Circle Detection - 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



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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)
#circles = cv2.HoughCircles(gray, cv.CV_HOUGH_GRADIENT, 1, 10)

circles = np.uint16(np.around(circles))

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()



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