Fashion MNIST Computer Vision Project

Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms


Dataset Obtained From:

All images were sized 28x28 in the original dataset

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.

Here's an example of how the data looks (each class takes three-rows):
Visualized Fashion MNIST dataset

Version 1 (original-images_Original-FashionMNIST-Splits):

  • Original images, with the original splits for MNIST: train (86% of images - 60,000 images) set and test (14% of images - 10,000 images) set only.
  • This version was not trained

Version 3 (original-images_trainSetSplitBy80_20):


  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},

Last Updated

2 months ago

Project Type





ankle boot, bag, coat, dress, pullover, sandal, shirt, sneaker, trouser, tshirt_top


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