# Support for Human3.6M Dataset Developer: Somedaywilldo (somedaywilldo@foxmail.com) ### Inverse Kinect and Reference Rendering If you want to learn movements directly from coordinates, you can use **inverse_kinect.py** and **reder_reference.py**, currently it just support a dataset created by [VideoPose3D](https://github.com/facebookresearch/VideoPose3D). Download the pre-prosessed Human3.6M dataset of Videopose3D at [here](https://www.dropbox.com/s/z5bwig0h6mww590/data_3d_h36m.npz?dl=0). After downloading the **data_3d_h36m.npz** file to this directory, then you can try to run this command: ```shell $ python render_reference.py \ --dataset_path= \ --subject=S11 \ --action=Walking \ --json_path= \ --fps=24 \ --loop=wrap \ --draw_gt ``` "--draw_gt" will draw the ground truth using **pybullet.addUserDebugLine()**, the right part of the humanoid lines will be red, other parts will be black. This is just for debugging, the render process will be much faster without the '--draw_gt' flag. If no errors shows, it should be look like this [video](https://www.youtube.com/watch?v=goew_FmUtOE). ### Contact Inverse kinect and reference rendering module is developed by Somedaywilldo. Email: somedaywilldo@foxmail.com ### Reference [1] DeepMimic: Example-Guided Deep Reinforcement Learning of Physics-Based Character Skills [[Link](https://arxiv.org/abs/1804.02717)] [2] 3D human pose estimation in video with temporal convolutions and semi-supervised training [[Link](https://arxiv.org/abs/1811.11742)]