ImDy: Human Inverse Dynamics from Imitated Observations

The code release is in progress.

Environment Setup

Create a conda environment from environment.yml: conda env create -f environment.yml

Data Acquisition

For data access, please get in touch with [email protected].

The file structure should be

- utils
- data
 |- raw_test
   |- grf.pkl
   |- pos.pkl
   |- rot.pkl
   |- torque.pkl
   |- weight.pkl
 |- raw_train
   |- ...
 |- nimble_test
   |- figure
     |- walking
   |- walking.pkl
- osim
 |- Geometry
   |- .....
 |- Rajagopal2015_passiveCal_hipAbdMoved_noArms.osim
 |- vtp_to_ply.py

- models
 |- containing SMPL models from https://smpl.is.tue.mpg.de
 |- containing Rajagopal2015 model without arm from https://addbiomechanics.org/download_data.html
- convert.py
- adb_motion_visualize.py

Run python convert.py to convert the raw data into a different format with per-sample pickle files including axis-angle format SMPL parameters, joints, and markers. The torques stored are acquired by summing two consecutive torques in the simulation.

Run adb_motion_visualize.py to visualize the motion from Addbiomechanics Dataset frame by frame. In line 64, you could change the angles of camera to better visualize the motion.

scene.set_camera(angles=(-pi/8,pi/2+pi/4,0),distance=2.5)