This Github project utilizes the YOLO object detection model to detect and count the number of cars in a video, based on their lane position. The system uses YOLO's pre-trained object detection to detect only cars, in a road with trucks, busses, vans, etc.
This project implements the YOLO model for car detection and integrates a lane detection algorithm to determine which lane each car is in. The system takes an input video and processes it frame by frame, detecting and counting the cars in each lane. The results are then displayed in a visual format, counting the number of cars passing in each lane at any given time.
Overall, the project is a powerful tool for detecting and counting cars in real-time, based on their lane position. It demonstrates the potential of deep learning and computer vision in solving real-world problems and can have various applications in traffic management, surveillance, and transportation.
Demo:
