code: def imshow(image, ax=None, show_cbar=None, **kwargs):
      """Show the input image and return the current axes.
  
      By default, the image is displayed in grayscale, rather than
      the matplotlib default colormap.
  
      Images are assumed to have standard range for their type. For
      example, if a floating point image has values in [0, 0.5], the
      most intense color will be gray50, not white.
  
      If the image exceeds the standard range, or if the range is too
      small to display, we fall back on displaying exactly the range of
      the input image, along with a colorbar to clearly indicate that
      this range transformation has occurred.
  
      For signed images, we use a diverging colormap centered at 0.
  
      Parameters
      ----------
      image : array, shape (M, N[, 3])
          The image to display.
      ax : `matplotlib.axes.Axes`, optional
          The axis to use for the image, defaults to plt.gca().
      show_cbar : boolean, optional.
          Whether to show the colorbar (used to override default behavior).
      **kwargs : Keyword arguments
          These are passed directly to `matplotlib.pyplot.imshow`.
  
      Returns
      -------
      ax_im : `matplotlib.pyplot.AxesImage`
          The `AxesImage` object returned by `plt.imshow`.
      """
      import matplotlib.pyplot as plt
      from mpl_toolkits.axes_grid1 import make_axes_locatable
  
      lo, hi, cmap = _get_display_range(image)
  
      kwargs.setdefault("interpolation", "nearest")
      kwargs.setdefault("cmap", cmap)
      kwargs.setdefault("vmin", lo)
      kwargs.setdefault("vmax", hi)
  
      ax = ax or plt.gca()
      ax_im = ax.imshow(image, **kwargs)
      if (
          cmap != _default_colormap and show_cbar is not False
      ) or show_cbar:
          divider = make_axes_locatable(ax)
          cax = divider.append_axes("right", size="5%", pad=0.05)
          plt.colorbar(ax_im, cax=cax)
      ax.get_figure().tight_layout()
  
      return ax_im
  
file_path: scikit-image/skimage/io/_plugins/matplotlib_plugin.py
imports: from collections import namedtuple
  import numpy
  from ...util import dtype
  from ...exposure import is_low_contrast
  from ..._shared.utils import warn
  from math import floor, ceil
label_desc: Use image node_id 4 for calling a global function with example usage: imshow(image, ax, show_cbar) and returns: ax_im