Thanks for the contribution! The newly added visualizer is not used right now. Is open3d an alternative to mlab? If so, could you please add an option so that we can choose the visualization backend.

hello,zhijian,
I am a git newbie, i dont know whether "push -f" is right, if there are some mistake please tell me,:)🤣

Hello, @suyunzzz
I've downloaded the file which you updated yesterday.
And I try to run the visualize code by default command:

python visualize.py

But I encounter some error about:

File "visualize.py", line 360, in
outputs = model(inputs)
ValueError: Expected more than 1 value per channel when training, got input size torch.Size([1, 84])

The parse argument is:

Model: SemanticKITTI_val_SPVNAS@65GMACs (default)
Velodyne_dir: sample_data(default)
visualize_backend: open3d(default)

Do you know how to solve this problem?
Hope you can give me some advise.
Thanks a lot!! 谢谢！

Hi @suyunzzz, thanks for the updates. Could you please remove init and all .pyc files? Also, the sample data is now stored under assets. Please remove sample_data as well. Thank you!

Btw, could you also reformat the code according to pre-commit (see https://github.com/mit-han-lab/spvnas/runs/6327544860?check_suite_focus=true for more details)? Thanks!

Hello, @suyunzzz I've downloaded the file which you updated yesterday. And I try to run the visualize code by default command:

python visualize.py

But I encounter some error about:

File "visualize.py", line 360, in
outputs = model(inputs)
ValueError: Expected more than 1 value per channel when training, got input size torch.Size([1, 84])

The parse argument is:

Model: SemanticKITTI_val_SPVNAS@65GMACs (default)
Velodyne_dir: sample_data(default)
visualize_backend: open3d(default)

Do you know how to solve this problem? Hope you can give me some advise. Thanks a lot!! 谢谢！

@QuasarsZ, could you please double-check the input size: inputs.F.shape?

Hello, @zhijian-liu. Thanks for your response.

I run the visualize code with:

python visualize.py --velodyne-dir ./dataset/semantic-kitti/00/velodyne/

And the input size is:

torch.Size([91852, 4])

Is my velodyne-dir set incorrectly?

Hello, @zhijian-liu. Thanks for your response.

I run the visualize code with:

python visualize.py --velodyne-dir ./dataset/semantic-kitti/00/velodyne/

And the input size is:

torch.Size([91852, 4])

Is my velodyne-dir set incorrectly?

Does it work if you use a original visualize.py?

Btw, could you also reformat the code according to pre-commit (see https://github.com/mit-han-lab/spvnas/runs/6327544860?check_suite_focus=true for more details)? Thanks!
hello, zhijian,
I am not sure that is need format code manually? or automatic?🤣

Hi, @suyunzzz. Thank's for your reply.

Run original visualize.py will get another error. (#90)

Then, I only modify this:

inds, labels, inverse_map = sparse_quantize(pc_,
feat_,
voxel_size,
return_index=True,
return_inverse=True)

to

coords_, inds, inverse_map = sparse_quantize(pc_,
return_index=True,
return_inverse=True)

And I will get error message about:

File "visualize.py", line 360, in
outputs = model(inputs)
ValueError: Expected more than 1 value per channel when training, got input size torch.Size([1, 84])

@suyunzzz To use precommit,

pip install pre-commit
pre-commit install
pre-commit run -a

It should reformat the code and then format the code before every commit.

@suyunzzz To use precommit,

pip install pre-commit
pre-commit install
pre-commit run -a

It should reformat the code and then format the code before every commit.

thanks, it seems work😄