Awesome GitHub RepositoriesFace Swapping

Deep-Live-Cam is a generative video transformation tool designed for real-time facial manipulation and cinematic enhancement. It functions as a local-first AI runtime, performing all media processing directly on the user's hardware to ensure complete data privacy without external network dependencies. By utilizing a high-performance processing pipeline, the application enables live face swapping and interactive video modifications during active streaming sessions or on pre-recorded media. The system distinguishes itself through a hardware-abstraction execution layer that dynamically routes co

Faceswap is a comprehensive framework for automated media manipulation and neural face synthesis. It provides a modular pipeline that manages the entire lifecycle of facial feature extraction, deep learning model training, and image conversion. By coordinating complex computer vision workflows, the system enables users to map facial identities between source and destination datasets while maintaining structural alignment and lighting consistency across video frames. The project distinguishes itself through a highly extensible plugin-based architecture that handles hardware-accelerated process

Facefusion is a modular framework designed for automated image and video manipulation, specializing in tasks such as face swapping, enhancement, and restoration. It functions as a computer vision processing pipeline that chains independent machine learning modules to perform complex transformations, including facial animation, age modification, and lip synchronization. The system is built to handle both real-time interactive feeds and large-scale batch processing tasks. The platform distinguishes itself through a highly extensible architecture that supports custom processing modules and inter

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

DeOldify is a deep learning system and a set of pre-trained computer vision models designed to apply realistic colors to grayscale photographs and video footage. It functions as a neural media restoration tool that uses trained networks to estimate original hues for black-and-white media and remove glitches and artifacts from aged images and film. The project employs a NoGAN colorization technique that removes the GAN discriminator during training to prevent artifacts and avoid over-saturation of pixels. For cinematic sequences, it applies temporal frame consistency to maintain color stabilit

Style2paints is a deep learning image processor designed for the automated colorization of grayscale line art. It functions as a generative style transfer engine that maps artistic color palettes and textures onto monochrome sketches, allowing users to transform black and white drawings into finished illustrations through neural network inference. The system distinguishes itself by incorporating user-provided color guidance and style references to influence the final output. It utilizes coordinate-mapped color points and hint-driven optimization to ensure that specific colors are applied prec

Paper2gui is a multi-modal AI toolkit and model GUI wrapper designed to deploy and run various artificial intelligence models through a visual interface. Its primary purpose is to provide a way to execute complex AI research papers and models without requiring manual software installation or coding. The project distinguishes itself by using a wrapper-based model interface that abstracts command line arguments into visual input fields, utilizing template-driven UI generation to create parameter sliders and forms based on the specific requirements of the underlying model. It includes a centrali

PaddleGAN is a generative AI framework and deep learning computer vision library built on the PaddlePaddle framework. It serves as a toolkit for image and video synthesis, providing a collection of generative adversarial network implementations for creating synthetic visual content. The library focuses on advanced synthesis capabilities, including the generation of talking heads through lip motion synchronization and the creation of synthetic videos via motion transfer from driving sequences. It provides tools for domain-to-domain translation, allowing for image style transfer and the transfo

Rope ist eine grafische Benutzeroberfläche für den Austausch von Gesichtern in Bildern und Videos. Es fungiert als Deepfake-Videoeditor und Image-Face-Swapper, der vortrainierte Deep-Learning-Modelle nutzt, um Identitäten in visuellen Medien zu ersetzen. Das Tool umfasst spezialisierte Funktionen für die KI-Videopostproduktion, wie z. B. okklusionsbewusstes Blending zur Handhabung von Vordergrundobjekten und Mouth-Parsing-Verfeinerung zur Anpassung von Gesichtsausdrücken. Es dient zudem als KI-Tool zur Gesichtsrestaurierung und nutzt saliency-basierte Wiederherstellung, um Klarheit und Schärfe in ausgetauschten Gesichtsbereichen zurückzugewinnen. Die Software bietet eine Pipeline für die Manipulation visueller Medien, die den gesamten Prozess vom initialen Gesichtsaustausch bis zur finalen digitalen Restaurierung umfasst.

SimSwap is a deep learning face swapping framework and computer vision media processor built with PyTorch. It functions as an image synthesis tool designed to replace a person's identity in images and videos with a target face using a single trained model. The system operates as a video identity replacement tool that swaps identities across frames while preserving the original expressions and lighting of the source media. It enables digital identity manipulation and the production of synthetic media through automated facial feature mapping. The framework supports both the application of trai

PRNet ist eine Python-Bibliothek für die 3D-Gesichtsrekonstruktion. Sie verwendet ein Deep-Learning-Regressionsmodell, um aus einem einzelnen 2D-Eingabebild die 3D-Gesichtsgeometrie und Vertex-Farben vorherzusagen und ein texturiertes Mesh zu generieren. Das Projekt bietet Werkzeuge für digitales Face-Swapping, mit denen ein Zielgesicht durch ein neues Bild ersetzt und Texturen an die ursprüngliche Pose angepasst werden können. Es enthält zudem ein Framework für den Austausch und das Blending von Gesichtstexturen, um sie an spezifische 3D-Posen anzupassen. Zusätzliche Funktionen umfassen die Gesichtsanalyse, einschließlich der Erkennung und Ausrichtung von Gesichtsmerkmalen sowie der Schätzung der Kopfhaltung und Kameramatrizen.

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 s

lite.ai.toolkit ist ein C++ Computer-Vision-Toolkit für Edge-KI-Deployments. Es ermöglicht die Ausführung vortrainierter Modelle für Objekterkennung, Bildklassifizierung und Segmentierung auf ressourcenbeschränkten Geräten. Das Projekt bietet eine Multi-Backend-Inferenz-Engine, die die ONNX-Model-Runtime unterstützt, wodurch KI-Modelle auf verschiedenen Hardware-Zielen ausgeführt werden können. Es enthält eine GPU-beschleunigte Pipeline speziell für NVIDIA-Hardware, um Latenzen zu reduzieren und die Verarbeitungsgeschwindigkeit zu erhöhen. Das Toolkit deckt ein breites Spektrum an Funktionen zur Gesichtsanalyse ab, einschließlich Emotionserkennung, Geschlechts- und Altersschätzung sowie Kopfhaltungserkennung. Es bietet zudem Tools für die Gesichtserkennung durch die Extraktion von Feature-Embeddings und die Berechnung der Kosinus-Ähnlichkeit zur Identitätsprüfung. Zusätzliche Funktionen umfassen Image-Matting zur Vordergrundisolierung, Kolorierung von Graustufenbildern und künstlerischen Style-Transfer.