ego-vision

Composable egocentric vision model components and pipelines for hand and camera geometry.

The initial scope is intentionally narrow: raw model wrappers plus an episode-level pipeline boundary for the best VGGT-Omega + HaWoR stack.

episodes of av.VideoFrame
  -> VGGTOmegaModel
  -> HaWoRHandReconstructor
       YoloHandDetector + HaWoRModel + ManoLayer
  -> HaWoRHandMotionInfiller
  -> HandTrackingPipeline result

The egovision.models namespace contains raw model components. The egovision.pipelines namespace owns model scheduling and hand-tracking orchestration.

VGGT-Omega and the HaWoR inference modules needed by the pipeline live under egovision.models, so users do not need separate research-repo checkouts or PYTHONPATH setup. Checkpoints are still loaded from local paths or Hugging Face.

from egovision import (
    EpisodeInput,
    HandTrackingConfig,
    HandTrackingPipeline,
    HaworReconstructionConfig,
    VggtOmegaConfig,
)

pipeline = HandTrackingPipeline(
    HandTrackingConfig(
        hand_reconstruction=HaworReconstructionConfig(batch_size=64),
        camera_pose_estimator=VggtOmegaConfig(batch_size=1),
    )
)
results = pipeline.predict_episodes(
    [EpisodeInput(frames=av_frames)]
)

Install

pip install ego-vision

Heavy model dependencies are optional:

pip install "ego-vision[models]"

Development

uv sync --dev
uv run pytest
uv run ruff check --force-exclude .
uv run ruff format --force-exclude --check .
uv run ty check

Local hooks use the same commands:

uv run pre-commit run --all-files

Release

Publishing is handled by GitHub Actions with PyPI trusted publishing.

To release:

Bump version in pyproject.toml.
Push the commit to main.
The Publish package workflow builds the wheel and sdist, publishes to PyPI, then creates the vX.Y.Z tag and GitHub release.

The workflow can also be run manually from GitHub Actions with target testpypi or pypi. The normal release path only needs the pypi trusted publishing environment configured for the ego-vision project.

Metadata

Release files for ego-vision 0.1.25

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for ego-vision 0.1.25
File	Size	Uploaded
ego_vision-0.1.25.tar.gz	123.8 kB	Jun 4, 2026	Details

Built distribution (wheel)

Table of built distributions (wheels) for ego-vision 0.1.25
File	Interpreter	ABI	Platform	Reset
ego_vision-0.1.25-py3-none-any.whl 144.8 kB Jun 4, 2026	Python 3	none	any	Details

Total release size: 268.7 kB

Release files / ego_vision-0.1.25.tar.gz

Download URL	ego_vision-0.1.25.tar.gz
Size	123.8 kB
Tags	Source
SHA-256 checksum How to use checksums	`5e006a4f0f298eeeced609a0c77856c06e61d8591552b7a8e6f4468c0efeae8a`
BLAKE2b-256 checksum How to use checksums	`4aad1d472f1f488e6020b54d930b95197aac3dcfd9a9f0be6c32c35ab883f61c`
Upload date	Jun 4, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/6.1.0 CPython/3.13.12`

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/macrodata-labs/ego-vision
Publishing commit: github.com/macrodata-labs/ego-vision/tree/1372eb592a09e9ff9c0828b59814bddc8c6af475

Workflow

Publishing configuration: github.com/macrodata-labs/ego-vision/blob/1372eb592a09e9ff9c0828b59814bddc8c6af475/.github/workflows/pypi-release.yml
Publishing logs: github.com/macrodata-labs/ego-vision/actions/runs/26945335019/attempts/1

Artifact

Subject: ego_vision-0.1.25.tar.gz
SHA-256 checksum: 5e006a4f0f298eeeced609a0c77856c06e61d8591552b7a8e6f4468c0efeae8a Verifying attestations

Release files / ego_vision-0.1.25-py3-none-any.whl

Download URL	ego_vision-0.1.25-py3-none-any.whl
Size	144.8 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`501363d08e441a05b62903625c3a818c2f169b17e6198a9ab33ebed0d445d981`
BLAKE2b-256 checksum How to use checksums	`2d53a2ab363cd2d853cf5dfbb4848aa06cd52632f916fd827693ae20d5720e52`
Upload date	Jun 4, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/6.1.0 CPython/3.13.12`

Provenance

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/macrodata-labs/ego-vision
Publishing commit: github.com/macrodata-labs/ego-vision/tree/1372eb592a09e9ff9c0828b59814bddc8c6af475

Workflow

Publishing configuration: github.com/macrodata-labs/ego-vision/blob/1372eb592a09e9ff9c0828b59814bddc8c6af475/.github/workflows/pypi-release.yml
Publishing logs: github.com/macrodata-labs/ego-vision/actions/runs/26945335019/attempts/1

Artifact

Subject: ego_vision-0.1.25-py3-none-any.whl
SHA-256 checksum: 501363d08e441a05b62903625c3a818c2f169b17e6198a9ab33ebed0d445d981 Verifying attestations