MaskDetectionFasterR-CNN Object Detection Dataset and Pre-Trained Model by Final Project

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Explore Dataset

Here are a few use cases for this project:

Public Health Compliance Monitoring: This model can be used to monitor compliance with public health guidelines, particularly in indoor public spaces such as shopping centers, airports, or train stations. The system could track mask usage and send real-time alerts when individuals are not wearing masks or are wearing them incorrectly.
Workplace Safety Assurance: In pandemic situations or hazardous environments where mask usage is essential, this model can aid in ensuring safety rules. It can monitor employees in real-time, identifying those who might forget to put on their mask or wear it incorrectly, ensuring occupational safety.
Mask Compliance in Schools: Schools attempting to enforce mask regulations can use this model to monitor students within classrooms, hallways, and common areas to assess compliance and identify students not following mask guidelines.
Public Transport Compliance: The model can be used in public transportation systems (buses, trains, metros) to ensure passengers comply with mask-wearing rules. Non-compliant passengers could be identified for further action, ensuring safer travels for all.
Study of Mask Usage Patterns: The system can collect anonymized data about mask usage in different areas of a city, or between different geographically located areas. This information could provide valuable insights for policy-makers, helping them understand areas of low compliance and directing targeted informational campaigns for better public awareness.

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{
                            maskdetectionfasterr-cnn_dataset,
                            title = { MaskDetectionFasterR-CNN Dataset },
                            type = { Open Source Dataset },
                            author = { Final Project },
                            howpublished = { \url{ https://universe.roboflow.com/final-project-vgin0/maskdetectionfasterr-cnn } },
                            url = { https://universe.roboflow.com/final-project-vgin0/maskdetectionfasterr-cnn },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { may },
                            note = { visited on 2024-04-25 },
                            }