Datasets:
Tasks:
Object Detection
Languages:
English
Multilinguality:
monolingual
Size Categories:
10K<n<100K
Source Datasets:
fashionpedia
License:
image_id
int64 23
50.5k
| image
imagewidth (px) 232
1.02k
| width
int64 232
1.02k
| height
int64 388
1.02k
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End of preview. Expand
in Dataset Viewer.
Dataset Card for Fashionpedia_4_categories
This dataset is a variation of the fashionpedia dataset available here, with 2 key differences:
- It contains only 4 categories:
- Clothing
- Shoes
- Bags
- Accessories
- New splits were created:
- Train: 90% of the images
- Val: 5%
- Test 5%
The goal is to make the detection task easier with 4 categories instead of 46 for the full fashionpedia dataset.
This dataset was created using the detection_datasets library (GitHub, PyPI), you can check here the full creation notebook.
In a nutshell, the following mapping was applied:
mapping = {
'shirt, blouse': 'clothing',
'top, t-shirt, sweatshirt': 'clothing',
'sweater': 'clothing',
'cardigan': 'clothing',
'jacket': 'clothing',
'vest': 'clothing',
'pants': 'clothing',
'shorts': 'clothing',
'skirt': 'clothing',
'coat': 'clothing',
'dress': 'clothing',
'jumpsuit': 'clothing',
'cape': 'clothing',
'glasses': 'accessories',
'hat': 'accessories',
'headband, head covering, hair accessory': 'accessories',
'tie': 'accessories',
'glove': 'accessories',
'belt': 'accessories',
'tights, stockings': 'accessories',
'sock': 'accessories',
'shoe': 'shoes',
'bag, wallet': 'bags',
'scarf': 'accessories',
}
As a result, annotations with no category equivalent in the mapping have been dropped.
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