = np.uint16(np.around(circles))
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for i in circles[0, :]:
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center = (i[0], i[1])
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# circle center
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cv2.circle(src, center, 1, (0, 100, 100), 3)
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# circle outline
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radius = i[2]
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cv2.circle(src, center, radius, (255, 0, 255), 3)
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## [draw]
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## [display]
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cv2.imshow("detected circles", src)
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cv2.waitKey(0)
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## [display]
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return 0
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if __name__ == "__main__":
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main(sys.argv[1:])
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