I am following this tutorial: https://www.pyimagesearch.com/2014/07/21/detecting-circles-images-using-opencv-hough-circles/
I was playing around with the parameters of HoughCircles and it seems very innacurate, in my project, the disks you see on the picture will be placed on random spots and i need to be able to detect them and their color.
Currently i am only able to detect few circles, and sometimes some random circles are drawn where there is no circles so i am a bit confused.
Is this the best way to do circle detection with openCV or is there a more accurate way of doing it ?
Initial board : https://imgur.com/BrPB5Ox
Circle drawn : https://imgur.com/dT7k29E
My code :
import numpy as np
img = cv2.imread('Photos/board.jpg') output = img.copy() gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) # detect circles in the image circles = cv2.HoughCircles(gray, cv2.HOUGH_GRADIENT, 1.2, 100) # ensure at least some circles were found if circles is not None: # convert the (x, y) coordinates and radius of the circles to integers circles = np.round(circles[0, :]).astype("int") # loop over the (x, y) coordinates and radius of the circles for (x, y, r) in circles: # draw the circle in the output image, then draw a rectangle # corresponding to the center of the circle cv2.circle(output, (x, y), r, (0, 255, 0), 4) cv2.rectangle(output, (x - 5, y - 5), (x + 5, y + 5), (0, 128, 255), -1) # show the output image cv2.imshow("output", np.hstack([img, output])) cv2.waitKey(0)
Thanks a lot.
Source: Python Questions