5G技术在安全监控中的应用：从“慢半拍”到“秒响应”

import cv2
import numpy as np
from tensorflow.keras.models import load_model

# 加载预训练的行为识别模型
model = load_model("security_model.h5")

# 初始化摄像头
cap = cv2.VideoCapture("rtsp://5G摄像头地址")

while True:
    ret, frame = cap.read()
    if not ret:
        break

    # 预处理视频帧
    processed_frame = cv2.resize(frame, (224, 224)) / 255.0
    processed_frame = np.expand_dims(processed_frame, axis=0)

    # 预测行为类别
    prediction = model.predict(processed_frame)
    action = np.argmax(prediction)

    # 显示警告信息
    if action == 1:  # 假设类别1为异常行为
        cv2.putText(frame, "警告: 可疑行为检测", (50, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)

    cv2.imshow("监控画面", frame)
    if cv2.waitKey(1) & 0xFF == ord("q"):
        break

cap.release()
cv2.destroyAllWindows()

import face_recognition
import cv2

# 读取监控摄像头
video_capture = cv2.VideoCapture("rtsp://5G摄像头地址")

# 载入已授权人员的脸部数据
authorized_face = face_recognition.load_image_file("authorized.jpg")
authorized_encoding = face_recognition.face_encodings(authorized_face)[0]

while True:
    ret, frame = video_capture.read()
    if not ret:
        break

    # 识别人脸
    face_locations = face_recognition.face_locations(frame)
    face_encodings = face_recognition.face_encodings(frame, face_locations)

    for encoding in face_encodings:
        matches = face_recognition.compare_faces([authorized_encoding], encoding)
        if not any(matches):
            cv2.putText(frame, "警告: 未授权人员检测", (50, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)

    cv2.imshow("监控画面", frame)
    if cv2.waitKey(1) & 0xFF == ord("q"):
        break

video_capture.release()
cv2.destroyAllWindows()