Weapon Threat Monitor is a real-time weapon detection and alerting system with a desktop GUI, a live web viewer, and an alert dashboard. It uses PyQt6 for the desktop client, OpenCV and Ultralytics YOLO for inference, Flask for live streaming/mobile upload support, and a FastAPI dashboard for alert storage and notifications.

What this project includes

• Desktop monitoring UI for webcam, CCTV/RTSP, or mobile camera input
• Real-time object detection using a trained YOLO model
• Live web-based preview and remote access support
• Optional QR-code sharing for mobile viewing
• Alert snapshots saved locally or uploaded to cloud storage
• Email notifications for detected events
• Optional ngrok tunneling for public access

Requirements

• Python 3.10+
• Windows recommended for the desktop GUI workflow
• Internet access is helpful for installing dependencies and enabling ngrok/cloud features

Notes

• This overall model Accuracy is only 49%.
• knife detect rate is higher then other classes
• The detection model is expected at weights/best.pt.
• If the model file is missing, detection will not run until the correct weights are placed in the folder.
• The alert dashboard depends on the local Flask app and the desktop client being available for the full monitoring workflow.