This repository contains a project that integrates YOLOv8 from Ultralytics with OpenCV for real-time object tracking and detection. The project allows you to run the YOLOv8 model on a video file or a live camera feed, tracking objects frame by frame and visualizing the results with annotations. YOLOv8 Object Tracking with OpenCV This project uses the YOLOv8 object detection model from Ultralytics along with OpenCV for video capture and live object tracking. You can either provide a video file path or use a live camera feed for real-time object detection.
Features YOLOv8 object tracking Live camera or video file feed Object annotation on video frames Easy-to-use and customizable Requirements Before running this project, ensure you have the following dependencies installed:
Python 3.x OpenCV Ultralytics YOLOv8 To install the required packages, run the following:
bash Copy code pip install ultralytics opencv-python Setup and Usage Clone the repository:
bash Copy code git clone https://github.com/yourusername/yolo-object-tracking.git Navigate to the project directory:
bash Copy code cd yolo-object-tracking Add your video file to the project directory or use a live camera feed.
Run the project:
bash Copy code python yolo_tracking.py