PathoOpenGait

PathoOpenGait: Pathological Gait Analysis With an Open-Source Cloud-Enabled Platform Empowered by Semi-Supervised Learning

For the details, please refer to our papar published in IEEE journal of biomedical and health informatics.

System design (Microservice architecture)

Get started

1. Please execute setup.sh to download pretrained weights for several models.

   $ ./setup.sh
   

2. Please modify database/sql/create_user.sql first to create accounts for default admin users.
3. Please create an .env file with the following format.

   JWT_SECRET_KEY=...
   MYSQL_ROOT_PASSWORD=...
   SQLALCHEMY_DATABASE_URI=mysql+pymysql://root:<MYSQL_ROOT_PASSWORD>@db:3306/ndd

4. Please make sure the model weights are present in the following path

   ./backend/algorithms/gait_basic/VideoPose3D/checkpoint/pretrained_h36m_detectron_coco.bin
   ./backend/algorithms/gait_basic/gait_study_semi_turn_time/weights/semi_vanilla_v2/epoch_94.pth
   

5. (Optional) By default, the video will be provided with a black backgound and full keypoints. If you would like to show the patients' body and the surrounding, please modify backend/routers/user.py

   # video_path = f'data/{video_uuid}/out/render-black-background.mp4'  # default one
   video_path = f'data/{video_uuid}/out/render.mp4'  # change to this one

6. Execute

   $ docker-compose up --build -d
   

Customized

Add new algorithms (models) or new data type

1. Please create a folder: backend/algorithms/<YOUR_ALGORITHM_NAME>.
2. Your folder should have a __init__.py and main files.
3. In main.py, add from .._analyzer import Analyzer.
4. Create a class for your algorithm, which should inherit Analyzer.

   class CustomizedAnalyzer(Analyzer):
       def __init__(
           self,
           ...
       ):
           ...
   
       def run(
           self,
           data_root_dir,
           file_id,  # '2021-04-01-1-4'
       ) -> t.List[t.Dict[str, t.Any]]:
           ...

5. Make sure the return of run is in the format of t.List[t.Dict[str, t.Any]].
6. Modify MAPPING in backend/inference/config.py. For example,

YOUR_MODELS = {
    'your_model_name_1': CustomizedAnalyzer,
    'your_model_name_2': CustomizedAnalyzerV2,
}

MAPPING = {
    'data_type': YOUR_MODELS,
}

7. Finish. If you need to modify the input interface or anything else, please directly modify those files.

Citation

@article{ho2024pathological,
  title={Pathological Gait Analysis With an Open-Source Cloud-Enabled Platform Empowered by Semi-Supervised Learning-PathoOpenGait},
  author={Ho, Ming-Yang and Kuo, Ming-Che and Chen, Ciao-Sin and Wu, Ruey-Meei and Chuang, Ching-Chi and Shih, Chi-Sheng and Tseng, Yufeng Jane},
  journal={IEEE journal of biomedical and health informatics},
  volume={28},
  number={2},
  pages={1066--1077},
  year={2024}
}