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from keras.utils.data_utils import get_file
import numpy as np
from scipy.io import loadmat
def load_data():
"""Loads the SVHN 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)`.
"""
dirname = 'svhn'
origin = 'http://ufldl.stanford.edu/housenumbers'
train_mat = get_file("svhn_train_32x32.mat", origin=f"{origin}/train_32x32.mat")
test_mat = get_file("svhn_test_32x32.mat", origin=f"{origin}/test_32x32.mat")
Train = loadmat(train_mat)
Test = loadmat(test_mat)
x_train = Train['X']
y_train = Train['y']
x_test = Test['X']
y_test = Test['y']
x_train = x_train[np.newaxis,...]
x_train = np.swapaxes(x_train,0,4).squeeze()
x_test = x_test[np.newaxis,...]
x_test = np.swapaxes(x_test,0,4).squeeze()
np.place(y_train,y_train == 10,0)
np.place(y_test,y_test == 10,0)
return (x_train, y_train), (x_test, y_test)