ball_handler Object Detection Dataset and Pre-Trained Model by Gaddy Radom

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Explore Dataset

Here are a few use cases for this project:

Sports Analytics: The "ball_handler" model could be implemented by basketball teams or broadcasters to accurately analyze the gameplay. It can help in determining crucial statistics such as ball possession time, player positioning on the court, and shooting accuracy based on rim detection.
Player Training and Performance Improvement: Coaches could use this model to analyze individual player's skills, such as ball-handling ability, court presence, and shooting style. This can then facilitate personalized training regimes to enhance their performance.
Video Game Development: This model could be useful in creating realistic basketball video games. It can help game developers create AI-powered characters that mimic real-world player movements, ball-handling dynamics and can even detect the rim for accurate shooting simulations.
Augmented Reality (AR) Sports Apps: "ball_handler" model could be used to build AR applications that provide interactive basketball training sessions. Users can practice ball-handling against virtual players or improve their shooting accuracy with rim detection feature.
Surveillance and Security: Beyond sports, this model could be used for surveillance purposes, particularly in public sports facilities. It can identify people, detect unusual movements (such as someone lying on the floor when they shouldn't be), and potentially provide alerts in real-time.

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{
                            ball_handler_dataset,
                            title = { ball_handler Dataset },
                            type = { Open Source Dataset },
                            author = { Gaddy Radom },
                            howpublished = { \url{ https://universe.roboflow.com/gaddy-radom-vofgh/ball_handler } },
                            url = { https://universe.roboflow.com/gaddy-radom-vofgh/ball_handler },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { mar },
                            note = { visited on 2024-05-04 },
                            }