Trying graph partitioning.

community.py

@@ -450,7 +450,7 @@ def init(self, graph, part = None) :
             for node in graph.nodes() :
                 com = part[node]
                 self.node2com[node] = com
-                deg = float(graph.degree(node, weigh = 'weight'))
+                deg = float(graph.degree(node, weight = 'weight'))
                 self.degrees[com] = self.degrees.get(com, 0) + deg
                 self.gdegrees[node] = deg
                 inc = 0.

generator.py

@@ -148,7 +148,8 @@ def _create_graph(fvector, xdim, ydim):
                 dist_max = hypot(xdim, ydim) * 1.0
                 dist = hypot(pos[0]-pos0[0], pos[1]-pos0[1])
 
-                weight = exp(-dot(V, V.T)) * log(dist_max/(1+dist))
+                #weight = exp(-dot(V, V.T)) * log(dist_max/(1+dist))
+                weight = exp(-dot(V, V.T)) * (1 - (dist/dist_max))
                 if weight > 10e-10:
                     G.add_edge(i, count, weight=weight)
                 count += 1
@@ -164,11 +165,4 @@ def create_graph(im, patch_size=8):
 
     return _create_graph(fvector, x, y)
 if __name__ == '__main__':
-    import time
-    im = imread('ball1.jpg')
-    print time.clock()
-    im = _preprocess_image(im)
-    fvector = _create_feature_vector(im)
-    x, y, z = im.shape
-    G = _create_graph(fvector, x, y)
-    print time.clock()
+    im = imread('src/ball1.jpg')

main.py

@@ -2,15 +2,23 @@
 
 from generator import *
 from processor import *
-from canny import Canny
+import metis
+
 patch_size = 8
-imname = 'flower.jpg'
+imname = 'src/new_image.jpg'
 im = imread(imname)
-im_edge = Canny(imname, 1).grad[1:-1, 1:-1]
-im_high = empty_like(im)
-im_high[:,:,0] = im_edge[:,:]
-im_high[:,:,1] = im_edge[:,:]
-im_high[:,:,2] = im_edge[:,:]
-G = create_graph(gaussian_filter(im, 2)+im_high,patch_size)
-community = process_graph(G)
-save_community_snapshot(im, G, community, patch_size)
+imtemp = im.copy()
+print 'Starting graph processing'
+G = create_graph(im,patch_size)
+comm, partition = process_graph(G)
+save_community_snapshot(im, G, comm, patch_size)
+node_list = [d for n,d in G.nodes_iter(data=True)]
+print 'Level Zero done.'
+(edgecuts, parts) = metis.part_graph(G, 2, recursive = True)
+
+for i in range(len(parts)):
+    if parts[i]==1:
+        x, y = G.node[i]['pos']
+        t = patch_size // 2
+        imtemp[x-t:x+t, y-t:y+t] += 50
+Image.fromarray(imtemp).convert('RGB').save('partition_check.jpg')

notes.txt

@@ -1,3 +1,3 @@
 1. The bounding box is a horrible misnomer
 2. Distance penality should be considered. Need to choose linear or exponential
-
+3. Trying METIS for graph partitioning

processor.py

@@ -30,7 +30,7 @@ def process_graph(imgraph):
     for i in range(n_nodes):
         communities[partition[i]].append(i)
 
-    return communities
+    return communities, partition
 
 def _draw_line(im, point1, point2):
     """