Convert the point cloud "ply" to "npy"

[tuanho27]

Hi there,

Thanks for the great work.
I've tried to inference my own point cloud based on your 3D match pretrained model and network. But I met a problem that the weight asking for the input to be shaped at Nx7 while the point shape is just Nx3.

Even I took a look at the evaluation data loader (match3d_eval_loader.py), still confusing. I just wonder that how did you convert the point cloud from ply to npy? Because when I check the 3D_Match_eval_npy, it's already converted to shape Nx7.
And Is the surface_normal_len need for inference?

Thank you in advance,
Tuan

[lijx10]

Hi, The other 4 elements are surface normal (nx, ny, nz) and curvature (scalar). They are computed using PCL library. In fact, these 4 elements has almost no effect to the performance. You may simply train your own model using Nx3. Thanks. Best Regards Jiaxin Li tuanho27 <notifications@github.com> 于2021年1月10日周日 下午4:37写道：

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Hi there, Thanks for the great work. I've tried to inference my own point cloud based on your 3D match pretrained model and network. But I met a problem that the weight asking for the input to be shaped at Nx7 while the point shape is just Nx3. Even I took a look at the evaluation data loader (match3d_eval_loader.py), still confusing. I just wonder that how did you convert the point cloud from ply to npy? Because when I check the 3D_Match_eval_npy, it's already converted to shape Nx7. And Is the surface_normal_len need for inference? Thank you in advance, Tuan — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub <#24>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AC5G72PVP5ACA24H5MNVKCDSZFRNBANCNFSM4V4IALRA> .

-- 黎嘉信 Jiaxin LI PhD, National University of Singapore B.S., Tsinghua University Mobile: 65-9094 1909 / 86-15201519053 Email: lijx1992@gmail.com / jli@u.nus.edu <jli@nus.edu.sg>

[tuanho27]

Hi, thanks for the reply.

So, It seems that I cannot directly use the provided pretrained model to test my point cloud.
PCL is the great lib, but I may dig into it later. I think I will try to re-train the model without the 4 added elements if it does not very effective to the performance.

Regards,
Tuan