pointconv_pytorch
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how can i train xyz points without normal?
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?
Take a look at the source.
@DylanWusee there is a bug in the released code. Signature of the classifier is wrong.
我也遇到了这个问题,请问您解决了吗
Where can I see the source ?
I have the same problem
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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