fashion_mnist

Fashion-MNIST is a dataset of Zalando's article images consisting of a training set of 60,000 examples and a test set of 10,000 examples. Each example is a 28x28 grayscale image, associated with a label from 10 classes.

Split Examples
'test' 10,000
'train' 60,000
  • Feature structure:
FeaturesDict({
    'image': Image(shape=(28, 28, 1), dtype=uint8),
    'label': ClassLabel(shape=(), dtype=int64, num_classes=10),
})
  • Feature documentation:
Feature Class Shape Dtype Description
FeaturesDict
image Image (28, 28, 1) uint8
label ClassLabel int64

Visualization

  • Citation:
@article{DBLP:journals/corr/abs-1708-07747,
  author    = {Han Xiao and
               Kashif Rasul and
               Roland Vollgraf},
  title     = {Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning
               Algorithms},
  journal   = {CoRR},
  volume    = {abs/1708.07747},
  year      = {2017},
  url       = {http://arxiv.org/abs/1708.07747},
  archivePrefix = {arXiv},
  eprint    = {1708.07747},
  timestamp = {Mon, 13 Aug 2018 16:47:27 +0200},
  biburl    = {https://dblp.org/rec/bib/journals/corr/abs-1708-07747},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}