55 lines
1.6 KiB
Python
55 lines
1.6 KiB
Python
"""
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==============================
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Rescale, resize, and downscale
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==============================
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`Rescale` operation resizes an image by a given scaling factor. The scaling
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factor can either be a single floating point value, or multiple values - one
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along each axis.
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`Resize` serves the same purpose, but allows to specify an output image shape
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instead of a scaling factor.
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Note that when down-sampling an image, `resize` and `rescale` should perform
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Gaussian smoothing to avoid aliasing artifacts. See the `anti_aliasing` and
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`anti_aliasing_sigma` arguments to these functions.
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`Downscale` serves the purpose of down-sampling an n-dimensional image by
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integer factors using the local mean on the elements of each block of the size
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factors given as a parameter to the function.
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"""
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import matplotlib.pyplot as plt
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from skimage import data, color
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from skimage.transform import rescale, resize, downscale_local_mean
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image = color.rgb2gray(data.astronaut())
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image_rescaled = rescale(image, 0.25, anti_aliasing=False)
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image_resized = resize(image, (image.shape[0] // 4, image.shape[1] // 4),
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anti_aliasing=True)
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image_downscaled = downscale_local_mean(image, (4, 3))
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fig, axes = plt.subplots(nrows=2, ncols=2)
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ax = axes.ravel()
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ax[0].imshow(image, cmap='gray')
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ax[0].set_title("Original image")
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ax[1].imshow(image_rescaled, cmap='gray')
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ax[1].set_title("Rescaled image (aliasing)")
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ax[2].imshow(image_resized, cmap='gray')
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ax[2].set_title("Resized image (no aliasing)")
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ax[3].imshow(image_downscaled, cmap='gray')
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ax[3].set_title("Downscaled image (no aliasing)")
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ax[0].set_xlim(0, 512)
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ax[0].set_ylim(512, 0)
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plt.tight_layout()
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plt.show()
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