Medical Mask Detection Object Detection Dataset and Pre-Trained Model by Grp8 Healthcare

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Here are a few use cases for this project:

Public Health Monitoring: This model can be used in public spaces such as airports, train stations, or shopping malls to monitor mask usage among people, ensuring that individuals are adhering to public health guidelines and wearing masks correctly.
Workplace Compliance: Businesses, particularly health-care facilities, food production plants, and office spaces, can utilize this model to maintain workplace safety and compliance with mandated mask-wearing protocols.
Education and Training: The model can be incorporated into educational programs or apps to provide visual training and feedback on the correct way to wear a mask, fostering COVID-19 preventive practices.
Video Surveillance Enhancement: Integrated with existing CCTV systems, this computer vision model could facilitate real-time identification of individuals without masks or wearing masks improperly, aiding security personnel in maintaining health protocols.
Access Control Systems: It can be used to integrate with access control systems at locations like academic institutions, government buildings, or corporate offices. Entry could be denied or permitted based on whether the individual is wearing a mask and how it's worn.

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{ medical-mask-detection-oe3nc_dataset,
    title = { Medical Mask Detection Dataset },
    type = { Open Source Dataset },
    author = { Grp8 Healthcare },
    howpublished = { \url{ https://universe.roboflow.com/grp8-healthcare/medical-mask-detection-oe3nc } },
    url = { https://universe.roboflow.com/grp8-healthcare/medical-mask-detection-oe3nc },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2022 },
    month = { oct },
    note = { visited on 2023-12-05 },
}