Circle detection without overlapping

Question

I want to do circle detection under the condition that: overlap circles will be count as 1 circle.

Particularly, when I do circle detection and put the letter \"P\" to e

Answer 1

I would suggest using contours instead. However, if you do want to use HoughCircles, look at the 4th parameter in the function. Changing this, I could get rid of the overlappings. Additionally, I tweaked a bit the parameters for canny threshold in the HoughCircles function until I got the desired results. I'd suggest understanding the parameters well before coming up with a conclusion.

Code:

import cv2
import numpy as np

arr = cv2.imread("U:/SO/032OR.jpg")
print(arr.shape)
imggray = cv2.cvtColor(arr, cv2.COLOR_BGR2GRAY)
# Not median blur 
imggray = cv2.GaussianBlur(imggray, (9,9),3)

circles_norm = cv2.HoughCircles(imggray, cv2.HOUGH_GRADIENT, 1, imggray.shape[0]/16, 
                                param1=20, param2=8, minRadius=15, maxRadius=30)
circles_norm = np.uint16(np.around(circles_norm))[0,:]

for i in circles_norm:
    center = (i[0], i[1])
    cv2.putText(arr, 'P', (i[0], i[1]), cv2.FONT_HERSHEY_COMPLEX, 0.5, 
               (0,0,255),1,cv2.LINE_AA)

Result: