AlphaMocap

An adapted version of EasyMocap for my own use. With the help of my adapted version of AlphaPose and some new tricks, this repo is targeted to achieve human motion capture in crowded scenes.

<sup>Videos with 42 calibrated and synchronized cameras.

Reconstruction of 3D skeleton with tracking and fitted SMPL.</sup>

Data Formats

The data is organized as follows:

<case_name>
|-- videos
    |-- 01.mp4
    |-- 02.mp4
    ...
|-- images
    |-- {camera_id}
        |-- {frames}.jpg
        ...
    ...
|--extri.yml
|--intri.yml

install

SMPL models

This step is the same as smplx.

To download the SMPL model go to this (male and female models, version 1.0.0, 10 shape PCs) and this (gender neutral model) project website and register to get access to the downloads section.

To download the SMPL+H model go to this project website and register to get access to the downloads section.

To download the SMPL-X model go to this project website and register to get access to the downloads section.

Place them as following:

data
└── smplx
    ├── J_regressor_body25.npy
    ├── J_regressor_body25_smplh.txt
    ├── J_regressor_body25_smplx.txt
    ├── J_regressor_mano_LEFT.txt
    ├── J_regressor_mano_RIGHT.txt
    ├── smpl
    │   ├── SMPL_FEMALE.pkl
    │   ├── SMPL_MALE.pkl
    │   └── SMPL_NEUTRAL.pkl
    ├── smplh
    │   ├── MANO_LEFT.pkl
    │   ├── MANO_RIGHT.pkl
    │   ├── SMPLH_FEMALE.pkl
    │   └── SMPLH_MALE.pkl
    └── smplx
        ├── SMPLX_FEMALE.pkl
        ├── SMPLX_MALE.pkl
        └── SMPLX_NEUTRAL.pkl

Requirements

• MyAlphaPose
• conda create -n alphamocap python==3.7.0
• conda install pytorch==1.6.0 torchvision==0.7.0 cudatoolkit=10.2 -c pytorch
• pip install -r requirements.txt
• python3 setup.py develop --user

Running

data=/home/wangyiming/AlphaMocap/dataset/jhd_1min/

conda activate alphapose
python scripts/preprocess/extract_video.py ${data} --mode alphapose --use-video

conda activate alphamocap
python apps/demo/my_mvmp.py ${data} --out ${data}/output --annot annots --cfg config/exp/mvmp1f_test.yml --undis --vis_det --vis_repro --vis3d --vis_match --sub_vis 01 15 25 40

python apps/demo/smpl_from_keypoints.py ${data} --skel ${data}/output/keypoints3d --out ${data}/output/smpl --verbose --opts smooth_poses 1e-1

Common Issues

pyglet.canvas.xlib.NoSuchDisplayException: Cannot connect to "None"