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tf.keras.datasets.fashion_mnist.load_data

Loads the Fashion-MNIST dataset.

Used in the notebooks

Used in the guide Used in the tutorials

This is a 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 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

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,)

License:

The copyright for Fashion-MNIST is held by Zalando SE. Fashion-MNIST is licensed under the MIT license.