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LivePortrait

AI GitHub Repos#33AI Animation Tools#5Open source · Linux, Windows, macOS

LivePortrait is an open-source PyTorch implementation for efficient portrait animation. It brings portraits to life by animating them with stitching and retargeting control, supporting both human and animal subjects. The project offers inference scripts and a Gradio interface for easy use.

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LivePortrait is a powerful open-source project that enables efficient portrait animation, bringing static images and videos to life with remarkable realism. Developed by KlingAIResearch, this PyTorch implementation focuses on stitching and retargeting control to achieve high-quality animation results for both human and animal subjects. The project aims to provide an accessible tool for creators, researchers, and developers interested in advanced video generation and manipulation.

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At its core, LivePortrait utilizes sophisticated algorithms to animate facial expressions and movements based on a driving video or audio input. The system is designed to be efficient, allowing for fast inference and integration into various workflows. It supports a range of customization options, including image-driven mode, regional control, and precise portrait editing within its Gradio interface. The project also offers a dedicated animals mode, expanding its applicability beyond human portraits.

Getting started with LivePortrait involves cloning the repository, setting up the environment with necessary dependencies like FFmpeg and PyTorch (with CUDA support for NVIDIA GPUs), and downloading pretrained weights. The project provides clear instructions for installation on Linux, Windows, and macOS with Apple Silicon, detailing specific requirements for each platform. Inference can be performed via command-line scripts for both humans and animals, or through an intuitive Gradio web interface.

The value proposition of LivePortrait lies in its ability to democratize advanced portrait animation. By offering an open-source solution with comprehensive documentation and community support, it empowers users to create engaging animated content. The project's continuous updates, including new features like pose editing, audio-video concatenation, and motion template making, ensure it remains at the forefront of portrait animation technology. The inclusion of ethical considerations highlights the project's commitment to responsible AI development.

LivePortrait is an invaluable resource for digital artists, content creators, researchers in computer vision and AI, and developers looking to integrate sophisticated animation capabilities into their applications. Its flexibility and performance make it suitable for a wide array of creative projects, from generating realistic talking avatars to animating pets in videos.

  • CategoryAI Animation Tools
  • Pricing ModelOpen source
  • DeploymentSelf-hosted
  • PlatformsLinux, Windows, macOS

  • Efficient portrait animation with stitching and retargeting control

  • Supports animation for both human and animal subjects

  • Image-driven and video-driven animation modes

  • Regional control for precise animation adjustments

  • Gradio interface for user-friendly interaction

  • Windows one-click installer available

  • macOS support for Apple Silicon (Humans mode)

  • Audio and video concatenating capabilities

  • Motion template making for privacy and speed

  • Pose editing for source portraits

  • Real-time preview options in community-developed tools

  1. Clone the repository: git clone https://github.com/KlingTeam/LivePortrait

  2. Set up the environment: Create and activate a conda environment, install dependencies via requirements.txt

  3. Download pretrained weights: Use huggingface-cli or download from provided links

  4. Run inference: Execute python inference.py for humans or python inference_animals.py for animals

  5. Utilize Gradio interface: Run python app.py or python app_animals.py for a web-based experience

  6. Configure options: Use command-line arguments for customization (e.g., source, driving video, cropping)

  7. Optimize performance: Enable --flag_do_torch_compile for faster inference on supported systems

  • Animated Portraits
  • Talking Avatars
  • Video Editing
  • Character Animation
  • AI Research
  • Content Creation
  • Animal Animation

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