A Python web API that uses headless Blender and MPFB2 to procedurally generate 3D bodies and fitted clothing from face images, fully containerized with Docker.

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CC0-1.0

Last updated

2026-07-29

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FR-AI / ANALYSIS

Why it is worth attention

It provides a practical foundation for digital afterlife and avatar cloning by automating the creation of customizable 3D human vessels from a single photo.

Who it is for

  • Developers building avatar or digital identity systems
  • 3D artists needing procedural body generation
  • VR/AR application creators
  • Researchers in digital resurrection and AI cloning

Use cases

  • Generating personalized 3D avatars for games or virtual worlds
  • Producing fitted virtual clothing for e-commerce try-on
  • Creating digital representations for memorial or afterlife platforms
  • Rapid prototyping of human models for animation or simulation

Strengths

  • Fully containerized with Docker, no local Blender or Python install needed
  • Uses MPFB2 for realistic, parameterized body generation from a face image
  • Clothing fitting is cached for near-instant subsequent requests
  • Released under CC0 public domain license for unrestricted use

Considerations

  • Requires Docker and a Linux host environment
  • Relies on the MPFB2 plugin which may have its own constraints
  • Limited clothing options (only one example shown)
  • Not designed for real-time generation (headless Blender processing)

README quick start

Yvonta - Body Factory

Your next life begins with an upload.

This application is a Python-based web API designed to procedurally generate 3D bodies and avatars. It leverages a headless instance of Blender in combination with the MPFB2 (MakeHuman Plugin for Blender) plugin to construct these assets, with the entire pipeline containerized within Docker for seamless deployment.


How to install?

Since the application is fully containerized, you do not need to install Blender or Python locally. Ensure you have Docker and Docker Compose installed on your system (e.g., Debian, Ubuntu, or your preferred Linux distribution).

  1. Clone the repository:
   git clone [https://github.com/Yvonta/body-factory.git](https://github.com/Yvonta/body-factory.git)
   cd body-factory

  1. Build the Docker container: This step pulls the base image, installs Python dependencies, downloads Blender, and configures the MPFB2 plugin.
docker build -t yvonta-body-factory .

  1. Run the application:
docker run -d -p 8090:8090 --name body-factory yvonta-body-factory

The API will now be accessible at http://localhost:8090.


How to use?

The application exposes a RESTful web API that generates .glb 3D models from face images and applies fitted clothing to the generated avatars.

1. Generate an Avatar

Submit a face image alongside macro parameters (gender, age, weight) to generate the base body. The API returns the 3D .glb file and provides a unique X-Avatar-Id in the response headers for future modifications.

curl -sS -D headers.txt -o avatar.glb \
    -F "gender=0.0" \
    -F "age=0.4" \
    -F "weight=0.5" \
    -F "file=@path/to/face.jpg" \
    "http://localhost:8090/v1/avatar/generate"

Check headers.txt for your X-Avatar-Id.

2. Fit Clothing to the Avatar

Using the X-Avatar-Id returned in step 1, you can request specific garments. The API runs a headless Blender process to fit the clothing to your exact avatar's proportions and caches the result for near-instant subsequent requests.

curl -sS -o clothing_1.glb \
    "http://localhost:8090/v1/avatar//clothing/toigo_basic_tucked_t-shirt"

*Tip: You can load both avatar.glb and clothing_1.glb together into a viewer like glTF Viewer to verify that the garment lines up

Description

Your next life begins with an upload

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