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Installation

System Dependencies

  • Linux (test on Ubuntu 16.04 and 18.04) or Windows (test on windows 10).
  • CUDA 10.1, 10.2, 11.0, or 11.1 with Nvidia GPU. Set the path of $CUDA_HOME, and add the $CUDA_HOME/bin into the system path.
  • gcc in Linux (supports C++14 and tests on 7.5+ ) or MSVC++ (Visual Studio 2019, supports C++14) in Windows.
  • ffmpeg (ffprobe) test on 4.3.1+.
  • Git test on 2.16.2+

Linux (test on Ubuntu 16.04 and 18.04)

  • Download the CUDA >= 10.1, and set the CUDA_HOME into the system environments. This is important. Since in the next setup stage, it needs to get the CUDA_HOME For example,

    export CUDA_HOME=/usr/local/cuda-10.1
    export PATH=${CUDA_HOME}/bin:$PATH
    export LD_LIBRARY_PATH=${CUDA_HOME}/lib64:$LD_LIBRARY_PATH 
  • Make sure that the gcc support C++14. Since in the next setup stage, it needs to compile some c++ codes from sources. Here, we use gcc 7.5.

  • It needs ffmpeg. If you have not installed it yet, you can run the followings

    apt-get install ffmpeg 
  • It needs Git. If you have not installed it yet, you can run the followings

    apt-get install git 

Windows 10

Python Dependencies

Setup Python

Using Python 3.6+. You can use Anaconda Python 3.6+, or the native Python 3.6+. Whatever Python you have used, be sure to create a virtual environment firstly.

  • For Anaconda Python

    conda create -n venv python=3.6.6
    conda activate venv
    
  • For Native Python

    pip install virtualenv
    virtualenv  venv
    source venv/bin/activate
    

Requirements and Install iPERCore

Install iPERCore by running the follows

python setup.py develop

**If the GPU device is RTX30+ (RTX 3060, RTX 3060ti, RTX 3070, RTX 3080, RTX 3090 ...), run the follows **

torch=1.8.1 python setup.py develop

It might takes 5-10 min. When you see Finished processing dependencies for iPERCore==0.1.1 in the console screen, it means you have installed the iPERCore successfully.

The details of requirements. Again be sure you have used a virtual environment to avoid the conflicts with your own python site-packages.

Download checkpoints and samples

Run the followings scripts to download checkpoints and samples (recommend).

sh assets/download.sh

Or manually download the checkpoints and samples (option).

If the above links are broken, try to download the "assets/checkpoints" and "assets/samples.zip" from the following available links:

Unzip checkpoints.zip and samples.zip, and move them to the ./assets directory.