Circle Detection with Hough Cirlces

cv2.HoughCircles(image, method, dp, MinDist, param1, param2, minRadius, MaxRadius)

• Method — currently only cv2.HOUGH_GRADIENT available
• dp — Inverse ratio of accumulator resolution
• MinDist — the minimum distance between the center of detected circles
• param1 — Gradient value used in the edge detection
• param2 — Accumulator threshold for the HOUGH_GRADIENT method, lower allows more circles to be detected (false positives)
• minRadius — limits the smallest circle to this size (via radius)
• MaxRadius — similarly sets the limit for the largest circles

import cv2
import numpy as np
import cv2.cv as cv
image = cv2.imread('images/bottlecaps.jpg')
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
blur = cv2.medianBlur(gray, 5)
circles = cv2.HoughCircles(blur, cv.CV_HOUGH_GRADIENT, 1.5, 10)
for i in circles[0,:]:
       # draw the outer circle
       cv2.circle(image,(i[0], i[1]), i[2], (255, 0, 0), 2)
      
       # draw the center of the circle
       cv2.circle(image, (i[0], i[1]), 2, (0, 255, 0), 5)
cv2.imshow('detected circles', image)
cv2.waitKey(0)
cv2.destroyAllWindows()