semvec/pypi-packages huggingface dataset:
python-mnist 0.7
Simple MNIST and EMNIST data parser written in pure Python
License: BSD

python-mnist
============

Simple MNIST and EMNIST data parser written in pure Python.

MNIST is a database of handwritten digits available on
http://yann.lecun.com/exdb/mnist/. EMNIST is an extended MNIST database
https://www.nist.gov/itl/iad/image-group/emnist-dataset.

Requirements
------------

-  Python 2 or Python 3

Usage
-----

-  ``git clone https://github.com/sorki/python-mnist``

-  ``cd python-mnist``

-  Get MNIST data:

   ::

      ./bin/mnist_get_data.sh

-  Check preview with:

   ::

      PYTHONPATH=. ./bin/mnist_preview

Installation
------------

Get the package from PyPi:

::

   pip install python-mnist

or install with ``setup.py``:

::

   python setup.py install

Code sample:

::

   from mnist import MNIST
   mndata = MNIST('./dir_with_mnist_data_files')
   images, labels = mndata.load_training()

To enable loading of gzip-ed files use:

::

   mndata.gz = True

Library tries to load files named t10k-images-idx3-ubyte
train-labels-idx1-ubyte train-images-idx3-ubyte and
t10k-labels-idx1-ubyte. If loading throws an exception check if these
names match.

EMNIST
------

-  Get EMNIST data:

   ::

      ./bin/emnist_get_data.sh

-  Check preview with:

   ::

      PYTHONPATH=. ./bin/emnist_preview

To use EMNIST datasets you need to call:

::

   mndata.select_emnist('digits')

Where digits is one of the available EMNIST datasets. You can choose
from

   -  balanced
   -  byclass
   -  bymerge
   -  digits
   -  letters
   -  mnist

EMNIST loader uses gziped files by default, this can be disabled by by
setting:

::

   mndata.gz = False

You also need to unpack EMNIST files as bin/emnist_get_data.sh script
won't do it for you. EMNIST loader also needs to mirror and rotate
images so it is a bit slower (If this is an issue for you, you should
repack the data to avoid mirroring and rotation on each load).

Notes
-----

This package doesn't use numpy by design as when I've tried to find a
working implementation all of them were based on some archaic version of
numpy and none of them worked. This loads data files with struct.unpack
instead.

Example
-------

::

   $ PYTHONPATH=. ./bin/mnist_preview
   Showing num: 3

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