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Prerequisites

Python Packages

We recommend using conda for environment setup. Please install PyTorch and PyTorch3D manually. Below is an example script installing PyTorch with CUDA 11.3 (please make sure the CUDA version matches your machine, as we will compile custom ops later):

conda create -n assembly python=3.8
conda activate assembly
# pytorch
conda install pytorch=1.10 torchvision torchaudio cudatoolkit=11.3 -c pytorch
# pytorch-lightning
conda install pytorch-lightning=1.6.2
# pytorch3d
conda install -c fvcore -c iopath -c conda-forge fvcore iopath
conda install pytorch3d -c pytorch3d

You can use nvcc --version to see the CUDA version of your machine. Note that the current code is only tested under PyTorch 1.10, and PyTorch 1.11 will fail due to changes to header files.

Finally, install other related packages and this package via:

pip install -e .

Custom Ops

Install custom CUDA ops for Chamfer distance and PointNet modules:

  1. Go to multi_part_assembly/utils/chamfer and run pip install -e .
  2. Go to multi_part_assembly/models/modules/encoder/pointnet2/pointnet2_ops_lib and run pip install -e .

If you meet any errors, make sure your PyTorch version <= 1.10.1 and your nvcc version is the same as the CUDA version that PyTorch is compiled for (cudatoolkit version from conda).

Data Preparation

The codebase currently supports two assembly datasets:

  • PartNet is a semantic assembly dataset, where each shape (furniture) is decomposed to semantically meaningful parts (e.g. chair legs, backs and arms). We adopt the pre-processed data provided by DGL. Please follow their instructions to download the data in .npy format.
  • Breaking-Bad is a geometric assembly dataset, where each shape breaks down to several fractures without clear semantics. Please follow their instructions to process the data. The main experiments are conducted on the everyday and artifact subsets. The other subset is very large (~900G) so you may exclude it.

After downloading and processing all the data, please modify the _C.data_dir key in the config files under configs/_base_/datasets.

Troubleshooting

Please refer to faq.md for a list of potential errors.