Edge Defect Detection Dataset for Flat Parts
#Defect Detection #Image Classification #Metal Quality Inspection #Assembly Consistency Assessment
- 15000 records
- 1.2G
- JPG/PNG/JSON
- CATL
MOBIUSI INC
Updated:2026-04-16
AI Analysis & Value Prop
In the current industrial landscape, the quality control of metal parts post-shearing is a critical challenge, as it directly affects the assembly process and product reliability. Many existing solutions rely on manual inspection, which is prone to human error and inefficiencies. Our dataset aims to address these issues by providing a comprehensive collection of images that specifically target edge defects in flat metal parts, which are often overlooked. The dataset is structured with images collected from high-resolution cameras in controlled environments, ensuring that the data is consistent and of high quality. Quality control measures include multi-round annotations and expert reviews to verify defect classifications, resulting in a reliable dataset. The images are stored in JPG format and organized systematically to facilitate easy access and processing.
Dataset Insights
Sample Examples
43d85cf9**.png|1531*1500|2.19 MB
7449cb4c**.png|1232*1500|3.47 MB
56c00c26**.png|1489*1500|1.04 MB
9d7fe964**.png|2060*1500|2.77 MB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| defect_type | string | Specific types of defects found on the edges, such as cracks, notches, etc. |
| defect_severity | string | The severity of the defect, such as minor, moderate, severe. |
| defect_width | int | The width of the defect in the image. |
| defect_height | int | The height of the defect in the image |
| component_material | string | The material of the flat parts, such as metal, plastic, etc. |
| image_orientation | string | The orientation in which the image was taken, such as front, side, etc. |
| background_complexity | string | The level of complexity of the image background, such as simple, complex |
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 is the Flat Part Edge Defect Detection Dataset?
- The Flat Part Edge Defect Detection Dataset is a high-quality image dataset designed for identifying and detecting edge defects of industrial parts, primarily used in automation detection.
- What types of images are included in this dataset?
- This dataset includes images of edge defects of various flat parts, intended for object detection tasks.
- What are the application areas of flat part edge defect detection?
- This dataset is primarily applied in the industrial automation sector to help improve the efficiency and accuracy of product quality inspection.
- How to use this dataset for object detection?
- You can use machine learning algorithms to train models that identify and detect edge defects of flat parts using the images from this dataset.
- Why does industrial automation need an edge defect detection dataset?
- Accurate edge defect detection in industrial automation can significantly improve production quality, thus reducing rework and waste.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Edge Defect Detection Dataset for Flat Parts},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/2512b2461436e1249722ff04d0d1f449?dataset_scene_id=2},
urldate={2025-08-28},
keywords={Edge Defect Detection,Industrial Quality Control,Metal Inspection Dataset,Flat Parts Defects},
version={1.0}
}Using this in research? Please cite us.
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