jihoonerd/robust-motion-in-betweening

📖 Paper: Robust Motion In-betweening 🏃

Robust Motion In-betweening

PyTorch Implementation of 'Robust Motion In-betweening'

Gallery

It implements a paper "Robust Motion In-betweening".

This article is a great source to understand authors intention and idea. This repo persues exact implementation of the paper, without tweaks and modifications.

Setup

1. Follow LAFAN1 dataset's installation guide. You need to install git lfs first before cloning the dataset repo. Your directory will look like this:

   .
   |-- README.md
   |-- config
   |-- requirements.txt
   |-- rmi
   |-- test.py
   |-- tests
   |-- train.py
   `-- ubisoft-laforge-animation-dataset
   

2. Run evaluate.py to unzip and validate it. (Install numpy first if you don't have it)

   $ pip install numpy
   $ python ubisoft-laforge-animation-dataset/evaluate.py 

   With this, you will have unpacked LAFAN dataset under ubisoft-laforge-animation-dataset folder.

3. (Optional) You can use your own skeleton format as long as it fits with TorchSkeleton class. However, I recommend to use PyMO since it provides easy-to-use skeleton parser. You can install it as below:

   $ git clone https://github.com/omimo/PyMO.git
   $ cd PyMO
   $ python setup.py install

   Do not install this repo through pip install pymo or you will get a totally different package.

4. Now, install packages listed in requirements.txt. Use appropriate pytorch version depending on your device(CPU/GPU).

Training & Test

You can simply run train.py and test.py for training and inference. In case of modifying training parameters, strongly recommend to change it from config/config.yaml.

Configuration

If you want to change configuration of processes, modify config_base.yaml in /config.

Reference

• Quaternion processing utility is employed from Facebook Research's QuaterNet.

  @inproceedings{pavllo:quaternet:2018,
  title={QuaterNet: A Quaternion-based Recurrent Model for Human Motion},
  author={Pavllo, Dario and Grangier, David and Auli, Michael},
  booktitle={British Machine Vision Conference (BMVC)},
  year={2018}}
  

• LAFAN1 Dataset and its utility codes are used in this repo.

  @article{harvey2020robust,
  author    = {Félix G. Harvey and Mike Yurick and Derek Nowrouzezahrai and Christopher Pal},
  title     = {Robust Motion In-Betweening},
  booktitle = {ACM Transactions on Graphics (Proceedings of ACM SIGGRAPH)},
  publisher = {ACM},
  volume    = {39},
  number    = {4},
  year      = {2020}
  }
  

robust-motion-in-betweening's Issues

test.py error

When run python test.py, a error as following:
Traceback (most recent call last):
File "/data1/fyy/Robust-Motion-In-betweening-main/test.py", line 223, in
test()
File "/data1/fyy/Robust-Motion-In-betweening-main/test.py", line 48, in test
lafan_dataset_test = LAFAN1Dataset(lafan_path=config['data']['data_dir'], processed_data_dir=config['test']['processed_data_dir'], train=False, device=device, window=window, training_frames=training_frames)
TypeError: LAFAN1Dataset.init() got an unexpected keyword argument 'training_frames'

the link of weights is not valid

1. the link of weights is not valid
2. can you add the config for lafan1

Waiting for help!

No module named 'pymo.parsers

When I run test.py, I met an issue "No module named 'pymo.parsers'".
But I already install pymo.

Visualization

Hello, could you please to show the visualization code about specified maximo character like the provided demo in this repo? Thank you in advance!