Pothole Detection Computer Vision Model
How to use the Pothole Detection Detection API
Try This Model
Drop an image here or click to upload
Code Snippets
from inference_sdk import InferenceHTTPClient
CLIENT = InferenceHTTPClient(
api_url="https://serverless.roboflow.com",
api_key="API_KEY"
)
result = CLIENT.infer("YOUR_IMAGE.jpg", model_id="pothole-detection-lwf9u/3")Or, Use Free 0, 1 and 2 Detection API
Powered by general detection model
pip install inference-sdk# 1. Import the library
from inference_sdk import InferenceHTTPClient
# 2. Connect to your workspace
client = InferenceHTTPClient(
api_url="https://serverless.roboflow.com",
api_key="API_KEY"
)
# 3. Run your workflow on an image
result = client.run_workflow(
workspace_name="<YOUR_WORKSPACE>",
workflow_id="<YOUR_WORKFLOW_ID>",
images={
"image": "YOUR_IMAGE.jpg" # Path to your image file
},
parameters={
"classes": "0, 1, 2, 3, 4"
},
use_cache=True # cache workflow definition for 15 minutes
)
# 4. Get your results
print(result)Run on custom image
Drop an image here or click to upload
About Pothole Detection Model
Here are a few use cases for this project:
-
Road Maintenance Planning: Using the Pothole Detection model, city planners and public works departments can identify roads with varying degrees of pothole severity, allowing them to prioritize and schedule road repair projects more efficiently.
-
Vehicle Safety and Damage Prevention: Fleet management companies, transportation service providers, and car rental businesses can utilize the model to identify routes with a higher number of potholes and adjust their routing accordingly to minimize vehicle wear and tear and avoid potential damages.
-
Infrastructure Health Monitoring & Assessments: Government agencies or engineering consultants can use the model to analyze and monitor the overall condition of road infrastructure, helping them make informed decisions about construction budgets, maintenance strategies, and long-term improvement plans.
-
Accident Risk Reduction: Traffic safety organizations can use the Pothole Detection model to identify areas with a higher risk of accidents due to potholes, enabling them to take necessary precautions such as road signage, temporary speed limits, and public awareness campaigns.
-
Insurance Claim Analysis: Insurance companies can incorporate the pothole information obtained using the model when evaluating accident claims related to road conditions, helping them validate claims and identify potential fraud.
Tell the agent what you want to build.
Cite This Project
LicenseCC BY 4.0If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{ pothole-detection-lwf9u_dataset,
title = { Pothole Detection Dataset },
type = { Open Source Dataset },
author = { BE Project },
howpublished = { \url{ https://universe.roboflow.com/be-project-i13op/pothole-detection-lwf9u } },
url = { https://universe.roboflow.com/be-project-i13op/pothole-detection-lwf9u },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { may },
note = { visited on 2026-07-29 },
}