From 6ca93121090c33fac979795d9560daee419d0698 Mon Sep 17 00:00:00 2001 From: shuaiqing Date: Fri, 2 Apr 2021 12:28:46 +0800 Subject: [PATCH] update Readme --- Readme.md | 198 +++++++++++----------------------- doc/feng/mv1pmf-smplx.gif | Bin 0 -> 4056445 bytes doc/installation.md | 53 +++++++++ doc/notquickstart.md | 61 +++++++++++ doc/quickstart.md | 26 +++++ doc/todo.md | 10 ++ scripts/calibration/Readme.md | 9 +- 7 files changed, 219 insertions(+), 138 deletions(-) create mode 100644 doc/feng/mv1pmf-smplx.gif create mode 100644 doc/installation.md create mode 100644 doc/notquickstart.md create mode 100644 doc/quickstart.md create mode 100644 doc/todo.md diff --git a/Readme.md b/Readme.md index f3669d4..887262e 100644 --- a/Readme.md +++ b/Readme.md @@ -2,164 +2,88 @@ * @Date: 2021-01-13 20:32:12 * @Author: Qing Shuai * @LastEditors: Qing Shuai - * @LastEditTime: 2021-03-13 21:52:17 + * @LastEditTime: 2021-04-02 12:26:56 * @FilePath: /EasyMocapRelease/Readme.md --> # EasyMocap -**EasyMocap** is an open-source toolbox for **markerless human motion capture** from RGB videos. +**EasyMocap** is an open-source toolbox for **markerless human motion capture** from RGB videos. In this project, we provide a lot of motion capture demos in different settings. -In this project, we provide the basic code for fitting SMPL[1]/SMPL+H[2]/SMPLX[3] model to capture body+hand+face poses from multiple views. +![python](https://img.shields.io/github/languages/top/zju3dv/EasyMocap) +![star](https://img.shields.io/github/stars/zju3dv/EasyMocap?style=social) -|Input(23 views)|:heavy_check_mark: Skeleton|:heavy_check_mark: SMPL| -|----|----|----| -|![input](doc/feng/000400.jpg)|![repro](doc/feng/skel.gif)|![smpl](doc/feng/smplx.gif)| +---- -> We plan to intergrate more interesting algorithms, please stay tuned! +## Core features -1. [[CVPR19] Multi-Person from Multiple Views](https://github.com/zju3dv/mvpose) -2. [[ECCV20] Mocap from Multiple **Uncalibrated** and **Unsynchronized** Videos](https://arxiv.org/pdf/2008.07931.pdf) -![](doc/imocap/frame_00036_036.jpg) -3. [[CVPR21] Dense Reconstruction and View Synthesis from **Sparse Views**](https://zju3dv.github.io/neuralbody/) -4. [[CVPR21] Reconstructing 3D Human Pose by Watching Humans in the **Mirror**](https://zju3dv.github.io/Mirrored-Human/) - - - - - -
图片名称图片名称
+### Multiple views of single person + +This is the basic code for fitting SMPL[1]/SMPL+H[2]/SMPL-X[3] model to capture body+hand+face poses from multiple views. + +
+ +
+ Videos are from ZJU-MoCap, with 23 calibrated and synchronized cameras. +
+ +### Internet video with a mirror + +[![report](https://img.shields.io/badge/mirrored-link-red)](https://arxiv.org/pdf/2104.00340.pdf) + +
+ +
+ This video is from Youtube. +
+ +### Multiple Internet videos with a specific action (Coming soon) + +[![report](https://img.shields.io/badge/imocap-link-red)](https://arxiv.org/pdf/2008.07931.pdf) + +
+ +
+ +### Multiple views of multiple people (Comming soon) + +[![report](https://img.shields.io/badge/mvpose-link-red)](https://arxiv.org/pdf/1901.04111.pdf) + + +### Others +This project is used by many other projects: +- [[CVPR21] Dense Reconstruction and View Synthesis from **Sparse Views**](https://zju3dv.github.io/neuralbody/) + +## Other features + +- [Camera calibration](./doc/todo.md) +- [Pose guided synchronization](./doc/todo.md) +- [Annotator](./doc/todo.md) +- [Exporting of multiple data formats(bvh, asf/amc, ...)](./doc/todo.md) + +## Updates +- 04/02/2021: We are now rebuilding our project for `v0.2`, please stay tuned. `v0.1` is available at [this link](https://github.com/zju3dv/EasyMocap/releases/tag/v0.1). ## Installation -### 1. Download SMPL models - -This step is the same as [smplx](https://github.com/vchoutas/smplx#model-loading). - -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. - -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. - -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. - -**Place them as following:** - -```bash -data -└── smplx - ├── J_regressor_body25.npy - ├── J_regressor_body25_smplh.txt - ├── J_regressor_body25_smplx.