Detect Football Shot Object Detection Dataset and Pre-Trained Model by Thomas Ngo

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Explore Dataset

Here are a few use cases for this project:

Sports Analytics: This model can be used to analyze football matches, helping teams develop insights into their strategies and shot technique. By identifying football shots, teams can assess their opponents' strengths and weaknesses.
Media and Entertainment: TV and online platforms can use this model to automatically generate highlights and summaries of a football game. By recognizing shots, the model can produce a clip featuring key moments of the game.
Training and Coaching: Coaches can use this model as a training tool for practicing football players. It can help measure player performance including shot accuracy, frequency, and effectiveness.
Video Games and Virtual Reality: This model can be implemented in designing football-based video games, allowing the system to understand and respond to the player's movements. In VR training simulations, users can improve their skills in virtual, realistic scenarios.
Security and Surveillance: In stadiums or public parks, the model can help identify activities related to football games, contributing to improved safety and management of public spaces by ensuring authorized use of the field.

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{
                            detect-football-shot_dataset,
                            title = { Detect Football Shot Dataset },
                            type = { Open Source Dataset },
                            author = { Thomas Ngo },
                            howpublished = { \url{ https://universe.roboflow.com/thomas-ngo-at1jn/detect-football-shot } },
                            url = { https://universe.roboflow.com/thomas-ngo-at1jn/detect-football-shot },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { apr },
                            note = { visited on 2024-05-10 },
                            }