text: """
  ==========================
  Region Boundary based RAGs
  ==========================
  
  Construct a region boundary RAG with the ``rag_boundary`` function. The
  function  :py:func:`skimage.future.graph.rag_boundary` takes an
  ``edge_map`` argument, which gives the significance of a feature (such as
  edges) being present at each pixel. In a region boundary RAG, the edge weight
  between two regions is the average value of the corresponding pixels in
  ``edge_map`` along their shared boundary.
  
  """
  from skimage.future import graph
  from skimage import data, segmentation, color, filters, io
  from matplotlib import pyplot as plt
  
  
  img = data.coffee()
  gimg = color.rgb2gray(img)
  
  labels = segmentation.slic(img, compactness=30, n_segments=400)
  edges = filters.sobel(gimg)
  edges_rgb = color.gray2rgb(edges)
  
  g = graph.rag_boundary(labels, edges)
  lc = graph.show_rag(labels, g, edges_rgb, img_cmap=None, edge_cmap='viridis',
                      edge_width=1.2)
  
  plt.colorbar(lc, fraction=0.03)
  io.show()
  