omniglot

Omniglot data set for one-shot learning. This dataset contains 1623 different handwritten characters from 50 different alphabets.

Split Examples
'small1' 2,720
'small2' 3,120
'test' 13,180
'train' 19,280
  • Feature structure:
FeaturesDict({
    'alphabet': ClassLabel(shape=(), dtype=int64, num_classes=50),
    'alphabet_char_id': int64,
    'image': Image(shape=(105, 105, 3), dtype=uint8),
    'label': ClassLabel(shape=(), dtype=int64, num_classes=1623),
})
  • Feature documentation:
Feature Class Shape Dtype Description
FeaturesDict
alphabet ClassLabel int64
alphabet_char_id Tensor int64
image Image (105, 105, 3) uint8
label ClassLabel int64

Visualization

  • Citation:
@article{lake2015human,
  title={Human-level concept learning through probabilistic program induction},
  author={Lake, Brenden M and Salakhutdinov, Ruslan and Tenenbaum, Joshua B},
  journal={Science},
  volume={350},
  number={6266},
  pages={1332--1338},
  year={2015},
  publisher={American Association for the Advancement of Science}
}