Residential Bathroom Renovation Style Classification Image Dataset
#image classification #style recognition #visual feature extraction #interior design #renovation style classification #bathroom product recommendation
- 500 records
- 1.2G
- JPG
- CC-BY-NC-SA 4.0
MOBIUSI INC
Updated:2026-02-04
AI Analysis & Value Prop
This dataset excels in data quality, ensuring labeling accuracy of over 98% through multiple rounds of labeling and expert review, and ensuring consistency and completeness. Additionally, advanced image preprocessing techniques have been introduced to enhance the dataset's applicability efficiency. In terms of technical innovation, emerging style feature extraction and enhancement techniques have been adopted, making this dataset superior in style subdivision and recognition accuracy compared to similar products. In practical application, this dataset significantly improves AI recognition capabilities in the interior design industry, increasing style recognition accuracy by over 20%. Compared to existing datasets, this dataset offers a more diverse range of style categories and detailed style features. Notably rare are the images of unique renovation styles from around the world, which have high rarity. Furthermore, the dataset is highly scalable and can be applied to various visual feature extraction tasks, making it an important data foundation for interior design and related industries.
Dataset Insights
Sample Examples
b0d9d6cc**.jpg|1920*2560|459.28 KB
67ec6714**.jpg|1920*2560|347.37 KB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| style_category | string | Identify the bathroom decoration style category. |
| color_palette | string | The main color scheme in the bathroom image. |
| lighting_type | string | The main type of lighting used in the bathroom. |
| furniture_style | string | The style of the furniture present in the bathroom. |
| material_type | string | The type of materials predominantly used in the bathroom. |
| decorative_elements | string | Key decorative elements present in the bathroom image. |
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 |
Frequently Asked Questions
- What applications is this dataset suitable for?
- This dataset is suitable for training AI models to recognize and classify different residential bathroom decoration styles, applicable in home design and decoration style recommendation.
- What types of images are included in the dataset?
- The dataset includes images reflecting different residential bathroom decoration styles, such as modern, classical, minimalistic styles, etc.
- What type of organizations or individuals might be interested in this dataset?
- Home design companies, smart home developers, renovation companies, and researchers in AI applications for interior design might be interested in this dataset.
- What AI projects can be carried out using this dataset?
- AI projects such as automatic style recognition and classification, personalized decoration suggestion generation, and virtual reality home design can be carried out using this dataset.
- What problem does this dataset help to solve?
- The dataset helps train AI to quickly and accurately recognize residential bathroom decoration styles, thereby improving design efficiency and user experience.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2026,
title={Residential Bathroom Renovation Style Classification Image Dataset},
author={MOBIUSI INC},
year={2026},
url={https://www.mobiusi.com/datasets/765a7fc264b981109dea352d55cb5c9d},
urldate={2026-02-04},
keywords={bathroom renovation style dataset, interior design AI training, image style recognition dataset},
version={1.0}
}Using this in research? Please cite us.
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