mask_detection Object Detection Dataset and Pre-Trained Model by Datasetmaskdetectionown

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Here are a few use cases for this project:

Public Safety Monitoring: The "mask_detection" model could be used to monitor security camera footage or live video streams in public spaces such as subways, malls, or airports to identify individuals not wearing masks, aiding in the enforcement of public health guidelines during pandemics.
Retail Store Compliance: Retail outlets can use this model to ensure customers and staff are adhering to mask-wearing guidelines as part of the COVID-19 safety protocol, helping to maintain a safe shopping environment.
Education Institutions: The model can be implemented in school and university campuses to monitor mask compliance among students and staff, thus reducing the risk of COVID-19 spread.
Corporate Workplace: Companies could use this model to ensure their employees are wearing masks correctly in the office, especially in shared spaces such as meeting rooms and cafeterias.
Healthcare Facilities: The model could be used in healthcare facilities to automatically detect and alert if any staff, patient, or visitor is not adhering to mask-wearing protocol, ensuring strict compliance with hygiene practices.

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{
                            mask_detection-fbcno_dataset,
                            title = { mask_detection Dataset },
                            type = { Open Source Dataset },
                            author = { Datasetmaskdetectionown },
                            howpublished = { \url{ https://universe.roboflow.com/datasetmaskdetectionown/mask_detection-fbcno } },
                            url = { https://universe.roboflow.com/datasetmaskdetectionown/mask_detection-fbcno },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { jul },
                            note = { visited on 2024-06-18 },
                            }