In congested urban environments, accurate detection and counting of humans and vehicles provide valuable insights for optimizing traffic flow, identifying congestion hotspots, and designing efficient transportation systems. By leveraging computer vision algorithms, such as deep learning based object detection models, real-time monitoring of pedestrian and vehicular traffic can be achieved with high accuracy and granularity. The ability to precisely quantify pedestrian and vehicle movements enables urban planners a…