This version of AviaNZ was developed within the scope of a master's thesis at the Unviversity of Applied Sciences Dresden and introduces the two BirdNET classifiers BirdNET-Lite and BirdNET-Analyzer into the original Version of AviaNZ.
This software enables you to:
- classify recordings with BirdNET
- review and listen to wav files from acoustic field recorders,
- segment and annotate the recordings,
- train filters to recognise calls from particular species,
- use filters that others have provided to batch process many files
- review annotations
- produce output in spreadsheet form, or as files ready for further statistical analyses
For more information about the project, see http://www.avianz.net
If you use this software, please credit us in any papers that you write. An appropriate reference is:
@article{Marsland19,
title = "AviaNZ: A future-proofed program for annotation and recognition of animal sounds in long-time field recordings",
author = "{Marsland}, Stephen and {Priyadarshani}, Nirosha and {Juodakis}, Julius and {Castro}, Isabel",
journal = "Methods in Ecology and Evolution",
volume = 10,
number = 8,
pages = "1189--1195",
year = 2019
}
Windows binaries are available under realeases. To install from source, follow the Linux instructions.
No binaries are available. The following procedure was succesfully testet with Python 3.9.16. On Ubuntu, install from source as follows:
- Ensure Python, pip and git are available on your system. these can be installed by running the following from the command line:
sudo apt install python3-pip git
- Clone the repository by running:
- Install the required packages by running:
pip3 install -r requirements.txt --user
- Build the Cython extensions by running:
cd ext; python3 setup.py build_ext -i; cd ..
- Done! Launch the software with:
python3 AviaNZ.py
AviaNZ is based on PyQtGraph and PyQt, and uses Librosa and Scikit-learn amongst others.
Development of this software was supported by the RSNZ Marsden Fund, and the NZ Department of Conservation.