PPE detection f Object Detection Dataset and Pre-Trained Model by ENSAM Meknes

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Explore Dataset

Here are a few use cases for this project:

Construction Site Safety: The model can be used at construction sites to monitor if all workers are wearing the necessary PPE, like hardhats and vests. It can identify safe workers (those fully equipped with PPE) and unsafe workers (those lacking some or all PPE).
Manufacturing Plant Compliance: The model can be employed in manufacturing plants for regular safety audits. It can provide real-time insights on workers' compliance with safety protocols.
Training and Education: This model can be integrated into educational and training programs to improve understanding of appropriate PPE usage. It can demonstrate examples of correct and incorrect PPE use.
Insurance Investigations: Insurance companies can use the model as part of an investigation into workplace incidents to verify if workers were adhering to safety protocols at the time of an accident.
Public Health Compliance: During a health crisis such as a pandemic, the model can monitor adherence to guidelines regarding PPE usage in public areas or healthcare facilities.

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{
                            ppe-detection-f_dataset,
                            title = { PPE detection f Dataset },
                            type = { Open Source Dataset },
                            author = { ENSAM Meknes },
                            howpublished = { \url{ https://universe.roboflow.com/ensam-meknes/ppe-detection-f } },
                            url = { https://universe.roboflow.com/ensam-meknes/ppe-detection-f },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jan },
                            note = { visited on 2024-04-28 },
                            }