View mmhuman3d on Snyk Open Source Advisor

Package Health Score

55 / 100

security
Security review needed
popularity
Small
maintenance
Inactive
community
Active

Explore Similar Packages

mutant
42

Popularity

Small

GitHub Stars: 1.17K
Forks: 125
Contributors: 40

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package mmhuman3d, we found that it has been starred 1,167 times.

Security

Security review needed

Security and license risk for latest version

Release Date: Apr 5, 2023
Direct Vulnerabilities: 0
C
0
H
0
M
0
L
Indirect Vulnerabilities: 0
C
0
H
0
M
0
L
License Risk: 1
H
1
M
0
L

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

License

Apache-2.0

Security Policy

We found a way for you to contribute to the project! Looks like mmhuman3d is missing a security policy.

You can connect your project's repository to Snyk to stay up to date on security alerts and receive automatic fix pull requests.

Keep your project free of vulnerabilities with Snyk

Maintenance

Inactive

Commit Frequency

No Recent Commits

Open Issues: 109
Open PR: 22
Last Release: 1 year ago
Last Commit: 1 year ago

Further analysis of the maintenance status of mmhuman3d based on released PyPI versions cadence, the repository activity, and other data points determined that its maintenance is Inactive.

An important project maintenance signal to consider for mmhuman3d is that it hasn't seen any new versions released to PyPI in the past 12 months, and could be considered as a discontinued project, or that which receives low attention from its maintainers.

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: 40
Funding: No

With more than 10 contributors for the mmhuman3d repository, this is possibly a sign for a growing and inviting community.

Embed Package Health Score Badge

Keep your project healthy

Check your requirements.txt

Ensure all the packages you're using are healthy and well-maintained

Snyk Vulnerability Scanner

Get health score & security insights directly in your IDE

Package

Python Versions Compatibility: ==3.6.*, ==3.7.*, ==3.8.*, ==3.9.*

Age: 3 years
Latest Release: 1 year ago
Dependencies: 20 Direct / 46 Total
Versions: 9
Maintainers: 1
Wheels: OS Independent

Readme

Introduction

English | 简体中文

MMHuman3D is an open-source PyTorch-based codebase for the use of 3D human parametric models in computer vision and computer graphics. It is a part of the OpenMMLab project.

The main branch works with PyTorch 1.7+.

If you are interested in multi-view motion capture, please refer to XRMoCap for more details.

https://user-images.githubusercontent.com/62529255/144362861-e794b404-c48f-4ebe-b4de-b91c3fbbaa3b.mp4

Major Features

Reproducing popular methods with a modular framework

MMHuman3D reimplements popular methods, allowing users to reproduce SOTAs with one line of code. The modular framework is convenient for rapid prototyping: the users may attempt various hyperparameter settings and even network architectures, without actually modifying the code.
Supporting various datasets with a unified data convention

With the help of a convention toolbox, a unified data format HumanData is used to align all supported datasets. Preprocessed data files are also available.
Versatile visualization toolbox

A suite of differentiale visualization tools for human parametric model rendering (including part segmentation, depth map and point clouds) and conventional 2D/3D keypoints are available.

News

2023-04-05: MMHuman3D v0.11.0 is released. Major updates include:
- Add ExPose inference
- Add PyMAF-X inference
- Support CLIFF
2022-10-12: MMHuman3D v0.10.0 is released. Major updates include:
- Add webcam demo and real-time renderer
- Update dataloader to speed up training
- Add balanced MSE loss for imbalanced HMR training
2022-07-08: MMHuman3D v0.9.0 is released. Major updates include:
- Support SMPL-X estimation with ExPose for simultaneous recovery of face, hands and body
- Support new body model STAR
- Release of GTA-Human dataset with SPIN-FT (51.98 mm) and PARE-FT (46.84 mm) baselines! (Official)
- Refactor registration and improve performance of SPIN to 57.54 mm

Benchmark and Model Zoo

More details can be found in model_zoo.md.

Supported body models:

(click to collapse)

[x] SMPL (SIGGRAPH Asia'2015)
[x] SMPL-X (CVPR'2019)
[x] MANO (SIGGRAPH ASIA'2017)
[x] FLAME (SIGGRAPH ASIA'2017)
[x] STAR (ECCV'2020)

Supported methods:

(click to collapse)

[x] SMPLify (ECCV'2016)
[x] SMPLify-X (CVPR'2019)
[x] HMR (CVPR'2018)
[x] SPIN (ICCV'2019)
[x] VIBE (CVPR'2020)
[x] HybrIK (CVPR'2021)
[x] PARE (ICCV'2021)
[x] DeciWatch (ECCV'2022)
[x] SmoothNet (ECCV'2022)
[x] ExPose (ECCV'2020)
[x] BalancedMSE (CVPR'2022)
[x] PyMAF-X (arXiv'2022)
[x] ExPose (ECCV'2020)
[x] PyMAF-X (arXiv'2022)
[x] CLIFF (ECCV'2022)

Supported datasets:

(click to collapse)

[x] 3DPW (ECCV'2018)
[x] AGORA (CVPR'2021)
[x] AMASS (ICCV'2019)
[x] COCO (ECCV'2014)
[x] COCO-WholeBody (ECCV'2020)
[x] CrowdPose (CVPR'2019)
[x] EFT (3DV'2021)
[x] GTA-Human (arXiv'2021)
[x] Human3.6M (TPAMI'2014)
[x] InstaVariety (CVPR'2019)
[x] LSP (BMVC'2010)
[x] LSP-Extended (CVPR'2011)
[x] MPI-INF-3DHP (3DC'2017)
[x] MPII (CVPR'2014)
[x] Penn Action (ICCV'2012)
[x] PoseTrack18 (CVPR'2018)
[x] SURREAL (CVPR'2017)
[x] UP3D (CVPR'2017)
[x] FreiHand (ICCV'2019)
[x] EHF (CVPR'2019)
[x] Stirling/ESRC-Face3D (FG'2018)

We will keep up with the latest progress of the community, and support more popular methods and frameworks.

