Dependencies

We use python 3 for this project.

Make sure FFMPEG is installed, or install by sudo apt install ffmpeg

Install the python packages dependencies by pip install -r requirements.txt

Preparing Data

Download the data from Total Capture official site.

Please Note that we have NO permission to redistribute this dataset. Please never ask us for a copy.

Then organize the data in below structure (put all data in ./data/totalcapture):

./data/totalcapture
├── calibration.cal
├── s1
│   ├── acting1
│   │   ├── acting1_BlenderZXY_YmZ.bvh
│   │   ├── acting1_Xsens_AuxFields.sensors
│   │   ├── gt_skel_gbl_ori.txt
│   │   ├── gt_skel_gbl_pos.txt
│   │   ├── s1_acting1_calib_imu_bone.txt
│   │   ├── s1_acting1_calib_imu_ref.txt
│   │   ├── s1_acting1_Xsens.sensors
│   │   ├── TC_S1_acting1_cam1.mp4
│   │   ├── TC_S1_acting1_cam2.mp4
│   │   ├── TC_S1_acting1_cam3.mp4
│   │   ├── TC_S1_acting1_cam4.mp4
│   │   ├── TC_S1_acting1_cam5.mp4
│   │   ├── TC_S1_acting1_cam6.mp4
│   │   ├── TC_S1_acting1_cam7.mp4
│   │   └── TC_S1_acting1_cam8.mp4
│   ├── acting2
│   │   ├── ...
│   ├── ...
├── s2
...

Usage

python gendata/gendb.py

# if cannot import tools
# export PYTHONPATH=".:$PYTHONPATH"; python gendata/gendb.py  

Options: You can change options in gendata/config.yaml, e.g.

• save_frame: whether extract frames from the videos
• gen_train: generate dataset for training
• gen_test: generate dataset for testing

Finally, you should have a bunch of images and two .pkl files in the ./data/images. Move the .pkl files to ../annot directory, and you get

./data/
├── images
│   ├── s_01_act_01_subact_01_ca_01
│   │   ├── 000000.jpg
│   │   ├── ...
│   ├── ...
├── annot
│   ├── totalcapture_train.pkl
│   ├── totalcapture_validation.pkl

If you want to archive all images in one zip file which is more efficient to be transferred to server or cloud storage, make sure your pwd is parent directory of images/, then run zip -0 -r images.zip images/.