The Precision Laser Beam Targeting and Tracking System utilizes advanced image processing techniques to enhance military applications by providing real-time target identification and tracking capabilities. The system employs the YOLO (You Only Look Once) model, a powerful deep learning-based object detection algorithm, to detect targets from live web capture. By integrating OpenCV for image processing and Python for backend development, the system ensures high-speed processing, real-time performance, and accuracy. The web application is developed using HTML, CSS, and JavaScript for a responsive frontend, while the backend is powered by Python and Django. The system enables users to register, log in, and access the prediction functionality to visualize bounding boxes on detected targets through a user-friendly interface. The SQLite database stores user information and prediction history. This system aims to provide military professionals with a reliable and efficient tool for precision targeting and tracking in dynamic environments.

Keywords: Precision targeting, Laser beam tracking, YOLO model, Image processing, OpenCV, Real-time detection, Military applications, Object detection, Web application, Django, SQLite, Bounding boxes.