#coding=utf-8

 #人脸识别类 - 使用face_recognition模块

 import cv2

 import face_recognition

 import os

 path = "img/face_recognition"  # 模型数据图片目录

 cap = cv2.VideoCapture(0)

 total_image_name = []

 total_face_encoding = []

 for fn in os.listdir(path):  #fn 表示的是文件名q

     print(path + "/" + fn)

     total_face_encoding.append(

         face_recognition.face_encodings(

             face_recognition.load_image_file(path + "/" + fn))[0])

     fn = fn[:(len(fn) - 4)]  #截取图片名（这里应该把images文件中的图片名命名为为人物名）

     total_image_name.append(fn)  #图片名字列表

 while (1):

     ret, frame = cap.read()

     # 发现在视频帧所有的脸和face_enqcodings

     face_locations = face_recognition.face_locations(frame)

     face_encodings = face_recognition.face_encodings(frame, face_locations)

     # 在这个视频帧中循环遍历每个人脸

     for (top, right, bottom, left), face_encoding in zip(

             face_locations, face_encodings):

         # 看看面部是否与已知人脸相匹配。

         for i, v in enumerate(total_face_encoding):

             match = face_recognition.compare_faces(

                 [v], face_encoding, tolerance=0.5)

             name = "Unknown"

             if match[0]:

                 name = total_image_name[i]

                 break

         # 画出一个框，框住脸

         cv2.rectangle(frame, (left, top), (right, bottom), (0, 255, 255), 2)

         # 画出一个带名字的标签，放在框下

         cv2.rectangle(frame, (left, bottom - 35), (right, bottom), (0, 255, 255),

                       cv2.FILLED)

         font = cv2.FONT_HERSHEY_DUPLEX

         cv2.putText(frame, name, (left + 6, bottom - 6), font, 1.0,

                     (255, 255, 255), 1)

     # 显示结果图像

     cv2.imshow('Video', frame)

     if cv2.waitKey(1) & 0xFF == ord('q'):

         break

 cap.release()

 cv2.destroyAllWindows()