Pothole Detection YOLOv8 Object Detection Dataset and Pre-Trained Model by Matt

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Explore Dataset

Here are a few use cases for this project:

City Infrastructure Maintenance: Municipalities could use this model to improve their road maintenance efficiency. The model could be integrated into mobile applications or vehicle-mounted cameras, allowing city workers to identify areas requiring pothole repair more accurately and promptly.
Road Safety Apps: An app developer could leverage this model to create a road safety app. The app would use the device's camera or user-uploaded pictures to detect potholes and alert drivers, bicyclists, and pedestrians about hazardous road conditions in real time.
Autonomous Vehicle Navigation: The model can enhance the perception system of autonomous vehicles. By detecting potholes, the vehicles can adjust their route to avoid potential damage, thereby improving the safety and durability of the autonomous vehicle fleet.
Insurance Claims Evaluation: Insurance companies could use this model to verify auto insurance claims related to pothole damage. It could help differentiate between pothole-related damage and other types of damage, providing a more factual basis for claim settlement.
Augmented Reality Gaming: Game developers could use the model to create a more immersive and adaptive gaming environment. For example, in an augmented reality racing game, real-world potholes could be translated into obstacles or points of interest in the game.

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{
                            pothole-detection-yolov8-ehkp9_dataset,
                            title = { Pothole Detection YOLOv8 Dataset },
                            type = { Open Source Dataset },
                            author = { Matt },
                            howpublished = { \url{ https://universe.roboflow.com/matt-s1uw6/pothole-detection-yolov8-ehkp9 } },
                            url = { https://universe.roboflow.com/matt-s1uw6/pothole-detection-yolov8-ehkp9 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { may },
                            note = { visited on 2024-06-29 },
                            }