80 lines
2.8 KiB
Markdown
80 lines
2.8 KiB
Markdown
<!--
|
|
* @Date: 2021-04-02 11:53:16
|
|
* @Author: Qing Shuai
|
|
* @LastEditors: Qing Shuai
|
|
* @LastEditTime: 2021-06-14 14:26:19
|
|
* @FilePath: /EasyMocapRelease/doc/quickstart.md
|
|
-->
|
|
# Quick Start
|
|
|
|
## Demo
|
|
|
|
We provide an example multiview dataset[[dropbox](https://www.dropbox.com/s/24mb7r921b1g9a7/zju-ls-feng.zip?dl=0)][[BaiduDisk](https://pan.baidu.com/s/1lvAopzYGCic3nauoQXjbPw)(vg1z)], which has 800 frames from 23 synchronized and calibrated cameras. After downloading the dataset, you can run the following example scripts.
|
|
|
|
```bash
|
|
data=path/to/data
|
|
# 0. extract the video to images
|
|
python3 scripts/preprocess/extract_video.py ${data} --handface
|
|
# 2.1 example for SMPL reconstruction
|
|
python3 apps/demo/mv1p.py ${data} --out ${data}/output/smpl --vis_det --vis_repro --undis --sub_vis 1 7 13 19 --vis_smpl
|
|
# 2.2 example for SMPL-X reconstruction
|
|
python3 apps/demo/mv1p.py ${data} --out ${data}/output/smplx --vis_det --vis_repro --undis --sub_vis 1 7 13 19 --body bodyhandface --model smplx --gender male --vis_smpl
|
|
# 2.3 example for MANO reconstruction
|
|
# MANO model is required for this part
|
|
python3 apps/demo/mv1p.py ${data} --out ${data}/output/manol --vis_det --vis_repro --undis --sub_vis 1 7 13 19 --body handl --model manol --gender male --vis_smpl
|
|
python3 apps/demo/mv1p.py ${data} --out ${data}/output/manor --vis_det --vis_repro --undis --sub_vis 1 7 13 19 --body handr --model manor --gender male --vis_smpl
|
|
```
|
|
|
|
# Demo On Your Dataset
|
|
|
|
## 0. Prepare Your Own Dataset
|
|
|
|
```bash
|
|
<seq>
|
|
├── intri.yml
|
|
├── extri.yml
|
|
└── videos
|
|
├── 1.mp4
|
|
├── 2.mp4
|
|
├── ...
|
|
├── 8.mp4
|
|
└── 9.mp4
|
|
```
|
|
|
|
The input videos are placed in `videos/`.
|
|
|
|
Here `intri.yml` and `extri.yml` store the camera intrinsici and extrinsic parameters.
|
|
|
|
See [`apps/calibration/Readme`](../apps/calibration/Readme.md) for instruction of camera calibration.
|
|
|
|
See [`apps/calibration/camera_parameters`](../apps/calibration/camera_parameters.md) for the format of camera parameters.
|
|
|
|
### 1. Run [OpenPose](https://github.com/CMU-Perceptual-Computing-Lab/openpose)
|
|
|
|
```bash
|
|
data=path/to/data
|
|
out=path/to/output
|
|
python3 scripts/preprocess/extract_video.py ${data} --openpose <openpose_path> --handface
|
|
```
|
|
|
|
- `--openpose`: specify the openpose path
|
|
- `--handface`: detect hands and face keypoints
|
|
|
|
### 2. Run the code
|
|
|
|
The input flags:
|
|
|
|
- `--undis`: use to undistort the images
|
|
- `--start, --end`: control the begin and end number of frames.
|
|
|
|
The output flags:
|
|
|
|
- `--vis_det`: visualize the detection
|
|
- `--vis_repro`: visualize the reprojection
|
|
- `--sub_vis`: use to specify the views to visualize. If not set, the code will use all views
|
|
- `--vis_smpl`: use to render the SMPL mesh to images.
|
|
- `--write_smpl_full`: use to write the full poses of the SMPL parameters
|
|
|
|
### 3. Output
|
|
|
|
Please refer to [output.md](../doc/02_output.md) |