downsampled_imagenet

• Description:

Dataset with images of 2 resolutions (see config name for information on the resolution). It is used for density estimation and generative modeling experiments.

For resized ImageNet for supervised learning (link) see imagenet_resized.

• Homepage: http://image-net.org/small/download.php

• Source code: tfds.datasets.downsampled_imagenet.Builder

• Versions:

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

• Auto-cached (documentation): No

• Splits:

• Feature structure:

FeaturesDict({
    'image': Image(shape=(None, None, 3), dtype=uint8),
})

• Feature documentation:

• Supervised keys (See as_supervised doc): None

• Citation:

@article{DBLP:journals/corr/OordKK16,
  author    = {A{"{a} }ron van den Oord and
               Nal Kalchbrenner and
               Koray Kavukcuoglu},
  title     = {Pixel Recurrent Neural Networks},
  journal   = {CoRR},
  volume    = {abs/1601.06759},
  year      = {2016},
  url       = {http://arxiv.org/abs/1601.06759},
  archivePrefix = {arXiv},
  eprint    = {1601.06759},
  timestamp = {Mon, 13 Aug 2018 16:46:29 +0200},
  biburl    = {https://dblp.org/rec/bib/journals/corr/OordKK16},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

downsampled_imagenet/32x32 (default config)

• Config description: A dataset consisting of Train and Validation images of 32x32 resolution.

• Download size: 3.98 GiB

• Dataset size: 3.05 GiB

• Figure (tfds.show_examples):

• Examples (tfds.as_dataframe):

downsampled_imagenet/64x64

• Config description: A dataset consisting of Train and Validation images of 64x64 resolution.

• Download size: 11.73 GiB

• Dataset size: 10.80 GiB

• Figure (tfds.show_examples):

• Examples (tfds.as_dataframe):