explaingit

bannedbook/faceswap

Analysis updated 2026-07-30 · repo last pushed 2019-09-08

1Audience · developerComplexity · 4/5DormantSetup · hard

TLDR

Free open-source tool that swaps faces in photos and videos using AI. It extracts faces, trains a model to map one face onto another, and applies the result to target media.

Mindmap

mindmap
  root((repo))
    What it does
      Swap faces in media
      Train AI face models
      GUI and command line
    Tech stack
      Python
      CUDA NVIDIA GPU
      AMD partial support
    Use cases
      Parody videos
      Learning AI techniques
      VFX and filmmaking
    Audience
      Hobbyists and learners
      VFX artists
      Curious beginners
    Ethics
      No nonconsensual use
      Education and commentary
      Zero tolerance policy

Code map

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What do people build with it?

USE CASE 1

Swap a friend's face into a movie scene for a parody video.

USE CASE 2

Learn how deepfake AI works by training a face-swap model from scratch.

USE CASE 3

Create VFX shots that replace one actor's face with another in a film project.

USE CASE 4

Experiment with reusing an existing trained model to speed up face swapping on a new person.

What is it built with?

PythonCUDANVIDIA GPUAMD GPU

How does it compare?

bannedbook/faceswap0xallam/posthog0xallam/search-engine
Stars111
LanguagePythonC++
Last pushed2019-09-082026-03-262023-08-23
MaintenanceDormantMaintainedDormant
Setup difficultyhardmoderatehard
Complexity4/53/53/5
Audiencedeveloperpm founderdeveloper

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · hard Time to first run · 1h+

Requires a modern NVIDIA GPU with CUDA support for reasonable performance, and training a model from scratch can take significant time.

The README does not specify the license, so usage rights are unclear.

In plain English

FaceSwap is a free, open-source tool that lets you replace one person's face with another in photos and videos. You might use it to swap a friend's face into a movie scene, create a parody video, or experiment with AI techniques as a learning exercise. The project bills itself as "deepfakes software for all," meaning it aims to make this technology accessible to anyone with a decent computer, not just researchers with advanced math degrees. The workflow has three main steps. First, you collect a set of photos or video frames containing the faces you want to use. The tool extracts and isolates those faces from the surrounding images. Second, you train a model, essentially, the software studies the two faces and learns how to map one onto the other through repetition and adjustment. Third, you run the conversion, which applies the trained model to your target images or video, producing the final swapped result. There's also a graphical interface if you prefer buttons to command-line instructions. The project runs on Windows, Linux, and macOS, but you'll want a modern graphics card with CUDA support (typically an NVIDIA GPU) for reasonable performance. AMD cards get partial support. The README notes that reusing an existing model trains much faster than starting from scratch, and if you don't have enough training data, you can start with someone who looks similar and then switch. Who would use this? Hobbyists learning about machine learning, VFX artists exploring new techniques, filmmakers working on projects that require face replacement, or anyone curious about how deepfakes actually work under the hood. The developers stress that the tool is meant for ethical uses, commentary, education, movies, experimentation, and explicitly prohibit using it for nonconsensual content or deception. One notable aspect is the project's framing. The README spends considerable space on a "manifesto" defending the technology, arguing that deepfakes opened up AI learning to people without PhDs and that the media focus on misuse overshadows legitimate applications. The developers take a zero-tolerance stance on unethical use, though the software itself is freely available.

Copy-paste prompts

Prompt 1
Help me install FaceSwap on Windows with an NVIDIA GPU and walk me through the three-step workflow of extracting faces, training a model, and converting a video.
Prompt 2
I want to use FaceSwap to create a parody video. Guide me through collecting training photos, extracting faces, and training the model with a GUI interface.
Prompt 3
I have an existing trained FaceSwap model. How do I reuse it to swap a new person's face, and what does the README say about starting with someone who looks similar?
Prompt 4
Walk me through the ethical guidelines in the FaceSwap README and what uses are prohibited, so I can make sure my project complies with their zero-tolerance policy.

Frequently asked questions

What is faceswap?

Free open-source tool that swaps faces in photos and videos using AI. It extracts faces, trains a model to map one face onto another, and applies the result to target media.

Is faceswap actively maintained?

Dormant — no commits in 2+ years (last push 2019-09-08).

What license does faceswap use?

The README does not specify the license, so usage rights are unclear.

How hard is faceswap to set up?

Setup difficulty is rated hard, with roughly 1h+ to a first successful run.

Who is faceswap for?

Mainly developer.

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