/SMPL-model-and-code

SMPL-model and code by MPL

Primary LanguagePython

Forked from MPL

http://files.is.tuebingen.mpg.de/classner/gp/ https://github.com/classner/generating_people http://smpl.is.tue.mpg.de/ HMR https://github.com/akanazawa/hmr#requirements https://github.com/mattloper/chumpy https://github.com/facebookresearch/DensePose http://files.is.tue.mpg.de/black/papers/SMPL2015.pdf

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.

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. You need to modify chumpy's cource code a little bit to make it compatible to preprocess.py (and Python 3). Here is an instruction in Chinese about this.
  3. Run python smpl_np.py or python smpl_tf.py to see the example.