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Loop through nodes and retrieve attributes in Networkx

I defined in python some shapes with corresponding corner points, for example:

square = [[251, 184],
          [22, 192],
          [41, 350],
          [244, 346]]

triangle = [[250, 181],
            [133, 43],
            [21, 188]]

pentagon = [[131,  37],
            [11, 192],
            [37, 354],
            [247, 350],
            [256, 182]]

Then I use NetworkX to create the graph:

G = nx.DiGraph()

Then I create a node in the graph for each shape:

G.add_node('square', points = square, center = (139, 265))
G.add_node('triangle', points = triangle, center = (139, 135))
G.add_node('pentagon', points = pentagon, center = (138, 223))

Now the problem is, I have to create several edges connecting the two nodes if the condition is met. A condition that satisfies the condition if the center of the form is inside or outside of another form , then create an edge like this:

G.add_edge('triangle', 'pentagon', relation = 'inside')
G.add_edge('triangle', 'square', relation = 'outside')

To do this, I need to go through the nodes , extract centershapes, draw pointsfrom other shapes (NOT yourself, it's useless) and do it pointPolygonTest.

I tried a lot, but did not get any solution. The closest (not very effective) solution I received is the following:

nodes_p=dict([((u),d['points']) for u,d in G.nodes(data=True)])
nodes_c=dict([((u),d['center']) for u,d in G.nodes(data=True)])
for z,c in nodes_c.items():
    print z + ' with center', c
    for z,p in nodes_p.items():
        p_array = np.asarray(p)
        if cv2.pointPolygonTest(p_array,c,False)>=0:
            print 'inside ' + z
            #create edge
        else:
            print 'outside ' + z
            #create edge

, , - , (, triangle inside triangle) (, pentagon inside square)

triangle with center (139, 135)
inside triangle
outside square
inside pentagon
square with center (139, 265)
outside triangle
inside square
inside pentagon
pentagon with center (138, 223)
outside triangle
inside square
inside pentagon

? . : , . , script, :

import numpy as np
import networkx as nx
import cv2
+3
1

Polygon image

-, , . 

for u,outer_d in G.nodes(data=True):
   center = outer_d['center']
   print u, "with center", center
   for v, inner_d in G.nodes(data=True):
        #Don't compare self to self
        if u != v:
            # Create a source image
            src = np.zeros((400,400),np.uint8)          
            # draw an polygon on image src
            points = np.array(inner_d['points'],np.int0)
            cv2.polylines(src,[points],True,255,3)
            contours,_ = cv2.findContours(src,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
            if cv2.pointPolygonTest(contours[0],center,True) <= 0:
                print 'outside',v
            else:
                print 'inside',v


pentagon with center (138, 223)
inside square
outside triangle
square with center (139, 265)
inside pentagon
outside triangle
triangle with center (139, 135)
inside pentagon
outside square

, , , , . ( , ) .

def checkPoint(point, poly,r=400):
    ''' determine if point is on the interior of poly'''
    # Create a source image
    src = np.zeros((r,r),np.uint8)       
    # draw an polygon on image src
    verts = np.array(poly,np.int0)
    cv2.polylines(src,[verts],True,255,3)
    contours,_ = cv2.findContours(src,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
    return cv2.pointPolygonTest(contours[0],tuple(point),True) > 0:


for u,outer_d in G.nodes(data=True):
    points = outer_d['points']
    center = outer_d['center']
    print u, "with center", center
    for v, inner_d in G.nodes(data=True):
        poly = inner_d['points']
        if u != v:
            if all([checkPoint(point,poly) for point in points]):
                print 'inside',v
            else:
                print 'outside',v

.

pentagon with center (138, 223)
outside square
outside triangle
square with center (139, 265)
inside pentagon
outside triangle
triangle with center (139, 135)
inside pentagon
outside square

, , . , , . cv2, . .

+3

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