If you have any feature requests, please feel free to leave a comment in the wishlist.

Get Started

Please see getting_started.md for the basic usage of MMHuman3D.

License

This project is released under the Apache 2.0 license. Some supported methods may carry additional licenses.

Citation

If you find this project useful in your research, please consider cite:

@misc{mmhuman3d,
    title={OpenMMLab 3D Human Parametric Model Toolbox and Benchmark},
    author={MMHuman3D Contributors},
    howpublished = {\url{https://github.com/open-mmlab/mmhuman3d}},
    year={2021}
}

Contributing

We appreciate all contributions to improve MMHuman3D. Please refer to CONTRIBUTING.md for the contributing guideline.

Acknowledgement

MMHuman3D is an open source project that is contributed by researchers and engineers from both the academia and the industry. We appreciate all the contributors who implement their methods or add new features, as well as users who give valuable feedbacks. We wish that the toolbox and benchmark could serve the growing research community by providing a flexible toolkit to reimplement existing methods and develop their own new models.

Projects in OpenMMLab

MMCV: OpenMMLab foundational library for computer vision.
MIM: MIM Installs OpenMMLab Packages.
MMClassification: OpenMMLab image classification toolbox and benchmark.
MMDetection: OpenMMLab detection toolbox and benchmark.
MMDetection3D: OpenMMLab next-generation platform for general 3D object detection.
MMSegmentation: OpenMMLab semantic segmentation toolbox and benchmark.
MMAction2: OpenMMLab next-generation action understanding toolbox and benchmark.
MMTracking: OpenMMLab video perception toolbox and benchmark.
MMPose: OpenMMLab pose estimation toolbox and benchmark.
MMEditing: OpenMMLab image and video editing toolbox.
MMOCR: A Comprehensive Toolbox for Text Detection, Recognition and Understanding.
MMGeneration: OpenMMLab next-generation toolbox for generative models.
MMFlow: OpenMMLab optical flow toolbox and benchmark.
MMFewShot: OpenMMLab FewShot Learning Toolbox and Benchmark.
MMHuman3D: OpenMMLab 3D Human Parametric Model Toolbox and Benchmark.
MMSelfSup: OpenMMLab self-supervised learning toolbox and benchmark.
MMRazor: OpenMMLab model compression toolbox and benchmark.
MMDeploy: OpenMMLab model deployment framework.

mmhuman3d dependencies

astropy cdflib chumpy colormap easydev einops h5py matplotlib numpy opencv-python pandas pickle5 plyfile rtree scikit-image scipy smplx tqdm trimesh vedo

FAQs

What is mmhuman3d?

OpenMMLab 3D Human Parametric Model Toolbox and Benchmark. Visit Snyk Advisor to see a full health score report for mmhuman3d, including popularity, security, maintenance & community analysis.

Is mmhuman3d popular?

The python package mmhuman3d receives a total of 160 weekly downloads. As such, mmhuman3d popularity was classified as small. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is mmhuman3d well maintained?

We found indications that mmhuman3d is an Inactive project. See the full package health analysis to learn more about the package maintenance status.

Is mmhuman3d safe to use?

While scanning the latest version of mmhuman3d, we found that a security review is needed. A total of 0 vulnerabilities or license issues were detected. See the full security scan results.

Last updated on 26 July-2024, at 19:17 (UTC).

Build a secure application checklist

Select a recommended open source package

Minimize your risk by selecting secure & well maintained open source packages

DONE

Scan your app for vulnerabilities

Scan your application to find vulnerabilities in your: source code, open source dependencies, containers and configuration files

SCAN NOW

Fix identified vulnerabilities

Easily fix your code by leveraging automatically generated PRs

AUTO FIX

Monitor for new issues

New vulnerabilities are discovered every day. Get notified if your application is affected

MONITOR APP

mmhuman3d

OpenMMLab 3D Human Parametric Model Toolbox and Benchmark For more information about how to use this package see README

Ensure you're using the healthiest python packages

Package Health Score

Explore Similar Packages

Popularity

Direct Usage Popularity

Security

Security and license risk for latest version

Maintenance

Commit Frequency

Community

Embed Package Health Score Badge

Keep your project healthy

Check your requirements.txt

Snyk Vulnerability Scanner

Package

Readme

Introduction

Major Features

News

Benchmark and Model Zoo

Get Started

License

Citation

Contributing

Acknowledgement

Projects in OpenMMLab

mmhuman3d dependencies

FAQs

What is mmhuman3d?

Is mmhuman3d popular?

Is mmhuman3d well maintained?

Is mmhuman3d safe to use?

Build a secure application checklist

Select a recommended open source package

Scan your app for vulnerabilities

Fix identified vulnerabilities

Monitor for new issues

Package Health Score

Explore Similar Packages

Direct Usage Popularity

Security and license risk for latest version

Commit Frequency

Embed Package Health Score Badge

Keep your project healthy

Check your requirements.txt

Snyk Vulnerability Scanner

Readme

Introduction

Major Features

News

Benchmark and Model Zoo

Get Started

License

Citation

Contributing

Acknowledgement

Projects in OpenMMLab

mmhuman3d dependencies

FAQs

What is mmhuman3d?

Is mmhuman3d popular?

Is mmhuman3d well maintained?

Is mmhuman3d safe to use?

Build a secure application checklist

Select a recommended open source package

Scan your app for vulnerabilities

Source Code

Open Source

Container

Config

Fix identified vulnerabilities

Monitor for new issues