Table Of Contents
Table Of Contents

FashionMNIST

class mxnet.gluon.data.vision.datasets.FashionMNIST(root='/var/lib/jenkins/.mxnet/datasets/fashion-mnist', train=True, transform=None)[source]

A dataset of Zalando’s article images consisting of fashion products, a drop-in replacement of the original MNIST dataset from https://github.com/zalandoresearch/fashion-mnist

Each sample is an image (in 3D NDArray) with shape (28, 28, 1).

Parameters:
  • root (str, default $MXNET_HOME/datasets/fashion-mnist') – Path to temp folder for storing data.
  • train (bool, default True) – Whether to load the training or testing set.
  • transform (function, default None) – A user defined callback that transforms each sample. For example:

:param ::: transform=lambda data, label: (data.astype(np.float32)/255, label)

__init__(root='/var/lib/jenkins/.mxnet/datasets/fashion-mnist', train=True, transform=None)[source]

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__([root, train, transform]) Initialize self.
transform(fn[, lazy]) Returns a new dataset with each sample transformed by the transformer function fn.
transform_first(fn[, lazy]) Returns a new dataset with the first element of each sample transformed by the transformer function fn.