ceramic-tile-defects Computer Vision Dataset
About ceramic-tile-defects Dataset
Here are a few use cases for this project:
-
Quality Control in Tile Manufacturing: Use the "ceramic-tile-defects" model to automate the quality assurance process in ceramic tile factories. Manufacturers can utilize the model to identify defective tiles (edge-chipping, hole, line) on the production line, reduce waste, and improve overall product quality.
-
Inventory Management for Tile Retailers: Tile retailers can use the "ceramic-tile-defects" model to scan and sort incoming shipments, automatically detecting and isolating tiles with defects. This will enable efficient inventory management and the ability to address issues with suppliers more effectively.
-
Tile Installation Assistance: Professional tile installers and DIY enthusiasts can use the "ceramic-tile-defects" model to quickly assess the quality of tiles before installation. This will help avoid the expense and time of installing defective tiles and ensure a higher-quality finished project.
-
Inspection Services for Construction Industry: Incorporate the "ceramic-tile-defects" model into construction inspection services to quickly and accurately assess the quality of tile work in new buildings or remodeling projects. This will help identify issues early, ensuring a safe and high-quality build.
-
Machine Learning Research and Development: Utilize the "ceramic-tile-defects" dataset to advance research in computer vision algorithms, specifically in the area of defect detection on textured surfaces like ceramic tiles. This will contribute to the overall improvement of computer vision models and applications in the industrial and manufacturing sectors.
Use Free Hole, Line and Edge-chipping 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": "hole, line, edge-chipping"
},
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
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{ ceramic-tile-defects-veck6-ej4ie_dataset,
title = { ceramic-tile-defects Dataset },
type = { Open Source Dataset },
author = { FOX },
howpublished = { \url{ https://universe.roboflow.com/fox-1uxaz/ceramic-tile-defects-veck6-ej4ie } },
url = { https://universe.roboflow.com/fox-1uxaz/ceramic-tile-defects-veck6-ej4ie },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2026 },
month = { jun },
note = { visited on 2026-07-29 },
}










