Grad_Project Object Detection Dataset and Pre-Trained Model by Project

Images

3307 images

Explore Dataset

Here are a few use cases for this project:

Smart Traffic Management: Grad_Project can be used in traffic control centers to monitor traffic signs in real-time, providing traffic controllers with valuable information on traffic flow restrictions, warnings, and up-to-date traffic behavior data to optimize traffic signals and proactively address congestion issues.
Autonomous Vehicle Navigation: The model can be integrated into self-driving car systems to identify traffic signs and make real-time decisions, such as adjusting the vehicle's speed, recognizing pedestrian crossings for increased safety, and obeying traffic restrictions like no U-turns or no parking zones.
Traffic Sign Maintenance: Grad_Project can assist local authorities and road maintenance crews by identifying damaged or obscured traffic signs that require repair or cleaning, helping to maintain a safe and efficient road network.
Driving Assistance Systems: The model can be incorporated into Advanced Driver Assistance Systems (ADAS) to alert drivers of upcoming traffic signs, providing critical information on speed limits, warnings, and restrictions, allowing drivers to make informed decisions in real-time and avoid traffic violations.
Education and Training: Grad_Project can be used in driving schools and simulation tools for teaching new drivers to recognize various traffic signs and their meanings, facilitating learning and reinforcing safe driving practices.

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{
                            grad_project-sbq7e_dataset,
                            title = { Grad_Project Dataset },
                            type = { Open Source Dataset },
                            author = { Project },
                            howpublished = { \url{ https://universe.roboflow.com/project-wyyo5/grad_project-sbq7e } },
                            url = { https://universe.roboflow.com/project-wyyo5/grad_project-sbq7e },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { mar },
                            note = { visited on 2024-05-04 },
                            }