MIT License

项目介绍

KosukeFukazawa/smpl2bvh 是一个托管在 GitHub 上的开源项目,主要使用 Python 编写,采用 MIT License 许可证,目前获得 230 个 Star、27 次 Fork。

仓库全名
KosukeFukazawa/smpl2bvh
开源许可证
MIT License
Star 数
230
Fork 数
27
未关闭 Issue
7

README 摘要

smpl2bvh This repository contains an example script to convert from a SMPL model to a bvh file. The left side of the figure shows the SMPL grand truth and the right side shows the bvh data. If you want to convert AMASS to bvh, please refer to my another repo. Notification This code is MIT licensed, but SMPL requires a separate license. Please see SMPL official website. Requirements You need to download SMPL models…

完整内容见 GitHub 原始 README 或本页 。

常见问题

smpl2bvh 用什么语言开发?

主要使用 Python 编写,采用 MIT License 许可证,目前有 230 个 Star。

smpl2bvh 可以免费商用吗?

仓库采用 MIT License 许可证,可免费使用与修改,商业使用请遵守许可证条款(例如保留版权声明与许可声明)。

如何获取 smpl2bvh 的源码?

可以直接克隆仓库:git clone https://github.com/KosukeFukazawa/smpl2bvh.git,默认分支为 main;安装与运行步骤见仓库 README。

smpl2bvh 最近还在维护吗?

仓库最近一次更新为 2023年6月9日,当前有 7 个未关闭 Issue;Star 数为 230,可作为社区活跃度的参考。

关于

GitHub 原始描述(英文)

This repository contains an example script to convert from a SMPL model to a bvh file.

描述取自 GitHub 官方 API,保持仓库作者书写的原文。

简要分析

热度分
287
价值分
146
活跃状态
活跃

语言占比

Python

README

smpl2bvh

This repository contains an example script to convert from a SMPL model to a bvh file.


The left side of the figure shows the SMPL grand truth and the right side shows the bvh data. If you want to convert AMASS to bvh, please refer to my another repo.

Notification

This code is MIT licensed, but SMPL requires a separate license.
Please see SMPL official website.

Requirements

You need to download SMPL models in ./data/smpl/smpl/.
You need to download smplx too.
To install from PyPi simply run:

    pip install smplx[all]

How to use?

After downloads all requirements, you can use smpl2bvh like this:

    python smpl2bvh.py --gender MALE --poses ${PATH_TO_Y0UR_INPUT} --fps 60 --output ${PATH_TO_SAVE} --mirror

poses is an .npz file or .pkl file.
.npz file must contain rotations and trans as keys.
rotations value is an np.array consisting of [fnum, 24, 3] and trans value is the root transition consisting of [fnum, 3] (fnum means frame number).

.pkl file must contain smpl_poses and smpl_scaling and smpl_trans as keys.
smpl_poses value is an np.array consisting of [fnum, 72] and smpl_scaling value is the scaling parameter. smpl_trans value is the root transition consisting of [fnum, 3].
The format of pkl file is the same as AIST++ dataset.
If you check --mirror as an argument, the mirrored motion is also saved.
After processing, you can find bvh file as --output.
For more information, please refer to smpl2bvh.py.

Reference

bvh.py and quat.py are based on Motion Matching.

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