Stressful Settings.

Dependencies

• Detectron2
  • python 3.7 >=
  • torch 1.8 >=
• scikit-learn == 0.22
  • it takes a while to set
  • pip: Cython
  • apt-get: gcc, g++
    • link
• official neural renderer is tensorflow version.

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Errors

“ImportError: libGL.so.1: cannot open shared object file: No such file or directory”

• apt-get update && apt-get install ffmpeg libsm6 libxext6 -y

ImportError: (‘Unable to load OpenGL library’, ‘OSMesa: cannot open shared object file: No such file or directory’, ‘OSMesa’, None)

• install OSMesa

AttributeError: ‘PosixPath’ object has no attribute ‘path’

• link
• link2
• PosixPath? When I print os.name, ‘posix’ returned.

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Docker

How to delete <none> docker images?

docker rmi $(docker images -f “dangling=true” -q)
After I tried this, every dockers are deleted.

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Installation

OpenPose

• Install guide link, link2
• I’m using Ubuntu server and don’t have GUI
• git clone regressively.
• …. I just download openpose docker image. docker pull d0ckaaa/openpose
• cmake ..
• make -j4nproc
• how to use: https://viso.ai/deep-learning/openpose/

OSMesa

• Try this. link
• Before try this,
  • apt-get install wget
  • apt-get install pkg-config
  • apt-get install libexpat1-dev
• i installed in /usr/local
• MESA_HOME=/usr/local (+/lib?)
• issues
  • https://redstarhong.tistory.com/98 GL? PyOpenGL?
  • update “/opt/conda/lib/python3.9/site-packages/OpenGL/platform/egl.py”
  • apt-get install libosmesa6-dev
  • if PyOpenGL is failed, clone git and reinstall PyOpenGL.

PHALP

I failed while using conda yml file because:

• First, I installed conda inside of a docker container to keep experiments going on.
  • when I tried to create conda env, it takes more than an hour to solve dependencies, but it still doesn’t finished.
• Then, I tried to install every commands on my own, neural renderer and cuda path problems occurred.
  • It was hard for me to find cuda path in conda env because someone said that each conda environment would only contain the parts of cuda
  • So I should export every paths of cuda related stuff, but when I searched cuda paths in my server computer, there are too many other settings, so I’m not sure what to add
• These are the reasons why I didn’t use conda

I use these commands sequentially. After that, demo works well on my docker container. Official PHALP’s colab pip output: phalp_colab.txt

! pip install pyrender
! pip install opencv-python
! pip install joblib
! pip install cython
! pip install scikit-learn==0.22
! pip install scikit-image
! pip install git+https://github.com/facebookresearch/detectron2.git
! pip install git+https://github.com/brjathu/pytube.git
! pip install git+https://github.com/brjathu/NMR.git
! pip install chumpy
! pip install ipython
! pip install gdown
! pip install dill
! pip install scenedetect[opencv]

But if you use v1.1, additional packages are needed.

• Install OSMesa
• pip install smplx submitit rich pyrootutils colordict
• pip install -e .
• install hydra-core again (Posix error)
• python scripts/demo.py video.source='“https://www.youtube.com/watch?v=xEH_5T9jMVU”'
  • I use osmesa, not egl