pymomentum-core 0.1.113.post0

A library providing foundational algorithms for human kinematic motion and numerical optimization solvers to apply human motion in various applications (core package without Torch C++ extensions)

Momentum

Momentum provides foundational algorithms for human kinematic motion and numerical optimization solvers to apply human motion in various applications.

Quick Start

Installation

Pre-built binaries are available for Windows, macOS, and Linux:

Install full conda/pixi packages -- recommended

# Install full python package from pixi, including modules with cpp torch dependencies
pixi add pymomentum

# Install full python package from conda, including modules with cpp torch dependencies
conda install -c conda-forge pymomentum

# Install cpp momentum package from pixi, including modules with cpp torch dependencies
pixi add momentum-cpp

# Install cpp momentum package from conda, including modules with cpp torch dependencies
conda install -c conda-forge momentum-cpp

Install PyPI wheels -- these are experimental ⚠️

# Install core package with NumPy/SciPy and PyTorch dependencies, but no Torch C++ extension modules
pip install pymomentum-core

# Install core package with optional visualization helpers
pip install "pymomentum-core[viser,rerun]"

# Install full package including diff_geometry and differentiable solver modules, linked against CPU PyTorch
pip install pymomentum-cpu

# Install full package including diff_geometry and differentiable solver modules, linked against CUDA PyTorch
pip install "torch>=2.8,<2.9" --index-url https://download.pytorch.org/whl/cu129
pip install pymomentum-gpu

Conda/Pixi currently publish the full PyMomentum package. Use the PyPI core package (since release v0.1.111) when you need a Python install without the Torch C++ extension dependency.

Install exactly one PyPI package for a given environment. The pymomentum-core package includes the NumPy/SciPy modules geometry, solver2, marker_tracking, axel, camera, and renderer, plus the torch-backed Python helper modules torch. The pymomentum-cpu and pymomentum-gpu packages provide differentiable optimization modules diff_geometry and solver, but they must match a supported PyTorch C++ ABI and therefore have stricter PyTorch version constraints.

⚠️ PyPI support is experimental. For the most stable experience, we recommend using Conda or Pixi.

📦 Browse packages: conda-forge • prefix.dev • PyPI

Building from Source

git clone https://github.com/facebookresearch/momentum
cd momentum
pixi run build      # Builds C++ library and Python bindings
pixi run test       # Runs tests
pixi run hello_world  # Runs example

For detailed instructions, see the comprehensive guides on our website:

• 📘 Python Getting Started - Installation, building from source, troubleshooting
• 📗 C++ Getting Started - Full build instructions, FBX support, examples

📖 Documentation

Visit our documentation website for comprehensive guides, examples, and API references:

• 🐍 Python API Reference - Complete Python API documentation
• ⚙️ C++ API Reference - Complete C++ API documentation

Contributing

Check our contributing guide to learn about how to contribute to the project.

License

Momentum is licensed under the MIT License. A copy of the license can be found here.