skeletor

Python 3 library to extract skeletons from 3D meshes


Keywords
mesh, skeletonization, contraction, skeleton, extraction, 3d, connectomics, meshes, neurons, python, skeleton-extraction, skeletonize, teasar, volumes
License
GPL-3.0
Install
pip install skeletor==1.3.0

Documentation

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Skeletor

Unlike its namesake, this Python 3 library does not (yet) seek to conquer Eternia but to turn meshes into skeletons.

Heads-up: skeletor 1.0.0 introduced some breaking changes and major reorganizations. Please see the changelog for details.

Install

pip3 install skeletor

For the dev version:

pip3 install git+https://github.com/navis-org/skeletor@master

Dependencies

Automatically installed with pip:

  • networkx
  • numpy
  • pandas
  • scipy
  • scikit-learn
  • trimesh
  • tqdm
  • python-igraph
  • ncollpyde

Optional because not strictly required for the core functions but highly recommended:

  • pyglet is required by trimesh to preview meshes/skeletons in 3D: pip3 install pyglet
  • fastremap for sizeable speed-ups with some methods: pip3 install fastremap

Documentation

Please see the documentation for details.

The change log can be found here.

Quickstart

For the impatient a quick example:

>>> import skeletor as sk
>>> mesh = sk.example_mesh()
>>> # To load and use your own mesh instead of the example mesh:
>>> # import trimesh as tm
>>> # mesh = tm.Trimesh(vertices, faces)  # or...
>>> # mesh = tm.load_mesh('mesh.obj')
>>> fixed = sk.pre.fix_mesh(mesh, remove_disconnected=5, inplace=False)
>>> skel = sk.skeletonize.by_wavefront(fixed, waves=1, step_size=1)
>>> skel
<Skeleton(vertices=(1258, 3), edges=(1194, 2), method=wavefront)>

All skeletonization methods return a Skeleton object. These are just convenient objects to represent and inspect the results.

>>> # location of vertices (nodes)
>>> skel.vertices
array([[16744, 36720, 26407],
       ...,
       [22076, 23217, 24472]])
>>> # child -> parent edges
>>> skel.edges
array([[  64,   31],
       ...,
       [1257, 1252]])
>>> # Mapping for mesh to skeleton vertex indices
>>> skel.mesh_map
array([ 157,  158, 1062, ...,  525,  474,  547])
>>> # SWC table
>>> skel.swc.head()
   node_id  parent_id             x             y             z    radius
0        0         -1  16744.005859  36720.058594  26407.902344  0.000000
1        1         -1   5602.751953  22266.756510  15799.991211  7.542587
2        2         -1  16442.666667  14999.978516  10887.916016  5.333333
>>> # Save SWC file
>>> skel.save_swc('skeleton.swc')

If you installed pyglet (see above) you can also use trimesh's plotting capabilities to inspect the results:

>>> skel.show(mesh=True)

skeletor_example

Benchmarks

skeletor_examples

Benchmarks were run on a 2018 MacBook Pro (2.2 GHz Core i7, 32Gb memory) with optional fastremap dependency installed. Note some of these functions (e.g. contraction and TEASAR/vertex cluster skeletonization) can vary a lot in speed based on parameterization.

Contributing

Pull requests are always welcome!

References & Acknowledgments

Mesh contraction and the edge collapse approach are based on this paper: [1] Au OK, Tai CL, Chu HK, Cohen-Or D, Lee TY. Skeleton extraction by mesh contraction. ACM Transactions on Graphics (TOG). 2008 Aug 1;27(3):44. The abstract and the paper can be found here. Also see this YouTube video.

Some of the code in skeletor was modified from the Py_BL_MeshSkeletonization addon for Blender 3D created by #0K Srinivasan Ramachandran and published under GPL3.

The mesh TEASAR approach was adapted from the implementation in meshparty by Sven Dorkenwald, Casey Schneider-Mizell and Forrest Collman.