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Car Counter This project demonstrates a car counting application using Python, OpenCV, YOLO, and the SORT tracker. It performs object detection, object tracking, and counts vehicles passing through a specific area in a video or live camera feed. This can be useful for traffic management and monitoring applications.
Features •Object Detection: Utilizes YOLOv8 for detecting vehicles in the video. •Object Tracking: Employs the SORT (Simple Online and Realtime Tracking) algorithm to track vehicles across frames. •Counting Vehicles: Counts the number of vehicles passing through a defined line on the screen. •Masking: Uses a region mask to focus on a specific area in the frame. •Visualization: Displays bounding boxes, IDs, and a count of vehicles in real-time.
Requirements •Python 3.x •OpenCV •cvzone •numpy •ultralytics (for YOLO) •sort (for tracking)
Usage The script reads from a video file (Media/cars.mp4) or you can modify it to use a live camera feed. The count_line variable defines the line on the screen where vehicles are counted. Vehicles are counted when they cross this line, and the count is displayed on the screen.