fashion_mnist.py

import sys
if sys.version_info >= (3,0):
    import urllib.request
else:
    import urllib
import gzip
import idx2numpy


def load_data():
    """Loads the Fashion MNIST dataset.

    # Arguments
        path: path where to cache the dataset locally
            (relative to ~/.keras/datasets).

    # Returns
        Tuple of Numpy arrays: `(x_train, y_train), (x_test, y_test)`.
    """

    if sys.version_info >= (3,0):
        path_x_train = urllib.request.urlretrieve('http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-images-idx3-ubyte.gz', 'train-images-idx3-ubyte.gz')
        path_y_train = urllib.request.urlretrieve('http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-labels-idx1-ubyte.gz', 'train-labels-idx1-ubyte.gz')
        path_x_test = urllib.request.urlretrieve('http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-images-idx3-ubyte.gz', 't10k-images-idx3-ubyte.gz')
        path_y_test = urllib.request.urlretrieve('http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-labels-idx1-ubyte.gz', 't10k-labels-idx1-ubyte.gz')
    else:
        path_x_train = urllib.urlretrieve('http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-images-idx3-ubyte.gz', 'train-images-idx3-ubyte.gz')
        path_y_train = urllib.urlretrieve('http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-labels-idx1-ubyte.gz', 'train-labels-idx1-ubyte.gz')
        path_x_test = urllib.urlretrieve('http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-images-idx3-ubyte.gz', 't10k-images-idx3-ubyte.gz')
        path_y_test = urllib.urlretrieve('http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-labels-idx1-ubyte.gz', 't10k-labels-idx1-ubyte.gz')

    with gzip.open('train-images-idx3-ubyte.gz', 'rb') as f:
        x_train = idx2numpy.convert_from_string(f.read())
    with gzip.open('train-labels-idx1-ubyte.gz', 'rb') as f:
        y_train = idx2numpy.convert_from_string(f.read())
    with gzip.open('t10k-images-idx3-ubyte.gz', 'rb') as f:
        x_test = idx2numpy.convert_from_string(f.read())
    with gzip.open('t10k-labels-idx1-ubyte.gz', 'rb') as f:
        y_test  = idx2numpy.convert_from_string(f.read())

    return (x_train, y_train), (x_test, y_test)