imagecircles.py

import cv2 
import numpy as np 
  
# Read image. 
camera_port = 0 
camera = cv2.VideoCapture(camera_port, cv2.CAP_DSHOW)
return_value, image = camera.read()
cv2.imwrite("circle.png", image)
cv2.imshow("circle.png", image)
camera.release()#releases the shutter of the camera
#waits for you to press 0
cv2.waitKey(0) 
#destroys all the additional wondows created by the program
cv2.destroyAllWindows()

img= cv2.imread("circle.png")
# Convert to grayscale. 
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) 
  
# Blur using 3 * 3 kernel. 
gray_blurred = cv2.blur(gray, (3, 3)) 
  
# Apply Hough transform(there's a good document that explains that) on the blurred image. 
detected_circles = cv2.HoughCircles(gray_blurred,cv2.HOUGH_GRADIENT, 1, 20, param1 = 50,param2 = 30, minRadius = 70, maxRadius = 100) 
  
# Draw circles that are detected. 
if detected_circles is not None: 
  
    # Convert the circle parameters a, b and r to integers. 
    detected_circles = np.uint16(np.around(detected_circles)) 
  
    for pt in detected_circles[0, :]: 
        a, b, r = pt[0], pt[1], pt[2] 
  
        # Draw the circumference of the circle. 
        cv2.circle(img, (a, b), r, (0, 255, 0), 2) 
  
        # Draw a small circle (of radius 1) to show the center. 
        cv2.circle(img, (a, b), 1, (0, 0, 255), 3) 
        cv2.imshow("Detected Circle", img) 
        cv2.waitKey(0) 
print("detection ended")