Notice: This repository is not operated or maintained by /u/deepfakes. Please read the explanation below for details.
Faceswap is a tool that utilizes deep learning to recognize and swap faces in pictures and videos.
The project has multiple entry points. You will have to:
- Gather photos (or use the one provided in the training data provided below)
- Extract faces from your raw photos
- Train a model on your photos (or use the one provided in the training data provided below)
- Convert your sources with the model
From your setup folder, run python faceswap.py extract
. This will take photos from src
folder and extract faces into extract
folder.
From your setup folder, run python faceswap.py train
. This will take photos from two folders containing pictures of both faces and train a model that will be saved inside the models
folder.
From your setup folder, run python faceswap.py convert
. This will take photos from original
folder and apply new faces into modified
folder.
-h
/--help
options with a arguments that they will accept. You're smart, you can figure out how this works, right?!Note: there is no conversion for video yet. You can use MJPG to convert video into photos, process images, and convert images back to video
Whole project with training images and trained model (~300MB):
https://anonfile.com/p7w3m0d5be/face-swap.zip or click here to download
Clone the repo and setup you environment. There is a Dockerfile that should kickstart you. Otherwise you can setup things manually, see in the Dockerfiles for dependencies.
Check out ../blob/master/INSTALL.md and ../blob/master/USAGE.md for basic information on how to configure virtualenv and use the program.
You also need a modern GPU with CUDA support for best performance
Some tips:
Reusing existing models will train much faster than starting from nothing.
If there is not enough training data, start with someone who looks similar, then switch the data.
If you prefer using Docker, You can start the project with:
- Build: docker build -t deepfakes .
- Run: docker run --rm --name deepfakes -v [src_folder]:/srv -it deepfakes bash
. bash
can be replaced by your command line
Note that the Dockerfile does not have all good requirments, so it will fail on some python 3 commands.
Also note that it does not have a GUI output, so the train.py will fail on showing image. You can comment this, or save it as a file.
Sorry no time for that
It is a community repository for active users.
The joshua-wu repo seems not active. Simple bugs like missing http:// in front of url has not been solved since days.
This is a friendly typosquat, and it is fully dedicated to the project. If /u/deepfakes wants to take over this repo/user and drive the project, he is welcomed to do so (Raise an issue, and he will be contacted on Reddit). Please do not send /u/deepfakes messages for help with the code you find here.
It's complicated. Here's a good video that makes the process understandable:
Here's a slightly more in depth video that tries to explain the basic functioning of a neural network:
tl;dr: training data + trial and error