TCC FINAL Object Detection Dataset and Pre-Trained Model by TCC FINAL

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Explore Dataset

Here are a few use cases for this project:

Workplace Safety Compliance: Businesses, especially those in construction, manufacturing, or any industry that require employees to wear safety equipment can use this model to monitor if employees are adhering to safety protocols, like wearing a helmet, goggles, or earmuffs.
Training Simulators: Training simulators for professions requiring safety gear could leverage this model to validate that trainees are correctly identifying and using the right type of equipment.
Automated Stock Detection: Supply chains or stock rooms that deal with safety gear could implement this model to keep track of their inventory by automatically counting the number of helmets, goggles, earmuffs, etc, in a room.
Emergency Response Applications: In situations like fire fighting or disaster response, the model could be used to verify that all members of the response team have the necessary protection equipment before they enter a risky area.
Educational/Academic Research: Schools and research institutions studying workplace safety could use the model to analyze how often workers are using the correct safety equipment, contributing to research in occupational safety and health.

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{
                            tcc-final_dataset,
                            title = { TCC FINAL Dataset },
                            type = { Open Source Dataset },
                            author = { TCC  FINAL },
                            howpublished = { \url{ https://universe.roboflow.com/tcc-final/tcc-final } },
                            url = { https://universe.roboflow.com/tcc-final/tcc-final },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { may },
                            note = { visited on 2024-05-15 },
                            }