Datasets:
file_name stringclasses 5 values | quality stringclasses 5 values | crack_presence stringclasses 1 value | crack_location stringclasses 5 values | crack_length stringclasses 4 values | crack_width stringclasses 5 values | crack_depth stringclasses 2 values | crack_type stringclasses 3 values | image_quality stringclasses 1 value | lighting_conditions stringclasses 3 values | panel_color stringclasses 1 value | background_clarity stringclasses 2 values |
|---|---|---|---|---|---|---|---|---|---|---|---|
29e38c4c563d11cabb6879a292ba1c80.jpg | 1080*1386 | Present | Upper right corner | Approximately 300 millimeters | Approximately 1 millimeter | Unknown | Surface crack | Clear | Natural light | Black | Clear |
4f8e30989a50a611d6e19101a8e3bc1d.jpg | 1080*1411 | Present | Bottom Right | 100 mm | 1 mm | Uncertain | Through Crack | Clear | Artificial Light | Black | Clear |
53eaa464d0ed875b09d47d0786ecd4dd.jpg | 1080*1408 | Present | Multiple locations, Center and Edge | Varying lengths of multiple cracks | Varying widths of multiple cracks | Unknown | Through Crack | Clear | Natural Light | Black | Clear |
8babceee8b78589b8fcc56abe39c4dc2.jpg | 1080*1440 | Present | Left Side | 100 mm | 2 mm | Unknown | Surface Crack | Clear | Natural Light | Black | Clear |
c0bd35749118e3b805691338339d79b7.jpg | 1080*1892 | Present | Center Right | Indeterminate, extending in multiple directions | Thin | Unknown | Through Crack | Clear | Natural Light | Black | Blurred |
Induction Cooker Ceramic Panel Crack Identification Dataset
In the current industrial field, the crack problem of induction cooker ceramic panels poses a threat to product safety, leading to potential explosion risks. Existing detection methods mostly rely on manual inspection, which is inefficient and prone to errors. This dataset aims to provide high-quality crack image data to train machine learning models, automating the detection process and improving detection efficiency and accuracy. The dataset contains 5000 crack images taken with high-resolution cameras in actual production environments, ensuring the data is authentic and reliable. Quality control measures include multiple rounds of annotation, consistency checks, and expert reviews to ensure the accuracy of the annotations. Data is stored in JPG format for easy loading and processing.
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| crack_presence | boolean | Determines the presence of cracks on the ceramic panel as a boolean value. |
| crack_location | string | The specific location of cracks on the ceramic panel, such as the upper left corner, lower right corner, etc. |
| crack_length | float | The length of the crack, measured in millimeters. |
| crack_width | float | The width of the crack, measured in millimeters. |
| crack_depth | float | The depth of the crack, measured in millimeters. |
| crack_type | string | The type of crack, such as surface crack, through crack, etc. |
| image_quality | string | The quality rating of the image, such as clear, blurred, etc. |
| lighting_conditions | string | Description of lighting conditions when the image was taken, such as natural light, artificial light, etc. |
| panel_color | string | The color of the ceramic panel of the induction cooker. |
| background_clarity | string | Description of the clarity of the background, such as clear, blurred, etc. |
Compliance Statement
| 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 |
Source & Contact
If you need more dataset details, please visit Mobiusi. or contact us via contact@mobiusi.com
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