Fashion MNIST dataset, an alternative to MNIST

load_data function

keras.datasets.fashion_mnist.load_data()

Loads the Fashion-MNIST dataset.

This is a dataset of 60,000 28×28 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 classes are:

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

Returns

Tuple of NumPy arrays: (x_train, y_train), (x_test, y_test).

x_train: uint8 NumPy array of grayscale image data with shapes (60000, 28, 28), containing the training data.

y_train: uint8 NumPy array of labels (integers in range 0-9) with shape (60000,) for the training data.

x_test: uint8 NumPy array of grayscale image data with shapes (10000, 28, 28), containing the test data.

y_test: uint8 NumPy array of labels (integers in range 0-9) with shape (10000,) for the test data.

Example

(x_train, y_train), (x_test, y_test) = fashion_mnist.load_data()
assert x_train.shape == (60000, 28, 28)
assert x_test.shape == (10000, 28, 28)
assert y_train.shape == (60000,)
assert y_test.shape == (10000,)