AI Football Analysis

Objective: The project aimed to develop a cutting-edge AI-powered solution for analyzing football team formations from videos or live streams. It focused on identifying strengths and weaknesses in team strategies through frame analysis, performed every 10 frames to handle heavy computation.

Technologies Used: The project leveraged Python for machine learning algorithms and APIs, while the frontend was developed using React for a seamless user experience.

Role and Contribution: As an independent developer, I took charge of both the webpage frontend and API development.

Features and Functionalities: The AI Football Analysis tool offers a user-friendly interface where users can input data, such as first and second team colors, referee colors, and the video URL for analysis.

Overcoming Challenges: During development, I faced an issue with displaying frames post-processing, as the images kept replacing each other. I successfully resolved this challenge by implementing an array of images, allowing users to scroll through them for enhanced analysis.

Outcome: I delivered the completed project to the client, but unfortunately, there was no further communication regarding the project's implementation or deployment.

With this project, I demonstrated my expertise in utilizing Python for machine learning and APIs, alongside React for frontend development, delivering a cutting-edge solution for AI-driven football analysis.