Pickle Ball - Tom Brady Reach Out Object Detection Dataset and Pre-Trained Model by Salo Levy

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Explore Dataset

Here are a few use cases for this project:

Sports Analysis: Use the "Pickle Ball - Tom Brady Reach Out" model to analyze pickle-ball games by identifying player positions, ball movements, and team dynamics. This can help coaches devise better strategies and help players improve their performance on the field.
Automated Scorekeeping: Integrate the model into a smart scoring system that can automatically track and update scores for each team during a pickle-ball match. This can reduce human error, increase efficiency, and allows players to focus on the game.
Event Organization: Utilize the model to assist event organizers in planning and managing pickle-ball tournaments by identifying the number of teams, their positions on the court, and match schedules. This can streamline the management process and improve the overall event experience for both players and spectators.
Sports Broadcasting: Use the "Pickle Ball - Tom Brady Reach Out" model to generate real-time insights and statistics during a live broadcast of a pickle-ball match. This can enhance the viewer experience by providing valuable information about team performance, ball movements, and interesting plays.
Player and Performance Tracking: Implement the model in a sports performance tracking system that can recognize players, monitor their movements, and track performance over time. This can be a valuable tool for players or coaches looking to improve their skills and gain a competitive edge on 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.

YOLOv8

This project has a YOLOv8 model checkpoint available for inference with Roboflow Deploy. YOLOv8 is a new state-of-the-art real-time object detection model.

YOLOv5

This project has a YOLOv5 model checkpoint available for inference with Roboflow Deploy. YOLOv5 is a proven and tested, production ready, state-of-the-art real-time object detection model.

Cite This Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{
                            pickle-ball-tom-brady-reach-out_dataset,
                            title = { Pickle Ball - Tom Brady Reach Out Dataset },
                            type = { Open Source Dataset },
                            author = { Salo Levy },
                            howpublished = { \url{ https://universe.roboflow.com/salo-levy-nlqrn/pickle-ball-tom-brady-reach-out } },
                            url = { https://universe.roboflow.com/salo-levy-nlqrn/pickle-ball-tom-brady-reach-out },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2024 },
                            month = { jan },
                            note = { visited on 2024-04-20 },
                            }