This repository includes a Django-based API to serve a deep learning model previously trained. A simple front end is provided to give non-power users the possibility to interact via UI.
The model used is an Emotion Classifier trained with audio files of the RAVDESS dataset. More info here: https://github.com/marcogdepinto/Emotion-Classification-Ravdess
The vision of this project is to show that artificial intelligence applications can be shipped to production, consumed by users and have a real impact. This is just a research project, but hope it can inspire someone to build something big :)
The user journey start on the index page at /index/
where it is possible to choose if
- Upload a new file on the server;
- Delete a file from the server (WIP);
- Make a prediction on a file already on the server;
Choosing Upload your audio file
the user will be redirected to a modified home page. The user will be asked to pick a file from his computer. The UI will confirm if the operation has been successful.
Choosing Make your prediction
the user will be redirected to a modified home page. In this page, it will be possible to see a list of the files already on the server. Following the path media/{filename}
it will be also possible to listen to the audio file.
After clicking on Submit
, the user will be redirected to a modified home page that will include the prediction made by the Keras model for the file selected.
There is a short demo of the first version on YouTube: https://youtu.be/86HhxTRL3_c . The UI has been updated since then, as now manages all the actions extending the index templates with the action templates. The above pictures are updated with the new workflow.
How to start the server and try it
git clone https://github.com/marcogdepinto/Django-Emotion-Classification-Ravdess-API.git
$ pip install -r requirements.txt
- Open a terminal window,
cd
into the project folder and runpython manage.py runserver
.
How to run the tests
python manage.py test
Other important topics
The Keras model is stored in the models
folder.
gitmedia
folder includes the pictures used for this README.
media
folder includes the audio files loaded using the server.
If you do not know how Django works, you can skip to the App/views.py
file to review the high level logic of the API.
User Stories
What is the plan for the future and what it is currently ongoing: https://github.com/marcogdepinto/Django-Emotion-Classification-Ravdess-API/projects/2