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Faceswap

Faceswap is a GPL-3.0-licensed Python application that uses deep learning to recognize and swap faces in images and videos. Its repository presents a workflow based on extraction, training and conversion, with a graphical user interface.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Faceswap — OpenViST project profile in Image & Video AI.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use Faceswap when you need a local, hands-on application for experimenting with face recognition and face replacement in images or videos, and can follow its installation documentation.

Who it is for

  • AI learners exploring deep-learning workflows
  • Python developers studying or extending face-swapping software
  • Visual-effects and film creators working on ethical projects
  • Researchers experimenting with face-recognition and face-swapping models

Documented uses

  • Recognize faces in images and videos
  • Train a face-swapping model within the documented workflow
  • Convert source material using a trained model
  • Experiment with deep-learning and face-processing techniques
  • Process image or video material through a graphical interface
Before you choose

Requirements & limits

The repository identifies Faceswap as public, open source and GPL-3.0 licensed. It describes support for Windows, Linux and macOS. The project instructs users to consult INSTALL.md before getting started.

  • The extract, train and convert stages provide a defined processing workflow.
  • The application is written in Python and released under GPL-3.0.
  • The repository describes a GUI as well as image and video processing.
  • Installation details should be checked in INSTALL.md before setup.
  • The project’s stated ethical guidance makes consent and transparent use central considerations.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Set up the documented Faceswap workflow

Prepare the Python application for its extract, train and convert workflow.

Before you start

  • A Windows, Linux or macOS system.
  • The Faceswap repository.
  • Review of the project’s INSTALL.md instructions.

Steps

  1. Open the Faceswap repository.

  2. Review INSTALL.md before getting started.

  3. Use the documented workflow stages: Extract, Train and Convert.

  4. Use the GUI described in the repository when working with the application.

Expected outcome

The project is prepared for the documented face-swapping workflow, subject to the installation instructions.

Guide limitations

  • The supplied material does not specify exact commands, dependency versions or hardware requirements.
  • This guide documents setup and workflow stages; it does not verify a successful local installation or completed swap.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
1 October 2026
Original website title
deepfakes/faceswap · Official homepage title · retained in its source language
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