Segmentation Damage Tire Computer Vision Model
How to use the Segmentation Damage Tire Segmentation 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="segmentation-damage-tire/1")Or, Use Free TY1, TY2 and TY3 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": "TY1, TY2, TY3, TY5, TY8"
},
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 Segmentation Damage Tire Model
Here are a few use cases for this project:
-
Tire Manufacturer Quality Control: This model could be used in tire manufacturing facilities to automatically detect and classify damaged tires in the production line, ensuring only high-quality products are distributed.
-
Automotive Repair and Maintenance: Car repair shops may use this model to automatically scan and determine the type of tire damage, helping them to accurately diagnose problems and suggest necessary repairs to customers.
-
Road Safety Authorities: The model could be used by road safety authorities and inspection centers to ensure the roadworthiness of vehicles, as part of routine checks or insurance assessments.
-
Used Car Dealerships: This computer vision model can be useful for used car dealerships to verify the condition of tires in the cars they are selling or buying, enhancing their decision-making process and ensuring the safety of customers.
-
Autonomous Vehicles: Autonomous vehicles could use this model as part of their on-board systems to monitor tire health in real-time, helping the vehicle identify when it may need tire-related maintenance.
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{ segmentation-damage-tire_dataset,
title = { Segmentation Damage Tire Dataset },
type = { Open Source Dataset },
author = { Print },
howpublished = { \url{ https://universe.roboflow.com/print/segmentation-damage-tire } },
url = { https://universe.roboflow.com/print/segmentation-damage-tire },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2025 },
month = { aug },
note = { visited on 2026-07-29 },
}