imagenet_resized

• Description:

This dataset consists of the ImageNet dataset resized to fixed size. The images here are the ones provided by Chrabaszcz et. al. using the box resize method.

For downsampled ImageNet for unsupervised learning see downsampled_imagenet.

• Homepage: https://patrykchrabaszcz.github.io/Imagenet32/

• Source code: tfds.image_classification.ImagenetResized

• Versions:

  • 0.1.0 (default): No release notes.

• Dataset size: Unknown size

• Auto-cached (documentation): Unknown

• Splits:

Split	Examples
'train'	1,281,167
'validation'	50,000

• Supervised keys (See as_supervised doc): ('image', 'label')

• Citation:

@article{chrabaszcz2017downsampled,
  title={A downsampled variant of imagenet as an alternative to the cifar datasets},
  author={Chrabaszcz, Patryk and Loshchilov, Ilya and Hutter, Frank},
  journal={arXiv preprint arXiv:1707.08819},
  year={2017}
}

imagenet_resized/8x8 (default config)

• Config description: Images resized to 8x8

• Download size: 237.11 MiB

• Features:

FeaturesDict({
    'image': Image(shape=(8, 8, 3), dtype=tf.uint8),
    'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=1000),
})

• Figure (tfds.show_examples):

• Examples (tfds.as_dataframe):

imagenet_resized/16x16

• Config description: Images resized to 16x16

• Download size: 923.34 MiB

• Features:

FeaturesDict({
    'image': Image(shape=(16, 16, 3), dtype=tf.uint8),
    'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=1000),
})

• Figure (tfds.show_examples):

• Examples (tfds.as_dataframe):

imagenet_resized/32x32

• Config description: Images resized to 32x32

• Download size: 3.46 GiB

• Features:

FeaturesDict({
    'image': Image(shape=(32, 32, 3), dtype=tf.uint8),
    'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=1000),
})

• Figure (tfds.show_examples):

• Examples (tfds.as_dataframe):

imagenet_resized/64x64

• Config description: Images resized to 64x64

• Download size: 13.13 GiB

• Features:

FeaturesDict({
    'image': Image(shape=(64, 64, 3), dtype=tf.uint8),
    'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=1000),
})

• Figure (tfds.show_examples):

• Examples (tfds.as_dataframe):