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how can i train xyz points without normal?

Open azizanajeeb opened this issue 4 years ago • 6 comments

when i train my dataset without normal i get and error: RuntimeError: Given groups=1, weight of size 64 6 1 1, expected input[32, 3, 32, 512] to have 6 channels, but got 3 channels instead is there a way i could resolve this?

azizanajeeb avatar Jan 29 '21 05:01 azizanajeeb

Take a look at the source.

@DylanWusee there is a bug in the released code. Signature of the classifier is wrong.

geyang avatar May 29 '21 19:05 geyang

我也遇到了这个问题,请问您解决了吗

chenyanjie519 avatar May 30 '21 08:05 chenyanjie519

Where can I see the source ?

chenyanjie519 avatar May 31 '21 11:05 chenyanjie519

I have the same problem

heexu976 avatar May 07 '22 10:05 heexu976

收到

294coder avatar May 07 '22 10:05 294coder

I encountered the same problem, reference (https://github.com/yanx27/Pointnet_Pointnet2_pytorch/) to the corresponding code to make the following changes, you can solve the problem of this channel.

Modify line 16 of the model/pointconv.py file: self.sa1 = PointConvDensitySetAbstraction(npoint=512, nsample=32, in_channel=feature_dim+3, mlp=[64, 64, 128], bandwidth = 0.1, group_all=False)

Modify in_channel=feature_dim+3 to in_channel=feature_dim. Then you can successfully process the data without normal vector.

@heexu976 @azizanajeeb @chenyanjie519

dhliubj avatar Jun 27 '22 18:06 dhliubj