histogram skimage.exposure.histogram(image, nbins=256) [source] Return histogram of image. Unlike numpy.histogram, this function returns the centers of bins and does not rebin integer arrays. For integer arrays, each integer value has its own bin, which improves speed and intensity-resolution. The histogram is computed on the flattened image: for color images, the function should be used separately on each channel to obtain a histogram for each color channel. Parameters: image : array Inpu

subdivide_polygon skimage.measure.subdivide_polygon(coords, degree=2, preserve_ends=False) [source] Subdivision of polygonal curves using B-Splines. Note that the resulting curve is always within the convex hull of the original polygon. Circular polygons stay closed after subdivision. Parameters: coords : (N, 2) array Coordinate array. degree : {1, 2, 3, 4, 5, 6, 7}, optional Degree of B-Spline. Default is 2. preserve_ends : bool, optional Preserve first and last coordinate of non-circ

square skimage.morphology.square(width, dtype=) [source] Generates a flat, square-shaped structuring element. Every pixel along the perimeter has a chessboard distance no greater than radius (radius=floor(width/2)) pixels. Parameters: width : int The width and height of the square. Returns: selem : ndarray A structuring element consisting only of ones, i.e. every pixel belongs to the neighborhood. Other Parameters: dtype : data-type The data type of the structuring element.

circle skimage.draw.circle(r, c, radius, shape=None) [source] Generate coordinates of pixels within circle. Parameters: r, c : double Centre coordinate of circle. radius: double Radius of circle. shape : tuple, optional Image shape which is used to determine the maximum extent of output pixel coordinates. This is useful for circles which exceed the image size. By default the full extent of the circle are used. Returns: rr, cc : ndarray of int Pixel coordinates of circle. May be use

Button class skimage.viewer.widgets.Button(name, callback) [source] Bases: skimage.viewer.widgets.core.BaseWidget Button which calls callback upon click. Parameters: name : str Name of button. callback : callable f() Function to call when button is clicked. __init__(name, callback) [source]

label skimage.morphology.label(input, neighbors=None, background=None, return_num=False, connectivity=None) [source] Label connected regions of an integer array. Two pixels are connected when they are neighbors and have the same value. In 2D, they can be neighbors either in a 1- or 2-connected sense. The value refers to the maximum number of orthogonal hops to consider a pixel/voxel a neighbor: 1-connectivity 2-connectivity diagonal connection close-up [ ] [ ] [ ]

hsobel skimage.filters.hsobel(*args, **kwargs) [source] Deprecated function. Use skimage.filters.sobel_h instead. Find the horizontal edges of an image using the Sobel transform. Parameters: image : 2-D array Image to process. mask : 2-D array, optional An optional mask to limit the application to a certain area. Note that pixels surrounding masked regions are also masked to prevent masked regions from affecting the result. Returns: output : 2-D array The absolute Sobel edge map. N

ball skimage.morphology.ball(radius, dtype=) [source] Generates a ball-shaped structuring element. This is the 3D equivalent of a disk. A pixel is within the neighborhood if the euclidean distance between it and the origin is no greater than radius. Parameters: radius : int The radius of the ball-shaped structuring element. Returns: selem : ndarray The structuring element where elements of the neighborhood are 1 and 0 otherwise. Other Parameters: dtype : data-type The data type of

star skimage.morphology.star(a, dtype=) [source] Generates a star shaped structuring element. Start has 8 vertices and is an overlap of square of size 2*a + 1 with its 45 degree rotated version. The slanted sides are 45 or 135 degrees to the horizontal axis. Parameters: a : int Parameter deciding the size of the star structural element. The side of the square array returned is 2*a + 1 + 2*floor(a / 2). Returns: selem : ndarray The structuring element where elements of the neighborhood

I/O Plugin Infrastructure A plugin consists of two files, the source and the descriptor .ini. Let’s say we’d like to provide a plugin for imshow using matplotlib. We’ll call our plugin mpl: skimage/io/_plugins/mpl.py skimage/io/_plugins/mpl.ini The name of the .py and .ini files must correspond. Inside the .ini file, we give the plugin meta-data: [mpl] <-- name of the plugin, may be anything description = Matplotlib image I/O plugin provides = imshow <-- a comma-separated list, one or mo