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 -``` - -### 2. Requirements - -- python>=3.6 -- torch==1.4.0 -- torchvision==0.5.0 -- opencv-python -- [pyrender](https://pyrender.readthedocs.io/en/latest/install/index.html#python-installation): for visualization -- chumpy: for loading SMPL model -- OpenPose[4]: for 2D pose - -Some of python libraries can be found in `requirements.txt`. You can test different version of PyTorch. +See [doc/install](./doc/install.md) for more instructions. ## Quick Start -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 -out=path/to/output -# 0. extract the video to images -python3 scripts/preprocess/extract_video.py ${data} -# 1. example for skeleton reconstruction -python3 code/demo_mv1pmf_skel.py ${data} --out ${out} --vis_det --vis_repro --undis --sub_vis 1 7 13 19 -# 2.1 example for SMPL reconstruction -python3 code/demo_mv1pmf_smpl.py ${data} --out ${out} --end 300 --vis_smpl --undis --sub_vis 1 7 13 19 --gender male -# 2.2 example for SMPL-X reconstruction -python3 code/demo_mv1pmf_smpl.py ${data} --out ${out} --undis --body bodyhandface --sub_vis 1 7 13 19 --start 400 --model smplx --vis_smpl --gender male -# 3.1 example for rendering SMPLX to ${out}/smpl -python3 code/vis_render.py ${data} --out ${out} --skel ${out}/smpl --model smplx --gender male --undis --start 400 --sub_vis 1 -# 3.2 example for rendering skeleton of SMPL to ${out}/smplskel -python3 code/vis_render.py ${data} --out ${out} --skel ${out}/smpl --model smplx --gender male --undis --start 400 --sub_vis 1 --type smplskel --body bodyhandface -``` +See [doc/quickstart](doc/quickstart.md) for more instructions. ## Not Quick Start -### 0. Prepare Your Own Dataset -```bash -zju-ls-feng -├── 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. For example, if the name of a video is `1.mp4`, then there must exist `K_1`, `dist_1` in `intri.yml`, and `R_1((3, 1), rotation vector of camera)`, `T_1(3, 1)` in `extri.yml`. The file format is following [OpenCV format](https://docs.opencv.org/master/dd/d74/tutorial_file_input_output_with_xml_yml.html). - -### 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 --handface -``` - -- `--openpose`: specify the openpose path -- `--handface`: detect hands and face keypoints - -### 2. Run the code - -```bash -# 1. example for skeleton reconstruction -python3 code/demo_mv1pmf_skel.py ${data} --out ${out} --vis_det --vis_repro --undis --sub_vis 1 7 13 19 -# 2. example for SMPL reconstruction -python3 code/demo_mv1pmf_smpl.py ${data} --out ${out} --end 300 --vis_smpl --undis --sub_vis 1 7 13 19 -``` - -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. - -### 3. Output - -Please refer to [output.md](doc/02_output.md) +See [doc/notquickstart](doc/notquickstart.md) for more instructions. ## Evaluation -In our code, we do not set the best weight parameters, you can adjust these according your data. If you find a set of good weights, feel free to tell me. +The weight parameters can be set according your data. -We will add more quantitative reports in [doc/evaluation.md](doc/evaluation.md) +More quantitative reports will be added in [doc/evaluation.md](doc/evaluation.md) ## Acknowledgements + Here are the great works this project is built upon: - SMPL models and layer are from MPII [SMPL-X model](https://github.com/vchoutas/smplx). @@ -169,12 +93,14 @@ Here are the great works this project is built upon: We also would like to thank Wenduo Feng who is the performer in the sample data. ## Contact -Please open an issue if you have any questions. + +Please open an issue if you have any questions. 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b/doc/installation.md @@ -0,0 +1,53 @@ + +# EasyMocap - Installation + +### 1. Download SMPL models + +This step is the same as [smplx](https://github.com/vchoutas/smplx#model-loading). + +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. + +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. + +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. + +**Place them as following:** + +```bash +data +└── smplx + ├── J_regressor_body25.npy + ├── J_regressor_body25_smplh.txt + ├── J_regressor_body25_smplx.