Skip to main content

A library providing foundational algorithms for human kinematic motion and numerical optimization solvers to apply human motion in various applications (GPU-accelerated version with CUDA support)

Project description

Momentum

CI Windows CI macOS CI Ubuntu Publish Website PyPI Wheels

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

Forward and Inverse Kinematics with Interpretable Parameterization RGBD Body Tracking Solver Monocular RGB Body Tracking Solver

Quick Start

Installation

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

# Python (PyPI) - uv preferred over pip
uv add pymomentum-cpu           # CPU version
uv add pymomentum-gpu           # GPU version with CUDA
pip install pymomentum-cpu      # Alternative: using pip
pip install pymomentum-gpu

# Python (Conda/Pixi)
pixi add pymomentum             # Auto-detects GPU/CPU
conda install -c conda-forge pymomentum

# C++ (Conda/Pixi only)
pixi add momentum-cpp
conda install -c conda-forge momentum-cpp

📦 Browse packages: PyPIconda-forgeprefix.dev

Quick Example

# Install and run
pip install pymomentum-cpu
python -c "import pymomentum.geometry as geom; print(dir(geom))"

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:

📖 Documentation

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

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.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

pymomentum_gpu-0.1.97.post20-cp313-cp313-manylinux_2_28_x86_64.whl (34.6 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.28+ x86-64

pymomentum_gpu-0.1.97.post20-cp312-cp312-manylinux_2_28_x86_64.whl (34.6 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.28+ x86-64

File details

Details for the file pymomentum_gpu-0.1.97.post20-cp313-cp313-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pymomentum_gpu-0.1.97.post20-cp313-cp313-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 db3a85052488872c0ef4027ea12313fb20f951b3bee39bdb37e90290da85817e
MD5 dae0ed05221deef29d949021fee1671d
BLAKE2b-256 6dce762d4772cde2ed1ebf59e6f0b13cc71d1f7e324b0b3ba15469d43ed739d3

See more details on using hashes here.

File details

Details for the file pymomentum_gpu-0.1.97.post20-cp312-cp312-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pymomentum_gpu-0.1.97.post20-cp312-cp312-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 5ad613b00f8ba1ebb7c5f313d83b38c0cd42e91752762029655c68f7966bdfa1
MD5 8f5b5cae1f1e77a7fbc2ad6f6d2a667b
BLAKE2b-256 18fd1f0f5235f3c0b2aff421934251a64e56c7d4324ccc7ec4a6fc1c36a98959

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page