ZDZW - Digitally Enhanced Non-destructive Inspection Services for globally competitive, clean, and sustainable production in European and Global Manufacturing

Part of EU Open Research Repository
Published April 7, 2025 | Version v1
Dataset Open

Coating Defect Detection Dataset

Authors/Creators

  • 1. ROR icon Universitat Politècnica de València
  • 2. Smart Systems and Smart Manufacturing Department (S3M). AIMEN Technology Centre, O Porriño, Spain
  • 3. GRI Renewable Industries, Madrid, Spain

Description

This dataset includes 2697 RGB images of Wind Tower Painting parts, along with bounding box annotations (YOLO format) for defect localization and classification. In 'class_labels.txt' a legend of the three labels of the defect classes is given. In 'metadata.csv' each image filename is related to the acquisition or section setup code. It also indicates the main label (in some images there is more than one defect), if a cold or warm white balance and high or low surface contrast are captured.

Files

Coating_Defect_Detection_Dataset.zip

Files (17.8 GB)

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Additional details

Funding

European Commission
ZDZW - Non-Destructive Inspection Services for Digitally Enhanced Zero Waste Manufacturing 101057404

Dates

Available
2025-04-07