guardrail_ditection Object Detection Dataset and Pre-Trained Model by Asano

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Explore Dataset

Here are a few use cases for this project:

Highway Safety Inspection: A computer vision model like "guardrail_detection" would be crucial in helping highway maintenance professionals assess the current state of guardrails on highways and bridges, ensuring their integrity and safety.
Infrastructure Monitoring: This model could be deployed in a real-time monitoring system to detect damages or changes to guardrails or fences, alerting authorities for potential maintenance or repair needs.
Urban Development Planning: During the planning or auditing of urban spaces, this model could help in identifying guardrail structures, helping authorities develop or alter public safety measures.
Autonomous Vehicle Navigation: This model could be used to aid autonomous vehicle systems in recognizing and differentiating various guardrail types, eventually improving the safety of autonomous navigation.
Industrial Safety: In factories or industrial environments, the model can be used to keep track of safety barriers such as guard pipes, vertical fences, or expanded metals to ensure employee safety and regulatory compliance.

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{
                            guardrail_ditection_dataset,
                            title = { guardrail_ditection Dataset },
                            type = { Open Source Dataset },
                            author = { Asano },
                            howpublished = { \url{ https://universe.roboflow.com/asano-ytoe5/guardrail_ditection } },
                            url = { https://universe.roboflow.com/asano-ytoe5/guardrail_ditection },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jan },
                            note = { visited on 2024-06-27 },
                            }