Fashion MNIST

class olympus.datasets.fashionmnist.FashionMNIST(data_path)

Bases: olympus.datasets.dataset.AllDataset

Fashion-MNIST, is a dataset comprising of 28x28 grayscale images of 70,000 fashion products from 10 categories, with 7,000 images per category. The training set has 60,000 images and the test set has 10,000 images. Fashion-MNIST is intended to serve as a direct drop-in replacement for the original MNIST dataset for benchmarking machine learning algorithms, as it shares the same image size, data format and the structure of training and testing splits. More on arxiv.

The full specification can be found at here. See also BalancedEMNIST and MNIST

References

[1]	Han Xiao, Kashif Rasul, Roland Vollgraf. “Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms” Aug 2017

Attributes:

classes: List[int]

Return the mapping between samples index and their class

input_shape: (28, 28)

Size of a sample stored in this dataset

output_shape: (10,)

The classes are (T-shirt, Trouser, Pullover, Dress, Coat, Sandals, Shirt, Sneaker, Bag, Ankle Boot)

train_size: 50000

Size of the train dataset

valid_size: 10000

Size of the validation dataset

test_size: 10000

Size of the test dataset

Methods

categories()	Dataset tags so we can filter what we want depending on the task
transforms()

register_datapipe_as_function
register_function

static categories()

Dataset tags so we can filter what we want depending on the task