def __init__(self, path):
        import dlib # lazy loading
        # use dlib 68-point facial landmark
        self._detector = dlib.shape_predictor(path + 'shape_predictor_68_face_landmarks.dat')
        (self._leye_start, self._leye_end) = face_utils.FACIAL_LANDMARKS_IDXS["left_eye"]
        (self._reye_start, self._reye_end) = face_utils.FACIAL_LANDMARKS_IDXS["right_eye"]
        try:
            (self._mouth_start, self._mouth_end) = face_utils.FACIAL_LANDMARKS_IDXS["inner_mouth"]
        except:
            (self._mouth_start, self._mouth_end) = (60, 68) 

def recognize():
    database = initialize()
    cap = cv2.VideoCapture(0)
    (lStart, lEnd) = face_utils.FACIAL_LANDMARKS_IDXS["left_eye"]
    (rStart, rEnd) = face_utils.FACIAL_LANDMARKS_IDXS["right_eye"]
    while True:
        ret, img = cap.read()
        img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
        subjects = detector(gray, 0)
        for subject in subjects:
            shape = predictor(gray, subject)
            shape = face_utils.shape_to_np(shape)  # converting to NumPy Array
            leftEye = shape[lStart:lEnd]
            rightEye = shape[rStart:rEnd]
            leftEAR = eye_aspect_ratio(leftEye)
            rightEAR = eye_aspect_ratio(rightEye)
            ear = (leftEAR + rightEAR) / 2.0
            leftEyeHull = cv2.convexHull(leftEye)
            rightEyeHull = cv2.convexHull(rightEye)
            cv2.drawContours(img, [leftEyeHull], -1, (0, 255, 0), 1)
            cv2.drawContours(img, [rightEyeHull], -1, (0, 255, 0), 1)
            extract_face_info(img, img_rgb, database,ear)
        cv2.imshow('Recognizing faces', img)
        if cv2.waitKey(1) == ord('q'):
            break

    cap.release()
    cv2.destroyAllWindows()