This project takes works on the You Only Look Once (YOLO) object detection algorithm, OpenCV, and Python to analyze data from the DFL - Bundesliga Data Shootout. The primary aim is to detect and track soccer players and the ball in video footage.

• Introduction
• Features
• Requirements
• Installation
• Usage
• References

The project is based on a tutorial video on YouTube which demonstrates how to utilize YOLO, OpenCV, and Python for sports analysis. The DFL - Bundesliga Data Shootout provides a rich dataset ideal for testing and developing computer vision models for sports analytics.

• Object Detection: Detect players and ball in the video.
• Tracking: Track the movement of detected objects across frames.
• Analysis: Perform analysis on the detected objects to gain insights.

• Python 3.x+
• OpenCV
• NumPy
• Matplotlib
• Pandas
• Ultralytics
• Supervision
• YOLOv3 and YOLOv5 weights and configuration files

git clone https://github.com/aaditya29/DFL---Bundesliga-Data-Shootout-Analysis.git
cd DFL---Bundesliga-Data-Shootout-Analysis

Download the YOLOv5 weights and configuration files from the official YOLO website or from the tutorial video description.

This project is inspired by the following YouTube tutorial video:

• YOLO Object Detection using OpenCV and Python