Welcome to the GitHub page of DeepTrackAI's Fashion-MNIST 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. The authors intend Fashion-MNIST to serve as a direct drop-in replacement for the original MNIST dataset for benchmarking machine learning algorithms.
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 |
To use the MNIST dataset in your project:
- Clone this repository to your local machine.
- Import the dataset into your machine learning framework of choice.
- Train or evaluate your models using the dataset.
To clone the repository and access the MNIST dataset:
git clone github.com/DeepTrackAI/FashionMNIST_dataset
cd FashionMNIST_datasetIf you use Fashion-MNIST in a scientific publication, we would appreciate references to the following paper:
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms. Han Xiao, Kashif Rasul, Roland Vollgraf. arXiv:1708.07747
Biblatex entry:
@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},
}The MIT License (MIT) Copyright © [2017] Zalando SE, https://tech.zalando.com
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