peak_local_max skimage.feature.peak_local_max(image, min_distance=1, threshold_abs=None, threshold_rel=None, exclude_border=True, indices=True, num_peaks=inf, footprint=None, labels=None) [source] Find peaks in an image as coordinate list or boolean mask. Peaks are the local maxima in a region of 2 * min_distance + 1 (i.e. peaks are separated by at least min_distance). If peaks are flat (i.e. multiple adjacent pixels have identical intensities), the coordinates of all such pixels are returne

percentile skimage.filters.rank.percentile(image, selem, out=None, mask=None, shift_x=False, shift_y=False, p0=0) [source] Return local percentile of an image. Returns the value of the p0 lower percentile of the local greyvalue distribution. Only greyvalues between percentiles [p0, p1] are considered in the filter. Parameters: image : 2-D array (uint8, uint16) Input image. selem : 2-D array The neighborhood expressed as a 2-D array of 1’s and 0’s. out : 2-D array (same dtype as input)

PaintTool class skimage.viewer.canvastools.PaintTool(manager, overlay_shape, radius=5, alpha=0.3, on_move=None, on_release=None, on_enter=None, rect_props=None) [source] Bases: skimage.viewer.canvastools.base.CanvasToolBase Widget for painting on top of a plot. Parameters: manager : Viewer or PlotPlugin. Skimage viewer or plot plugin object. overlay_shape : shape tuple 2D shape tuple used to initialize overlay image. alpha : float (between [0, 1]) Opacity of overlay on_move : function

page skimage.data.page() [source] Scanned page. This image of printed text is useful for demonstrations requiring uneven background illumination.

otsu skimage.filters.rank.otsu(image, selem, out=None, mask=None, shift_x=False, shift_y=False) [source] Local Otsu’s threshold value for each pixel. Parameters: image : ndarray Image array (uint8 array). selem : 2-D array The neighborhood expressed as a 2-D array of 1’s and 0’s. out : ndarray If None, a new array will be allocated. mask : ndarray Mask array that defines (>0) area of the image included in the local neighborhood. If None, the complete image is used (default). shif

pad skimage.util.pad(array, pad_width, mode=None, **kwargs) [source] Pads an array. Parameters: array : array_like of rank N Input array pad_width : {sequence, array_like, int} Number of values padded to the edges of each axis. ((before_1, after_1), ... (before_N, after_N)) unique pad widths for each axis. ((before, after),) yields same before and after pad for each axis. (pad,) or int is a shortcut for before = after = pad width for all axes. mode : str or function One of the followin

ORB class skimage.feature.ORB(downscale=1.2, n_scales=8, n_keypoints=500, fast_n=9, fast_threshold=0.08, harris_k=0.04) [source] Bases: skimage.feature.util.FeatureDetector, skimage.feature.util.DescriptorExtractor Oriented FAST and rotated BRIEF feature detector and binary descriptor extractor. Parameters: n_keypoints : int, optional Number of keypoints to be returned. The function will return the best n_keypoints according to the Harris corner response if more than n_keypoints are detect

opening skimage.morphology.opening(image, selem=None, *args, **kwargs) [source] Return greyscale morphological opening of an image. The morphological opening on an image is defined as an erosion followed by a dilation. Opening can remove small bright spots (i.e. “salt”) and connect small dark cracks. This tends to “open” up (dark) gaps between (bright) features. Parameters: image : ndarray Image array. selem : ndarray, optional The neighborhood expressed as an array of 1’s and 0’s. If No

open skimage.novice.open(path) [source] Return Picture object from the given image path.

octahedron skimage.morphology.octahedron(radius, dtype=) [source] Generates a octahedron-shaped structuring element. This is the 3D equivalent of a diamond. A pixel is part of the neighborhood (i.e. labeled 1) if the city block/Manhattan distance between it and the center of the neighborhood is no greater than radius. Parameters: radius : int The radius of the octahedron-shaped structuring element. Returns: selem : ndarray The structuring element where elements of the neighborhood are