Google colab stuck on downloading Fashion_Mnist dataset - python-3.x

Question

I have tried running my code from google collab for the fashion using this code but it is stuck on downloading the code. I also switched between the hardware accelerators but still nothing. Is there any workaround to this problem?

Answer 1

For Google Colab
At the top write !pip install mnist. Use import mnist.
Then simply store the images and labels:
train_images = mnist.train_images()
train_labels = mnist.train_labels()
test_images = mnist.test_images()
test_labels = mnist.test_labels()
That's it!!!

Answer 2

You can download it from the github repository.
Put the downloaded files (from the readme links) in a directory in your current path called data/fashion/, then you can use their loader.
def load_mnist(path, kind='train'):
import os
import gzip
import numpy as np
"""Load MNIST data from `path`"""
labels_path = os.path.join(path,
'%s-labels-idx1-ubyte.gz'
% kind)
images_path = os.path.join(path,
'%s-images-idx3-ubyte.gz'
% kind)
with gzip.open(labels_path, 'rb') as lbpath:
labels = np.frombuffer(lbpath.read(), dtype=np.uint8,
offset=8)
with gzip.open(images_path, 'rb') as imgpath:
images = np.frombuffer(imgpath.read(), dtype=np.uint8,
offset=16).reshape(len(labels), 784)
return images, labels
X_train, y_train = load_mnist('data/fashion', kind='train')
X_test, y_test = load_mnist('data/fashion', kind='t10k')
The other option would be to use the torchvision FMNIST dataset.
Edit
You can also use:
from tensorflow.examples.tutorials.mnist import input_data
data = input_data.read_data_sets('data/fashion', source_url='http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/')
Edit 2
Here is the code for downloading the files (it can be improved with some try-catch):
import os
import requests
path = 'data/fashion'
def download_fmnist(path):
DEFAULT_SOURCE_URL = 'http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/'
files = dict(
TRAIN_IMAGES='train-images-idx3-ubyte.gz',
TRAIN_LABELS='train-labels-idx1-ubyte.gz',
TEST_IMAGES='t10k-images-idx3-ubyte.gz',
TEST_LABELS='t10k-labels-idx1-ubyte.gz')
if not os.path.exists(path):
os.mkdir(path)
for f in files:
filepath = os.path.join(path, files[f])
if not os.path.exists(filepath):
url = DEFAULT_SOURCE_URL + files[f]
r = requests.get(url, allow_redirects=True)
open(filepath, 'wb').write(r.content)
print('Successfully downloaded', f)
download_fmnist(path)

Answer 3

The command keras.datasets.fashion_mnist.load_data() returns a tuple of numpy arrays: (xtrain, ytrain) and (xtest, ytest).
The dataset won't be downloaded to your local storage this way. This is why the command cd fashion-mnist/ raises an error. There was no directory created. The fashion-mnist dataset was loaded correctly into (xtrain, ytrain) and (xtest, ytest) in your code.