mirror of
https://github.com/wassname/scikit-image.git
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Nelson Brown
314 lines
8.3 KiB
Python
314 lines
8.3 KiB
Python
"""
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:author: Damian Eads, 2009
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:license: modified BSD
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"""
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import numpy as np
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from scipy import ndimage
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def square(width, dtype=np.uint8):
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"""
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Generates a flat, square-shaped structuring element. Every pixel
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along the perimeter has a chessboard distance no greater than radius
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(radius=floor(width/2)) pixels.
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Parameters
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----------
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width : int
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The width and height of the square
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Other Parameters
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----------------
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dtype : data-type
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The data type of the structuring element.
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Returns
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-------
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selem : ndarray
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A structuring element consisting only of ones, i.e. every
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pixel belongs to the neighborhood.
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"""
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return np.ones((width, width), dtype=dtype)
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def rectangle(width, height, dtype=np.uint8):
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"""
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Generates a flat, rectangular-shaped structuring element of a
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given width and height. Every pixel in the rectangle belongs
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to the neighboorhood.
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Parameters
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----------
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width : int
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The width of the rectangle
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height : int
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The height of the rectangle
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Other Parameters
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----------------
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dtype : data-type
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The data type of the structuring element.
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Returns
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-------
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selem : ndarray
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A structuring element consisting only of ones, i.e. every
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pixel belongs to the neighborhood.
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"""
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return np.ones((width, height), dtype=dtype)
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def diamond(radius, dtype=np.uint8):
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"""
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Generates a flat, diamond-shaped structuring element of a given
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radius. A pixel is part of the neighborhood (i.e. labeled 1) if
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the city block/manhattan distance between it and the center of the
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neighborhood is no greater than radius.
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Parameters
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----------
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radius : int
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The radius of the diamond-shaped structuring element.
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Other Parameters
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----------------
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dtype : data-type
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The data type of the structuring element.
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Returns
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-------
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selem : ndarray
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The structuring element where elements of the neighborhood
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are 1 and 0 otherwise.
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"""
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half = radius
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(I, J) = np.meshgrid(range(0, radius * 2 + 1), range(0, radius * 2 + 1))
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s = np.abs(I - half) + np.abs(J - half)
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return np.array(s <= radius, dtype=dtype)
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def disk(radius, dtype=np.uint8):
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"""
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Generates a flat, disk-shaped structuring element of a given radius.
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A pixel is within the neighborhood if the euclidean distance between
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it and the origin is no greater than radius.
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Parameters
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----------
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radius : int
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The radius of the disk-shaped structuring element.
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Other Parameters
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----------------
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dtype : data-type
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The data type of the structuring element.
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Returns
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-------
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selem : ndarray
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The structuring element where elements of the neighborhood
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are 1 and 0 otherwise.
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"""
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L = np.linspace(-radius, radius, 2 * radius + 1)
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(X, Y) = np.meshgrid(L, L)
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s = X**2
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s += Y**2
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return np.array(s <= radius * radius, dtype=dtype)
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def cube(width, dtype=np.uint8):
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"""
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Generates a cube-shaped structuring element (the 3D equivalent of
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a square). Every pixel along the perimeter has a chessboard distance
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no greater than radius (radius=floor(width/2)) pixels.
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Parameters
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----------
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width : int
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The width, height and depth of the cube
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Other Parameters
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----------------
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dtype : data-type
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The data type of the structuring element.
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Returns
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-------
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selem : ndarray
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A structuring element consisting only of ones, i.e. every
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pixel belongs to the neighborhood.
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"""
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return np.ones((width, width, width), dtype=dtype)
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def octahedron(radius, dtype=np.uint8):
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"""
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Generates a octahedron-shaped structuring element of a given radius
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(the 3D equivalent of a diamond). A pixel is part of the
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neighborhood (i.e. labeled 1) if the city block/manhattan distance
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between it and the center of the neighborhood is no greater than
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radius.
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Parameters
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----------
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radius : int
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The radius of the octahedron-shaped structuring element.
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Other Parameters
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----------------
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dtype : data-type
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The data type of the structuring element.
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Returns
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-------
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selem : ndarray
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The structuring element where elements of the neighborhood
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are 1 and 0 otherwise.
