omniglot

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

Features

FeaturesDict({
    'alphabet': ClassLabel(shape=(), dtype=tf.int64, num_classes=50),
    'alphabet_char_id': Tensor(shape=(), dtype=tf.int64),
    'image': Image(shape=(105, 105, 3), dtype=tf.uint8),
    'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=1623),
})

Statistics

Split Examples
ALL 38,300
TRAIN 19,280
TEST 13,180
SMALL2 3,120
SMALL1 2,720

Homepage

Supervised keys (for as_supervised=True)

(u'image', u'label')

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}
}