old_contents: import numpy as np
  from ..morphology import dilation, square
  from ..util import img_as_float
  from ..color import gray2rgb
  from .._shared.utils import deprecated
  
  
  def find_boundaries(label_img):
      """Return bool array where boundaries between labeled regions are True."""
      boundaries = np.zeros(label_img.shape, dtype=np.bool)
      boundaries[1:, :] += label_img[1:, :] != label_img[:-1, :]
      boundaries[:, 1:] += label_img[:, 1:] != label_img[:, :-1]
      return boundaries
  
  
  def mark_boundaries(image, label_img, color=(1, 1, 0), outline_color=None):
      """Return image with boundaries between labeled regions highlighted.
  
      Parameters
      ----------
      image : (M, N[, 3]) array
          Grayscale or RGB image.
      label_img : (M, N) array
          Label array where regions are marked by different integer values.
      color : length-3 sequence
          RGB color of boundaries in the output image.
      outline_color : length-3 sequence
          RGB color surrounding boundaries in the output image. If None, no
          outline is drawn.
      """
      if image.ndim == 2:
          image = gray2rgb(image)
      image = img_as_float(image, force_copy=True)
  
      boundaries = find_boundaries(label_img)
      if outline_color is not None:
          outer_boundaries = dilation(boundaries.astype(np.uint8), square(2))
          image[outer_boundaries != 0, :] = np.array(outline_color)
      image[boundaries, :] = np.array(color)
      return image
  
  
  @deprecated('mark_boundaries')
  def visualize_boundaries(*args, **kwargs):
      return mark_boundaries(*args, **kwargs)
  
new_contents: import numpy as np
  from ..morphology import dilation, square
  from ..util import img_as_float
  from ..color import gray2rgb
  from .._shared.utils import deprecated
  
  
  def find_boundaries(label_img):
      """Return bool array where boundaries between labeled regions are True."""
      boundaries = np.zeros(label_img.shape, dtype=np.bool)
      boundaries[1:, :] += label_img[1:, :] != label_img[:-1, :]
      boundaries[:, 1:] += label_img[:, 1:] != label_img[:, :-1]
      return boundaries
  
  
  def mark_boundaries(image, label_img, color=(1, 1, 0), outline_color=(0, 0, 0)):
      """Return image with boundaries between labeled regions highlighted.
  
      Parameters
      ----------
      image : (M, N[, 3]) array
          Grayscale or RGB image.
      label_img : (M, N) array
          Label array where regions are marked by different integer values.
      color : length-3 sequence
          RGB color of boundaries in the output image.
      outline_color : length-3 sequence
          RGB color surrounding boundaries in the output image. If None, no
          outline is drawn.
      """
      if image.ndim == 2:
          image = gray2rgb(image)
      image = img_as_float(image, force_copy=True)
  
      boundaries = find_boundaries(label_img)
      if outline_color is not None:
          outer_boundaries = dilation(boundaries.astype(np.uint8), square(2))
          image[outer_boundaries != 0, :] = np.array(outline_color)
      image[boundaries, :] = np.array(color)
      return image
  
  
  @deprecated('mark_boundaries')
  def visualize_boundaries(*args, **kwargs):
      return mark_boundaries(*args, **kwargs)
  
subject: Make black the default boundary color for mark_boundaries.