A model for emotion classification based on text and audio.
Give audio and text as input and get back the dominant emotion.
Be sure to add double quotes to lines containing one or more commas for .csv files.
For graphical interface, use https://a62-emotion.herokuapp.com/index and upload .wav and .csv files.
In [1]: import requests
In [2]: with open("./data/raw_sample/audio/UlTJmndbGHM.wav", "rb") as fd:
...: response = requests.post("https://a62-emotion.herokuapp.com/predict", files={'files[]': fd})
...:
In [3]: response.json()
Out[3]: {'predictions_audio': {'UlTJmndbGHM.wav': 'positive'}, 'predictions_texte': {}}
curl -F 'files[]=@/home/user/emotion/data/raw_sample/audio/DatH-ra0VKY.wav' -F 'files[]=@/home/user/file.csv' https://a62-emotion.herokuapp.com/predict
{"predictions_audio":{"DatH-ra0VKY.wav":"positive"},"predictions_texte":{"file.csv":{"DAMON WILLIAMS: I am the Senior Vice President and Chief Education and Youth Development Officer for the Boys and Girls Clubs of America.":"neutral","In that role, I help to shape the education policy and youth development direction for more than 4,000 clubs that are part of our federated network, having an impact on more than 4 million young people across this nation.":"positive"}}}
POST /predict
| Parameter | Type | Description |
|---|---|---|
files[] | File | Required. File(s) to process |
Install emotion with pip
pip install a62-emotion
To run this project, you will need to add the following environment variables to your .env file
GDRIVE_CREDENTIALS_DATA
FLASK_SECRET_KEY
For audio, you will need to install libsndfile1 (and libsndfile1-dev on some systems)
sudo apt-get install libsndfile1
Be sure to have python 3.8.13 as the python executable
python3 --version
To install Poetry, run:
curl -sSL https://install.python-poetry.org | POETRY_VERSION=1.1.14 python3 - --yes
(Optional) To install the Heroku CLI, follow these steps
https://devcenter.heroku.com/articles/heroku-cli#standalone-installation-with-a-tarball
Clone the project
git clone https://github.com/philipgaudreau/emotion
Go to the project directory
cd emotion
Install dependencies (add flag --without-dev if you do not want development dependencies)
poetry install
Activate the virtual environment
poetry shell
Pull cloud data if needed (You will need to export GDRIVE_CREDENTIALS_DATA)
dvc pull [<.dvc file>]
Start using the command line interface (Not implemented yet)
emotion --help
To run tests, run the following command (development dependencies must be installed)
pytest tests
This project is automatically deployed on Heroku when a PR is merged. To test locally, run (You will need to export FLASK_SECRET_KEY)
heroku local
CI: GitHub Actions, DVC
CD: GitHub Actions, Heroku
Frameworks: Scikit-learn, Tensorflow, Flask
Versionning: Poetry, SemVer
Cloud: G-Drive, GitHub, Heroku
If you have any feedback, please reach out to one of us.
We are on our way to finish a degree in Machine Learning.
FAQs
A model for emotion classification based on text and audio.
We found that a62-emotion demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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