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Ravana

B
B tier on AI Face Swap ToolsScore 7.0 · #7 of 57
Android app
Not listed
Free plan
Yes
Runs on
Linux, Mac, self-hosted, Windows
github.com
The Ravana homepage
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Summary

Ravana is an open-source Python SDK for swapping faces in images, video, and webcam feeds. It supports the HyperSwap and InSwapper models, with restoration options including GFPGAN, GPEN, CodeFormer, RestoreFormer++, and OpenCV. For real-time use, it can detect faces every set number of frames, track a region of interest, skip heavy restoration, and display a webcam FPS HUD. Face selection options include all, largest, first, index, and pose; the project also lists ArcFace identity and sharpness metrics. ONNX Runtime can use CUDA, AMD DirectML, or CPU, and its automatic device setting selects among them. An optional PySide6 desktop app adds drag-and-drop, batch processing, webcam support, scoring, video playback, and result saving. The README documents Python installation and a one-folder Windows executable build. The software is MIT-licensed, though downloaded model weights may have separate licenses that should be checked before commercial use. The project recommends consent-based creative uses and offers optional invisible DCT watermarking for provenance.

Who it is for

Ravana is aimed at developers who need a face-swap SDK across images, video, or webcam. Its optional desktop interface may also suit users who prefer batch processing and playback controls.

What is good

  • Supports images, video, and webcam
  • Offers multiple face-swap models and restoration options
  • ONNX Runtime supports CUDA, DirectML, or CPU
  • Optional GUI includes batch processing and video playback
  • Optional DCT watermarking supports provenance

What to know first

  • Third-party model licenses apply to downloaded weights
  • README cautions against non-consensual deepfakes, impersonation, and fraud

Verdict

Ravana offers a broad set of face-swap, restoration, and real-time controls in an open-source Python package. Review model licenses before commercial use, and follow the project’s consent guidance.

Ravana plans and pricing

All plans
Open-source Free MIT-licensed software; third-party model licenses apply to downloaded weights github.com · 4 Oct 2026

Compared on AI face swap tools

Video face swap
Yesgithub.com
Multiple faces
Yesgithub.com

Facts

Product
Ravana is an open-source Python face-swap SDK for images, video, and webcam.github.com · 4 Oct 2026
Face-swap models
It supports HyperSwap and InSwapper face-swap models.github.com · 4 Oct 2026
Enhancement
Listed restoration options include GFPGAN, GPEN, CodeFormer, RestoreFormer++, and OpenCV.github.com · 4 Oct 2026
Real-time features
Its real-time mode supports detection every N frames, ROI tracking, skipping heavy restoration, and a webcam FPS HUD.github.com · 4 Oct 2026
Face selection and metrics
Face selection includes all, largest, first, index, and pose, and the project lists ArcFace identity and sharpness metrics.github.com · 4 Oct 2026
Hardware support
ONNX Runtime can use CUDA, AMD DirectML, or CPU, and the automatic device setting selects among them.github.com · 4 Oct 2026
Desktop app
An optional PySide6 desktop GUI supports drag-and-drop, batch processing, webcam, scoring, video playback, and saving results.github.com · 4 Oct 2026
Distribution
The README documents Python installation and a Windows one-folder executable build.github.com · 4 Oct 2026
Intended users
The package metadata lists developers as its intended audience.github.com · 4 Oct 2026
Ethical use
The README recommends use for entertainment, VFX, privacy, and creative work with consent, and says not to use it for non-consensual deepfakes, impersonation, or fraud.github.com · 4 Oct 2026
Provenance
Optional invisible DCT watermarking is available for provenance.github.com · 4 Oct 2026
Third-party licensing
The README says third-party model licenses apply to downloaded weights and should be reviewed before commercial use.github.com · 4 Oct 2026
Support channel
The repository links to GitHub Issues for reporting or discussing issues.github.com · 4 Oct 2026

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