Datasets:

detection-datasets
/

fashionpedia_4_categories

image_id int64 23 50.5k	width int64 232 1.02k	height int64 388 1.02k	objects sequence
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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.

Downloads last month: 110

Papers with Code

Size of downloaded dataset files:

3.47 GB

Size of the auto-converted Parquet files:

3.47 GB

Number of rows:

46,780

Models trained or fine-tuned on detection-datasets/fashionpedia_4_categories

kesimeg/yolov8n-clothing-detection

Object Detection • Updated Oct 5