Team_Maximes Object Detection Dataset and Pre-Trained Model by Maxime Cheve

Images

473 images

Explore Dataset

Here are a few use cases for this project:

Sports Analytics: Analysts can use the "Team_Maximes" model to collect real-time data during basketball games. This could involve tracking player movement, identifying possession changes, checking violation of some game rules, and making statistics on the success rate of teams from different shooting zones.
Media Broadcasting: TV broadcasters and Sports networks could use this model to enhance viewers' experience with real-time graphics, game statistics, player tracking, and to predict next moves. Additionally, it can be used in automatic gathering of game highlights.
Sports Betting Platforms: The firms can use the model as a tool to provide live data inputs that are critical to making betting decisions such as current scores, player statistics, and timing left.
Virtual Reality Training: Software developers could use this model to provide real-world, statistical data-driven scenarios for VR training programs for basketball players. This would allow players to practice against different simulated match scenarios aided by real-time data.
Crowd Management: Given the visual perspective, the model can help in strategic crowd management in live games, optimizing security by providing potential insights on crowd distribution and movement patterns.

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{
                            team_maximes_dataset,
                            title = { Team_Maximes Dataset },
                            type = { Open Source Dataset },
                            author = { Maxime Cheve },
                            howpublished = { \url{ https://universe.roboflow.com/maxime-cheve/team_maximes } },
                            url = { https://universe.roboflow.com/maxime-cheve/team_maximes },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { aug },
                            note = { visited on 2024-04-28 },
                            }