RandLA-Net-pytorch
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.npy vs .ply
Question about Semantic3d data preparation. Why are we converting point clouds to .npy instead of .ply format? Is this more convenient when using PyTorch? faster to read? I have seen that the TF implementation of RandLa is using the ply format. Thank you