a Python machine learning library for animal vocalizations and bioacoustics
Project description
hybrid-vocal-classifier
a Python machine learning library for animal vocalizations and bioacoustics
Getting Started
You can install with pip: $ pip install hybrid-vocal-classifier
For more detail, please see: https://hybrid-vocal-classifier.readthedocs.io/en/latest/install.html#install
To learn how to use hybrid-vocal-classifier
, please see the documentation at:
http://hybrid-vocal-classifier.readthedocs.io
You can find a tutorial here: https://hybrid-vocal-classifier.readthedocs.io/en/latest/tutorial.html
A more interactive tutorial in Jupyter notebooks is here:
https://github.com/NickleDave/hybrid-vocal-classifier-tutorial
Project Information
the hybrid-vocal-classifier
library (hvc
for short)
makes it easier for researchers studying
animal vocalizations and bioacoustics
to apply machine learning algorithms to their data.
The focus on automating the sort of annotations
often used by researchers studying
vocal learning
sets hvc
apart from more general software tools for bioacoustics.
In addition to automating annotation of data,
hvc
aims to make it easy for you to compare different models people have proposed,
using the data you have in your lab,
so you can see for yourself which one works best for your needs.
A related goal is to help you figure out
just how much data you have to label to get "good enough" accuracy for your analyses.
You can think of hvc
as a high-level wrapper around
the scikit-learn
library,
plus built-in functionality for working with annotated animal sounds.
Support
If you are having issues, please let us know.
- Issue Tracker: https://github.com/NickleDave/hybrid-vocal-classifier/issues
Contribute
- Issue Tracker: https://github.com/NickleDave/hybrid-vocal-classifier/issues
- Source Code: https://github.com/NickleDave/hybrid-vocal-classifier
CHANGELOG
You can see project history and work in progress in the CHANGELOG
License
The project is licensed under the BSD license.
Citation
If you use this library, please cite its DOI:
Backstory
hvc
was originally developed in the Sober lab
as a tool to automate annotation of birdsong (as shown in the picture above).
It grew out of a submission to the
SciPy 2016 conference
and later developed into a library,
as presented in this talk: https://youtu.be/BwNeVNou9-s
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file hybrid-vocal-classifier-0.3.1.tar.gz
.
File metadata
- Download URL: hybrid-vocal-classifier-0.3.1.tar.gz
- Upload date:
- Size: 1.2 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: python-requests/2.26.0
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 21f1aacbdde232876115fde90b84c8b1a2a2de1318f6c275157e6cf10dc010cf |
|
MD5 | 3252eedb3bc11fa02d8446bc80a1abe4 |
|
BLAKE2b-256 | 4e12d0ff3495d5800c7f7a43b4f53675df4ac83488bf8e1908fb774fc2737e11 |
File details
Details for the file hybrid_vocal_classifier-0.3.1-py3-none-any.whl
.
File metadata
- Download URL: hybrid_vocal_classifier-0.3.1-py3-none-any.whl
- Upload date:
- Size: 95.5 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: python-requests/2.26.0
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | eaa49c24888c9905ecb3312556156a0b40baaf8fba5928078ebda72f350990d9 |
|
MD5 | 077e3a3e4c8d8c8e7e8ab563ed3ef6a6 |
|
BLAKE2b-256 | 20cfb8742a1dfa6fb1a2a998aee09e11ee14ecaa9ef14f99564aea717bdab3d1 |