Safety_PPE Object Detection Dataset and Pre-Trained Model by Safety

Images

6629 images

Explore Dataset

Here are a few use cases for this project:

Construction Site Safety: This model could be implemented to monitor video feeds from construction sites, ensuring workers are wearing required PPE like helmets, gloves, goggles, shoes, safety harnesses and more.
Industrial Plant Monitoring: The model can be deployed in manufacturing units, chemical plants, power plants, and other industrial environments where workers are required to don specific protective gear. The system can alert supervisors if PPE compliance is not met, ensuring worker safety.
Research Lab Safety Compliance: The model can be used in laboratory settings where PPE is necessary. Monitoring scientists and researchers to ensure they are wearing the proper protective gear like gloves, goggles and lab coats.
Mines Safety Management: In industries like coal or mineral mining, where PPE usage is paramount, the model can help ensure workers' safety by monitoring and identifying if someone isn't wearing the right protective gear.
Training and Education: The computer vision model can be used for training purposes in safety education programs, providing real-time feedback to trainees about their PPE usage. It can also be used in simulation for risk assessment to identify potential safety hazards.

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{ safety_ppe_dataset,
    title = { Safety_PPE Dataset },
    type = { Open Source Dataset },
    author = { Safety },
    howpublished = { \url{ https://universe.roboflow.com/safety-jmser/safety_ppe } },
    url = { https://universe.roboflow.com/safety-jmser/safety_ppe },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2023 },
    month = { feb },
    note = { visited on 2023-12-05 },
}