Classification of Potholes Computer Vision Project
Updated a year ago
458
20
Metrics
Here are a few use cases for this project:
-
Road Maintenance: Public work departments and road agencies can use this model to identify, classify, and prioritize the repair of potholes, improving efficiency and road safety.
-
Vehicle Safety: Automobile manufacturers or tech companies could integrate this model into vehicle systems to alert drivers about upcoming potholes, enhancing driving safety and preventing vehicle damage.
-
Infrastructure Analysis: Urban city planners and engineers can use the model to assess the current condition of road infrastructure, aid in planning future road projects, and allocate repair resources more effectively.
-
Autonomous Vehicles: Self-driving car systems could use the model to detect and navigate around potholes, contributing to the overall navigational and safety features of the vehicle.
-
Ride-Sharing Apps: Companies like Uber or Lyft could make use of this model to provide safer and smoother rides to their customers by avoiding roads with severe potholes, thus enhancing the user's experience.
Use This Trained Model
Try it in your browser, or deploy via our Hosted Inference API and other deployment methods.
Build Computer Vision Applications Faster with Supervision
Visualize and process your model results with our reusable computer vision tools.
Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
classification-of-potholes_dataset,
title = { Classification of Potholes Dataset },
type = { Open Source Dataset },
author = { Pothole Defects },
howpublished = { \url{ https://universe.roboflow.com/pothole-defects/classification-of-potholes } },
url = { https://universe.roboflow.com/pothole-defects/classification-of-potholes },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { aug },
note = { visited on 2024-12-21 },
}