python - Finding the coordinates of the center of the iris in real time python opencv

Question

I'm working on a project to detect the eya gaze direction, so first I want to find the exact coordinates of the centre of the iris, to do so, i'm using the hough circles and it's returning no circle.

Can anyone tell me where is the problem in my code.

import cv2
import dlib 
import numpy as np 
from math import hypot
import imutils



cap = cv2.VideoCapture(0)

detector = dlib.get_frontal_face_detector()  
predictor = dlib.shape_predictor("shape_predictor_68_face_landmarks.dat") 

def midpoint(p1 ,p2):
    return int((p1.x + p2.x)/2), int((p1.y + p2.y)/2)





while True:
    _, frame = cap.read()
    
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    faces = detector(gray)
    
    for face in faces:
        x, y = face.left(), face.top()
        x1, y1 = face.right(), face.bottom()
        cv2.rectangle(frame, (x, y), (x1, y1), (0, 255, 0), 2)

        landmarks = predictor(gray, face)

        left_point = (landmarks.part(36).x, landmarks.part(36).y)
        right_point = (landmarks.part(39).x, landmarks.part(39).y)
        center_top = midpoint(landmarks.part(37), landmarks.part(38))
        center_bottom = midpoint(landmarks.part(40), landmarks.part(41))
        
        #hor_line = cv2.line(frame, left_point, right_point, (255,0 , 0), 2)
        #ver_line = cv2.line(frame, center_top, center_bottom, (255, 0, 0), 2)


        hor_line_lenght = hypot((left_point[0] - right_point[0]), (left_point[1] - right_point[1]))   #calcul de la distance de la ligne horizentale
        ver_line_lenght = hypot((center_top[0] - center_bottom[0]), (center_top[1] - center_bottom[1]))
        
        x = (left_point[0]) + int(hor_line_lenght / 2) 
        y = (center_bottom[1] - int(ver_line_lenght / 2))
        #cv2.circle(frame,(x,y), 2,(0,0,255),2)


        roi = np.array([(landmarks.part(36).x, landmarks.part(36).y),
                                (landmarks.part(37).x, landmarks.part(37).y),
                                (landmarks.part(38).x, landmarks.part(38).y),
                                (landmarks.part(39).x, landmarks.part(39).y),
                                (landmarks.part(40).x, landmarks.part(40).y),
                                (landmarks.part(41).x, landmarks.part(41).y)], np.int32)

        min_x = np.min(roi[:, 0]) 
        max_x = np.max(roi[:, 0])
        min_y = np.min(roi[:, 1])
        max_y = np.max(roi[:, 1])
        eye = frame[min_y:max_y, min_x:max_x]
        gray_eye = cv2.cvtColor(eye,cv2.COLOR_BGR2GRAY)
        gray_eye = cv2.GaussianBlur(gray_eye,(7,7),40)
        
        circles = cv2.HoughCircles(gray_eye,cv2.HOUGH_GRADIENT,1,20, param1=50,param2=30,minRadius=0,maxRadius=0)
        
        if circles is not None:
            circles = np.uint16(np.around(circles))
            for i in circles[0, :]:

                center = (i[0], i[1])
            # circle center
                cv2.circle(eye, center, 1, (0, 100, 100), 3)
            # circle outline
                radius = i[2]
                cv2.circle(eye, center, radius, (0, 0, 255), 3)

        #roi_only = cv2.resize(roi_only,None, fx=7, fy=7)
        cv2.imshow("roi", eye)
        
    cv2.imshow("Frame", frame)
    cv2.imshow("gray", gray)
    
    key = cv2.waitKey(1)
    if key == 27:
        break

cap.release()
cv2.destroyAllWindows()