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imagenet_resized

imagenet_resized is configured with tfds.image.imagenet_resized.ImagenetResizedConfig and has the following configurations predefined (defaults to the first one):

  • 8x8 (v0.1.0) (Size: 237.11 MiB): This dataset consists of the ImageNet dataset resized to 8x8. 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.

WARNING: The integer labels used are defined by the authors and do not match those from the other ImageNet datasets provided by Tensorflow datasets. See the original label list, and the labels used by this dataset. Additionally, the original authors 1 index there labels which we convert to 0 indexed by subtracting one.

  • 16x16 (v0.1.0) (Size: 923.34 MiB): This dataset consists of the ImageNet dataset resized to 16x16. 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.

WARNING: The integer labels used are defined by the authors and do not match those from the other ImageNet datasets provided by Tensorflow datasets. See the original label list, and the labels used by this dataset. Additionally, the original authors 1 index there labels which we convert to 0 indexed by subtracting one.

  • 32x32 (v0.1.0) (Size: 3.46 GiB): This dataset consists of the ImageNet dataset resized to 32x32. 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.

WARNING: The integer labels used are defined by the authors and do not match those from the other ImageNet datasets provided by Tensorflow datasets. See the original label list, and the labels used by this dataset. Additionally, the original authors 1 index there labels which we convert to 0 indexed by subtracting one.

  • 64x64 (v0.1.0) (Size: 13.13 GiB): This dataset consists of the ImageNet dataset resized to 64x64. 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.

WARNING: The integer labels used are defined by the authors and do not match those from the other ImageNet datasets provided by Tensorflow datasets. See the original label list, and the labels used by this dataset. Additionally, the original authors 1 index there labels which we convert to 0 indexed by subtracting one.

imagenet_resized/8x8

This dataset consists of the ImageNet dataset resized to 8x8. 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.

WARNING: The integer labels used are defined by the authors and do not match those from the other ImageNet datasets provided by Tensorflow datasets. See the original label list, and the labels used by this dataset. Additionally, the original authors 1 index there labels which we convert to 0 indexed by subtracting one.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 1,331,167
TRAIN 1,281,167
VALIDATION 50,000

Features

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

Homepage

Supervised keys (for as_supervised=True)

(u'image', u'label')

imagenet_resized/16x16

This dataset consists of the ImageNet dataset resized to 16x16. 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.

WARNING: The integer labels used are defined by the authors and do not match those from the other ImageNet datasets provided by Tensorflow datasets. See the original label list, and the labels used by this dataset. Additionally, the original authors 1 index there labels which we convert to 0 indexed by subtracting one.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 1,331,167
TRAIN 1,281,167
VALIDATION 50,000

Features

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

Homepage

Supervised keys (for as_supervised=True)

(u'image', u'label')

imagenet_resized/32x32

This dataset consists of the ImageNet dataset resized to 32x32. 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.

WARNING: The integer labels used are defined by the authors and do not match those from the other ImageNet datasets provided by Tensorflow datasets. See the original label list, and the labels used by this dataset. Additionally, the original authors 1 index there labels which we convert to 0 indexed by subtracting one.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 1,331,167
TRAIN 1,281,167
VALIDATION 50,000

Features

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

Homepage

Supervised keys (for as_supervised=True)

(u'image', u'label')

imagenet_resized/64x64

This dataset consists of the ImageNet dataset resized to 64x64. 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.

WARNING: The integer labels used are defined by the authors and do not match those from the other ImageNet datasets provided by Tensorflow datasets. See the original label list, and the labels used by this dataset. Additionally, the original authors 1 index there labels which we convert to 0 indexed by subtracting one.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 1,331,167
TRAIN 1,281,167
VALIDATION 50,000

Features

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

Homepage

Supervised keys (for as_supervised=True)

(u'image', u'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}
}