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"""
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# note that in contrast to diamond(), this method allows non-integer radii
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n = 2 * radius + 1
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Z, Y, X = np.mgrid[-radius:radius:n*1j,
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-radius:radius:n*1j,
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-radius:radius:n*1j]
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s = np.abs(X) + np.abs(Y) + np.abs(Z)
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return np.array(s <= radius, dtype=dtype)
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def ball(radius, dtype=np.uint8):
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"""
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Generates a ball-shaped structuring element of a given radius (the
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3D equivalent of a disk). A pixel is within the neighborhood if the
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euclidean distance between it and the origin is no greater than
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radius.
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Parameters
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----------
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radius : int
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The radius of the ball-shaped structuring element.
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Other Parameters
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----------------
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dtype : data-type
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The data type of the structuring element.
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Returns
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-------
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selem : ndarray
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The structuring element where elements of the neighborhood
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are 1 and 0 otherwise.
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"""
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n = 2 * radius + 1
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Z, Y, X = np.mgrid[-radius:radius:n*1j,
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-radius:radius:n*1j,
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-radius:radius:n*1j]
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s = X**2 + Y**2 + Z**2
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return np.array(s <= radius * radius, dtype=dtype)
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def octagon(m, n, dtype=np.uint8):
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"""
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Generates an octagon shaped structuring element with a given size of
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horizontal and vertical sides and a given height or width of slanted
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sides. The slanted sides are 45 or 135 degrees to the horizontal axis
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and hence the widths and heights are equal.
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Parameters
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----------
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m : int
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The size of the horizontal and vertical sides.
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n : int
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The height or width of the slanted sides.
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Other Parameters
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----------------
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dtype : data-type
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The data type of the structuring element.
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Returns
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-------
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selem : ndarray
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The structuring element where elements of the neighborhood
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are 1 and 0 otherwise.
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"""
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from . import convex_hull_image
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selem = np.zeros((m + 2*n, m + 2*n))
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selem[0, n] = 1
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selem[n, 0] = 1
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selem[0, m + n - 1] = 1
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selem[m + n - 1, 0] = 1
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selem[-1, n] = 1
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selem[n, -1] = 1
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selem[-1, m + n - 1] = 1
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selem[m + n - 1, -1] = 1
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selem = convex_hull_image(selem).astype(dtype)
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return selem
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def star(a, dtype=np.uint8):
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"""
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Generates a star shaped structuring element that has 8 vertices and is an
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overlap of square of size `2*a + 1` with its 45 degree rotated version.
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The slanted sides are 45 or 135 degrees to the horizontal axis.
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Parameters
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----------
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a : int
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Parameter deciding the size of the star structural element. The side
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of the square array returned is `2*a + 1 + 2*floor(a / 2)`.
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Other Parameters
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----------------
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dtype : data-type
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The data type of the structuring element.
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Returns
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-------
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selem : ndarray
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The structuring element where elements of the neighborhood
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are 1 and 0 otherwise.
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"""
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from . import convex_hull_image
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if a == 1:
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bfilter = np.zeros((3, 3), dtype)
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bfilter[:] = 1
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return bfilter
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m = 2 * a + 1
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n = a // 2
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selem_square = np.zeros((m + 2 * n, m + 2 * n))
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selem_square[n: m + n, n: m + n] = 1
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c = (m + 2 * n - 1) // 2
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selem_rotated = np.zeros((m + 2 * n, m + 2 * n))
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selem_rotated[0, c] = selem_rotated[-1, c] = selem_rotated[c, 0] = selem_rotated[c, -1] = 1
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selem_rotated = convex_hull_image(selem_rotated).astype(int)
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selem = selem_square + selem_rotated
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selem[selem > 0] = 1
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return selem.astype(dtype)
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def _default_selem(ndim):
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"""
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Generates a cross-shaped structuring element (connectivity=1). This is the
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default structuring element (selem) if no selem was specified.
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Parameters
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----------
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ndim : int
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Number of dimensions of the image.
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Returns
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-------
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selem : ndarray
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The structuring element where elements of the neighborhood
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are 1 and 0 otherwise.
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"""
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return ndimage.morphology.generate_binary_structure(ndim, 1)
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