From 7a2eeba1cd20595f10c3efe6c950fc5c3f6f8f9f Mon Sep 17 00:00:00 2001 From: shuaiqing Date: Sun, 17 Jan 2021 21:08:07 +0800 Subject: [PATCH] update readme --- Readme.md | 30 +++++++++++++++++++----------- 1 file changed, 19 insertions(+), 11 deletions(-) diff --git a/Readme.md b/Readme.md index 12f8565..9d38d2d 100644 --- a/Readme.md +++ b/Readme.md @@ -2,21 +2,27 @@ * @Date: 2021-01-13 20:32:12 * @Author: Qing Shuai * @LastEditors: Qing Shuai - * @LastEditTime: 2021-01-14 21:43:44 + * @LastEditTime: 2021-01-17 21:07:07 * @FilePath: /EasyMocapRelease/Readme.md --> # EasyMocap -**EasyMocap** is an open-source toolbox for **markerless human motion capture**. +**EasyMocap** is an open-source toolbox for **markerless human motion capture** from RGB videos. + +## Features +- [x] multi-view, single person => 3d body keypoints +- [x] multi-view, single person => SMPL parameters -## Results |:heavy_check_mark: Skeleton|:heavy_check_mark: SMPL| |----|----| |![repro](doc/feng/repro_512.gif)|![smpl](doc/feng/smpl_512.gif)| > The following features are not released yet. We are now working hard on them. Please stay tuned! -- [ ] Whole body 3d keypoints estimation -- [ ] SMPL-H/SMPLX support -- [ ] Dense reconstruction and view synthesis from sparse view: [Neural Body](https://zju3dv.github.io/neuralbody/). + +|Input|Output| +|----|----| +|multi-view, single person | whole body 3d keypoints| +|multi-view, single person | SMPL-H/SMPLX/MANO parameters| +|sparse view, single person | dense reconstruction and view synthesis: [NeuralBody](https://zju3dv.github.io/neuralbody/).| |:black_square_button: Whole Body|:black_square_button: [Detailed Mesh](https://zju3dv.github.io/neuralbody/)| |----|----| @@ -24,7 +30,7 @@ ## Installation ### 1. Download SMPL models -To download the *SMPL* model go to [this](http://smpl.is.tue.mpg.de) (male and female models) and [this](http://smplify.is.tue.mpg.de) (gender neutral model) project website and register to get access to the downloads section. **Place them as following:** +To download the *SMPL* model go to [this](http://smpl.is.tue.mpg.de) (male and female models, version 1.0.0, 10 shape PCs) and [this](http://smplify.is.tue.mpg.de) (gender neutral model) project website and register to get access to the downloads section. Prepare the model as [smplx](https://github.com/vchoutas/smplx#model-loading). **Place them as following:** ```bash data └── smplx @@ -39,7 +45,7 @@ data - torch==1.4.0 - torchvision==0.5.0 - opencv-python -- pyrender: for visualization +- [pyrender](https://pyrender.readthedocs.io/en/latest/install/index.html#python-installation): for visualization - chumpy: for loading SMPL model Some of python libraries can be found in `requirements.txt`. You can test different version of PyTorch. @@ -131,6 +137,10 @@ The data in `smpl/000000.json` is also a list, each element represents the SMPL ``` We set the first 3 dimensions of `poses` to zero, and add a new parameter `Rh` to represents the global oritentation, the vertices of SMPL model V = RX(theta, beta) + T. +## Evaluation + +We will add more quantitative reports in [doc/evaluation.md](doc/evaluation.md) + ## Acknowledgements Here are the great works this project is built upon: @@ -164,6 +174,4 @@ Please consider citing these works if you find this repo is useful for your proj journal={arXiv preprint arXiv:2012.15838}, year={2020} } -``` - - +``` \ No newline at end of file