rubenwiersma / deltaconv Goto Github PK

Hi @rubenwiersma,
Thx for sharing this excellent work.
While I was going through the paper details, I got confused by the implementation of $\partial_{u} \Gamma\left(u_{j}, v_{j}\right) \text{ and } \partial_{v} \Gamma\left(u_{j}, v_{j}\right)$ in these two lines L173-174.
Why is the implementation different from that of grad? Can u plz give detailed mathematical expressions for this?

Hi, thanks for your excellent work,
I do some simple tests feeding rotated point clouds into DeltaNetSegmentation
it seems coordinate-independency breaks(output features are different) when using xyz-coordinates as input scalar field,
is it an expected behavior?
should we set constant values to each node to guarantee coordinate-independency?

here is my test code:

    # coordinate independent
    model = deltaconv.models.DeltaNetSegmentation(1, 256).to('cuda')
    # not coordinate independent
    # model = deltaconv.models.DeltaNetSegmentation(3, 256).to('cuda')
    torch.set_printoptions(precision=2, threshold=10)
    pos = torch.randn(100, 3).cuda() 
    batch_ids = torch.zeros(100).cuda().long()
    input = torch.ones(100,1).cuda()
    for R in RandomRotations():
        pos_r = pos @ R
        # coordinate independent
        feats = model(DataSeg(pos_r, batch_ids, input))
        # not coordinate independent
        # feats = model(DataSeg(pos_r, batch_ids))
        print(torch.sum(feats, dim=0).detach())
        print(feats[5:8].detach())

Hi, first of all thanks for sharing the great work!
I am quite interested in the visualization of the single scalar- or vector feature of each layer (figure 5 in the paper). Can you please also release the codes for the visualization? Thanks a lot!

In transforms/__init__.py, there is from tkinter import W. This import seems out of place. Can you please confirm?

This actually caused a issue when using in a docker container with python 3.8.

  File "/home/algorithm/.local/lib/python3.8/site-packages/deltaconv/__init__.py", line 4, in <module> 
    from . import transforms
  File "/home/algorithm/.local/lib/python3.8/site-packages/deltaconv/transforms/__init__.py", line 1, in <module>
    from tkinter import W
  File "/opt/conda/lib/python3.8/tkinter/__init__.py", line 36, in <module>
    import _tkinter # If this fails your Python may not be configured for Tk
ImportError: libX11.so.6: cannot open shared object file: No such file or directory

This work is very interesting, I think if I have a group of point clouds with different shapes but all perpendicular to the xy plane (similar to walls with various shapes perpendicular to the ground), can I use your algorithm directly to determine how much they are perpendicular to the ground (some walls are not exactly perpendicular to the ground)