[https://github.com/liaopeiyuan/artbench](ArtBench) samples encoded to SDXL latents via [Ollin VAE](https://huggingface.co/madebyollin/sdxl-vae-fp16-fix).

Dataset created using [this script](https://github.com/Birch-san/sdxl-diffusion-decoder/blob/main/script/make_sdxl_latent_dataset.py).

Schema/usage:

```python
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

```python
# 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]
```