Fashion-MNIST database of fashion articles

Dataset of 60,000 28x28 grayscale images of the 10 fashion article classes, along with a test set of 10,000 images. This dataset can be used as a drop-in replacement for MNIST. The class labels are encoded as integers from 0-9 which correspond to T-shirt/top, Trouser, Pullover, Dress, Coat, Sandal, Shirt,

Usage

dataset_fashion_mnist(convert = TRUE)

Arguments

convert

When TRUE (default) the datasets are returned as R arrays. If FALSE, objects are returned as NumPy arrays.

Value

Lists of training and test data: train$x, train$y, test$x, test$y, where x is an array of grayscale image data with shape (num_samples, 28, 28) and y is an array of article labels (integers in range 0-9) with shape (num_samples).

str(dataset_fashion_mnist())

## List of 2
##  $ train:List of 2
##   ..$ x: int [1:60000, 1:28, 1:28] 0 0 0 0 0 0 0 0 0 0 ...
##   ..$ y: int [1:60000(1d)] 9 0 0 3 0 2 7 2 5 5 ...
##  $ test :List of 2
##   ..$ x: int [1:10000, 1:28, 1:28] 0 0 0 0 0 0 0 0 0 0 ...
##   ..$ y: int [1:10000(1d)] 9 2 1 1 6 1 4 6 5 7 ...

str(dataset_fashion_mnist(convert = FALSE))

## List of 2
##  $ train:List of 2
##   ..$ x: <numpy.ndarray shape(60000,28,28), dtype=uint8>
##   ..$ y: <numpy.ndarray shape(60000), dtype=uint8>
##  $ test :List of 2
##   ..$ x: <numpy.ndarray shape(10000,28,28), dtype=uint8>
##   ..$ y: <numpy.ndarray shape(10000), dtype=uint8>

Details

Dataset of 60,000 28x28 grayscale images of 10 fashion categories, along with a test set of 10,000 images. This dataset can be used as a drop-in replacement for MNIST. The class labels are:

• 0 - T-shirt/top

• 1 - Trouser

• 2 - Pullover

• 3 - Dress

• 4 - Coat

• 5 - Sandal

• 6 - Shirt

• 7 - Sneaker

• 8 - Bag

• 9 - Ankle boot

See also

Other datasets:
dataset_boston_housing()
dataset_california_housing()
dataset_cifar10()
dataset_cifar100()
dataset_imdb()
dataset_mnist()
dataset_reuters()