vest Object Detection Dataset and Pre-Trained Model by project-stixd

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Here are a few use cases for this project:

Workplace Safety: The "vest" model can be deployed in industrial settings like construction sites, warehouses, mines and factories to ensure workers are properly dressed in requisite safety gear. This could help reduce workplace accidents significantly.
Security Enforcement: The model can be used in security or law enforcement contexts. For instance, it can detect whether policemen, fire-rescue teams, or security guards are wearing their safety vests and helmets during their duties or in public areas.
Fashion and Retail: In the fashion industry, the model can be used to sort and categorize items based on whether they are vests or not, whether they come with a belt, and more, aiding in inventory and data management.
Sports: During live sports events or for sport training purposes, this model could be used to verify if participants are properly equipped according to their game rules.
Traffic Monitoring: Traffic authorities could use the "vest" model to identify whether motorcyclists or cyclists are using proper safety gear, like helmets and high-visibility vests, thereby promoting road safety.

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{
                            vest-5byyt_dataset,
                            title = { vest Dataset },
                            type = { Open Source Dataset },
                            author = { project-stixd },
                            howpublished = { \url{ https://universe.roboflow.com/project-stixd/vest-5byyt } },
                            url = { https://universe.roboflow.com/project-stixd/vest-5byyt },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { may },
                            note = { visited on 2024-04-28 },
                            }