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Rename smpl->smplpytorch.

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gulvarol
2019-07-16 15:41:45 +02:00
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@ -7,18 +7,31 @@ It can be integrated into any architecture as a differentiable layer to predict
The code is adapted from the [manopth](https://github.com/hassony2/manopth) repository by [Yana Hasson](https://github.com/hassony2).
<p align="center">
<img src="image.png" alt="smpl" width="300"/>
<img src="assets/image.png" alt="smpl" width="300"/>
</p>
## Setting up
* Dependencies:
* Install the dependencies listed in [environment.yml](environment.yml)
* In an existing conda environment, `conda env update -f environment.yml`
* In a new environment, `conda env create -f environment.yml`, will create a conda environment named `smplpytorch`
* Download SMPL pickle files:
## Setup
### 1. The `smplpytorch` package
* **Run without installing:** You will need to install the dependencies listed in [environment.yml](environment.yml):
* `conda env update -f environment.yml` in an existing environment, or
* `conda env create -f environment.yml`, for a new `smplpytorch` environment
* **Install:** To import `SMPL_Layer` in another project with `from smplpytorch.pytorch.smpl_layer import SMPL_Layer` do one of the following.
* Option 1: This should automatically install the dependencies.
``` bash
git clone https://github.com/gulvarol/smplpytorch.git
cd smplpytorch
pip install .
```
* Option 2: You can install `smplpytorch` from [PyPI](https://pypi.org/project/smplpytorch/). Additionally, you might need to install [chumpy](https://github.com/hassony2/chumpy.git).
``` bash
pip install smplpytorch
```
### 2. Download SMPL pickle files
* Download the models from the [SMPL website](http://smpl.is.tue.mpg.de/) by choosing "SMPL for Python users". Note that you need to comply with the [SMPL model license](http://smpl.is.tue.mpg.de/license_model).
* Extract and copy the `models` folder into the `smpl/native/` folder.
* Extract and copy the `models` folder into the `smplpytorch/native/` folder (or set the `model_root` parameter accordingly).
## Demo