celeb_a_hq

• Description:

High-quality version of the CELEBA dataset, consisting of 30000 images in 1024 x 1024 resolution.

• Additional Documentation: Explore on Papers With Code north_east

• Homepage: https://github.com/tkarras/progressive_growing_of_gans

• Source code: tfds.datasets.celeb_a_hq.Builder

• Versions:

  • 2.0.0 (default): New split API (https://tensorflow.org/datasets/splits)

• Download size: Unknown size

• Manual download instructions: This dataset requires you to download the source data manually into download_config.manual_dir (defaults to ~/tensorflow_datasets/downloads/manual/):
  manual_dir should contain multiple tar files with images (data2x2.tar, data4x4.tar .. data1024x1024.tar). Detailed instructions are here: https://github.com/tkarras/progressive_growing_of_gans#preparing-datasets-for-training

• Splits:

• Supervised keys (See as_supervised doc): None

• Citation:

@article{DBLP:journals/corr/abs-1710-10196,
  author    = {Tero Karras and
               Timo Aila and
               Samuli Laine and
               Jaakko Lehtinen},
  title     = {Progressive Growing of GANs for Improved Quality, Stability, and Variation},
  journal   = {CoRR},
  volume    = {abs/1710.10196},
  year      = {2017},
  url       = {http://arxiv.org/abs/1710.10196},
  archivePrefix = {arXiv},
  eprint    = {1710.10196},
  timestamp = {Mon, 13 Aug 2018 16:46:42 +0200},
  biburl    = {https://dblp.org/rec/bib/journals/corr/abs-1710-10196},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

celeb_a_hq/1024 (default config)

• Config description: CelebaHQ images in 1024 x 1024 resolution

• Dataset size: 54.04 GiB

• Auto-cached (documentation): No

• Feature structure:

FeaturesDict({
    'image': Image(shape=(1024, 1024, 3), dtype=uint8),
    'image/filename': Text(shape=(), dtype=string),
})

• Feature documentation:

• Figure (tfds.show_examples):

• Examples (tfds.as_dataframe):

celeb_a_hq/512

• Config description: CelebaHQ images in 512 x 512 resolution

• Dataset size: 15.33 GiB

• Auto-cached (documentation): No

• Feature structure:

FeaturesDict({
    'image': Image(shape=(512, 512, 3), dtype=uint8),
    'image/filename': Text(shape=(), dtype=string),
})

• Feature documentation:

• Figure (tfds.show_examples):

• Examples (tfds.as_dataframe):

celeb_a_hq/256

• Config description: CelebaHQ images in 256 x 256 resolution

• Dataset size: 4.21 GiB

• Auto-cached (documentation): No

• Feature structure:

FeaturesDict({
    'image': Image(shape=(256, 256, 3), dtype=uint8),
    'image/filename': Text(shape=(), dtype=string),
})

• Feature documentation:

• Figure (tfds.show_examples):

• Examples (tfds.as_dataframe):

celeb_a_hq/128

• Config description: CelebaHQ images in 128 x 128 resolution

• Dataset size: 1.13 GiB

• Auto-cached (documentation): No

• Feature structure:

FeaturesDict({
    'image': Image(shape=(128, 128, 3), dtype=uint8),
    'image/filename': Text(shape=(), dtype=string),
})

• Feature documentation:

• Figure (tfds.show_examples):

• Examples (tfds.as_dataframe):

celeb_a_hq/64

• Config description: CelebaHQ images in 64 x 64 resolution

• Dataset size: 310.94 MiB

• Auto-cached (documentation): No

• Feature structure:

FeaturesDict({
    'image': Image(shape=(64, 64, 3), dtype=uint8),
    'image/filename': Text(shape=(), dtype=string),
})

• Feature documentation:

• Figure (tfds.show_examples):

• Examples (tfds.as_dataframe):

celeb_a_hq/32

• Config description: CelebaHQ images in 32 x 32 resolution

• Dataset size: 85.39 MiB

• Auto-cached (documentation): Yes

• Feature structure:

FeaturesDict({
    'image': Image(shape=(32, 32, 3), dtype=uint8),
    'image/filename': Text(shape=(), dtype=string),
})

• Feature documentation:

• Figure (tfds.show_examples):

• Examples (tfds.as_dataframe):

celeb_a_hq/16

• Config description: CelebaHQ images in 16 x 16 resolution

• Dataset size: 25.71 MiB

• Auto-cached (documentation): Yes

• Feature structure:

FeaturesDict({
    'image': Image(shape=(16, 16, 3), dtype=uint8),
    'image/filename': Text(shape=(), dtype=string),
})

• Feature documentation:

• Figure (tfds.show_examples):

• Examples (tfds.as_dataframe):

celeb_a_hq/8

• Config description: CelebaHQ images in 8 x 8 resolution

• Dataset size: 9.42 MiB

• Auto-cached (documentation): Yes

• Feature structure:

FeaturesDict({
    'image': Image(shape=(8, 8, 3), dtype=uint8),
    'image/filename': Text(shape=(), dtype=string),
})

• Feature documentation:

• Figure (tfds.show_examples):

• Examples (tfds.as_dataframe):

celeb_a_hq/4

• Config description: CelebaHQ images in 4 x 4 resolution

• Dataset size: 5.10 MiB

• Auto-cached (documentation): Yes

• Feature structure:

FeaturesDict({
    'image': Image(shape=(4, 4, 3), dtype=uint8),
    'image/filename': Text(shape=(), dtype=string),
})

• Feature documentation:

• Figure (tfds.show_examples):

• Examples (tfds.as_dataframe):

celeb_a_hq/2

• Config description: CelebaHQ images in 2 x 2 resolution

• Dataset size: 3.94 MiB

• Auto-cached (documentation): Yes

• Feature structure:

FeaturesDict({
    'image': Image(shape=(2, 2, 3), dtype=uint8),
    'image/filename': Text(shape=(), dtype=string),
})

• Feature documentation:

• Figure (tfds.show_examples):

• Examples (tfds.as_dataframe):

celeb_a_hq/1

• Config description: CelebaHQ images in 1 x 1 resolution

• Dataset size: 3.62 MiB

• Auto-cached (documentation): Yes

• Feature structure:

FeaturesDict({
    'image': Image(shape=(1, 1, 3), dtype=uint8),
    'image/filename': Text(shape=(), dtype=string),
})

• Feature documentation:

• Figure (tfds.show_examples):

• Examples (tfds.as_dataframe):