Skip to main content

Multi-backend parametric body models (SMPL, SMPLH, SMPLX, FLAME, SKEL, ANNY, MHR, SOMA, GarmentMeasurements, BrainCo, G1) for NumPy, PyTorch, and JAX

Project description

Body model lineup

body-models

body-models provides a shared interface for parametric human body, head, hand, anatomical, measurement, and robot models across NumPy, PyTorch, and JAX.

Documentation: https://abcamiletto.github.io/body-models/

Features

  • Shared API across human, anatomical, hand, head, measurement, and robot models
  • NumPy, PyTorch, and JAX backends
  • Separate mesh and skeleton forwards with forward_vertices() and forward_skeleton()
  • Prepared identities for repeated poses with fixed shape/expression parameters
  • Mesh simplification and vertex-subset forwards for supported mesh models
  • Multiple rotation representations for supported pose models

Install

uv add body-models

Install optional extras when needed:

uv add "body-models[torch]"
uv add "body-models[jax]"

Quick Start

from body_models.smpl.torch import SMPL

model = SMPL(gender="neutral")
params = model.get_rest_pose(batch_dims=(1,))

vertices = model.forward_vertices(**params)
skeleton = model.forward_skeleton(**params)

When shape-dependent identity parameters stay fixed across many poses, prepare them once and pass the returned dictionary back through identity. This avoids recomputing rest joints, local offsets, and rest vertices on every forward pass.

shape = params.pop("shape")
identity = model.prepare_identity(shape)

vertices = model.forward_vertices(**params, identity=identity)
skeleton = model.forward_skeleton(**params, identity=identity)

For models with expression-dependent rest state, such as SMPL-X and FLAME, pass both identity controls to prepare_identity(shape, expression). Skeleton-only work can use skip_vertices=True to avoid preparing rest vertices.

Supported Models

  • Full bodies: SMPL, SMPL-H, SMPL-X, ANNY, MHR, SOMA, GarmentMeasurements
  • Anatomicals: SKEL, MyoFullBody
  • Heads: FLAME
  • Hands: MANO
  • Robots: BrainCo, G1

See the model docs for setup, supported backends, inputs, and model-specific behavior.

Development

uv run ruff format .
uv run ruff check .
uv run ty check

License

See the documentation and upstream model projects for model-specific license terms.

Project details


Download files

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

Source Distribution

body_models-0.14.1.tar.gz (163.3 kB view details)

Uploaded Source

Built Distribution

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

body_models-0.14.1-py3-none-any.whl (295.9 kB view details)

Uploaded Python 3

File details

Details for the file body_models-0.14.1.tar.gz.

File metadata

  • Download URL: body_models-0.14.1.tar.gz
  • Upload date:
  • Size: 163.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: uv/0.11.18 {"installer":{"name":"uv","version":"0.11.18","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for body_models-0.14.1.tar.gz
Algorithm Hash digest
SHA256 92680450087912cf3eb53470ca4101b024f38c93ce30e32cd3a5a26fb0a02bf8
MD5 6dbe6dec7bb1100b36ff266e5dab66fe
BLAKE2b-256 634514c5e821619e78e5e0ee68941253e4b565eea2456fae439fa260be5ecd88

See more details on using hashes here.

File details

Details for the file body_models-0.14.1-py3-none-any.whl.

File metadata

  • Download URL: body_models-0.14.1-py3-none-any.whl
  • Upload date:
  • Size: 295.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: uv/0.11.18 {"installer":{"name":"uv","version":"0.11.18","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for body_models-0.14.1-py3-none-any.whl
Algorithm Hash digest
SHA256 93f75bd5e980064816253945c6e2af1711fe2c188f064324c60a7f3fb181b1aa
MD5 797d7fb75c7d647ea8bc766a2a69380d
BLAKE2b-256 a46d27b281e5b5a7141ff5bf4499455645e647efeec67dfe112743b97aa01589

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