Sampling colored point cloud from kaolin.io.obj.ObjMesh

[qiminchen]

Hi, are there any ways to sample colored point clouds from obj mesh loaded from kaolin.io.shapenet or kaolin.io.obj.import_mesh? Since it will return vertices, faces, uvs, face_uvs_idx, materials etc.

[Caenorst]

Hi @qiminchen , thank you for your interest in Kaolin.

Great timing! I just pushed an MR for data preprocessing, including a small example doing exactly what you are asking for!

[qiminchen]

Hi @Caenorst, thank you so much, this is definitely helpful! By the way, does it only work for ShapeNet.v2? What about v1

[Caenorst]

It should also work with V1 (just change the dataset name), I would be careful with ShapeNetV1 as I found out that a big part of the dataset is just unusable

[qiminchen]

perfect thanks, and yea I agree. Let me try it out very quick and I will let you know how it goes! Thank you so much

[qiminchen]

Hi @Caenorst, I just tested the fast_mesh_sampling.py and it works perfectly fine for ShapeNetV1 and V2 so far. Thank you so much, this saves me a lot of time! Really appreciate. Amazing job!

[qiminchen]

below example is 8a4f09913603d76cb8cf782e8c539948 from ShapeNet v1 Car category, 1st image is a snapshot of mesh in Meshlab, 2nd image is the sampled color point cloud using fast_mesh_sampling.py, I didn't include the vertex normal, otherwise it would look better.

[Caenorst]

Glad to hear that it's working well for you! Wxtracting normals should be pretty easy to extend, you should be able to get the normal using https://kaolin.readthedocs.io/en/latest/modules/kaolin.ops.mesh.html#kaolin.ops.mesh.face_normals (I need to verify the quality of normals stored in the obj, if any).

[qiminchen]

Hi @Caenorst, I'm not sure if this is an issue, I tested fffb1660a38af30ba4cf3601fb6b2442 from ShapeNet v2 Car category, the 1st image is the snapshot from Meshlab, the 2nd image is the sampled color point cloud (500k points), if you look at the roof, the color is not consistent, this issue happens in many shapes from v2, but code seems to work fine in v1, can you please take a look at this?

btw I convert color pixel range to [0, 255] using colors = (colors * 255).astype(np.uint8), I hope this does not cause the issue

[Caenorst]

The problem is from ShapeNet, some models have very weird internal structures that are overlapping with the visible shape. I've observed that when using the rasterization: typically you will have those glitches if you rasterize while ignoring face normals.

[qiminchen]

are there any ways to improve the sampling?

[Caenorst]

From the top of my head: 1) you can use rendering to generate some points, such as our rasterizer or you can use our Omniverse Kaolin App. You can also do a bunch of rasterization from different point of views 2) if a faces is not displayed in any rasterization then you can assume it's "not visible" and discard it.

Both methods are actually kinda similar

[qiminchen]

Thanks, I will try both. Please let me know if you have any updates on this MR for solving the glitches issue. Appreciate it.

[muzhou-yu]

Thanks, I will try both. Please let me know if you have any updates on this MR for solving the glitches issue. Appreciate it.

Hi, have you tried the method for solving the color inconsistent problem? I have also faced this issue. Thanks.