View lightning-pose on Snyk Open Source Advisor

Package Health Score

80 / 100

security
No known security issues
popularity
Limited
maintenance
Healthy
community
Active

Popularity

Limited

GitHub Stars: 238
Forks: 35
Contributors: 20

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package lightning-pose, we found that it has been starred 238 times.

Security

No known security issues

Security and license risk for latest version

Release Date: Nov 13, 2024
Direct Vulnerabilities: 0
C
0
H
0
M
0
L
Indirect Vulnerabilities: 0
C
0
H
0
M
0
L
License Risk: 0
H
0
M
0
L

All security vulnerabilities belong to production dependencies of direct and indirect packages.

License

MIT

Security Policy

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Maintenance

Healthy

Commit Frequency

Open Issues: 8
Open PR: 2
Last Release: 12 days ago
Last Commit: 1 month ago

Further analysis of the maintenance status of lightning-pose based on released PyPI versions cadence, the repository activity, and other data points determined that its maintenance is Healthy.

We found that lightning-pose demonstrates a positive version release cadence with at least one new version released in the past 3 months.

As a healthy sign for on-going project maintenance, we found that the GitHub repository had at least 1 pull request or issue interacted with by the community.

Community

Active

Readme: Yes
Contributing.md: Yes
Code of Conduct: Yes
Contributors: 20
Funding: No

With more than 10 contributors for the lightning-pose repository, this is possibly a sign for a growing and inviting community.

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Package

Python Versions Compatibility: Unspecified

Age: 2 years
Latest Release: 12 days ago
Dependencies: 21 Direct
Versions: 15
Maintainers: 2
Wheels: OS Independent

Readme

GitHub PyPI

Pose estimation models implemented in Pytorch Lightning, supporting massively accelerated training on unlabeled videos using NVIDIA DALI. Models can be evaluated with TensorBoard, FiftyOne, and Streamlit.

As of June 2024, Lightning Pose is now published in Nature Methods!

Try our demo

Train a network on an example dataset and visualize the results in Google Colab.

Getting Started

Please see the Lightning Pose documentation for installation instructions and user guides. Note that the Lightning Pose package provides tools for training and evaluating models on already labeled data and unlabeled video clips.

We also offer a browser-based application that supports the full life cycle of a pose estimation project, from data annotation to model training to diagnostic visualizations.

The Lightning Pose team also actively develops the Ensemble Kalman Smoother (EKS), a simple and performant post-processor that works with any pose estimation package including Lightning Pose, DeepLabCut, and SLEAP.

Community

Lightning Pose is primarily maintained by Dan Biderman (Columbia University) and Matt Whiteway (Columbia University).

Lightning Pose is under active development and we welcome community contributions. Whether you want to implement some of your own ideas or help out with our development roadmap, please get in touch with us on Discord (see contributing guidelines here).

lightning-pose dependencies

fiftyone h5py hydra-core imgaug kaleido kornia lightning matplotlib moviepy nvidia-dali-cuda120 opencv-python-headless pillow plotly pytest seaborn streamlit tensorboard torchtyping torchvision typeguard typing

FAQs

What is lightning-pose?

Semi-supervised pose estimation using pytorch lightning. Visit Snyk Advisor to see a full health score report for lightning-pose, including popularity, security, maintenance & community analysis.

Is lightning-pose popular?

The python package lightning-pose receives a total of 161 weekly downloads. As such, lightning-pose popularity was classified as limited. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is lightning-pose well maintained?

We found that lightning-pose demonstrated a healthy version release cadence and project activity. It has a community of 20 open source contributors collaborating on the project. See the full package health analysis to learn more about the package maintenance status.

Is lightning-pose safe to use?

The python package lightning-pose was scanned for known vulnerabilities and missing license, and no issues were found. Thus the package was deemed as safe to use. See the full health analysis review.

Last updated on 21 November-2024, at 00:13 (UTC).

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lightning-pose

Semi-supervised pose estimation using pytorch lightning For more information about how to use this package see README

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Readme

Try our demo

Getting Started

Community

lightning-pose dependencies

FAQs

What is lightning-pose?

Is lightning-pose popular?

Is lightning-pose well maintained?

Is lightning-pose safe to use?

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Source Code

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