- Description:
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.
Additional Documentation: Explore on Papers With Code
Source code:
tfds.image_classification.FashionMNISTVersions:
3.0.1(default): No release notes.
Download size:
29.45 MiBDataset size:
36.42 MiBAuto-cached (documentation): Yes
Splits:
| 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 |
Supervised keys (See
as_superviseddoc):('image', 'label')Figure (tfds.show_examples):
- Examples (tfds.as_dataframe):
- 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}
}