"""
====================================================
Region Boundary based Region adjacency graphs (RAGs)
====================================================

Construct a region boundary RAG with the ``rag_boundary`` function. The
function  :py:func:`skimage.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 import graph
from skimage import data, segmentation, color, filters
from matplotlib import pyplot as plt


img = data.coffee()
gimg = color.rgb2gray(img)

labels = segmentation.slic(img, compactness=30, n_segments=400, start_label=1)
edges = filters.sobel(gimg)
edges_rgb = color.gray2rgb(edges)

fig, ax = plt.subplots()

g = graph.rag_boundary(labels, edges)
lc = graph.show_rag(
    labels, g, edges_rgb, img_cmap=None, ax=ax, edge_cmap='viridis', edge_width=1.2
)


plt.colorbar(lc, fraction=0.03)
plt.show()