Object Detection

This project focuses on developing an object detection system to identify and track various entities in urban environments, such as vehicles, pedestrians, traffic signs, and animals. Using deep learning models like YOLO (You Only Look Once), Faster R-CNN, or SSD (Single Shot MultiBox Detector), the system processes images or video feeds to detect multiple objects in real time.