explaingit

ivanfioravanti/fasterliveportrait-mlx

18PythonAudience · generalComplexity · 2/5Setup · moderate

TLDR

Animate portrait photos and videos on Apple Silicon Macs using AI, feed it a webcam, video, audio, or text to make still images move and speak. No GPU required, runs on Mac's unified memory via Apple's MLX framework.

Mindmap

mindmap
  root((repo))
    What it does
      Animate portraits
      Transfer expressions
      Multi-face support
      Animal subjects
    Driving inputs
      Webcam live feed
      Video clip
      Audio recording
      Text prompt
    Tech stack
      Apple MLX
      Gradio UI
      FastAPI endpoint
      Hugging Face models
    Audience
      Mac creators
      Video makers
      AI experimenters
    Setup
      Apple Silicon only
      Python 3.11 plus
      uv package manager
      ffmpeg required
Click or tap to explore — scroll the page freely

Code map

Detail Auto

An interactive map of this repo's files and how they connect — its source is parsed live in your browser. Click Visualize to build it.

filefunction / class

Things people build with this

USE CASE 1

Bring a still profile photo to life by driving it with your webcam in real time.

USE CASE 2

Generate a talking-head video from a portrait photo using an audio clip or typed sentence.

USE CASE 3

Animate an animal photo or a group shot with up to three faces using a single driving video.

USE CASE 4

Batch-process portrait animations via the CLI or FastAPI endpoint for automated workflows.

Tech stack

PythonMLXGradioFastAPIHugging Faceffmpeguv

Getting it running

Difficulty · moderate Time to first run · 30min

Requires Apple Silicon Mac, Python 3.11+, ffmpeg, and the uv package manager. One command installs the Python env, models download automatically from Hugging Face on first run.

Derived from open-source LivePortrait work, license not explicitly stated in the explanation.

In plain English

This project lets you animate portrait photos and videos on an Apple Silicon Mac. You supply a source image, a portrait photo or animal picture, and a driving input, a video clip, a live webcam feed, an audio recording, or even a text prompt, and the tool transfers the motion or expression from the driving source onto the subject in your photo. The result is a video where your still image moves and speaks according to whatever drove it. Under the hood it uses Apple's MLX framework, which runs directly on the unified memory of Apple Silicon chips rather than requiring a separate GPU. All the core AI models, the face analysis, the motion estimation, the image warping and blending, are converted to MLX format and downloaded automatically from Hugging Face when you first run the app. You do not need to fetch or convert any weights by hand for normal use. The web interface is built with Gradio and launches at a local address in your browser. From there you pick your source portrait, choose what will drive the animation, and click Generate. The CLI offers the same features with command flags, which is handy for scripting or batch work. An experimental FastAPI endpoint is also included for programmatic access. Multiple quality profiles let you trade off fidelity for speed, which matters when driving with a live webcam where latency is noticeable. Beyond single-face human portraits, the tool supports animating animal subjects and can detect up to three faces in one source image, animating all of them simultaneously from a single driving face. Audio and text driving are marked experimental: you can feed an audio clip or a typed sentence and the system will generate corresponding lip and head motion, relying on additional models for the voice and motion conversion. Setup requires an Apple Silicon Mac, Python 3.11 or newer, ffmpeg, and the uv package manager. After installing those, one command installs the Python environment and another starts the web UI. The project is derived from warmshao/FasterLivePortrait, which is itself based on the LivePortrait work from KwaiVGI.

Copy-paste prompts

Prompt 1
I have a portrait photo and a short video clip. Using fasterliveportrait-mlx, how do I animate the portrait so it mimics the facial movements in the video? Give me the exact CLI command.
Prompt 2
Using fasterliveportrait-mlx, how do I set up live webcam-driven animation at the lowest latency quality profile on my Apple Silicon Mac? Walk me through setup and the command to start it.
Prompt 3
I want to make a still image of my cat talk using an audio file with fasterliveportrait-mlx. What steps do I follow and which flags or UI options should I use?
Prompt 4
How do I call the fasterliveportrait-mlx FastAPI endpoint programmatically in Python to submit a source image and a driving video and receive the animated result?
Prompt 5
I have a group photo with three faces. How does fasterliveportrait-mlx handle animating all three simultaneously from a single driving face, and how do I trigger that via the Gradio UI?
Open on GitHub → Explain another repo

← ivanfioravanti on gitmyhub — every repo by this author, as a profile.

Verify against the repo before relying on details.