Lane Detection for Self-Driving Cars

– The project focuses on developing a real-time vehicle detection and lane analysis system using computer vision techniques. The system is designed to process video inputs, detect vehicles, analyze lane curvature, and provide safety suggestions to drivers. The application leverages YOLO (You Only Look Once) for vehicle detection, optical flow for speed estimation, and Hough Transform for lane detection. The system is implemented as a Flask-based web application, allowing users to upload video files, process them, and view the results with overlays indicating vehicle distances, lane status, and safety suggestions. The project aims to enhance road safety by providing real-time feedback to drivers about their surroundings.