import cv2

eye_image = cv2.imread("f.jpg")

#_,image = cv2.threshold(image, 150, 255, cv2.THRESH_BINARY)

binary_eye_image = None
if eye_image is not None:
    eye_histogram = [0]*256
    eye_image = cv2.cvtColor(eye_image, cv2.COLOR_RGB2GRAY)
    for i in xrange(256):
        value_count = (eye_image == i).sum()
        eye_histogram[i] = value_count
    count = 0
    index = 255
    while count < (eye_image.size*3/4):
        count += eye_histogram[index]
        index -= 1
    quarter_threshold = index
    #Multiply all parts of eye above bottom 1/4 brightness by 0
    #Might not work on people with light irises. Have not tried.
    binary_eye_image = cv2.equalizeHist((eye_image < quarter_threshold) * eye_image)

relative_iris_coordinates = None
if binary_eye_image is not None:
    eye_circles = cv2.HoughCircles(binary_eye_image, cv2.HOUGH_GRADIENT, 3, 500, maxRadius = binary_eye_image.shape[0]/5)
    if eye_circles is not None:
        #Usually gets the job done. Messy.
        circle = eye_circles[0][0]
        relative_iris_coordinates = (circle[0], circle[1])

print relative_iris_coordinates



cv2.imshow("hey", binary_eye_image)
cv2.waitKey(0)