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Env.md

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Environment

A single RTX 3090 graphics card is enough to run the code.

  1. Create an virtual environment using conda:
conda create -n cora python=3.9
conda activate cora
  1. Install pytorch and torchvision. Here we use cuda 11.6 as an example. For other cuda version, please find the corresponding whl file path at here.
pip install -i https://pypi.tuna.tsinghua.edu.cn/simple \
    https://download.pytorch.org/whl/cu116/torch-1.13.1%2Bcu116-cp39-cp39-linux_x86_64.whl \
    https://download.pytorch.org/whl/cu116/torchvision-0.14.1%2Bcu116-cp39-cp39-linux_x86_64.whl
  1. Install pytorch3d. Again, if you want to install pytorch3d in other cuda version, please find the corresponding file path at here.
conda install https://anaconda.org/pytorch3d/pytorch3d/0.7.4/download/linux-64/pytorch3d-0.7.4-py39_cu116_pyt1131.tar.bz2
  1. Install tinycudann:
pip install git+https://github.com/NVlabs/tiny-cuda-nn/#subdirectory=bindings/torch
  1. Install other libs:
pip install nerfacc==0.3.1 \
    moviepy \
    kornia \
    pyyaml \
    lpips \
    tensorboard \
    scikit-learn \
    PyMCubes==0.1.2 \
    trimesh \
    pymeshlab \
    fake-bpy-module-3.1 \
    networks \
    scikit-image==0.19.1 \
    fvcore \
    iopath \
    pymeshfix \
    pyfacer \
    av \
    pims \
    timm \
    face_alignment \
    mediapipe \
    opencv-python==4.5.2.52 \
    opencv-python-headless==4.5.2.52 \
    chumpy \
    numpy==1.22.4
  1. Install Blender for UV unwrap:
cd blender

# Download Blender
wget https://mirror.clarkson.edu/blender/release/Blender3.1/blender-3.1.0-linux-x64.tar.xz or download from https://cloud.tsinghua.edu.cn/f/44a204b6c5824133ad92/?dl=1


# extract files
tar -xvf blender-3.1.0-linux-x64.tar.xz