Extract images from .idx3-ubyte file or GZIP via Python

Download the training/test images and labels:

• train-images-idx3-ubyte.gz: training set images
• train-labels-idx1-ubyte.gz: training set labels
• t10k-images-idx3-ubyte.gz: test set images
• t10k-labels-idx1-ubyte.gz: test set labels

And uncompress them in a workdir, say samples/.

Get the python-mnist package from PyPi:

pip install python-mnist

Import the mnist package and read the training/test images:

from mnist import MNIST

mndata = MNIST('samples')

images, labels = mndata.load_training()
# or
images, labels = mndata.load_testing()

To display an image to the console:

index = random.randrange(0, len(images))  # choose an index ;-)
print(mndata.display(images[index]))

You’ll get something like this:

............................
............................
............................
............................
............................
.................@@.........
..............@@@@@.........
............@@@@............
..........@@................
..........@.................
...........@................
...........@................
...........@...@............
...........@@@@@.@..........
...........@@@...@@.........
...........@@.....@.........
..................@.........
..................@@........
..................@@........
..................@.........
.................@@.........
...........@.....@..........
...........@....@@..........
............@@@@............
.............@..............
............................
............................
............................

Explanation:

• Each image of the images list is a Python list of unsigned bytes.
• The labels is an Python array of unsigned bytes.