prewitt skimage.filters.prewitt(image, mask=None) [source] Find the edge magnitude using the Prewitt 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 Prewitt edge map. See also sobel, scharr Notes Return the square root of the sum of squares

combine_stains skimage.color.combine_stains(stains, conv_matrix) [source] Stain to RGB color space conversion. Parameters: stains : array_like The image in stain color space, in a 3-D array of shape (.., .., 3). conv_matrix: ndarray The stain separation matrix as described by G. Landini [R31]. Returns: out : ndarray The image in RGB format, in a 3-D array of shape (.., .., 3). Raises: ValueError If stains is not a 3-D array of shape (.., .., 3). Notes Stain combination matrices

warn skimage.viewer.warn(message, category=None, stacklevel=2) [source] A version of warnings.warn with a default stacklevel of 2.

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.

wiener skimage.filters.wiener(data, impulse_response=None, filter_params={}, K=0.25, predefined_filter=None) [source] Minimum Mean Square Error (Wiener) inverse filter. Parameters: data : (M,N) ndarray Input data. K : float or (M,N) ndarray Ratio between power spectrum of noise and undegraded image. impulse_response : callable f(r, c, **filter_params) Impulse response of the filter. See LPIFilter2D.__init__. filter_params : dict Additional keyword parameters to the impulse_response f

img_as_uint skimage.img_as_uint(image, force_copy=False) [source] Convert an image to 16-bit unsigned integer format. Parameters: image : ndarray Input image. force_copy : bool Force a copy of the data, irrespective of its current dtype. Returns: out : ndarray of uint16 Output image. Notes Negative input values will be clipped. Positive values are scaled between 0 and 65535.

black_tophat skimage.morphology.black_tophat(image, selem=None, *args, **kwargs) [source] Return black top hat of an image. The black top hat of an image is defined as its morphological closing minus the original image. This operation returns the dark spots of the image that are smaller than the structuring element. Note that dark spots in the original image are bright spots after the black top hat. Parameters: image : ndarray Image array. selem : ndarray, optional The neighborhood expre

gradient_percentile skimage.filters.rank.gradient_percentile(image, selem, out=None, mask=None, shift_x=False, shift_y=False, p0=0, p1=1) [source] Return local gradient of an image (i.e. local maximum - local minimum). 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) If None, a new array is

separate_stains skimage.color.separate_stains(rgb, conv_matrix) [source] RGB to stain color space conversion. Parameters: rgb : array_like The image in RGB format, in a 3-D array of shape (.., .., 3). conv_matrix: ndarray The stain separation matrix as described by G. Landini [R55]. Returns: out : ndarray The image in stain color space, in a 3-D array of shape (.., .., 3). Raises: ValueError If rgb is not a 3-D array of shape (.., .., 3). Notes Stain separation matrices availab

ellipsoid skimage.draw.ellipsoid(a, b, c, spacing=(1.0, 1.0, 1.0), levelset=False) [source] Generates ellipsoid with semimajor axes aligned with grid dimensions on grid with specified spacing. Parameters: a : float Length of semimajor axis aligned with x-axis. b : float Length of semimajor axis aligned with y-axis. c : float Length of semimajor axis aligned with z-axis. spacing : tuple of floats, length 3 Spacing in (x, y, z) spatial dimensions. levelset : bool If True, returns the