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Getting started
---------------
``scikit-image`` is an image processing Python package that works with
:mod:`numpy` arrays. The package is imported as ``skimage``: ::
>>> import skimage as ski
Most functions of ``skimage`` are found within submodules: ::
>>> camera = ski.data.camera()
A list of submodules and functions is found on the `API reference
<https://scikit-image.org/docs/stable/api/api.html>`_ webpage.
Within scikit-image, images are represented as NumPy arrays, for
example 2-D arrays for grayscale 2-D images ::
>>> type(camera)
<type 'numpy.ndarray'>
>>> # An image with 512 rows and 512 columns
>>> camera.shape
(512, 512)
The :mod:`skimage.data` submodule provides a set of functions returning
example images, that can be used to get started quickly on using
scikit-image's functions: ::
>>> coins = ski.data.coins()
>>> threshold_value = ski.filters.threshold_otsu(coins)
>>> threshold_value
107
Of course, it is also possible to load your own images as NumPy arrays
from image files, using :func:`skimage.io.imread`: ::
>>> import os
>>> filename = os.path.join(ski.data_dir, 'moon.png')
>>> moon = ski.io.imread(filename)
Use `natsort <https://pypi.org/project/natsort/>`_ to load multiple images ::
>>> import os
>>> from natsort import natsorted, ns
>>> list_files = os.listdir('.')
>>> list_files
['01.png', '010.png', '0101.png', '0190.png', '02.png']
>>> list_files = natsorted(list_files)
>>> list_files
['01.png', '02.png', '010.png', '0101.png', '0190.png']
>>> image_list = []
>>> for filename in list_files:
... image_list.append(ski.io.imread(filename))
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