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