1 /** 2 * @file HoughCircle_Demo.cpp 3 * @brief Demo code for Hough Transform 4 * @author OpenCV team 5 */ 6 7 #include "opencv2/imgcodecs.hpp" 8 #include "opencv2/highgui/highgui.hpp" 9 #include "opencv2/imgproc/imgproc.hpp" 10 #include <iostream> 11 12 using namespace std; 13 using namespace cv; 14 15 namespace 16 { 17 // windows and trackbars name 18 const std::string windowName = "Hough Circle Detection Demo"; 19 const std::string cannyThresholdTrackbarName = "Canny threshold"; 20 const std::string accumulatorThresholdTrackbarName = "Accumulator Threshold"; 21 const std::string usage = "Usage : tutorial_HoughCircle_Demo <path_to_input_image>\n"; 22 23 // initial and max values of the parameters of interests. 24 const int cannyThresholdInitialValue = 200; 25 const int accumulatorThresholdInitialValue = 50; 26 const int maxAccumulatorThreshold = 200; 27 const int maxCannyThreshold = 255; 28 29 void HoughDetection(const Mat& src_gray, const Mat& src_display, int cannyThreshold, int accumulatorThreshold) 30 { 31 // will hold the results of the detection 32 std::vector<Vec3f> circles; 33 // runs the actual detection 34 HoughCircles( src_gray, circles, HOUGH_GRADIENT, 1, src_gray.rows/8, cannyThreshold, accumulatorThreshold, 0, 0 ); 35 36 // clone the colour, input image for displaying purposes 37 Mat display = src_display.clone(); 38 for( size_t i = 0; i < circles.size(); i++ ) 39 { 40 Point center(cvRound(circles[i][0]), cvRound(circles[i][1])); 41 int radius = cvRound(circles[i][2]); 42 // circle center 43 circle( display, center, 3, Scalar(0,255,0), -1, 8, 0 ); 44 // circle outline 45 circle( display, center, radius, Scalar(0,0,255), 3, 8, 0 ); 46 } 47 48 // shows the results 49 imshow( windowName, display); 50 } 51 } 52 53 54 int main(int argc, char** argv) 55 { 56 Mat src, src_gray; 57 58 if (argc < 2) 59 { 60 std::cerr<<"No input image specified\n"; 61 std::cout<<usage; 62 return -1; 63 } 64 65 // Read the image 66 src = imread( argv[1], 1 ); 67 68 if( src.empty() ) 69 { 70 std::cerr<<"Invalid input image\n"; 71 std::cout<<usage; 72 return -1; 73 } 74 75 // Convert it to gray 76 cvtColor( src, src_gray, COLOR_BGR2GRAY ); 77 78 // Reduce the noise so we avoid false circle detection 79 GaussianBlur( src_gray, src_gray, Size(9, 9), 2, 2 ); 80 81 //declare and initialize both parameters that are subjects to change 82 int cannyThreshold = cannyThresholdInitialValue; 83 int accumulatorThreshold = accumulatorThresholdInitialValue; 84 85 // create the main window, and attach the trackbars 86 namedWindow( windowName, WINDOW_AUTOSIZE ); 87 createTrackbar(cannyThresholdTrackbarName, windowName, &cannyThreshold,maxCannyThreshold); 88 createTrackbar(accumulatorThresholdTrackbarName, windowName, &accumulatorThreshold, maxAccumulatorThreshold); 89 90 // infinite loop to display 91 // and refresh the content of the output image 92 // until the user presses q or Q 93 int key = 0; 94 while(key != 'q' && key != 'Q') 95 { 96 // those paramaters cannot be =0 97 // so we must check here 98 cannyThreshold = std::max(cannyThreshold, 1); 99 accumulatorThreshold = std::max(accumulatorThreshold, 1); 100 101 //runs the detection, and update the display 102 HoughDetection(src_gray, src, cannyThreshold, accumulatorThreshold); 103 104 // get user key 105 key = waitKey(10); 106 } 107 108 return 0; 109 } 110
