#66th of 10 in Image and video

faceswap

Python tool that trains neural models to swap faces in images and video

Stars
57.6k
License
GPL-3.0
Last commit
Aug 2026
Last release
Dec 2025
Language
Python
Stars, last 29 weeks+2,966
24 Mar 2026: 54,601 stars31 Mar 2026: 54,658 stars7 Apr 2026: 54,717 stars14 Apr 2026: 54,764 stars21 Apr 2026: 54,811 stars28 Apr 2026: 54,841 stars5 May 2026: 54,870 stars12 May 2026: 54,904 stars19 May 2026: 54,928 stars26 May 2026: 54,951 stars2 Jun 2026: 54,976 stars9 Jun 2026: 55,005 stars16 Jun 2026: 55,037 stars23 Jun 2026: 55,067 stars30 Jun 2026: 55,097 stars7 Jul 2026: 55,115 stars14 Jul 2026: 55,141 stars21 Jul 2026: 55,160 stars28 Jul 2026: 55,745 stars4 Aug 2026: 57,070 stars11 Aug 2026: 57,281 stars18 Aug 2026: 57,334 stars25 Aug 2026: 57,373 stars1 Sept 2026: 57,408 stars8 Sept 2026: 57,437 stars15 Sept 2026: 57,463 stars22 Sept 2026: 57,486 stars29 Sept 2026: 57,514 stars6 Oct 2026: 57,534 stars13 Oct 2026: 57,567 stars

54,601 on 24 Mar 202657,567 on 13 Oct 2026

From GitHub's daily star counts.

Checked on GitHub.

Overview

FaceSwap is a Python program with three stages run through `faceswap.py`: extract faces from photos or video frames, train a model on two sets of faces, and convert source media with the trained model. It ships a Tkinter-style GUI (`faceswap.py gui`) alongside the CLI, and includes models such as Villain and Phaze-A. It runs on Windows, Linux and macOS, with CUDA GPUs recommended and some AMD support via ROCm on Linux.

Who it is for: Hobbyists and VFX users training face-swap models on their own GPU

Strengths

  • Covers the full workflow: extract, train and convert, via CLI or GUI
  • Multiple model architectures named in the README, including Villain, Phaze-A, DFL-H128 and DFaker
  • Runs on Windows, Linux and macOS; AMD GPUs supported via ROCm on Linux
  • Existing models can be reused to shorten training on new faces

Weaknesses

  • Training requires a modern CUDA GPU for acceptable speed; exact VRAM needs are unknown
  • No Docker or compose setup in the repo
  • Setup problems are directed to the forum and Discord, not GitHub issues
  • Manual workflow: gathering and curating face data is left to the user

What it needs

  • GPU required
  • Needs CUDA, ROCm (AMD, Linux), ffmpeg (optional)
  • Models: Villain, Phaze-A, DFL-H128, DFaker, Unbalanced

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