tennis-tracker Computer Vision Project
Here are a few use cases for this project:
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"Sports Analysis": The "tennis-tracker" model could be used for detailed game analysis in broadcasting. Being able to differentiate between player-front, player-back, and ball are crucial elements for sports analysts to study player movements, strategies, and game patterns.
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"Player Performance Evaluation": Coaches and trainers could use this model to assess players' performance during training or matches. The model's ability to identify players and tennis balls can be used for tracking player movement, speed, consistency, and accuracy, contributing to better training strategies.
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"Automated Replay System": This model can be utilized for managing replays in live or recorded matches. It can quickly identify key moments or points of interest (like when a player hits the ball) to create automated highlights or checks for foul play.
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"Augmented Reality Tennis Game": Game developers could use this model in the development of AR-based tennis games. The model could identify player and ball positions to create a realistic and interactive gaming experience.
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"Crowd Control & Safety Management": During major tournaments, security staff can use this model to monitor crowd behavior. Distinguishing between players, balls, and spectators can help identify potential disruptions or emergencies. It can also ensure player safety, tracking unauthorized individuals entering the court.
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.
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{
tennis-tracker-duufq_dataset,
title = { tennis-tracker Dataset },
type = { Open Source Dataset },
author = { tennistracker },
howpublished = { \url{ https://universe.roboflow.com/tennistracker-dogbm/tennis-tracker-duufq } },
url = { https://universe.roboflow.com/tennistracker-dogbm/tennis-tracker-duufq },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { may },
note = { visited on 2024-04-27 },
}
Connect Your Model With Program Logic
Find utilities and guides to help you start using the tennis-tracker project in your project.
Source
Last Updated
a year ago
Project Type
Object Detection
Subject
players-balls
Views: 1890
Downloads: 51
