metadata

dataset_info:
  features:
    - name: image
      dtype: image
  splits:
    - name: train
      num_bytes: 4450242498.020249
      num_examples: 287968
    - name: test
      num_bytes: 234247797.33875093
      num_examples: 15157
  download_size: 4756942293
  dataset_size: 4684490295.359
license: mit

Dataset Card for "lsun-bedrooms"

This is a 20% sample of the bedrooms category in LSUN, uploaded as a dataset for convenience.

The license for this compilation only is MIT. The data retains the same license as the original dataset.

This is (roughly) the code that was used to upload this dataset:

import os
import shutil

from miniai.imports import *
from miniai.diffusion import *

from datasets import load_dataset

path_data = Path('data')
path_data.mkdir(exist_ok=True)
path = path_data/'bedroom'

url = 'https://s3.amazonaws.com/fast-ai-imageclas/bedroom.tgz'
if not path.exists():
    path_zip = fc.urlsave(url, path_data)
    shutil.unpack_archive('data/bedroom.tgz', 'data')

dataset = load_dataset("imagefolder", data_dir="data/bedroom")
dataset = dataset.remove_columns('label')
dataset = dataset['train'].train_test_split(test_size=0.05)
dataset.push_to_hub("pcuenq/lsun-bedrooms")