An advanced drone detection system combining a Next.js web interface, deep learning models, and synthetic dataset generation using Blender. This project is designed to detect UAVs (Unmanned Aerial Vehicles) in real-time, offering high accuracy and adaptability across various scenarios.
The UAV Detection System is an advanced solution for detecting drones, combining cutting-edge computer vision models with an intuitive web interface. It supports photo analysis, video processing, and real-time camera stream detection, making it adaptable to various surveillance needs. The system leverages a robust data pipeline, utilizing Blender for synthetic data generation and augmentation techniques to enhance model performance. A YOLO-based architecture is fine-tuned for UAV detection, ensuring high accuracy. The web interface, built with Next.js, provides real-time visualization and interaction. The model training process follows a structured pipeline, optimizing detection performance and ensuring reproducibility through saved metrics and checkpoints
