This repository contains the code for the paper "Seamless Monitoring of Stress Levels Leveraging a Universal Model for Time Sequences".
The following command installs the required dependencies:
# Install the dependencies
pip install -r requirements.txt
The following datasets are used in this project:
The datasets are preprocessed using the following steps:
# Download and extract the datasets
./data/download-datasets.sh
# Preprocess the datasets
python preprocess.py
Ensure to be logged and to set your WANDB_USER in the file run.py
to log the results to Weights & Biases.
The following command launches the training of the models:
# Train the models
python run.py
The evaluation results are processed from logged runs on Weights & Biases. To retrieve the evaluation results, run the following command:
# Evaluate the models
python results.py
This project use the code from the repositiories of UniTS, TranAD and HypAD for the implementation of the models.