hat_symbol Object Detection Dataset and Pre-Trained Model by staff

Images

9411 images

Explore Dataset

Here are a few use cases for this project:

Safety and Hazard Detection: The "hat_symbol" model could be used to analyze images of work sites and identify safety or hazard symbols and signage, ensuring that necessary safety measures and warnings are effective and clearly visible.
Educational Material Analysis: The model could be applied to assess educational materials, such as textbooks, diagrams, and presentations, helping educators better understand and categorize the use of specific symbols in various subject matters, like chemistry or physics.
Automatic Inventory Management: In the chemical or manufacturing industries, the model could help with automatic detection and categorization of products based on their symbol classification, enabling improved stock management and organization.
Emergency and Rescue Operations: The "hat_symbol" computer vision model could be utilized by first responders and emergency personnel in analyzing real-time images or drone footage to quickly identify and locate dangerous substances or hazards during natural disasters, accidents, or other emergency situations.
Environmental Monitoring and Research: The model could play a significant role in conducting large-scale environmental analysis by identifying various symbols and potential contaminants or hazardous materials in images of air, water, and soil samples, thereby aiding scientists in their research and decision-making processes.

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{
                            hat_symbol_dataset,
                            title = { hat_symbol Dataset },
                            type = { Open Source Dataset },
                            author = { staff },
                            howpublished = { \url{ https://universe.roboflow.com/staff-uwyzv/hat_symbol } },
                            url = { https://universe.roboflow.com/staff-uwyzv/hat_symbol },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jan },
                            note = { visited on 2024-06-22 },
                            }