An Intelligent Monitoring and Security System built usingOpenCV,YOLO,face_recognition,PySide6.
- Data Collection and Preprocessing: Utilizes the OpenCV library to capture and preprocess data from the camera feed.
- Face Detection: Employs the YOLOv8 model to detect faces and other objects in the real-time video stream.
- Face Recognition and Analysis: Integrates the face_recognition (dlib) library to detect, recognize, and analyze facial features. This includes silent liveness detection and facial feature analysis using the APIs provided byiFLYTEK andTencent Cloud.
- Behavior Detection: Monitors and detects the behavior of individuals in the camera feed.
- Object Detection and Recognition: Leverages the YOLOv8 model to detect and recognize various objects in the video stream.
- Security Alerts: Sends timely email alerts using the smtplib and email libraries when suspicious activities or unknown faces are detected.
It is recommended to configure the required dependencies in a virtual Python environment
pip install -r requirements.txt
The version described inrequirements.txt is exported by thepipreq command. In theory, similar versions can also run smoothly.
After preparing the dependent environment, you need to fill inexample-config.json inresource directory and rename it toconfig.json before it can run normally.
The face login function relies oniFlytek's silent liveness detection API, theface feature analysis relies on Tencent SDK, and the security alert email function requires theSMTP service provided by the email service provider. If you need to use all the functions of the system, please fill in all items in theconfig.json file.
