face_landmarks.py

    import cv2
    import dlib
    import numpy as np
    
    initial_image = cv2.imread('images/image9.jpg')
    initial_image_in_rgb = cv2.cvtColor(initial_image, cv2.COLOR_BGR2RGB)
    reference_image = initial_image_in_rgb.copy()

    classifier_path = dlib.shape_predictor('classifier/shape_predictor_68_face_landmarks.dat')
    frontal_face_detector = dlib.get_frontal_face_detector()

    rectangles = frontal_face_detector(initial_image, 1)

    for k, d in enumerate(rectangles):
        cv2.rectangle(reference_image, (d.left(), d.top()), (d.right(), d.bottom()), (255, 255, 0), 2)

    landmarks = []

    for rectangle in rectangles:
        landmarks.append(np.matrix([[p.x, p.y] for p in classifier_path(reference_image, rectangle).parts()]))

    for landmark in landmarks:
        for index, point in enumerate(landmark):
            point_center = (point[0, 0], point[0, 1])
            cv2.circle(reference_image, point_center, 3, (255, 255, 0), -1)
            cv2.putText(reference_image, str(index), point_center, cv2.FONT_HERSHEY_COMPLEX, 3, (255, 255, 255), 2)