The Tornado-based web server provdes a REST interface to an SQLite database for the management of skeleton animation data and machine learning models using a collections, tags and skeletons. The database is integrated with anim_utils using a Python client. To visualize the motions in the database a Unity WebGL client is provided.

To edit and annotate data in the database, the motion_preprocessing_tool can be used. Motion editing functions can also be registered as data transforms to be executed via the web client on a batch of motions.

1. Install Python 3.6 or above in a virtual environment.

2. Clone the repository with all submodules.

git clone --recursive git@github.com:eherr/motion_database_server.git

3. Install the base packages for animation data editing and Python API

pip install git+https://github.com/eherr/anim_utils

pip install git+https://github.com/eherr/motion_db_interface

4. Install other dependencies

pip install -r requirements.txt

5. Create a new database:

python create_database.py PROJECT_NAME ADMIN_NAME ADMIN_PASSWORD ADMIN_EMAIL

6. Import default data types and data transforms:

python import_data_types.py default_data_types.json

7. Add a first skeleton using an example BVH file:

python import_skeleton.py SKELETON_NAME BVH_FILE

8. Import BVH files from a directory specifying the previously imported skeleton:

python import_bvh_from_directory.py PROJECT_NAME SKELETON_NAME DIRECTORY_PATH

9. Start the web server:

python main.py

10. Build the web client using angular:

cd webclient 
ng build

11. Open the URL "localhost:8888" in browser to view the using the web client. Login using the admin user, to be able to upload motions. The port can be changed in db_server_config.json.

12. To upload and edit animations or upload and edit skeletons for retargeting you can also use the motion_preprocessing_tool.

Herrmann, E., Du, H., Antalki, A., Rubinstein, D., Schubotz, R., Sprenger, J., Hosseini, S., Cheema, N., Zinnikus, I., Manns, M., Fischer, K. Slusallek, P., "Motion Data and Model Management for Applied Statistical Motion Synthesis" In: Proceedings of the Conference on Smart Tools and Applications in Computer Graphics. Eurographics Association, 2019.

Copyright (c) 2019 DFKI GmbH.
MIT License, see the LICENSE file.