[机器学习][face recognition] 一个视频人脸识别实现

开发环境和用到的库：

• Ubuntu
• jupyter notebook（python3.6）
• OpenCV
• Dlib
• face_recognition

实现效果如下（视频截图）：

 #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()