import numpy as np
import argparse
import cv2

# construct the argument parser and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-i", "--image", required = True, help = "Path to the image")
args = vars(ap.parse_args())

image = cv2.imread(args["image"])
output = image.copy()
image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8,8))
cl1 = clahe.apply(image)

cl1 = cv2.medianBlur(cl1,5)
# detect circles in the image
circles = cv2.HoughCircles(cl1, cv2.cv.CV_HOUGH_GRADIENT, 1.8, 75)

# 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", output)

cv2.imshow("cl1",cl1)
cv2.waitKey(0)