Skeleton Network

build net work from nd skeleton image

graph = sknw.build_sknw(ske， multi=False)

ske: should be a nd skeleton image

multi: if True，a multigraph is retured, which allows more than one edge between two nodes and self-self edge. default is False.

return: is a networkx Graph object

graph detail:

graph.node[id]['pts'] : Numpy(x, n), coordinates of nodes points

graph.node[id]['o']: Numpy(n), centried of the node

graph.edge(id1, id2)['pts']: Numpy(x, n), sequence of the edge point

graph.edge(id1, id2)['weight']: float, length of this edge

if it's a multigraph, you must add a index after two node id to get the edge, like: graph.edge(id1, id2)[0].

Build Graph:

build Graph by Skeleton, then plot as a vector Graph in matplotlib.
from skimage.morphology import skeletonize
from skimage import data
import sknw

open and skeletonize

img = data.horse() ske = skeletonize(~img).astype(np.uint16)

build graph from skeleton

graph = sknw.build_sknw(ske)

draw image

plt.imshow(img, cmap='gray')

draw edges by pts

for (s,e) in graph.edges(): ps = graph[s][e]['pts'] plt.plot(ps[:,1], ps[:,0], 'green')

draw node by o

nodes = graph.nodes() ps = np.array([nodes[i]['o'] for i in nodes]) plt.plot(ps[:,1], ps[:,0], 'r.')

title and show

plt.title('Build Graph') plt.show()


![](http://home.imagepy.org/sknw/buildgraph.png "解压")
### Find Path
then you can use networkx do what you want
![](http://home.imagepy.org/sknw/findpath.png "解压")
### 3D Skeleton
sknw can works on nd image, this is a 3d demo by mayavi
![](http://home.imagepy.org/sknw/3dgraph.png "解压")

### About ImagePy
[https://github.com/Image-Py/imagepy](https://github.com/Image-Py/imagepy)

ImagePy is my opensource image processihng framework. It is the ImageJ of Python, you can wrap any numpy based function esaily. And sknw is a sub module of ImagePy. You can use sknw without any code.

![](http://myvi.imagepy.org/imgs/imagepy.jpg "vessel")