Football Info Detection Computer Vision Project
Here are a few use cases for this project:
-
Sports Analytics: This computer vision model could be used by sports analysts and coaches to track and analyze the movements and strategies of players and teams during matches. By identifying logos, faces, and names, they can gain detailed insights on individual and team performance.
-
Digital Media Management: News outlets and sports websites could use the model to simplify their media archiving and retrieval processes. For instance, they can easily locate images of specific players, teams, or brands through keyword-based searches, then use these images for different articles or reports.
-
E-commerce: Online retail platforms selling sports merchandise could use this model to categorize and organize their product images more effectively. By recognizing logos, brands, and club names, they could easily categorize items and enhance search functionality for the users.
-
Advertising and Audience Measurement: Advertisers could utilize this model to measure the effectiveness of their sponsorship or advertising campaigns within football matches. It could help quantify logo or partner visibility during a game, providing valuable data for marketers.
-
Fan Engagement: Apps or websites focused on fan engagement could use the model to create interactive content. For instance, implementing a 'find the logo' or 'identify the player' game based on the vision model's identification capabilities.
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.
Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
football-info-detection_dataset,
title = { Football Info Detection Dataset },
type = { Open Source Dataset },
author = { Duong Tran },
howpublished = { \url{ https://universe.roboflow.com/duong-tran/football-info-detection } },
url = { https://universe.roboflow.com/duong-tran/football-info-detection },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { aug },
note = { visited on 2024-03-28 },
}
Connect Your Model With Program Logic
Find utilities and guides to help you start using the Football Info Detection project in your project.