Draft: Research mesh tooling with kaolin

  • Status: draft
  • Deciders: V-Sekai,
  • Tags: V-Sekai,

Context and Problem Statement

Need geometric tools for many things in the V-Sekai.

[Describe the context and problem statement, e.g., in free form using two to three sentences. You may want to articulate the problem in the form of a question.]

Describe the proposed option and how it helps to overcome the problem or limitation

Use kaolin for some of the tools.

Describe how your proposal will work, with code, pseudo-code, mock-ups, or diagrams

  1. git clone https://github.com/NVIDIAGameWorks/kaolin.git
  2. Install https://github.com/conda-forge/miniforge#mambaforge
  3. conda create --name kaolin python=3.9
  4. conda activate kaolin
  5. conda install pytorch torchvision torchaudio cudatoolkit=11.3 -c pytorch
  6. python setup.py develop
  7. Test the install. python -c "import kaolin; print(kaolin.__version__)"

Questions

Hi fire , thanks for your interest in Kaolin. Currently probably the best way to learn Kaolin is to take a look through the documentation and look for relevant functions. We hope to make more demos which will make learning Kaolin smoother in the future.

The functions which will be useful to you would be:

kaolin.io.obj.import_mesh to import a mesh.

torch.meshgrid to generate a bunch of 3D coordinates of a voxel grid.

kaolin.metrics.trianglemesh.point_to_mesh_distance to get the distance function for those points.

kaolin.ops.mesh.check_sign to get the sign of the points to multiply with the distance.

kaolin.ops.conversions.voxelgrids_to_trianglemeshes to convert the SDF grid to a mesh.

Positive Consequences

  • [e.g., improvement of quality attribute satisfaction, follow-up decisions required, …]

Negative Consequences

  • Might require the GPU.
  • Inferencing may be difficult at interactive rates.

Option graveyard:

  • Option:
  • Rejection Reason:

If this enhancement will not be used often, can it be worked around with a few lines of script?

CUDA, PyTorch and c++ are significant works.

Is there a reason why this should be core and done by us?

I have an approach!

References

  • https://kaolin.readthedocs.io/en/latest/notes/installation.html
  • https://www.alecjacobson.com/weblog/?tag=qslim

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