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ClothingADC Dataset
ClothingADC is a large-scale clothing image dataset with fine-grained attribute annotations, designed for mental image retrieval research.
Dataset Statistics
- Total images: 1,076,738
- Clothing categories: 12 (Dress, Shirt, T-shirt, Jacket, Hoodie, Sweater, Suit, Vest, Windbreaker, Knitwear, Shawl, Underwear)
- Color attributes: 36 colors
- Material attributes: various fabrics (Linen, Wool, Cotton, etc.)
- Pattern attributes: various patterns (Paisley, Geometric, Solid, etc.)
Dataset Fields
| Field | Type | Description |
|---|---|---|
id |
string | Unique image identifier |
image |
Image | Clothing image (PNG) |
class |
string | Clothing category |
color |
string | Dominant color |
material |
string | Fabric material |
pattern |
string | Visual pattern |
Usage
from datasets import load_dataset
ds = load_dataset("mikelmh025/ClothingADC")
sample = ds["train"][0]
print(sample["class"], sample["color"], sample["material"], sample["pattern"])
sample["image"].show()
Citation
If you use this dataset, please cite:
@article{genir2024,
title={GenIR: Generative Visual Feedback for Mental Image Retrieval},
author={...},
year={2024}
}
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