segmentation_road Instance Segmentation Dataset and Pre-Trained Model by image segmentation

Images

707 images

Explore Dataset

Here are a few use cases for this project:

Autonomous Vehicle Navigation: The "segmentation_road" model can be incredibly useful for autonomous vehicles to identify and navigate through different kinds of road patterns which will ultimately contribute to better decisions while on the commute (like turning or changing lanes).
Traffic Management Systems: Implementing this model can help traffic management systems understand and predict the flow of traffic in different road patterns, improving congestion management, and implementing dynamic traffic signal controls.
Urban Planning: Understanding roads' layout using this model can assist city planners and architects when planning city infrastructures, ensuring a more efficient and safer road system.
Road Maintenance and Monitoring: The model can be used by city services to monitor road conditions, identify road degradation over time and prioritize maintenance and repairs.
Virtual Reality (VR) & Gaming: In the development of VR applications or games, this model can help in creating more realistic virtual environments by distinguishing various road layout patterns.

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{
                            segmentation_road_dataset,
                            title = { segmentation_road Dataset },
                            type = { Open Source Dataset },
                            author = { image segmentation },
                            howpublished = { \url{ https://universe.roboflow.com/image-segmentation-awhml/segmentation_road } },
                            url = { https://universe.roboflow.com/image-segmentation-awhml/segmentation_road },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { mar },
                            note = { visited on 2024-06-18 },
                            }