compare_ssim skimage.measure.compare_ssim(X, Y, win_size=None, gradient=False, dynamic_range=None, multichannel=False, gaussian_weights=False, full=False, **kwargs) [source] Compute the mean structural similarity index between two images. Parameters: X, Y : ndarray Image. Any dimensionality. win_size : int or None The side-length of the sliding window used in comparison. Must be an odd value. If gaussian_weights is True, this is ignored and the window size will depend on sigma. gradient

compare_psnr skimage.measure.compare_psnr(im_true, im_test, dynamic_range=None) [source] Compute the peak signal to noise ratio (PSNR) for an image. Parameters: im_true : ndarray Ground-truth image. im_test : ndarray Test image. dynamic_range : int The dynamic range of the input image (distance between minimum and maximum possible values). By default, this is estimated from the image data-type. Returns: psnr : float The PSNR metric. References [R260] https://en.wikipedia.org/wiki

ComboBox class skimage.viewer.widgets.ComboBox(name, items, ptype='kwarg', callback=None) [source] Bases: skimage.viewer.widgets.core.BaseWidget ComboBox widget for selecting among a list of choices. Parameters: name : str Name of ComboBox parameter. If this parameter is passed as a keyword argument, it must match the name of that keyword argument (spaces are replaced with underscores). In addition, this name is displayed as the name of the ComboBox. items: list of str Allowed parameter

compare_nrmse skimage.measure.compare_nrmse(im_true, im_test, norm_type='Euclidean') [source] Compute the normalized root mean-squared error (NRMSE) between two images. Parameters: im_true : ndarray Ground-truth image. im_test : ndarray Test image. norm_type : {‘Euclidean’, ‘min-max’, ‘mean’} Controls the normalization method to use in the denominator of the NRMSE. There is no standard method of normalization across the literature [R259]. The methods available here are as follows: ‘Euc

compare_mse skimage.measure.compare_mse(im1, im2) [source] Compute the mean-squared error between two images. Parameters: im1, im2 : ndarray Image. Any dimensionality. Returns: mse : float The mean-squared error (MSE) metric.

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

CollectionViewer class skimage.viewer.viewers.CollectionViewer(image_collection, update_on='move', **kwargs) [source] Bases: skimage.viewer.viewers.core.ImageViewer Viewer for displaying image collections. Select the displayed frame of the image collection using the slider or with the following keyboard shortcuts: left/right arrows Previous/next image in collection. number keys, 0–9 0% to 90% of collection. For example, “5” goes to the image in the middle (i.e. 50%) of the collection. home/

CollectionViewer class skimage.viewer.CollectionViewer(image_collection, update_on='move', **kwargs) [source] Bases: skimage.viewer.viewers.core.ImageViewer Viewer for displaying image collections. Select the displayed frame of the image collection using the slider or with the following keyboard shortcuts: left/right arrows Previous/next image in collection. number keys, 0–9 0% to 90% of collection. For example, “5” goes to the image in the middle (i.e. 50%) of the collection. home/end keys

coins skimage.data.coins() [source] Greek coins from Pompeii. This image shows several coins outlined against a gray background. It is especially useful in, e.g. segmentation tests, where individual objects need to be identified against a background. The background shares enough grey levels with the coins that a simple segmentation is not sufficient. Notes This image was downloaded from the Brooklyn Museum Collection. No known copyright restrictions.

coffee skimage.data.coffee() [source] Coffee cup. This photograph is courtesy of Pikolo Espresso Bar. It contains several elliptical shapes as well as varying texture (smooth porcelain to course wood grain). Notes No copyright restrictions. CC0 by the photographer (Rachel Michetti).