#1919th of 24 in Image and videoFor image, video and design, image and design, video and animation
liveportrait
Animates a still portrait from a driving video, with stitching and retargeting
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- Stars
- 19.3k
- License
- custom license
- Last commit
- Jun 2026
- Language
- Python
17,821 on 31 Mar 202619,278 on 20 Oct 2026
From GitHub's daily star counts.
Checked on GitHub.
Overview
Official PyTorch implementation of the LivePortrait paper. It animates a source image or video of a human, cat or dog using motion from a driving video or a precomputed .pkl motion template. It ships CLI scripts (inference.py, inference_animals.py) and a Gradio app with pose and regional editing, and pretrained weights are hosted on Hugging Face.
Who it is for: Researchers and creators animating portraits locally, ideally with an NVIDIA GPU
Strengths
- Accepts image or video sources, including portrait video editing and image-driven mode
- Motion templates (.pkl) speed up inference and avoid sharing the driving video
- Gradio UI, Windows one-click installer and a Hugging Face Space demo are provided
- Optional torch.compile gives 20-30% faster inference per the README (not on Windows or macOS)
Weaknesses
- Animals mode needs X-Pose and a compiled CUDA op; tested only with NVIDIA GPUs
- Apple Silicon is not supported for Animals mode and is about 20x slower than an RTX 4090
- Needs conda, FFmpeg and a manual weight download; no Docker setup
- License is not detected automatically (NOASSERTION); check the repo before commercial use
What it needs
- GPU optional
- Needs conda, FFmpeg, PyTorch, Gradio, huggingface_hub, X-Pose (Animals mode)
- Models: LivePortrait Humans model, LivePortrait Animals model, KlingTeam/LivePortrait weights on Hugging Face
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