Traffic Object Object Detection Dataset and Pre-Trained Model by Nota Bota

Images

4588 images

Explore Dataset

Here are a few use cases for this project:

Autonomous Driving Software: The "Traffic Object" model can be used to train self-driving vehicles to recognize different traffic objects such as cars, motorcycles, speed limit signs, and traffic lights.
Traffic Flow Analysis: It can be applied in understanding and analyzing traffic flow in different areas by identifying the types of vehicles, their movement, and traffic signals.
Traffic Rules Compliance Monitoring: Municipalities can use this model to monitor compliance with traffic regulations such as following speed limits and obeying No U-Turn or No Entry signs.
Augmented Reality Navigation Apps: In AR-based navigation applications, this model can be used to enhance the user's understanding of the road conditions ahead – for example, identifying a car accident or ambulance ahead and advising an alternate route.
Security Surveillance: The model can aid in security surveillance in traffic-heavy areas by identifying vehicles and other traffic objects. It can specifically detect suspicious activities like unauthorized parking, rudimentary vehicles in forbidden zones, or identify unattended objects at intersections or crosswalks.

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{
                            traffic-object-oyifo_dataset,
                            title = { Traffic Object Dataset },
                            type = { Open Source Dataset },
                            author = { Nota Bota },
                            howpublished = { \url{ https://universe.roboflow.com/nota-bota/traffic-object-oyifo } },
                            url = { https://universe.roboflow.com/nota-bota/traffic-object-oyifo },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jul },
                            note = { visited on 2024-04-25 },
                            }