Python 3.x 在两台摄像机上执行人脸识别

我有一个面部识别项目，使用相机没有任何问题

我现在想用两台摄像机同时拍摄

这是我一个摄像头的代码，我不知道如何使用两个摄像头

import face_recognition
import cv2
import numpy as np
video_capture = cv2.VideoCapture('rtsp://admin:11111@192.168.1.13:554/mode=real&idc=1&ids=2')


farid_image = face_recognition.load_image_file("farid.jpg")
farid_face_encoding = face_recognition.face_encodings(farid_image)[0]

# Load a second sample picture and learn how to recognize it.
roice_image = face_recognition.load_image_file("roice.jpg")
roice_face_encoding = face_recognition.face_encodings(roice_image)[0]

known_face_encodings = [
    farid_face_encoding,
    roice_face_encoding
]
known_face_names = [
    "farid",
    "roice"
]

while True:

    ret, frame = video_capture.read()
    rgb_frame = frame[:, :, ::-1]


    face_locations = face_recognition.face_locations(rgb_frame)
    face_encodings = face_recognition.face_encodings(rgb_frame, face_locations)

    # Loop through each face in this frame of video
    for (top, right, bottom, left), face_encoding in zip(face_locations, face_encodings):
        # See if the face is a match for the known face(s)
        matches = face_recognition.compare_faces(known_face_encodings, face_encoding)

        name = "Unknown"

        # Calculate face distance
        face_distance = face_recognition.face_distance(known_face_encodings, face_encoding)
        # If a match was found in known_face_encodings, just use the first one.
        if True in matches:
           # first_match_index = matches.index(True)
            # Sort nearest distance
            name = known_face_names[np.argsort(face_distance)[0]]

        # Draw a box around the face
        cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)

        # Draw a label with a name below the face
        cv2.rectangle(frame, (left, bottom - 35), (right, bottom), (0, 0, 255), cv2.FILLED)
        font = cv2.FONT_HERSHEY_DUPLEX
        cv2.putText(frame, name, (left + 6, bottom - 6), font, 1.0, (255, 255, 255), 1)

    # Display the resulting image
    cv2.imshow('Video', frame)

    # Hit 'q' on the keyboard to quit!
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

# Release handle to the webcam
video_capture.release()
cv2.destroyAllWindows()

---

我可以使用

cv2.VideoCapture（）

模块简单地添加更多摄像头，但是如何更改

人脸识别

以使用两个摄像头？

您可以尝试将此多线程化。每个摄像头都有一个线程，可以对看到的图像进行自己的面部识别

它们将独立地作用于各自的流，但是您可以从两个线程获得结果，以组合信息以改进检测和/或识别