lanedetector Instance Segmentation Dataset and Pre-Trained Model by RDL

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Explore Dataset

Here are a few use cases for this project:

Autonomous Vehicle Navigation: The "lanedetector" model can be used in self-driving cars to identify and navigate between different lanes, including those marked with LaneLine, thereby ensuring safe travel.
Traffic Management Systems: Infrastructure and transport authorities can use the model to analyze traffic flow, locate potential traffic hazards or congestion steadily increasing in certain lanes to implement better traffic management solutions.
Road Maintenance: Government agencies in charge of road maintenance can use the "lanedetector" model to identify lanes or LaneLine that are fading or damaged, prioritizing road repairs and maintenance.
Traffic Rule Enforcement: The model can be integrated within traffic cameras to identify vehicles that are not adhering to their correct lanes, aiding enforcement of traffic rules.
Advanced Driver-Assistance Systems (ADAS): The model can be utilized in designing advanced driver-assistance systems by providing real-time lane identification data, aiding in features like lane departure warning and assistance.

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{
                            lanedetector-zsct6_dataset,
                            title = { lanedetector Dataset },
                            type = { Open Source Dataset },
                            author = { RDL },
                            howpublished = { \url{ https://universe.roboflow.com/rdl/lanedetector-zsct6 } },
                            url = { https://universe.roboflow.com/rdl/lanedetector-zsct6 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { mar },
                            note = { visited on 2024-05-07 },
                            }