87 lines
2.8 KiB
Markdown
87 lines
2.8 KiB
Markdown
<!--
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* @Date: 2021-04-02 11:52:33
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* @Author: Qing Shuai
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* @LastEditors: Qing Shuai
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* @LastEditTime: 2021-06-21 21:18:45
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* @FilePath: /EasyMocapRelease/doc/installation.md
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-->
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# EasyMocap - Installation
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## 0. Download models
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## 0.1 SMPL models
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This step is the same as [smplx](https://github.com/vchoutas/smplx#model-loading).
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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.
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To download the *SMPL+H* model go to [this project website](http://mano.is.tue.mpg.de) and register to get access to the downloads section.
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To download the *SMPL-X* model go to [this project website](https://smpl-x.is.tue.mpg.de) and register to get access to the downloads section.
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**Place them as following:**
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```bash
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data
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└── smplx
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├── J_regressor_body25.npy
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├── J_regressor_body25_smplh.txt
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├── J_regressor_body25_smplx.txt
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├── J_regressor_mano_LEFT.txt
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├── J_regressor_mano_RIGHT.txt
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├── smpl
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│ ├── SMPL_FEMALE.pkl
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│ ├── SMPL_MALE.pkl
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│ └── SMPL_NEUTRAL.pkl
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├── smplh
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│ ├── MANO_LEFT.pkl
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│ ├── MANO_RIGHT.pkl
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│ ├── SMPLH_FEMALE.pkl
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│ └── SMPLH_MALE.pkl
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└── smplx
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├── SMPLX_FEMALE.pkl
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├── SMPLX_MALE.pkl
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└── SMPLX_NEUTRAL.pkl
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```
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## 0.2 (Optional) SPIN model
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This part is used in `1v1p*.py`. You can skip this step if you only use the multiple views dataset.
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Download pretrained SPIN model [here](http://visiondata.cis.upenn.edu/spin/model_checkpoint.pt) and place it to `data/models/spin_checkpoints.pt`.
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Fetch the extra data [here](http://visiondata.cis.upenn.edu/spin/data.tar.gz) and place the `smpl_mean_params.npz` to `data/models/smpl_mean_params.npz`.
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## 0.3 (Optional) 2D model
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You can skip this step if you use openpose as your human keypoints detector.
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Download [yolov4.weights]() and place it into `data/models/yolov4.weights`.
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Download pretrained HRNet [weight]() and place it into `data/models/pose_hrnet_w48_384x288.pth`.
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```bash
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data
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└── models
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├── smpl_mean_params.npz
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├── spin_checkpoint.pt
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├── pose_hrnet_w48_384x288.pth
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└── yolov4.weights
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```
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## 2. Requirements
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- python>=3.6
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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](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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- OpenPose[4]: for 2D pose
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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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## 3. Install
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```bash
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python3 setup.py develop --user
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``` |