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 +``` + +### 2. Requirements + +- python>=3.6 +- torch==1.4.0 +- torchvision==0.5.0 +- opencv-python +- [pyrender](https://pyrender.readthedocs.io/en/latest/install/index.html#python-installation): for visualization +- chumpy: for loading SMPL model +- OpenPose[4]: for 2D pose + +Some of python libraries can be found in `requirements.txt`. You can test different version of PyTorch. \ No newline at end of file diff --git a/doc/notquickstart.md b/doc/notquickstart.md new file mode 100644 index 0000000..19dc502 --- /dev/null +++ b/doc/notquickstart.md @@ -0,0 +1,61 @@ + + +### 0. Prepare Your Own Dataset + +```bash +zju-ls-feng +├── 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. For example, if the name of a video is `1.mp4`, then there must exist `K_1`, `dist_1` in `intri.yml`, and `R_1((3, 1), rotation vector of camera)`, `T_1(3, 1)` in `extri.yml`. The file format is following [OpenCV format](https://docs.opencv.org/master/dd/d74/tutorial_file_input_output_with_xml_yml.html). + +### 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 --handface +``` + +- `--openpose`: specify the openpose path +- `--handface`: detect hands and face keypoints + +### 2. Run the code + +```bash +# 1. example for skeleton reconstruction +python3 code/demo_mv1pmf_skel.py ${data} --out ${out} --vis_det --vis_repro --undis --sub_vis 1 7 13 19 +# 2. example for SMPL reconstruction +python3 code/demo_mv1pmf_smpl.py ${data} --out ${out} --end 300 --vis_smpl --undis --sub_vis 1 7 13 19 +``` + +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. + +### 3. Output + +Please refer to [output.md](doc/02_output.md) \ No newline at end of file diff --git a/doc/quickstart.md b/doc/quickstart.md new file mode 100644 index 0000000..54e15d1 --- /dev/null +++ b/doc/quickstart.md @@ -0,0 +1,26 @@ + + +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 +out=path/to/output +# 0. extract the video to images +python3 scripts/preprocess/extract_video.py ${data} +# 1. example for skeleton reconstruction +python3 code/demo_mv1pmf_skel.py ${data} --out ${out} --vis_det --vis_repro --undis --sub_vis 1 7 13 19 +# 2.1 example for SMPL reconstruction +python3 code/demo_mv1pmf_smpl.py ${data} --out ${out} --end 300 --vis_smpl --undis --sub_vis 1 7 13 19 --gender male +# 2.2 example for SMPL-X reconstruction +python3 code/demo_mv1pmf_smpl.py ${data} --out ${out} --undis --body bodyhandface --sub_vis 1 7 13 19 --start 400 --model smplx --vis_smpl --gender male +# 3.1 example for rendering SMPLX to ${out}/smpl +python3 code/vis_render.py ${data} --out ${out} --skel ${out}/smpl --model smplx --gender male --undis --start 400 --sub_vis 1 +# 3.2 example for rendering skeleton of SMPL to ${out}/smplskel +python3 code/vis_render.py ${data} --out ${out} --skel ${out}/smpl --model smplx --gender male --undis --start 400 --sub_vis 1 --type smplskel --body bodyhandface +``` \ No newline at end of file diff --git a/doc/todo.md b/doc/todo.md new file mode 100644 index 0000000..c7d403f --- /dev/null +++ b/doc/todo.md @@ -0,0 +1,10 @@ + +# TODO + +This part is coming soon, please stay tuned. \ No newline at end of file diff --git a/scripts/calibration/Readme.md b/scripts/calibration/Readme.md index 720b393..2d089c4 100644 --- a/scripts/calibration/Readme.md +++ b/scripts/calibration/Readme.md @@ -2,15 +2,20 @@ * @Date: 2021-03-02 16:14:48 * @Author: Qing Shuai * @LastEditors: Qing Shuai - * @LastEditTime: 2021-03-02 17:09:02 + * @LastEditTime: 2021-03-27 21:56:34 * @FilePath: /EasyMocap/scripts/calibration/Readme.md --> # Camera Calibration +Before reading this document, you should read the OpenCV-Python Tutorials of [Camera Calibration](https://docs.opencv.org/master/dc/dbb/tutorial_py_calibration.html) carefully. + +## Some Tips +1. Use a chessboard as big as possible. +2. You must keep the same resolution during all the steps. ## 0. Prepare your chessboard ## 1. Distortion and Intrinsic Parameter Calibration -TODO + ## 2. Extrinsic Parameter Calibration Prepare your images as following:

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