This project implements a self-driving computer vision pipeline using deep learning models for multiple perception tasks. It runs object detection and tracking, lane detection with curve fitting, road segmentation, and depth estimation on images or video. The system uses projective geometry to transform images from normal view to top-down view and calculate distances. Inference is accelerated via TensorRT on GPU or TensorFlow Lite with XNNPACK on CPU.