myojos / fall-detection

ojos-fall-detection

A repository containing the code related to the fall detection models used by OJOS

Project Organization

├── Makefile           <- Makefile with commands like `make data` or `make train`
├── README.md          <- The top-level README for developers using this project.
├── data
│   ├── processed      <- The final, canonical data sets for modeling.
│   └── raw            <- The original, immutable data dump.
│
├── results            <- Everything that can be shown to the outside world
│   ├── models         <- Trained and serialized models, model predictions, or model summaries
│   └── reports        <- Generated analysis as HTML, PDF, LaTeX, etc.
│
├── notebooks          <- Jupyter notebooks. Naming convention is a number (for ordering),
│   │                     the creator's initials, and a short `-` delimited description, e.g.
│   │                     `1.0-jqp-initial-data-exploration` (<step>-<ghuser>-<description>.ipynb).
│   │
│   ├── exploratory    <- Initial explorations
│   └── reports        <- More polished work that can be exported as HTML to the reports directory
│
├── environment.yml    <- The conda environment file for reproducing the analysis environment, e.g.
│                         generated with `conda env export > environment.yml`
│
├── setup.py           <- makes project pip installable (pip install -e .) so ojosfd can be imported
└── ojosfd             <- Source code for use in this project. 
    ├── __init__.py    <- Makes it a Python module
    │
    ├── datasets       <- Pytorch datasets for this project
    │
    ├── utils          <- Pytorch modules that are useful for training (trasnformers, pipelines, etc...)
    │
    ├── models         <- Pytorch models
    │
    └── visualization  <- Scripts to create exploratory and results oriented visualizations
        └── visualize.py

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