LimaGuilherme

    import cv2
    
    group_of_people_image = cv2.imread('images/image7.jpg')
    frontal_face_classifier = cv2.CascadeClassifier('classifier/haarcascade_frontalface_default.xml')
    image_in_gray_scale = cv2.cvtColor(group_of_people_image, cv2.COLOR_BGR2GRAY)
    
    faces = frontal_face_classifier.detectMultiScale(image=image_in_gray_scale, scaleFactor=1.3, minNeighbors=6)

    for (x_axis, y_axis, weight, height) in faces:
        cv2.rectangle(group_of_people_image, (x_axis, y_axis), (x_axis + weight, y_axis + height), (255, 0, 0), 2)

LimaGuilherme

    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()