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.
- URL: https://github.com/zalandoresearch/fashion-mnist
DatasetBuilder
:tfds.image.mnist.FashionMNIST
- Version:
v1.0.0
Versions:
1.0.0
(default):3.0.0
: S3: www.tensorflow.org/datasets/splits
Size:
29.45 MiB
Features
FeaturesDict({
'image': Image(shape=(28, 28, 1), dtype=tf.uint8),
'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=10),
})
Statistics
Split | Examples |
---|---|
ALL | 70,000 |
TRAIN | 60,000 |
TEST | 10,000 |
Homepage
Supervised keys (for as_supervised=True
)
(u'image', u'label')
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}
}