Datasets:
file_name stringclasses 5 values | quality stringclasses 3 values | brand_logo_presence stringclasses 2 values | color_dominance stringclasses 2 values | door_type stringclasses 2 values | display_panel_presence stringclasses 2 values | control_knob_presence stringclasses 2 values | water_inlet_location stringclasses 5 values | energy_efficiency_label stringclasses 1 value | additional_features_text stringclasses 4 values |
|---|---|---|---|---|---|---|---|---|---|
0cd7d1439ec0d5799163adefb7c26c0d.jpg | 1224*1632 | Yes | White | Top-loading | No | No | Cannot be determined | No | None |
6a48c67e7df93318c886850d0dd6c3db.jpg | 1224*1632 | Yes | Gray | Top-loading | Yes | No | Uncertain | No | Multiple washing program options |
6be812329cf14bea72fa6dba8c7a192d.jpg | 1224*1632 | Yes | White | Front-loading | No | Yes | Not visible | No | Temperature, Time, Quick |
7f70a5be8d965bc98579c803c13a6bff.jpg | 1632*1224 | No | White | Top-loading | No | Yes | Rear | No | Washing, Drain, Timer |
aba4fe149d0fff0dd1e6ee674b39bf57.jpg | 1290*1450 | Yes | White | Top-loading | No | Yes | No obvious inlet | No | None |
Washing Machine Appearance Recognition Dataset
The washing machine industry faces challenges in accurately identifying different types of washing machines, such as drum, pulsator, and mini types, which complicates inventory management and enhances the risk of misclassification. Current solutions often rely on manual classification, which is time-consuming and error-prone. This dataset aims to provide a robust framework for training machine learning models that can automate the classification of washing machine appearances, thereby improving efficiency and accuracy in e-commerce applications. The dataset consists of images collected from various online retail platforms, ensuring a diverse representation of washing machines. Quality control measures include multiple rounds of annotation, consistency checks among annotators, and expert reviews to ensure high-quality labels. The images are stored in JPG format and organized in a directory structure by class labels.
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| brand_logo_presence | boolean | Whether the image contains a brand identifier. |
| color_dominance | string | The main color category of the washing machine, such as white, silver, black, etc. |
| door_type | string | The type of door of the washing machine, such as front-opening, top-opening. |
| display_panel_presence | boolean | Whether a display panel is visible in the image. |
| control_knob_presence | boolean | Whether the image includes a control knob |
| water_inlet_location | string | The position of the water inlet in the image, such as left side, right side, etc. |
| energy_efficiency_label | boolean | Whether the image includes an energy efficiency label |
| additional_features_text | string | The additional functions or textual descriptions on the washing machine, such as quick wash, hot air |
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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