ABSTRACT:

This project aims to implement a real-time weapon detection system using YOLO-v9 for CCTV footage analysis. The system captures live camera feed, processes the frames to detect specific weapons such as Knife, Gun, Pistol, Rifle, and others, using the YOLO-v9 object detection model trained on a custom dataset. Upon detecting a weapon, the system triggers an email alert to notify the user and simultaneously plays a buzzer sound for immediate attention. The backend is developed in Python, utilizing OpenCV for real-time video capture, and smtplib for sending email alerts. The frontend interface is built using Streamlit, allowing users to interact with the system, monitor the video feed, and receive real-time notifications. This project enhances security surveillance systems by providing automatic weapon detection and alert mechanisms, offering a proactive approach to security management.

Keywords: YOLO-v9, Weapon Detection, CCTV, Real-Time, Python, Streamlit, Email Alert, Buzzer Sound, OpenCV, Security Surveillance.