Smart Washing Machine Image Classification Dataset

#image classification #object detection #smart home #device recognition #image processing
  • 5000 records
  • 1.2G
  • JPG/PNG/JSON
  • CC-BY-NC-SA 4.0
  • MOBIUSI INCMOBIUSI INC
Updated:2026-03-11

AI Analysis & Value Prop

The current smart home industry is developing rapidly, and smart washing machines, as an important component, face the challenge of accurately identifying different models and functions. Existing recognition systems mostly rely on traditional methods and lack sufficient image data support, resulting in low recognition accuracy. Therefore, this dataset aims to provide a rich set of smart washing machine image samples to support the training of machine learning models in image classification tasks. Data collection is done through high-resolution cameras under standard lighting conditions to ensure image quality. To ensure data quality, multiple rounds of annotation and expert review procedures are adopted to ensure the accuracy of each image label. Data storage uses the JPEG format for ease of subsequent processing and analysis. This dataset has a clear structure, making it easy to retrieve and use quickly.

Dataset Insights

Sample Examples

8c557089**.jpg|1065*1280|118.81 KB

f1f9a500**.jpg|1084*1280|140.44 KB

fcc03677**.jpg|976*1280|124.33 KB

c1b2a9a8**.jpg|1007*1280|196.15 KB

f8a0e75e**.jpg|1080*1362|136.64 KB

Technical Specifications

Compliance Statement

Authorization TypeCC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike)
Commercial UseRequires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and AnonymizationNo PII, no real company names, simulated scenarios follow industry standards
Compliance SystemCompliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

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Cite this Work

@dataset{Mobiusiundefined,
  title={},
  author={Mobiusi},
  year={undefined},
  url={https://www.mobiusi.com/datasets/5faf4b53ee7958710b12c8aa92a1f6c8},
  urldate={},
  keywords={},
  version={}
}

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