Enhancement Ideas

[mikedh]

I was pinged recently looking for some projects to help out with, here are some ideas. PR's are always appreciated!

Updated 7/27/2020

• (docs) Figure out how to get the examples embedded in the actual docs webpage. Right now when you build docs, example ipynb files are rendered to HTML which is just linked to from the examples page. It would be really nice if each example was embedded in sphinx somehow, and kept the sidebar on the left so one could navigate around between examples and back to the docs.
• (feature) Mesh simplification, either through creating a meshlabserver interface or through implementing a vectorized numpy version of quadratic edge collapse: Decimate a mesh #41
• (feature) MSH support, as requested in Export mesh in .msh fileformat #206. Probably via meshio
• (feature) Color and line width in Path objects: Geometry colors and line widths in Scene #356
• (feature) More 3MF tests. Trimesh has a 3MF importer, it would be great to put together a test corpus of various small- ish models (specifically interesting would be multibody assemblies with duplication) from various exporters.
• (feature) Do whatever it takes to get pyinstaller to work with trimesh, as per Pyinstaller issues #412
• (infrastructure) Put all of Shapenet, Thingiverse 10k, GLTF samples, and all available meshes into an AWS S3 bucket, and continuously benchmark trimesh, pymesh, and assimp for percentage of files loaded and time. Memory issues with 3.0 obj loader and large files #510
• (community) See if upstream numpy has interest in including TrackedArray or ndarray.crc [Upstream Improvement] TrackedArray into scipy/numpy? #283
• (speedup) Add broad-phase culling for mesh.slice_plane to speed up on large meshes: Return subset of mesh using bound #630
• (feature) Exact rather than approximate medial axis calculation as per issue with medial axis not being straight #924

[Marviel]

@mikedh awesome list, we'd all love to see some of these changes, stoked to know you're considering things like built-in mesh simplification, etc.

A convention I've seen in some other repos is to have each task listed as their own github issue, and give them an easy medium hard label applied to them, based on the perceived difficulty.

Also allows us to start threaded conversations on each of the tasks in your list.

Anyhow just a thought! Not sure the extent to which we want to use Issues here :)

[mikedh]

Yeah it would be great to get some of this stuff! In the interest of avoiding a ton of immediately orphaned new issues the process I'd suggest initially would be:

1. I'll update this list in- place with new ideas.
2. If someone is interested in working on one of the ideas, they can open a new issue looking for advice before PR'ing.

[mmatl]

@mikedh I'm going to try to tackle textures. Let me know if you have any thoughts -- I was also thinking a new TextureVisuals object. Loading the texture file itself will probably requireimageio -- are you okay with introducing that dep? It's really lightweight.

[mikedh]

Sounds good, discussion for texture in #218

[LinJiarui]

@mikedh Hey mike, it's great to see that you mentioned IFC, which I'm quite familiar with. I also used IfcOpenShell to get geometries from IFC file and then voxelize them with trimesh. That's why I found trimesh and created two PRs :) So, maybe I can help in IFC importing.

[mikedh]

Hey @LinJiarui that would be great! I took a look at ifcopenshell-python briefly, and it looks like the biggest stumbling block would be packaging. As per IfcOpenShell/IfcOpenShell#146, you can't install it via pip, and it would be preferable to address that before adding it as a dependency.

CIbuildwheel might be a good solution, but is definitely a lot of work!

[nschloe]

Perhaps optimesh is something for you, too.

(BTW I just added trimesh to the awesome list.)

[FXXB]

@mikedh Thank you for your trimesh library. Just awesome.
I am rewriting my code which so far mainly deals with numpy.stl's. Since trimesh really does the job I am in the process of switching from numpy.stl to trimesh. So far I couldn´t find something to convert numpy.stl to trimesh.
Is there already a method to convert numpy.stl files to trimesh and vice versa. I would highly appreciate a hint on how to resolve.
Thank you and best regards

[FXXB]

Hi @bbarroqueiro Thank you for your quick response.
Yes, of course, I can save the numpy.stl representation as *.stl and reload it as *.stl in the trimesh representation, but I would prefer to do the job without export/import. Something like
trimesh.load (numpy-stl.data)
I wondered if this direct conversion between numpy-stl and trimesh already exists...
Sorry for the confusion

[FXXB]

Hi @bbarroqueiro
Thank you for your assistance. I will give it a try and let you know.
Best regards

[mikedh]

Oh numpy-stl from pypi? It looks like they just use a custom dtype, you can probably access the data directly:

In [1]: import trimesh

In [2]: from stl import Mesh

In [3]: r = Mesh.from_file('models/featuretype.STL')

In [4]: r.data
Out[4]: 
array([([ 0.        , -0.        ,  0.01694411], [[ 1.8933141 ,  0.5625    ,  1.        ], [ 1.8952131 ,  0.58420604,  1.        ], [ 1.125     ,  0.703125  ,  1.        ]], [0]),
       ([ 0.        , -0.        ,  0.01688094], [[ 1.8952131 ,  0.58420604,  1.        ], [ 1.9008526 ,  0.60525256,  1.        ], [ 1.125     ,  0.703125  ,  1.        ]], [0]),
       ([ 0.        ,  0.        ,  0.01622234], [[ 1.125     ,  0.703125  ,  1.        ], [ 1.9008526 ,  0.60525256,  1.        ], [ 1.9100609 ,  0.625     ,  1.        ]], [0]),
       ...,
       ([ 0.        ,  0.0625    ,  0.        ], [[ 1.75      , -0.25      ,  1.        ], [ 1.25      , -0.25      ,  0.875     ], [ 1.25      , -0.25      ,  1.        ]], [0]),
       ([ 0.        , -0.        ,  0.25      ], [[ 1.75      , -0.25      ,  0.875     ], [ 1.75      ,  0.25      ,  0.875     ], [ 1.25      , -0.25      ,  0.875     ]], [0]),
       ([ 0.        ,  0.        ,  0.25      ], [[ 1.25      , -0.25      ,  0.875     ], [ 1.75      ,  0.25      ,  0.875     ], [ 1.25      ,  0.25      ,  0.875     ]], [0])],
      dtype=[('normals', '<f4', (3,)), ('vectors', '<f4', (3, 3)), ('attr', '<u2', (1,))])

In [5]: r.vectors.shape
Out[5]: (3476, 3, 3)

In [6]: m = trimesh.Trimesh(**trimesh.triangles.to_kwargs(r.vectors))

In [7]: m.faces.shape
Out[7]: (3476, 3)

[FXXB]

Thank you so much. That's it. I must have missed the .to_kwargs method. Thanks again