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Installing and setting up this DFL fork

Wyverex-GR6 edited this page Sep 3, 2022 · 25 revisions

Please note: This article is written with Windows 10/11 in mind. While it is possible to run DFL on Linux, that will not be covered in this article.


Installing and updating the MVE-DFL fork is easiest via Git.
If you don't already have it, it is recommended you install Git for Windows.
You do not need to know (almost) anything about Git itself, it will be enough to copy the commands from this article.


Additional .bat files

It is recommended you download and extract the additional .bat files that make it easier to use some of the new functionality of this fork.
You can download them from here: DeepFaceLab-bat_files.zip
And then simply extract them in your main DFL directory, next to your existing .bat files.



Fresh DFL installation

First visit https://github.com/iperov/DeepFaceLab, and use one of the available options (torrent, or direct download from Mega.nz or Yandex.ru) to download DFL.

Make sure to download the build appropriate for your hardware:

  • DeepFaceLab NVIDIA RTX 3000 series build - for Nvidia 3000 series GPUs (uses CUDA)
  • DeepFaceLab NVIDIA up to RTX 2080 TI build - for Nvidia GPUs that support CUDA, and are not from series 3000. This includes series 2000, 1600, 1000, and 900
  • DeepFaceLab DirectX 12 build - for AMD, Intel, or Nvidia GPUs that fully support DX12. This includes AMD Radeon R5, R7, R9 200 and newer, Intel HD Graphics 500 and newer, and some older Nvidia GPUs

CUDA-based builds will provide better performance than DX12 build


Secondly, run the downloaded executable file, or use your archive application of choice (ie 7-zip) to extract the content.

It is recommended you avoid any spaces in the path to the directory where you extract DFL
It is also recommended you put DFL on an SSD, if possible


Inside your DFL directory you should find:

  • directory called _internal
  • directory called workspace
  • a lot of different .bat files
  • and a changelog.html

Depending on which build you downloaded and extracted, your DFL directory will look something like this:
DFL_directory_structure


You can now continue to Installing the MVE-DFL fork with existing DFL installation.



Installing the MVE-DFL fork with an existing DFL installation

If you already have DFL installed and set up, there's only a few steps to do to start using this fork.

Installing with Git - recommended

This is the recommended option, as it will make updating easier as well.

  1. go to your existing DFL directory and open _internal, you should see something like this:
    _internal
  2. either rename DeepFaceLab, for example into DeepFaceLab_old so you keep a copy if you run into problems (recommended) or delete it
  3. open Command Prompt (Win+R > cmd) and navigate to your DFL\_internal directory, something like this:
    image_2022-05-26_174700357
  4. type and run setenv
  5. type and run git clone https://github.com/MachineEditor/DeepFaceLab
  6. after it is done, type and run cd DeepFaceLab
  7. type and run python -m pip install -r requirements-cuda.txt

After everything is done you should be able to see a new DeepFaceLab directory inside your _internal, something like this:
image_2022-05-26_174155334
And if you did not encounter any errors, congratulations, you are done! :)


Installing without Git

Please note: you will not be able to use Git to update this kind of install.

Before going over the steps to set everything up, first go to the MVE-DFL fork's project page and then click Code > Download ZIP as in this picture:
download_project_zip

The file offered for download should be called DeepFaceLab-master.zip

Next follow these steps:

  1. go to your existing DFL directory and open _internal, you should see something like this:
    _internal
  2. either rename DeepFaceLab, for example into DeepFaceLab_old so you keep a copy if you run into problems (recommended) or delete it
  3. extract the downloaded .zip file here (in _internal)
  4. rename extracted directory from DeepFaceLab-master into DeepFaceLab
  5. double click python_console.bat, after which you should see something like this
    python_console
  6. now type and run cd ..\DeepFaceLab
  7. type and run python -m pip install -r requirements-cuda.txt

And you're done now :)



Updating the MVE-DFL fork's files

The easiest way to update is via the git pull command.

Updating if you used Git to install

  1. open Command Prompt and navigate to long_DFL_directory_name\_internal\DeepFaceLab
  2. type and run git pull

If you did not encounter any errors, congratulations, you are done! :)

Updating if you downloaded the zip and did not use Git

You will need to download the latest full project's zip file and extract it. Follow the steps 1-3 from Installing without Git