soccerfinal Object Detection Dataset and Pre-Trained Model by class

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Explore Dataset

Here are a few use cases for this project:

Sports Analytics: The "soccerfinal" computer vision model could be used to analyze matches by automatically tracking player movements, ball interactions, and referee calls. This information could help coaches develop new strategies, evaluate player performance, and identify patterns in the opposing team's gameplay.
Live Game Highlight Creation: The model can be used to automatically detect key moments in a soccer match, such as goals, penalties, and corner kicks. This information can be used to create real-time highlights for viewers, improving fan engagement and media coverage.
Soccer Training App: A mobile app can incorporate the "soccerfinal" model to provide personalized training for amateur and professional players. The app could analyze user-recorded soccer practice videos, providing feedback and tips to help players improve their skills and moves.
Virtual and Augmented Reality Sports Experiences: The "soccerfinal" model can be integrated into VR/AR applications, allowing users to immerse themselves in a realistic soccer environment. Users could learn about specific game situations, analyze tactics, or practice their skills in a virtual setting.
Security and Crowd Management: By identifying and tracking different elements and people (such as referees, players, and unauthorized persons) in a soccer match, the model can help ensure security and effective crowd management in stadiums, deterring trespassing, and reducing the likelihood of incidents during games.

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{
                            soccerfinal_dataset,
                            title = { soccerfinal Dataset },
                            type = { Open Source Dataset },
                            author = { class },
                            howpublished = { \url{ https://universe.roboflow.com/class-fok1e/soccerfinal } },
                            url = { https://universe.roboflow.com/class-fok1e/soccerfinal },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { sep },
                            note = { visited on 2024-06-15 },
                            }