Shoe Dryer Shape Classification Dataset
#Image Classification #Object Detection #Product Classification #Image Recognition #E-commerce Application
- 5000 records
- 1.5G
- JPG/PNG/JSON
- CATL
MOBIUSI INC
Updated:2026-10-19
AI Analysis & Value Prop
The retail e-commerce industry faces challenges in accurately classifying product types, particularly in niche markets such as shoe dryers. Current solutions struggle with distinguishing between various shapes like folding, plug-in, and embedded designs, leading to inefficiencies in inventory management and customer experience. This dataset aims to address the need for a reliable classification system for shoe dryer shapes, enhancing product discoverability and operational efficiency. Data collection involved photographing shoe dryers in controlled lighting conditions to ensure clarity and consistency. Quality control measures included multiple rounds of annotation, consistency checks among annotators, and expert reviews to validate the accuracy of classifications. The dataset is organized in JPG format, with images stored alongside metadata in a structured manner for easy access.
Dataset Insights
Sample Examples
3d60a756**.jpg|1259*1586|139.10 KB
b22d7673**.jpg|1224*1632|104.28 KB
078e2a55**.jpg|1224*1632|218.95 KB
6b9c618e**.jpg|1352*1478|132.55 KB
9e8ad108**.jpg|1224*1632|247.34 KB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| shape_type | string | The specific shape types of the shoe dryer, such as round, square, etc. |
| color | string | The color of the shoe dryer as displayed in the image. |
| material | string | The potential materials used to make the shoe dryer, such as plastic or metal. |
| brand_mark | string | Whether there is a brand logo in the image and its name. |
| size_dimension | string | The size specifications of the shoe dryer, such as length, width, and height. |
| condition | string | The surface condition of the shoe dryer, such as new, old, or damaged. |
| position | string | The placement position of the shoe dryer in the image, such as front, side, etc. |
| usage_state | string | The usage status of the shoe dryer, such as in use, not in use, etc. |
| temperature_display | boolean | Whether there is a temperature display for the shoe dryer in the image. |
| plug_type | string | The plug type of the shoe dryer, such as EU standard, US standard, etc. |
Compliance Statement
| Authorization Type | Proprietary - Commercial AI Training License (No Redistribution) |
| 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 |
Frequently Asked Questions
- What is the Shoe Dryer Shape Type Classification Dataset?
- The Shoe Dryer Shape Type Classification Dataset is an image dataset used to classify shoe dryers according to their shape.
- Which industry is the Shoe Dryer Shape Type Classification Dataset applied to?
- This dataset is mainly applied in the retail industry for analyzing and classifying shoe dryer products.
- What is the data modality of the Shoe Dryer Shape Type Classification Dataset?
- The data modality of this dataset is images, containing pictures of shoe dryers of various shapes.
- What can this dataset help retailers achieve?
- Retailers can use this dataset to optimize inventory management and develop better sales and marketing strategies.
- How can this dataset be used for image classification?
- Machine learning algorithms can be used to train models, using this dataset to train models for classifying different shapes of shoe dryers.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Shoe Dryer Shape Classification Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/cb3f07b1dc9e38e3ae4638dbf9c05e2b?dataset_scene_id=9},
urldate={2025-08-28},
keywords={shoe dryer dataset,image classification,e-commerce product classification,machine learning dataset},
version={1.0}
}Using this in research? Please cite us.
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