basketball Object Detection Dataset and Pre-Trained Model by zaki

Images

1063 images

Explore Dataset

Here are a few use cases for this project:

Sports Analysis: Coaches and analysts can use this computer vision model to track the performance of players during a game or practice session. They can get insights about precise ball movements, successful hits, and goal rates, leading to better training and strategic decisions.
Highlight Generation: Sports media companies can implement the "basketball" model to automatically detect exciting moments like successful goals or impressive hits during a game. This can enable them to create instant highlights for social media, web portals, or live broadcasts, enhancing user engagement.
Virtual Coaching: This model can be integrated into mobile applications or websites that offer virtual basketball coaching. Users would be able to upload their videos, and the model would provide them with feedback based on their technique, ball handling, and shooting accuracy.
Smart Camera Systems: The "basketball" model can be embedded in smart cameras for sports facilities or courts. This would allow the cameras to follow the action as it happens, automatically zooming in on goals or exciting plays, thus enhancing the overall viewing experience for spectators.
Basketball Simulation Games: Game developers can utilize the model's capability to recognize various aspects of a basketball game to create more realistic and engaging basketball simulation games. The AI-driven virtual players would exhibit authentic in-game actions and responses, providing a closer-to-real gaming experience to the users.

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{
                            basketball-jagmz_dataset,
                            title = { basketball Dataset },
                            type = { Open Source Dataset },
                            author = { zaki },
                            howpublished = { \url{ https://universe.roboflow.com/zaki-b86c6/basketball-jagmz } },
                            url = { https://universe.roboflow.com/zaki-b86c6/basketball-jagmz },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { may },
                            note = { visited on 2024-06-18 },
                            }