https://github.com/liaopeiyuan/artbench samples encoded to SDXL latents via Ollin VAE.
Dataset created using this script.
Schema/usage:
from typing import TypedDict, Iterator
from webdataset import WebDataset
Sample = TypedDict('Sample', {
'__key__': str,
'__url__': str,
'cls.txt': bytes, # UTF-8 encoded class id from 0 to 9 inclusive
'img.png': bytes, # PIL image, serialized
'latent.pth': bytes, # FloatTensor, serialized
})
it: Iterator[Sample] = WebDataset('train/{00000..00004}.tar')
for sample in it:
pass
The data sources of ArtBench-10 is released under a Fair Use license, as requested by WikiArt, Ukiyo-e.org database and The Surrealism Website.
For more information, see https://www.wikiart.org/en/terms-of-use, https://ukiyo-e.org/about and https://surrealism.website/
train: 50000 samples
test: 10000 samples
# test/avg/val.pt:
[-0.11362826824188232, -0.7059057950973511, 0.4819808006286621, 2.2327630519866943]
# test/avg/sq.pt:
[52.59075927734375, 30.115631103515625, 44.977020263671875, 30.228885650634766]
# train/avg/val.pt:
[-0.1536690890789032, -0.7142514586448669, 0.4706766605377197, 2.24863600730896]
# train/avg/sq.pt:
[51.99677276611328, 30.184646606445312, 44.909732818603516, 30.234216690063477]