Object Detection and Tracking using YOLO and SORT

This project demonstrates real-time object detection and tracking in videos using YOLO (You Only Look Once) for detection and SORT (Simple Online and Realtime Tracking) for tracking.

Requirements

• Python 3.x
• OpenCV (pip install opencv-python)
• CVZone (pip install cvzone)
• Ultralytics YOLO (pip install ultralytics)

Setup

1. Clone the repository:

git clone https://github.com/yourusername/your-repo.git
cd your-repo

Install dependencies:

pip install -r requirements.txt

Usage:

• Replace videos_and_images/test2/highway_traffic_flow.mp4 with your video file path for detection.

• Ensure your model weights (yolov8n.pt) are located in model_weights/.

• Adjust the mask region (mask_region.png) and graphic overlays (graphics.png) in the videos_and_images/test2/ directory as per your video setup.

• Run the script:

python object_detection_tracking.py

View the live video feed:

View the live video feed with object detection and tracking results. Objects detected and tracked will be annotated with bounding boxes and IDs.