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. We intend Fashion-MNIST to serve as a direct drop-in replacement for the original MNIST dataset for benchmarking machine learning algorithms. It shares the same image size and structure of training and testing splits.
Each training and test example is assigned to one of the following labels:
Label | Description |
---|---|
0 | T-shirt/top |
1 | Trouser |
2 | Pullover |
3 | Dress |
4 | Coat |
5 | Sandal |
6 | Shirt |
7 | Sneaker |
8 | Bag |
9 | Ankle boot |
Use utils/mnist_reader
in this repo:
import mnist_reader
X_train, y_train = mnist_reader.load_mnist('data/fashion', kind='train')
X_test, y_test = mnist_reader.load_mnist('data/fashion', kind='t10k')
Make sure you have downloaded the data
and placed it in data/fashion
. Otherwise, Tensorflow will download and use the original
MNIST.
from tensorflow.examples.tutorials.mnist import input_data
data = input_data.read_data_sets('data/fashion')
data.train.next_batch(BATCH_SIZE)
Note, Tensorflow supports passing in a source url to the read_data_sets
. You may use:
data = input_data.read_data_sets('data/fashion', source_url='http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/')
Also, an official Tensorflow tutorial of using tf.keras
, a high-level API to train Fashion-MNIST
can be found here.
To date, the following libraries have included Fashion-MNIST as a built-in dataset. Therefore, you don't need to download Fashion-MNIST by yourself. Just follow their API and you are ready to go.
You are welcome to make pull requests to other open-source machine learning packages, improving their support to Fashion-MNIST dataset.
As one of the Machine Learning community's most popular datasets, MNIST has inspired people to implement loaders in many different languages. You can use these loaders with the Fashion-MNIST dataset as well. (Note: may require decompressing first.) To date, we haven't yet tested all of these loaders with Fashion-MNIST.
Please use the following citation when referencing the dataset:
@online{xiao2017/online,
author = {Han Xiao and Kashif Rasul and Roland Vollgraf},
title = {Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms},
date = {2017-08-28},
year = {2017},
eprintclass = {cs.LG},
eprinttype = {arXiv},
eprint = {cs.LG/1708.07747},
}