def load_extra_data():
extra_data = scipy.io.loadmat(data_path + 'extra_32x32.mat',
variable_names='X').get('X')
extra_labels = scipy.io.loadmat(data_path + 'extra_32x32.mat',
variable_names='y').get('y')
images = extra_data.transpose((3, 0, 1, 2)) / 255.0
cls = extra_labels[:, 0]
cls[cls == 10] = 0
return images, cls, dataset_utils.one_hot_encoded(class_numbers=cls,
num_classes=num_classes)
def load_test_data():
"""Load all the test-data for the SVHN data-set.
Returns the images, class-numbers and one-hot encoded class-labels.
"""
test_data = scipy.io.loadmat(data_path + 'test_32x32.mat',
variable_names='X').get('X')
test_labels = scipy.io.loadmat(data_path + 'test_32x32.mat',
variable_names='y').get('y')
images = test_data.transpose((3, 0, 1, 2)) / 255.0
cls = test_labels[:, 0]
cls[cls == 10] = 0
return images, cls, dataset_utils.one_hot_encoded(class_numbers=cls,
num_classes=num_classes)