skimage.novice A special Python image submodule for beginners. Description skimage.novice provides a simple image manipulation interface for beginners. It allows for easy loading, manipulating, and saving of image files. This module is primarily intended for teaching and differs significantly from the normal, array-oriented image functions used by scikit-image. Note This module uses the Cartesian coordinate system, where the origin is at the lower-left corner instead of the upper-right and the

sum_bilateral skimage.filters.rank.sum_bilateral(image, selem, out=None, mask=None, shift_x=False, shift_y=False, s0=10, s1=10) [source] Apply a flat kernel bilateral filter. This is an edge-preserving and noise reducing denoising filter. It averages pixels based on their spatial closeness and radiometric similarity. Spatial closeness is measured by considering only the local pixel neighborhood given by a structuring element (selem). Radiometric similarity is defined by the greylevel interva

imread skimage.data.imread(fname, as_grey=False, plugin=None, flatten=None, **plugin_args) [source] Load an image from file. Parameters: fname : string Image file name, e.g. test.jpg or URL. as_grey : bool If True, convert color images to grey-scale (32-bit floats). Images that are already in grey-scale format are not converted. plugin : str Name of plugin to use. By default, the different plugins are tried (starting with the Python Imaging Library) until a suitable candidate is found.

TiffSequence class skimage.external.tifffile.TiffSequence(files, imread=, pattern='axes', *args, **kwargs) [source] Bases: object Sequence of image files. The data shape and dtype of all files must match. Examples >>> tifs = TiffSequence("test.oif.files/*.tif") >>> tifs.shape, tifs.axes ((2, 100), 'CT') >>> data = tifs.asarray() >>> data.shape (2, 100, 256, 256) Attributes files (list) List of file names. shape (tuple) Shape of image sequence. axe

push skimage.io.push(img) [source] Push an image onto the shared image stack. Parameters: img : ndarray Image to push.

deltaE_ciede94 skimage.color.deltaE_ciede94(lab1, lab2, kH=1, kC=1, kL=1, k1=0.045, k2=0.015) [source] Color difference according to CIEDE 94 standard Accommodates perceptual non-uniformities through the use of application specific scale factors (kH, kC, kL, k1, and k2). Parameters: lab1 : array_like reference color (Lab colorspace) lab2 : array_like comparison color (Lab colorspace) kH : float, optional Hue scale kC : float, optional Chroma scale kL : float, optional Lightness sca

deltaE_cmc skimage.color.deltaE_cmc(lab1, lab2, kL=1, kC=1) [source] Color difference from the CMC l:c standard. This color difference was developed by the Colour Measurement Committee (CMC) of the Society of Dyers and Colourists (United Kingdom). It is intended for use in the textile industry. The scale factors kL, kC set the weight given to differences in lightness and chroma relative to differences in hue. The usual values are kL=2, kC=1 for “acceptability” and kL=1, kC=1 for “imperceptib

resize skimage.transform.resize(image, output_shape, order=1, mode='constant', cval=0, clip=True, preserve_range=False) [source] Resize image to match a certain size. Performs interpolation to up-size or down-size images. For down-sampling N-dimensional images by applying the arithmetic sum or mean, see skimage.measure.local_sum and skimage.transform.downscale_local_mean, respectively. Parameters: image : ndarray Input image. output_shape : tuple or ndarray Size of the generated output i

immunohistochemistry skimage.data.immunohistochemistry() [source] Immunohistochemical (IHC) staining with hematoxylin counterstaining. This picture shows colonic glands where the IHC expression of FHL2 protein is revealed with DAB. Hematoxylin counterstaining is applied to enhance the negative parts of the tissue. This image was acquired at the Center for Microscopy And Molecular Imaging (CMMI). No known copyright restrictions.

FigureCanvas class skimage.viewer.utils.FigureCanvas(figure, **kwargs) [source] Bases: matplotlib.backends.backend_qt4agg.FigureCanvasQTAgg Canvas for displaying images. __init__(figure, **kwargs) [source] resizeEvent(event) [source]