Region Boundary based RAGs

Construct a region boundary RAG with the rag_boundary function. The function 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.

Traceback (most recent call last):
  File "/build/skimage-Lp2Zl4/skimage-0.16.2/doc/examples/segmentation/plot_rag_boundary.py", line 1
    ==========================
    ^
SyntaxError: invalid syntax

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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()

Total running time of the script: ( 0 minutes 0.000 seconds)