深度学习与人脸识别之-身份识别

1.加载已知身份人脸数据

#载入已经人脸数据
def load_known_faces(dirname):
    for img in fnmatch.filter(os.listdir(dirname), '*.jpg'):
        print('load image:',img)
        image = facer.load_image_file(dirname + img)
        en_img = facer.face_encodings(image)
        if len(en_img) > 0:
            known_face_encodings.append(en_img[0])
            known_face_names.append(img[:-4])

在这里，使用了几个公众人物的图像作为载入数据：

Andrew:

范冰冰(程序中使用fanbb代替)

2.载入测试数据并识别身份

def detect_and_authorization(know_faces_dir,image_for_testing):

    #加载已经身份的人脸数据
    load_known_faces(know_faces_dir)

    #加载测试人脸数据
    test_img = facer.load_image_file(image_for_testing)
    test_img = cv2.cvtColor(test_img,cv2.COLOR_BGR2RGB)
    cv2.imshow('test_img',test_img)
    
    #检测脸部数据
    faces = facer.face_locations(test_img)
    encod_faces = facer.face_encodings(test_img, faces)

    #把测试脸部数据与已经加载的人脸数据比较，从实现身份识别
    for (top, right, bottom, left), encod_face in zip(faces, encod_faces):

        #比较脸部数据
        matches = facer.compare_faces(known_face_encodings, encod_face)

        #通过比较结果获取身份名称
        if True in matches:
            foundindex = matches.index(True)
            name = known_face_names[foundindex]
        else:
            name = "Unknown"

        #绘制身份名称
        cv2.rectangle(test_img, (left, top), (right, bottom), (0, 255, 0), 2)
        cv2.rectangle(test_img, (left, bottom - 35), (right, bottom), (0, 255, 0), cv2.FILLED)
        cv2.putText(test_img, name, (left + 6, bottom - 6), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1.0, (255, 255, 255), 1)

    
    cv2.imshow("Face ID", test_img)

    cv2.waitKey(0) 
    cv2.destroyAllWindows()

3.程序运行结果