DEEP OC Audio Classification (Tensorflow)

By DEEP-Hybrid-DataCloud Consortium | Created: - Updated:

models, services, library/tensorflow, library/keras, docker

License: MIT

Build Status

This is a plug-and-play tool to perform audio classification with Deep Learning. It allows the user to classify their samples of audio as well as training their own classifier for a custom problem.

The classifier is currently pretrained on the 527 high-level classes from the AudioSet dataset.

References

Run locally on your computer

Using Docker

You can run this module directly on your computer, assuming that you have Docker installed, by following these steps:

$ docker pull deephdc/deep-oc-audio-classification-tf
$ docker run -ti -p 5000:5000 deephdc/deep-oc-audio-classification-tf

Using udocker

If you do not have Docker available or you do not want to install it, you can use udocker within a Python virtualenv:

$ virtualenv udocker
$ source udocker/bin/activate
$ git clone https://github.com/indigo-dc/udocker
$ cd udocker
$ pip install .
$ udocker pull deephdc/deep-oc-audio-classification-tf
$ udocker create deephdc/deep-oc-audio-classification-tf
$ udocker run -p 5000:5000  deephdc/deep-oc-audio-classification-tf

Once running, point your browser to http://127.0.0.1:5000/ and you will see the API documentation, where you can test the module functionality, as well as perform other actions (such as training).

For more information, refer to the user documentation.