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@@ -25,10 +25,13 @@ def slic(image, n_segments=100, compactness=10., max_iter=10, sigma=0,
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n_segments : int, optional
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The (approximate) number of labels in the segmented output image.
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compactness : float, optional
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Balances color-space proximity and image-space proximity. Higher
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values give more weight to image-space. As `compactness` tends to
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infinity, superpixel shapes become square/cubic. In SLICO mode, this
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is the initial compactness.
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Balances color proximity and space proximity. Higher values give
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more weight to space proximity, making superpixel shapes more
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square/cubic. In SLICO mode, this is the initial compactness.
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This parameter depends strongly on image contrast and on the
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shapes of objects in the image; we recommend exploring possible
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values on a log scale, e.g., 0.01, 0.1, 1, 10, 100, before
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refining around a chosen value.
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max_iter : int, optional
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Maximum number of iterations of k-means.
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sigma : float or (3,) array-like of floats, optional
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