Metadata-Version: 2.1
Name: disco_sound
Version: 0.0.2
Summary: DISCO Implements Sound Classification Obediently.
Author-email: Kayla Irish <kayla.irish@umontana.edu>, Thomas Colligan <thomas.colligan@umontana.edu>
Description-Content-Type: text/markdown
Requires-Dist: numpy
Requires-Dist: matplotlib
Requires-Dist: pytorch_lightning
Requires-Dist: torchaudio
Requires-Dist: pomegranate
Requires-Dist: pyyaml
Requires-Dist: numpy<1.24.0
Requires-Dist: tensorboard
Requires-Dist: sacred
Requires-Dist: pandas
Requires-Dist: tqdm
Requires-Dist: scikit-learn
Project-URL: Home, https://github.com/TravisWheelerLab/disco

[![Generic badge](https://img.shields.io/badge/Contributions-Welcome-brightgreen.svg)](CONTRIBUTING.md)
<a href="https://github.com/psf/black"><img alt="Code style: black" src="https://img.shields.io/badge/code%20style-black-000000.svg"></a>

# DISCO Implements Sound Classification Obediently
This tool annotates sound files using neural networks. It uses a 1D architecture based on U-Net with additional
post-processing heuristics including a Hidden Markov Model.

DISCO is ideal for long streams of sound that need to be classified over time, producing output fully compatible with
The Cornell Lab of Ornithology's sound tool [RAVEN](https://ravensoundsoftware.com/). Work is currently underway to
annotate short samples of data with a single label. DISCO began jointly with the University of Montana's [Emlen Lab](https://hs.umt.edu/dbs/labs/emlen/)
as an annotator for Japanese and Taiwanese Rhinoceros Beetle courtship songs, but it now generalizes to any kind of
recording.

## Quickstart
Install requires python version >=3.8.
Install directly from git with pip:
```
pip install git+https://github.com/TravisWheelerLab/disco.git
```

DISCO contains subcommands useful for training and evaluating models on sound data. Deep learning projects typically follow a series of steps, and DISCO tries to emulate each of these steps:
`label`, `extract`, `shuffle`, `train`, `infer`. 

*NOTE*

Models were updated in the most recent version. Remove them with `rm ~/.cache/disco/*` before running any `disco` commands.

Learn more about how to use the tools provided in this package in the [wiki](https://github.com/TravisWheelerLab/disco/wiki).

