Wood Surface Defect Inspection and Material Defect Recognition Image Dataset
#Defect object detection #Flaw image classification #Defect region localization #Surface defect recognition #Lumber production line inspection #Furniture panel incoming inspection #Wood grading and sorting #Processing quality tracking
- 2144
- 0.2GB
- piece
- CATL
MOBIUSI INC
Updated:2026-11-05
AI Analysis & Value Prop
This dataset focuses on surface flaws and material defects in wood, providing wood images along with annotation file paths, category IDs, image dimensions, and format information. It supports the development of wood defect recognition and quality inspection workflows for applications such as wood processing, panel sorting, and production-line inspection.
Dataset Insights
Sample Examples
5a284085**.jpg||0 B
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| image_id | string | Unique identifier for the image record. |
| image_path | string | Path to the image file. |
| label_path | string | Path to the annotation file associated with the image. |
| category_id | array | Identifier for the image's defect category. |
| image_width | number | Width of the image in pixels. |
| image_format | string | File format of the image. |
| image_height | number | Height of the image in pixels. |
Compliance Statement
| Authorization Type | Proprietary - Commercial AI Training License (No Redistribution) |
| Commercial Use | Requires exclusive subscription or authorization contract (monthly or per-invocation charging) |
| Privacy and Anonymization | No PII, no real company names, simulated scenarios follow industry standards |
| Compliance System | Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs |
Frequently Asked Questions
- What does the dataset contain?
- The dataset centers on wood surface images and provides fields for image identifiers, image paths, annotation file paths, category IDs, image width, image height, and image format.
- Which models can be trained with this dataset?
- It can support wood flaw image classification, defect object detection, and defect region localization. Whether a specific task is feasible depends on the annotation format and category information available in the annotation files.
- Which real-world applications is it suited for?
- Potential applications include lumber production line inspection, incoming inspection of furniture panels, wood grading and sorting, and quality tracking during processing. It can serve as training or validation data for automated visual inspection systems.
- How can I access the data, and what should I check before using it?
- Check the data provider's platform for available access methods, file formats, and licensing terms. Before use, verify that annotation files correspond to the correct image paths and confirm that the license covers your intended project.
Can't find the data you need?
Post a request and let data providers reach out to you.
Get this Dataset
Verified for Enterprise UseCite this Work
@dataset{Mobiusi2026,
title={Wood Surface Defect Inspection and Material Defect Recognition Image Dataset},
author={MOBIUSI INC},
year={2026},
url={https://www.mobiusi.com/datasets/1b1e65eb6b9b9769ee623b4c192904da},
urldate={2026-11-05},
keywords={wood defect dataset,wood defect recognition,wood surface inspection,wood panel defect detection,wood image dataset,panel quality inspection,industrial visual inspection,wood flaw annotations},
version={1.0}
}Using this in research? Please cite us.
placeholder
placeholder
placeholder
placeholder
placeholder
placeholder
placeholder