Datasets:
file_name stringclasses 5 values | quality stringclasses 5 values | object_presence stringclasses 1 value | object_count stringclasses 1 value | object_position stringclasses 5 values | object_size stringclasses 1 value | liquid_level stringclasses 5 values | liquid_color stringclasses 3 values | visibility_level stringclasses 3 values | label_quality stringclasses 3 values | background_clarity stringclasses 3 values | environment_lighting stringclasses 3 values |
|---|---|---|---|---|---|---|---|---|---|---|---|
683bcff7946fb440e1d740129def1421.jpg | 3840*2592 | Present | 1 | Roughly in the middle of the image, slightly to the left | Medium | Medium position | Pink | Visible | Good | Clear | Good and natural |
82a430649a81913f820a538edc7dc2b5.jpg | 1280*960 | Present | 1 | Near the center of the image, slightly to the right | Medium | Approximately in the upper middle of the pot | Orange | Clear | Good | Moderate | Well-lit |
931c0c394b852ad3be92c0a465a25dfd.jpg | 2560*1440 | Present | 1 | Middle, slightly to the right | Medium | Almost full | Pink | Clear | Good | Clear | Good |
93dc865e13d4aaec47d3587bba2e68b0.jpg | 1080*1440 | Present | 1 | Near the center of the image | Medium | Near the upper mark of the pot | Clear/Light yellow | Visible | High | Relatively clear | Well-lit |
af098bd2c18cb93ed29a4e6734ca4fd7.jpg | 1280*720 | Present | 1 | Near the middle of the image, slightly to the left | Medium | Near mid-height | Pink | Very clear | High quality | Clear | Good |
Cooling Liquid Reservoir Detection Dataset
The Cooling Liquid Reservoir Detection Dataset was created to address the growing challenge in the industrial sector of monitoring and maintaining cooling systems. Current practices often rely on manual inspections, which are time-consuming and prone to human error. Existing automated solutions lack the required accuracy and adaptability to various environments. This dataset aims to improve the detection of liquid levels and anomalies in cooling systems through advanced image analysis techniques. The dataset comprises images collected from various industrial settings using high-resolution cameras under controlled lighting conditions. Quality control measures include multi-round annotations by trained experts and consistency checks to ensure data reliability. The images are stored in JPG format, organized by date and time of capture, facilitating easy retrieval and analysis.
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| object_presence | boolean | Whether there is a coolant jug in the picture. |
| object_count | int | The number of coolant jugs in the picture. |
| object_position | string | The position of the coolant jug in the picture, usually represented by the coordinates of a detection box. |
| object_size | string | The size of the coolant jug, commonly represented by the width and height of the detection box. |
| liquid_level | string | The height position of the liquid level in the coolant jug. |
| liquid_color | string | The color of the coolant liquid in the picture. |
| visibility_level | string | The clarity or visibility of the coolant bottle in the image |
| label_quality | string | Quality assessment of the target detection label for the coolant bottle |
| background_clarity | string | The clarity of the image background |
| environment_lighting | string | The lighting conditions when the image was taken |
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
- Downloads last month
- 13