acoupi_birdnet#
What is acoupi_birdnet?#
acoupi_birdnet is an open-source Python package that implement the BirdNET-Analyzer bioacoustic deep-learning model on edge devices like the Raspberry Pi, using the acoupi framework. The BirdNET-Analyzer DL model has been developed by the K. Lisa Yang Center for Conservation Bioacoustics at the Cornell Lab of Ornithology in collaboration with Chemnitz University of Technology to detect and classify more than 6000 bird species.
What is the difference between acoupi and acoupi_birdnet?
acoupi_birdnet and acoupi are different. The acoupi_birdnet program is built on top of the acoupi python package. Think of acoupi like a bag of LEGO pieces that you can assemble into multiple shapes and forms. acoupi_birdnet would be the results of assembling some of these LEGO pieces into "birds"!
Get familiar with acoupi
acoupi_birdnet builds on and inherits features from acoupi. If you want to learn more the acoupi framework, we recommand starting with acoupi's home documentation.
Requirements#
acoupi_birdnet is designed to run on single-board computers like the Raspberry Pi. It can be installed and tested on any Linux-based machines with Python version >=3.8,<3.12.
- A Linux-based single-board computer such as the Raspberry Pi 4B.
- A SD Card with the 64-bit Lite OS version installed.
- An audible frequency range microphone, such as an AudioMoth USB Microphone or a Lavalier.
Recommended Hardware
The software has been extensively developed and tested with the RPi 4B. We advise users to select the RPi 4B or a device featuring similar specifications.
Installation#
To install acoupi_birdnet on your embedded device, you will need to first have acoupi installed on your device. Follow these steps to install both acoupi and acoupi_birdnet:
Step1: Install acoupi and its dependencies
Using acoupi_birdnet from the command line
To check what are the available commands for acoupi_birdnet, enter acoupi --help
. For more details about each of the commands, refer to the acoupi CLI documentation for further info.
What is acoupi? 🚀#
acoupi is an open-source Python package that simplifies the use and implementation of bioacoustic classifiers on edge devices. It integrates and standardises the entire bioacoustic monitoring workflow, facilitating the creation of custom sensors, by handling audio recordings, processing, classifications, detections, communication, and data management.
Licenses and Usage
acoupi_birdnet can not be used for commercial purposes.
The acoupi_birdnet program inherits the BirdNET-Analyzer model license, published under the Creative Commons Attribution-NonCommercial 4.0 International. Please make sure to review this license to ensure your intended use complies with its terms.
Model Output Reliability
Please note that acoupi_birdnet program is not responsible for the accuracy or reliability of predictions made by the BirdNET-Analyzer model. It is essential to understand the model's performance and limitations before using it in your project.
For more details on the BirdNET model, refer to the publication Kahl S., et al., (2021) BirdNET: A deep learning solution for avian diversity monitoring. To learn more about using the BirdNET scores and outputs from the model, refer to Wood CM. and Kahl S., (2024) Guidelines for appropriate use of BirdNET scores and other detector outputs
Available acoupi programs!
acoupi offers various programs that can be configured to meet your needs. These programs can be used to simply record audio, send messages, or even detect and classify birds species. Check out the full list of available acoupi programs to learn more.
Next steps 📖#
Get to know acoupi better by exploring this documentation.
Tutorials
Step-by-step information on how to install, configure and deploy acoupi_birdnet for new users. |
Explanation
Learn more about the building blocks constituing acoupi_birdnet program. |
Reference
Technical information refering to acoupi_birdnet code. |
Important
We would love to hear your feedback about the documentation. We are always looking to hearing suggestions to improve readability and user's ease of navigation. Don't hesitate to reach out if you have comments!