Datasets:
file_name stringclasses 5 values | quality stringclasses 4 values | image_quality stringclasses 1 value | image_brightness stringclasses 3 values | image_contrast stringclasses 3 values | belt_position stringclasses 5 values | belt_path stringclasses 5 values | slack_detection stringclasses 3 values | defect_annotation stringclasses 5 values | object_count stringclasses 4 values | lighting_conditions stringclasses 5 values | focus_quality stringclasses 1 value |
|---|---|---|---|---|---|---|---|---|---|---|---|
00b168509284beb3e52166488195fb2a.jpg | 984*1813 | High | Slightly bright | Moderate | Bottom left of the image | Runs along the pulley | No significant slack | Worn fibers at edge | 3 | Naturally bright lighting | Clear |
03d34c5925be167ef8fcfe8dfe7ad34a.jpg | 984*1813 | High | Medium | Medium | Located slightly to the left of the center of the image | Going along the gear | No obvious slack | Existence of wear and breakage | 3 | Shot under natural light | Clear |
2c6aa8b2dbca24cbe1514a3d19a76d19.jpg | 1080*1330 | High | Lower | Moderate | Slightly below the center of the image | Following gear grooves | No obvious slack | Belt surface has cracks | Few recognizable objects | Natural lighting, weak light | Clear |
9b7c51fb161da1079bba492ba0f9e7ff.jpg | 1080*1317 | High | Medium | Normal | In the engine compartment, the belt is held on the right | Belt bypassing engine accessories | No obvious slack | Belt shows significant wear and tears | Multiple recognizable objects, including engine accessories | Even lighting, clear details | Clear |
f54c88cf8348945c2281181d35deef39.jpg | 1080*726 | High | Medium | Medium | Located in the center of the image, spanning the gear | Travels along the gear circumference | Slight slack present | No obvious defects | Multiple gear devices | Natural light, slightly soft | Clear |
Belt Detection Dataset
The current industrial sector faces significant challenges in ensuring optimal belt operation, which is critical for manufacturing efficiency. Existing solutions often lack real-time monitoring capabilities and fail to provide accurate assessments of belt conditions. This dataset aims to address these technical issues by providing high-quality images for effective object detection and path recognition of belts. The data was collected using high-resolution cameras in controlled industrial environments. Quality control was ensured through multiple rounds of annotation, consistency checks, and expert reviews. Data is stored in JPG format, organized by specific conditions and labeled accurately.
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| image_quality | string | Quality rating of the image, such as high, medium, low. |
| image_brightness | float | Overall brightness value of the image. |
| image_contrast | float | Contrast value of the image. |
| belt_position | string | Detailed description of the belt's position in the image. |
| belt_path | string | Description of the belt's movement path. |
| slack_detection | boolean | Whether there is slack in the belt in the image. |
| defect_annotation | string | Description of belt defects in the image, such as cracks, wear, etc. |
| object_count | integer | Number of recognizable objects in the image. |
| lighting_conditions | string | Description of lighting conditions during image capture |
| focus_quality | string | Description of the image focus condition, such as sharp, blurred |
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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