Mold Template Defect Recognition Dataset
V1.0Latest Update: | 2025-10-16 | Samples: | 5000 records |
Samples: | 5000 records | ||
File Size: | 1.2G | Format: | JPG/PNG/JSON |
Format: | JPG/PNG/JSON | ||
Data Domain: | Image | Holder: |  MOBIUSI INC |
Holder: | MOBIUSI INC | ||
Industry Scope: | Industrial Inspection | Quality Control | Defect Detection | ||
Applications: | Image Classification | Object Detection | ||
Brief Introduction
In the industrial sector, mold quality inspection is crucial for ensuring product integrity but faces challenges such as inconsistent defect detection and high rates of false negatives. Existing solutions often rely on manual inspection, which is time-consuming and prone to human error, leading to inefficiencies. This dataset aims to address these challenges by providing a comprehensive collection of labeled images that enhance machine learning models for accurate defect recognition in mold templates. Data was collected using high-resolution cameras in controlled industrial environments, ensuring clarity and consistency. Quality control measures included multiple rounds of labeling, consistency checks among annotators, and expert reviews to maintain high accuracy. The images are stored in JPG format, organized in directories by defect type, facilitating easy access and processing.
Sample Examples
| Image | File Name | Resolution | Defect Type | Defect Location | Severity Level | Bounding Box Coordinates | Surface Condition | Lighting Conditions | Image Quality |
|---|---|---|---|---|---|---|---|---|---|
 | 8422f40db2daec16658744c0586b7185.jpg | 1080*1414 | Cracks and wear | Slits and openings in the central part of the mold | Moderate | (150, 100, 300, 200) | Slight surface wear with metal shavings | Natural light | Clear |
 | ddfdfae294b72f292dd207659a87d6a8.jpg | 1074*1888 | Notch | Edge of the circular hole | Moderate | (100, 150, 200, 250) | Relatively rough, with wear | Natural light | Relatively clear |
 | a4e76f92f1ba140093566059c85336ed.jpg | 1080*1403 | Crack | Multiple slits in the central part of the mold | Medium | (100, 100, 200, 200) | Slightly worn | Natural light | Clear |
 | f4d4b8eee780f6c263646b3d7fe17f3d.jpg | 1920*1038 | No significant defect observed | None | None | None | Good | Natural light | Clear |
Data Structure
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| defect_type | string | The types of defects appearing on the mold, such as cracks and pores. |
| defect_location | string | A detailed description of the defect's specific location on the mold. |
| severity_level | integer | The severity level of the defect as defined by the standards. |
| bounding_box_coordinates | string | Coordinates of the bounding box that marks the defect in the target detection task. |
| surface_condition | string | The overall condition of the mold surface, including the presence of oxidation or wear. |
| light_condition | string | The lighting conditions when capturing the image, such as natural light or artificial light. |
| image_quality | string | The quality assessment of the image, such as clarity or blurriness. |
Compliance Statement
| Item | Content |
|---|---|
| Authorization Type | CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike) |
| 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 |
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