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Readme.md
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* @Date: 2021-01-13 20:32:12
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* @Author: Qing Shuai
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* @LastEditors: Qing Shuai
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* @LastEditTime: 2021-01-14 21:43:44
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* @LastEditTime: 2021-01-17 21:07:07
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* @FilePath: /EasyMocapRelease/Readme.md
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-->
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# EasyMocap
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**EasyMocap** is an open-source toolbox for **markerless human motion capture**.
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**EasyMocap** is an open-source toolbox for **markerless human motion capture** from RGB videos.
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## Features
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- [x] multi-view, single person => 3d body keypoints
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- [x] multi-view, single person => SMPL parameters
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## Results
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|:heavy_check_mark: Skeleton|:heavy_check_mark: SMPL|
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|----|----|
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|![repro](doc/feng/repro_512.gif)|![smpl](doc/feng/smpl_512.gif)|
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> The following features are not released yet. We are now working hard on them. Please stay tuned!
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- [ ] Whole body 3d keypoints estimation
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- [ ] SMPL-H/SMPLX support
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- [ ] Dense reconstruction and view synthesis from sparse view: [Neural Body](https://zju3dv.github.io/neuralbody/).
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|Input|Output|
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|----|----|
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|multi-view, single person | whole body 3d keypoints|
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|multi-view, single person | SMPL-H/SMPLX/MANO parameters|
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|sparse view, single person | dense reconstruction and view synthesis: [NeuralBody](https://zju3dv.github.io/neuralbody/).|
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|:black_square_button: Whole Body|:black_square_button: [Detailed Mesh](https://zju3dv.github.io/neuralbody/)|
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|----|----|
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## Installation
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### 1. Download SMPL models
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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:**
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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:**
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```bash
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data
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└── smplx
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@ -39,7 +45,7 @@ data
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- torch==1.4.0
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- torchvision==0.5.0
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- opencv-python
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- pyrender: for visualization
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- [pyrender](https://pyrender.readthedocs.io/en/latest/install/index.html#python-installation): for visualization
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- chumpy: for loading SMPL model
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Some of python libraries can be found in `requirements.txt`. You can test different version of PyTorch.
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@ -131,6 +137,10 @@ The data in `smpl/000000.json` is also a list, each element represents the SMPL
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```
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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.
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## Evaluation
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We will add more quantitative reports in [doc/evaluation.md](doc/evaluation.md)
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## Acknowledgements
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Here are the great works this project is built upon:
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@ -165,5 +175,3 @@ Please consider citing these works if you find this repo is useful for your proj
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year={2020}
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}
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```
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<!-- ## License -->
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