用已经搭建好 face_recognition，dlib 环境来进行人脸识别
未搭建好环境请参考：
使用opencv 调用摄像头
import face_recognition
import cv2
video_capture = cv2.videocapture(0)
# videocapture打开摄像头，0为笔记本内置摄像头，1为外usb摄像头，或写入视频路径
mayun_img = face_recognition.load_image_file("mayun.jpg")
jobs_img = face_recognition.load_image_file("jobs.jpg")
mayun_face_encoding = face_recognition.face_encodings(mayun_img)[0]
jobs_face_encoding = face_recognition.face_encodings(jobs_img)[0]
face_locations = []
face_encodings = []
face_names = []
process_this_frame = true
while true:
ret, frame = video_capture.read()
# video_capture.read()按帧读取视频，ret,frame是获video_capture.read()方法的两个返回值。
# 其中ret是布尔值，如果读取帧是正确的则返回true，
# 如果文件读取到结尾，它的返回值就为false。frame就是每一帧的图像，是个三维矩阵。
small_frame = cv2.resize(frame, (0, 0), fx=0.25, fy=0.25)
# 对截取到的图像进行处理
if process_this_frame:
face_locations = face_recognition.face_locations(small_frame)
face_encodings = face_recognition.face_encodings(small_frame, face_locations)
face_names = []
for face_encoding in face_encodings:
match = face_recognition.compare_faces([mayun_face_encoding, jobs_face_encoding], face_encoding)
if match[0]:
name = "mayun"
elif match[1]:
name = "jobs"
else:
name = "unknown"
print(name)
face_names.append(name)
process_this_frame = not process_this_frame
for (top, right, bottom, left), name in zip(face_locations, face_names):
top *= 4
right *= 4
bottom *= 4
left *= 4
cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)
cv2.rectangle(frame, (left, bottom - 35), (right, bottom), (0, 0, 255), 2)
font = cv2.font_hershey_duplex
cv2.puttext(frame, name, (left+6, bottom-6), font, 1.0, (255, 255, 255), 1)
cv2.imshow('video', frame)
if cv2.waitkey(1) & 0xff == ord('q'):
break
video_capture.release()
cv2.destroyallwindows()
我使用手机中的照片来进行验证
因为是按每一帧进行读取：
有些人在使用时会出现摄像头打不开的情况
我使用的是win10系统给出一个建议：
在设置中找到隐私设置，在找到相机选项，把权限打开即可
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