Getting started
scikit-image is an image processing Python package that works with numpy arrays. The package is imported as skimage:
1 | >>> import skimage |
Most functions of skimage are found within submodules:
1 2 | >>> from skimage import data>>> camera = data.camera() |
A list of submodules and functions is found on the API reference webpage.
Within scikit-image, images are represented as NumPy arrays, for example 2-D arrays for grayscale 2-D images
1 2 3 4 5 | >>> type(camera)<type 'numpy.ndarray'>>>> # An image with 512 rows and 512 columns>>> camera.shape(512, 512) |
The 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:
1 2 3 4 5 | >>> coins = data.coins()>>> from skimage import filters>>> threshold_value = filters.threshold_otsu(coins)>>> threshold_value107 |
Of course, it is also possible to load your own images as NumPy arrays from image files, using skimage.io.imread():
1 2 3 4 | >>> import os>>> filename = os.path.join(skimage.data_dir, 'moon.png')>>> from skimage import io>>> moon = io.imread(filename) |
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