利用face_recognition，dlib与OpenCV调用摄像头进行人脸识别

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()