DeepFaceLab Guide for Linux Users

Prerequisite: You need CUDA enabled GPU.

Note: This method installs DFL on Centos 7/8 or Ubuntu 18.04 and provides an option to use Anaconda
    To install CentOS, refer here
    To install Ubuntu, [coming soon]

The directory structure is important.
This is how the project tree will look like:

DeepFaceLab_NVIDIA_Linux
|-- _internal               
|   |-- DeepFaceLab         # Created via git clone command (Step #2)
|   |-- pretrain_CelebA     # Manually copied after extracting .EXE (Step #3)
|   `-- pretrain_Quick96    # Manually copied after extracting .EXE (Step #3)
|-- install_script          # Created via git clone command (Step #0)
|-- scripts                 # Created via git clone command (Step #0)
`-- workspace               # Created through one of the scripts in /scripts

Step #0: Preparation

Clone this repository

git clone https://github.com/jwchoi09/DeepFaceLab_NVIDIA_Linux.git
cd DeepFaceLab_NVIDIA_Linux

Install NVIDIA driver and Dependencies
Navigate to DeepFaceLab_NVIDIA_Linux/install_script directory and run:

1. CentOS:

   bash 1_CentOS_install_dependencies.sh

2. Ubuntu:

   bash 1_Ubuntu_install_dependencies.sh

Step #1: Setup Environment

1. on Anaconda: (recommended)

   Install Anaconda

   URL #4: https://www.anaconda.com/distribution/#linux
   URL #5: https://docs.anaconda.com/anaconda/install/linux/

   Note: Download Python 3.7 version (at the time of writing: 05/22/2020)
   Through the terminal, locate to Anaconda download destination and run the following:

   bash Anaconda3-2020.02-Linux-x86_64.sh

   The installer prompts "In order to continue the installation process, please review the license agreement."
   Click Enter to view license terms.
   Scroll to the bottom of the license terms and enter "Yes" to agree.
   Accept the default install location.
   Type "yes" to the prompt, "Do you wish the installer to initialize Anaconda3 by running conda init?"
   Close and open your terminal window for the installation to take effect, or you can enter the command:

   source ~/.bashrc

   Create the DeepFaceLab environment with the following libraries in the terminal:

   conda create -n deepfacelab -c main python=3.6.8 cudnn=7.6.5 cudatoolkit=10.0.130

   Activate the environment

   conda activate deepfacelab

2. on system:

   Install python 3.6.8, cudnn 7.6.5, cudatoolkit 10.0.130

   1. CentOS:
   2. Ubuntu:

Install Python Dependencies

python3 -m pip install -r ./DeepFaceLab/requirements-cuda.txt  

Step #2: Install [or Update] DeepFaceLab

This step involves deleting the already existing DeepFaceLab directory from the _internal directory, and
cloning DeepFaceLab from the main repository to the _internal directory

sudo rm -rf DeepFaceLab
git clone https://github.com/iperov/DeepFaceLab.git

Step #3: Download CelebA Dataset and Quick96 Model

Download the latest NVIDIA build(.EXE) from the main repo for Windows
To download, refer to the Google Drive link provided in here: https://github.com/iperov/DeepFaceLab/
Extract the build.

7z x DeepFaceLab_NVIDIA_build_XX_XX_XXX.exe

Once the build has been extracted, there will be _internal directory.
From it, copy both pretrain_CelebA and pretrain_Quick96 to the directory DeepFaceLab_NVIDIA_Linux/_internal/

Step #4: Navigate to the scripts directory and begin using DeepFaceLab

(Further guide coming soon!)