awesome-repositories.com
Blog
MCP
awesome-repositories.com

Discover the best open-source repositories with AI-powered search.

ExploreCurated searchesOpen-source alternativesSelf-hosted softwareBlogSitemap
ProjectMCP serverAboutHow we rankPress
LegalPrivacyTerms
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
sensity-ai avatar

sensity-ai/dot

0
View on GitHub↗
4,529 stars·474 forks·Python·bsd-3-clause·17 views

Dot

Dot is a deep learning face swap tool used to replace faces in live video streams, recorded media, and static images. It functions as a deepfake media processor and real-time video manipulator that applies facial transformations through neural network mapping.

The system includes a virtual camera video injector that routes processed output into a system-level virtual device to simulate a physical hardware webcam. This allows generated video to be used within third-party video conferencing software.

The tool supports real-time source switching via keyboard inputs to toggle between different source images during active sessions. It utilizes a unified media pipeline to handle both live camera streams and pre-recorded files, processing frames in a continuous loop to minimize latency.

Features

  • Real-Time Face Swapping - Provides real-time identity replacement in live video feeds using deep learning models.
  • Face Swapping - Uses neural networks to analyze facial landmarks and map source textures onto target video streams.
  • Deepfake Generation - Implements high-fidelity identity replacement in video and image content using deep learning.
  • Face Swapping Tools - A deep learning application for replacing faces in live video streams, recorded media, and static images.
  • Live Video Manipulation - Changes visual elements and source images in a real-time video stream using keyboard triggers.
  • Face Swap Processing - Applies deep learning face-swapping transformations to static image files and pre-recorded video files.
  • Automated Processors - Provides an automated pipeline for applying face-swapping transformations to pre-recorded video files and image sets.
  • Real-Time Video Filtering - Applies low-latency facial transformations and source switching to live video streams.
  • Video Frame Processing - Processes video frames in a continuous loop to apply transformations with minimal latency for live output.
  • Virtual Camera Drivers - Provides a virtual camera device to route processed deepfake video into third-party conferencing software.
  • Agnostic Pipelines - Utilizes a unified media pipeline that standardizes data flow for both live camera streams and static files.
  • Source Image Toggles - Enables real-time toggling between different source images using keyboard inputs during active sessions.

Star history

Star history chart for sensity-ai/dotStar history chart for sensity-ai/dot

How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.

AI search

Explore more awesome repositories

Describe what you need in plain English — the AI ranks thousands of curated open-source projects by relevance.

Start searching with AI

Open-source alternatives to Dot

Similar open-source projects, ranked by how many features they share with Dot.
  • iperov/deepfacelabiperov avatar

    iperov/DeepFaceLab

    19,256View on GitHub↗

    DeepFaceLab is a deep learning software suite designed for face swapping and the creation of deepfake videos. It functions as a neural network image compositor that replaces human faces or entire heads in video files to produce synthetic media. The tool provides capabilities for digital facial manipulation, including the ability to modify the perceived age of people in video sequences. It uses automated pattern recognition to blend source faces onto target frames to create seamless visual composites. The system covers a broad technical surface including landmark-based face alignment, autoenc

    Python
    View on GitHub↗19,256
  • royshil/obs-backgroundremovalroyshil avatar

    royshil/obs-backgroundremoval

    4,120View on GitHub↗

    This project is a plugin for OBS Studio that uses neural networks to isolate subjects from backgrounds in real-time video streams. It functions as an AI video segmentation tool that predicts portrait masks to create virtual green-screen effects without the need for physical hardware. The software includes a real-time depth estimation filter that identifies scene depth to produce a blurred background while keeping the foreground subject in focus. It also provides low-light video enhancement to improve visibility and visual quality for portrait video captured in poorly lit environments. The pl

    C++background-segmentationcomputer-visionimage-segmentation
    View on GitHub↗4,120
  • iperov/deepfaceliveiperov avatar

    iperov/DeepFaceLive

    30,536View on GitHub↗

    DeepFaceLive is a desktop application designed for real-time facial replacement and animation within live video streams. By utilizing deep learning models, the software performs high-speed identity mapping and facial feature analysis to transform video content as it is captured. The engine relies on GPU-accelerated inference to execute these complex image manipulation tasks at interactive frame rates. The application distinguishes itself through a modular video processing pipeline that chains specialized tasks to maintain high throughput and low latency. It features a virtual camera streaming

    Pythondeepfakefaceswapmachine-learning
    View on GitHub↗30,536
  • steveseguin/vdo.ninjasteveseguin avatar

    steveseguin/vdo.ninja

    3,910View on GitHub↗

    VDO.Ninja is a low-latency peer-to-peer media routing service and video streaming platform designed to integrate remote audio and video feeds into professional production workflows. It functions as a WebRTC broadcast integration tool and studio controller, allowing for the direct transmission of high-definition media between publishers and viewers with minimal delay. The platform distinguishes itself through extensive protocol bridging, converting between WebRTC, WHIP, WHEP, SRT, and RTMP to ensure compatibility across diverse network environments and professional studio software. It includes

    JavaScriptlivelow-latencyninja
    View on GitHub↗3,910
See all 30 alternatives to Dot→

Frequently asked questions

What does sensity-ai/dot do?

Dot is a deep learning face swap tool used to replace faces in live video streams, recorded media, and static images. It functions as a deepfake media processor and real-time video manipulator that applies facial transformations through neural network mapping.

What are the main features of sensity-ai/dot?

The main features of sensity-ai/dot are: Real-Time Face Swapping, Face Swapping, Deepfake Generation, Face Swapping Tools, Live Video Manipulation, Face Swap Processing, Automated Processors, Real-Time Video Filtering.

What are some open-source alternatives to sensity-ai/dot?

Open-source alternatives to sensity-ai/dot include: iperov/deepfacelab — DeepFaceLab is a deep learning software suite designed for face swapping and the creation of deepfake videos. It… royshil/obs-backgroundremoval — This project is a plugin for OBS Studio that uses neural networks to isolate subjects from backgrounds in real-time… iperov/deepfacelive — DeepFaceLive is a desktop application designed for real-time facial replacement and animation within live video… steveseguin/vdo.ninja — VDO.Ninja is a low-latency peer-to-peer media routing service and video streaming platform designed to integrate… hillobar/rope — Rope is a graphical user interface for swapping faces in images and videos. It functions as a deepfake video editor… peterl1n/backgroundmattingv2 — BackgroundMattingV2 is a deep learning background matting tool and real-time image segmentation framework. It provides…