Soccer Object Detection and Tracking

Note: This project is currently under development.

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Overview

This project focuses on detecting and tracking objects in soccer videos, specifically players, referees, and the ball. It uses a YOLO model for object detection and the ByteTrack algorithm for tracking objects across frames. The project is implemented in Python and leverages libraries such as Ultralytics, Supervision, and OpenCV.

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Features

• Object Detection: Uses a pre-trained YOLO model to detect players, referees, and the ball in each frame of a soccer video.
• Object Tracking: Implements the ByteTrack algorithm to maintain the identity of detected objects across multiple frames.
• Data Serialization: Supports serialization and deserialization of tracking data using Python's pickle module.
• Visualization: Provides functionality to draw bounding boxes and ellipses around detected objects for visualization.

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Project Structure