FIFA YOLO Project Computer Vision Project

koju

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Classes (9)
ball
gametime
goalkeeper
goalpost
player
playername
referee
score
team_name
Description

Here are a few use cases for this project:

  1. Sports Broadcasting Enhancement: The "FIFA YOLO Project" could be employed to improve live broadcasting of football matches. It can provide real-time, on-screen metadata about players, ball location, gametime, and the score to enhance viewers' understanding and interaction with the game.

  2. Gaming and Virtual Reality: Developers of football video games and virtual reality simulations could use this model to create more realistic and immersive experiences. Player movements, ball trajectories, and game dynamics could be modeled more accurately based on insights gathered from this computer vision model.

  3. Player Performance Analysis: Sports analytics companies and football teams could use it to evaluate players' performances during games. Identifying where players are on the field, their interaction with the ball, and how they engage with other players could provide valuable insights into a player's skills, strengths, and weaknesses.

  4. Smart Refereeing Systems: The model could be integrated into AI-based refereeing systems to assist in making correct decisions during a football game. It could track ball position, players' actions, goalie position relative to goalpost and determine if a goal was valid, a foul was committed or an offside rule was violated.

  5. Sports Betting Applications: Sports betting platforms could evolve with the introduction of this model, providing real-time data analysis of ongoing matches. This can help bettors make more informed decisions based on the real-time performance of the teams and players.

Supervision

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Cite This Project

LICENSE
CC BY 4.0

If you use this dataset in a research paper, please cite it using the following BibTeX:

                        @misc{
                            fifa-yolo-project-okfg6_dataset,
                            title = { FIFA YOLO Project Dataset },
                            type = { Open Source Dataset },
                            author = { koju },
                            howpublished = { \url{ https://universe.roboflow.com/koju/fifa-yolo-project-okfg6 } },
                            url = { https://universe.roboflow.com/koju/fifa-yolo-project-okfg6 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2024 },
                            month = { sep },
                            note = { visited on 2024-09-25 },
                            }
                        
                    

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