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Region Boundary based RAGs#
Construct a region boundary RAG with the rag_boundary
function. The
function 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, io
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)
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 1.167 seconds)