label Computer Vision Project
Here are a few use cases for this project:
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Personal Protective Equipment (PPE) Compliance: Using the "label" model to monitor construction sites, factories, or healthcare facilities for compliance with safety protocols regarding the use of personal protective equipment (e.g., helmets, boots, vests, gloves).
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Sports Equipment Analysis: The model could be used in sports training centers to validate if sportspersons are properly equipped during training or competitions, ensuring safety measures are followed satisfactorily.
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Augmented Reality Applications: In AR games or applications that need to identify real-world objects like helmets, boots etc., this model can be used to facilitate a more interactive and engaging user experience.
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Safety Training Programs: The use of this model can enhance the quality of safety training programs, by providing real-time feedback on whether the trainee has worn the appropriate gear correctly.
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Disaster Response Scenarios: In disaster response scenarios where rescuers require wearing protective gear, the model can be used to confirm if all the safety equipments are worn properly before entering the hazardous zones.
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{
label-dt40y_dataset,
title = { label Dataset },
type = { Open Source Dataset },
author = { nckh },
howpublished = { \url{ https://universe.roboflow.com/nckh-zlhgt/label-dt40y } },
url = { https://universe.roboflow.com/nckh-zlhgt/label-dt40y },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { feb },
note = { visited on 2024-04-27 },
}
Connect Your Model With Program Logic
Find utilities and guides to help you start using the label project in your project.
