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Tuning parameters for cv2.houghcircle() method ?

asked 2017-05-04 05:47:56 -0500

MayankSoni gravatar image

I am unable to get the desired parameters after applying the cv2.houghcircle() method


import cv2
import numpy as np

planets = cv2.imread('E:/Users/msoni3/Desktop/solar.jpg')
#planets = cv2.resize(planets, (1000,600))
gray_img = cv2.cvtColor(planets, cv2.COLOR_BGR2GRAY)
#img = cv2.medianBlur(gray_img, 5)
img = cv2.GaussianBlur(gray_img, (3,3), 0)

cimg = cv2.cvtColor(img,cv2.COLOR_GRAY2BGR)

circles = cv2.HoughCircles(img,cv2.HOUGH_GRADIENT,1,120,

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

for i in circles[0,:]:
    # draw the outer circle,(i[0],i[1]),i[2],(0,255,0),2)
    # draw the center of the circle,(i[0],i[1]),2,(0,0,255),3)

cv2.imwrite("planets_circles.jpg", planets)
cv2.imshow("HoughCirlces", planets)

MY INPUT IMAGE: image description

and my output is My Output

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answered 2017-05-04 13:57:34 -0500

electron gravatar image

updated 2017-05-04 14:17:21 -0500

Not sure that cv2.HoughCircles is the best option here. I recommend to try findContours also. Anyway question is about houghCircles, so example of code that detects all planets correctly:

import cv2
import numpy as np

planets = cv2.imread(path)
gray_img = cv2.cvtColor(planets, cv2.COLOR_BGR2GRAY)
gray_img = cv2.medianBlur(gray_img, 3)
circles = cv2.HoughCircles(gray_img, cv2.HOUGH_GRADIENT, 1, 10,
                    param1=350, param2=10, minRadius=2, maxRadius=13)
if circles is not None:  # circles found
    circles = np.uint16(np.around(circles))

    for i in circles[0,:]:,(i[0],i[1]),i[2],(0,255,0),2),(i[0],i[1]),2,(0,0,255),3)

cv2.imshow("HoughCirlces", planets)

What I corrected in your code: set minimum distance between circles centers from 120 to 10, changed min and max radius for circle, changed param1 and param2. Also I adde check for case if no circles were found.

Docs that I used: link

Hope this helps!

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Asked: 2017-05-04 05:47:56 -0500

Seen: 1,169 times

Last updated: May 04 '17