Added example for region boundary merging

doc/examples/segmentation/plot_boundary_merge.py

@@ -1,36 +1,78 @@
-from skimage import data, io, segmentation, color
+"""
+============================================
+Hierarchical Merging of Region Boundary RAGs
+============================================
+
+TODO: Description
+"""
+
+from skimage import data, segmentation, filters, color
 from skimage.future import graph
-import numpy as np
+from matplotlib import pyplot as plt
 
 
 def weight_boundary(graph, src, dst, n):
-    if graph.has_edge(src, n) and graph.has_edge(dst, n):
-        count_src = graph[src][n]['count']
-        count_dst = graph[dst][n]['count']
+    """
+    Callback to handle merging of nodes of a region boundary RAG.
 
-        weight_src = graph[src][n]['weight']
-        weight_dst = graph[dst][n]['weight']
+    This function computes the `"weight"` and the count `"count"`
+    attributes of the edge between `n` and the node formed after
+    merging `src` and `dst`.
 
-        count = count_src + count_dst
-        return {
-            'count': count,
-            'weight': (count_src*weight_src + count_dst*weight_dst)/count
-        }
 
-    elif graph.has_edge(src, n):
-        return graph[src][n]
-    elif graph.has_edge(dst, n):
-        return graph[dst][n]
+    Parameters
+    ----------
+    graph : RAG
+        The graph under consideration.
+    src, dst : int
+        The vertices in `graph` to be merged.
+    n : int
+        A neighbor of `src` or `dst` or both.
+
+    Returns
+    -------
+    data : dict
+        A dictionary with the `"weight"` and `"count"` attributes to be
+        assigned for the merged node.
+
+    """
+    default = {'weight': 0.0, 'count': 0}
+
+    count_src = graph[src].get(n, default)['count']
+    count_dst = graph[dst].get(n, default)['count']
+
+    weight_src = graph[src].get(n, default)['weight']
+    weight_dst = graph[dst].get(n, default)['weight']
+
+    count = count_src + count_dst
+    return {
+        'count': count,
+        'weight': (count_src*weight_src + count_dst*weight_dst)/count
+    }
 
 
 def merge_boundary(graph, src, dst):
     pass
 
 img = data.coffee()
+edges = filters.sobel(color.rgb2gray(img))
 labels = segmentation.slic(img, compactness=30, n_segments=400)
-g = graph.rag_mean_color(img, labels)
+g = graph.rag_boundary(labels, edges)
 
-labels2 = graph.merge_hierarchical(labels, g, thresh=40, rag_copy=False,
+graph.show_rag(labels, g, img)
+plt.title('Initial RAG')
+
+labels2 = graph.merge_hierarchical(labels, g, thresh=0.08, rag_copy=False,
                                    in_place_merge=True,
                                    merge_func=merge_boundary,
                                    weight_func=weight_boundary)
+
+graph.show_rag(labels, g, img)
+plt.title('RAG after hierarchical merging')
+
+plt.figure()
+out = color.label2rgb(labels2, img, kind='avg')
+plt.imshow(out)
+plt.title('Final segmentation')
+
+plt.show()