SMPL

Numpy and Tensorflow implementation of SMPL model. For any questions, feel free to contact me.

Overview

I wrote this because the author-provided implementation was mainly based on chumpy in Python 2, which is kind of unpopular. Meanwhile, the official one cannot run on GPU.

This numpy version is faster(since some computation is re-wrote in a vectorized manner) and easier to understand(hope so), and the tensorflow version can run on GPU.

For more details about SMPL model, see SMPL.

Also, I provide a file CMU_Mocap_Markers.pp, which gives the correspondence between SMPL model and CMU Mocap Dataset markers in .c3d files. For more detailes see the Usage section.

Usage

1. Download the model file here.
2. Run python preprocess.py /PATH/TO/THE/DOWNLOADED/MODEL to preprocess the official model. preprocess.py will create a new file model.pkl. smpl_np.py and smpl_tf.py both rely on model.pkl. NOTE: the official pickle model contains chumpy object, so prerocess.py requires chumpy to extract official model.
3. Run python smpl_np.py to see the example.
4. About CMU_Mocap_Markers.pp: you can first generate a standard SMPL model mesh(zero pose and zero beta), open it in MeshLab, and load this file in MeshLab. It gives 42 markers' position on the model surface. I simply mark these things by hand so there might be some small errors.

One More Thing

If this repo is used in any publication or project, it would be nice to let me know. I will be very happy and encouraged =)