Football Object Detection Object Detection Dataset and Pre-Trained Model by football detect

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Explore Dataset

Here are a few use cases for this project:

Sports Broadcasting Enhancement: The "Football Object Detection" model can be used in sports broadcasting to enhance the viewing experience by automatically identifying and highlighting key elements of the game such as players, referee, ball, etc. It could create real-time annotations and infographics to improve viewer comprehension.
Sports Analytics: In football analysis, the model can aid in player performance evaluation by tracking specific players, the ball, or the goalkeeper during games. The generated data can be used to assess strategies, possession, player movements, and scoring opportunities.
Coaching Aid: Football coaches could utilize this model to analyze and strategize gameplay. It could help in scrutinizing the performance of individual players and the team as a whole during practices and match reviews, potentially aiding in improved decision-making.
Interactive Gaming and Virtual Reality: The model could find application in the development of football-themed video games and VR experiences. It can help in achieving realistic movements of virtual players, goalkeepers, referees, and ball dynamics.
Security and Crowd Management: For crowded football events, this model could be used to monitor crowd behavior, track any prohibited items, or assess emergency situations, contributing to improved stadium security and safety.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite This Project

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

@misc{
                            football-object-detection_dataset,
                            title = { Football Object Detection Dataset },
                            type = { Open Source Dataset },
                            author = { football detect },
                            howpublished = { \url{ https://universe.roboflow.com/football-detect/football-object-detection } },
                            url = { https://universe.roboflow.com/football-detect/football-object-detection },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jan },
                            note = { visited on 2024-04-26 },
                            }