Skip to content

nick8592/AutoAvatar-Installation-Guide

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

7 Commits
 
 
 
 

Repository files navigation

AutoAvatar-Installation-Guide

DFaust Data Preparation

  • Create "DFaust" folder under <workspace_folder>.
cd <workspace_folder>
mkdir DFaust
  • Download SMPL+H parameters, gets "DFaust.tar.bz2".
    • Move "DFaust.tar.bz2" to <workspace_folder>/DFaust, and unzip to get folder DFaust_67/...
  • Download DFaust Scan Data, gets "50002.tar.xz".
    • Here use 50002 as example for the following steps.
    • Unzip "50002.tar.xz" to <workspace_folder>/DFaust, and gets folder scans/50002/...
  • Download SMPL model, gets "basicmodel_m_lbs_10_207_0_v1.0.0.pkl", "basicModel_f_lbs_10_207_0_v1.0.0.pkl".
    • Move "basicmodel_m_lbs_10_207_0_v1.0.0.pkl", "basicModel_f_lbs_10_207_0_v1.0.0.pkl" to <workspace_folder>/SMPL
  • Download SMPL meta data, gets "uv_info.npz", "smpl_resample_idxs.npz".
    • Move "uv_info.npz", "smpl_resample_idxs.npz" to <workspace_folder>/SMPL
  • Download SMPL+H, gets "smplh.tar.xz".
    • Move "smplh.tar.xz" to <workspace_folder>/SMPL, and unzip to get folder smplh/...
  • Download DMPLs, gets "dmpls.tar.xz".
    • Move "dmpls.tar.xz" to <workspace_folder>/SMPL, and unzip to get folder dmpls/...
  • Clone AutoAvatar to <workspace_folder>
cd <workspace_folder>
git clone https://github.com/facebookresearch/AutoAvatar.git
  • Create external folder under <workspace_folder>
cd <workspace_folder>
mkdir external
cd <workspace_folder>/external
git clone https://github.com/nghorbani/human_body_prior.git
  • Now we should have the folder structure as link.

Environment Setup

  • Install Anaconda or Miniconda. Then run the setup script.
cd <workspace_folder>/AutoAvatar
conda create -n AutoAvatar python=3.8
conda activate AutoAvatar
bash setup.sh
cd <workspace_folder>/external
cd human_body_prior
python setup.py develop

Data Preprocess

  • Run DFaust_generate.py to preprocess data.
  • Note that this may take a long time due to the mesh simplification.
  • Mesh simplification is to speed up data loading during training.
cd <workspace_folder>/AutoAvatar
export PYTHONPATH=<workspace_folder>/AutoAvatar
python data/DFaust_generate.py --ws_dir <workspace_folder>

About

Installation Guide for AutoAvatar

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published