Skip to main content

Lightning Pose App

PyPI version

Web-based GUI for Lightning Pose — a semi-supervised pose estimation library for single- and multi-view animal tracking.

The app provides an end-to-end workflow:

  • Project management — create and organize pose estimation projects
  • Labeler — extract video frames and annotate keypoints
  • Models — configure and launch model training, monitor progress in real time
  • Inference — run trained models across video sessions
  • Viewer — inspect predictions overlaid on video with per-keypoint controls

Installation

Install Lightning Pose and the app:

pip install lightning-pose lightning-pose-app

Usage

litpose run_app

Then open http://localhost:4200 in your browser.

Documentation

Full documentation, including installation guides and tutorials:

👉 https://lightning-pose.readthedocs.io

Requirements

  • Linux or WSL (Windows Subsystem for Linux)
  • NVIDIA GPU with CUDA 12+
  • Python 3.10–3.12

Source

This package contains only the app server and compiled UI. The core modeling library lives at paninski-lab/lightning-pose.

Download files

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

Source Distribution

lightning_pose_app-2.3.0.3.tar.gz (11.4 MB view details)

Uploaded Source

Built Distribution

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

lightning_pose_app-2.3.0.3-py3-none-any.whl (11.6 MB view details)

Uploaded Python 3

File details

Details for the file lightning_pose_app-2.3.0.3.tar.gz.

File metadata

  • Download URL: lightning_pose_app-2.3.0.3.tar.gz
  • Upload date:
  • Size: 11.4 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/7.0.0 CPython/3.13.14

File hashes

Hashes for lightning_pose_app-2.3.0.3.tar.gz
Algorithm Hash digest
SHA256 9625caa27e217a4a4ddcc8106698c5225e403d64cace76042a5b84ebe359b9e4
MD5 390ab0e0f71a73a31c3ebf3ac5388c1a
BLAKE2b-256 25cd6478ebc9d0dc54fda9d1e5ed8d28e2af10f3a00e0668316bead1560d2d05

See more details on using hashes here.

Provenance

The following attestation bundles were made for lightning_pose_app-2.3.0.3.tar.gz:

Publisher: publish.yml on paninski-lab/lightning-pose-app

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file lightning_pose_app-2.3.0.3-py3-none-any.whl.

File metadata

File hashes

Hashes for lightning_pose_app-2.3.0.3-py3-none-any.whl
Algorithm Hash digest
SHA256 1467f6a1580e6b905ed39a3dd0b02ba6ddf9c976d6ab8fa378e85482add000a1
MD5 e786819c67174cba60016c08c8050306
BLAKE2b-256 30c1a6a0f3e6894d0637c4ef7b793c54c3f77390ba9464f537de4873fc0a150a

See more details on using hashes here.

Provenance

The following attestation bundles were made for lightning_pose_app-2.3.0.3-py3-none-any.whl:

Publisher: publish.yml on paninski-lab/lightning-pose-app

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.
Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page