16-10-22 1-3 Object Detection Dataset and Pre-Trained Model by PROgrammers

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Explore Dataset

Here are a few use cases for this project:

Sports Broadcasting Analytics: This model could aid sports broadcasters in providing real-time game statistics by identifying players, their positions, and ball interaction during a football match. It could be used to automate tagging of game highlights, key events, and player performances.
Player Performance Analysis: Teams or coaching staff could use this model to evaluate the performance of specific players based on their on-field activity. This could help to develop strategies, determine training needs, and analyze opposition strengths and weaknesses.
Augmented Reality Applications: This model could be utilized in AR football games or applications. Given its ability to classify different components of a football game, it could provide real-time information to the users, enhancing their interactive experience.
Sports Betting Intelligence: This model could be used to gather data for developing insights for sports betting platforms. It would provide bettors with additional information about player performances, team trends, and activity during matches to help more accurately place bets.
Fair Play Analysis and Decision Making: This model could assist in monitoring fair play during matches. Variables like ball possession, player interaction, and potential infringement of rules could be identified by this model, helping to refine referee decisions.

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{
                            16-10-22-1-3_dataset,
                            title = { 16-10-22 1-3 Dataset },
                            type = { Open Source Dataset },
                            author = { PROgrammers },
                            howpublished = { \url{ https://universe.roboflow.com/programmers/16-10-22-1-3 } },
                            url = { https://universe.roboflow.com/programmers/16-10-22-1-3 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { may },
                            note = { visited on 2024-06-26 },
                            }