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# Windows installation tutorial |
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Another [issue#16](https://github.com/YuliangXiu/ECON/issues/16) shows the whole process to deploy ECON on *Windows* |
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## Dependencies and Installation |
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- Use [Anaconda](https://www.anaconda.com/products/distribution) |
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- NVIDIA GPU + [CUDA](https://developer.nvidia.com/cuda-downloads) |
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- [Wget for Windows](https://eternallybored.org/misc/wget/1.21.3/64/wget.exe) |
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- Create a new folder on your C drive and rename it "wget" and move the downloaded "wget.exe" over there. |
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- Add the path to your wget folder to your system environment variables at `Environment Variables > System Variables Path > Edit environment variable` |
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- Install [Git for Windows 64-bit](https://git-scm.com/download/win) |
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- [Visual Studio Community 2022](https://visualstudio.microsoft.com/) (Make sure to check all the boxes as shown in the image below) |
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## Getting started |
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Start by cloning the repo: |
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```bash |
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git clone https://github.com/yuliangxiu/ECON.git |
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cd ECON |
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``` |
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## Environment |
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- Windows 10 / 11 |
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- **CUDA=11.3** |
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- Python = 3.8 |
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- PyTorch >= 1.12.1 (official [Get Started](https://pytorch.org/get-started/locally/)) |
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- Cupy >= 11.3.0 (offcial [Installation](https://docs.cupy.dev/en/stable/install.html#installing-cupy-from-pypi)) |
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- PyTorch3D = 0.7.1 (official [INSTALL.md](https://github.com/facebookresearch/pytorch3d/blob/main/INSTALL.md), recommend [install-from-local-clone](https://github.com/facebookresearch/pytorch3d/blob/main/INSTALL.md#2-install-from-a-local-clone)) |
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```bash |
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# install required packages |
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cd ECON |
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conda env create -f environment-windows.yaml |
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conda activate econ |
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# install pytorch and cupy |
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pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 --extra-index-url https://download.pytorch.org/whl/cu113 |
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pip install -r requirements.txt |
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pip install cupy-cuda11x |
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pip install git+https://github.com/facebookresearch/[email protected] |
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# install libmesh & libvoxelize |
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cd lib/common/libmesh |
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python setup.py build_ext --inplace |
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cd ../libvoxelize |
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python setup.py build_ext --inplace |
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``` |
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## Register at [ICON's website](https://icon.is.tue.mpg.de/) |
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Required: |
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- [SMPL](http://smpl.is.tue.mpg.de/): SMPL Model (Male, Female) |
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- [SMPL-X](http://smpl-x.is.tue.mpg.de/): SMPL-X Model, used for training |
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- [SMPLIFY](http://smplify.is.tue.mpg.de/): SMPL Model (Neutral) |
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- [PIXIE](https://icon.is.tue.mpg.de/user.php): PIXIE SMPL-X estimator |
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:warning: Click **Register now** on all dependencies, then you can download them all with **ONE** account. |
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## Downloading required models and extra data (make sure to install git and wget for windows for this to work) |
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```bash |
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cd ECON |
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bash fetch_data.sh # requires username and password |
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``` |
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## Citation |
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:+1: Please consider citing these awesome HPS approaches: PyMAF-X, PIXIE |
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``` |
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@article{pymafx2022, |
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title={PyMAF-X: Towards Well-aligned Full-body Model Regression from Monocular Images}, |
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author={Zhang, Hongwen and Tian, Yating and Zhang, Yuxiang and Li, Mengcheng and An, Liang and Sun, Zhenan and Liu, Yebin}, |
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journal={arXiv preprint arXiv:2207.06400}, |
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year={2022} |
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} |
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@inproceedings{PIXIE:2021, |
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title={Collaborative Regression of Expressive Bodies using Moderation}, |
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author={Yao Feng and Vasileios Choutas and Timo Bolkart and Dimitrios Tzionas and Michael J. Black}, |
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booktitle={International Conference on 3D Vision (3DV)}, |
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year={2021} |
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} |
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``` |
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