The Quickest Way to Run BirdNET on Any Computer

Intro

Have you ever wondered what birds are chirping in your backyard? BirdNET is an incredible research project that uses machine learning to identify bird species by sound. While it’s a powerful tool, setting it up manually can be a bit of a headache, often involving complex dependency installations and Python environment management.

That’s where Docker comes in. By containerizing the application, you can bypass all the setup hassle and get BirdNET running on virtually any computer in minutes—whether it’s a powerful desktop, a Raspberry Pi, or a spare Mini PC in your Home Lab. In this guide, I’ll walk you through the quickest way to start running BirdNET locally using a Docker Compose setup I’ve put together called birdnet-go-docker-compose.

Prerequisites

Before we dive in, you’ll need two things installed on your computer:

• Docker
• Docker Compose

If you’re new to Docker, don’t worry—it’s just a tool that lets you run applications in isolated packages called containers.

The Solution: Birdnet-Go

I created the Birdnet-Go repository to simplify the process of running the Birdnet-Go client (a Go implementation of the BirdNET-Analyzer). This setup bundles everything you need into a single docker-compose.yml file, making deployment as simple as running a few commands.

Step-by-Step Guide

1. Clone the Repository

First, you’ll need to grab the code. Open your terminal and run:

git clone https://github.com/ndiesslin/birdnet-go-docker-compose.git
cd birdnet-go-docker-compose

2. Configure Your Environment

The repository comes with an example environment file. We’ll copy this to creating our actual configuration file:

cp .env.example .env

Now, open the .env file in your favorite text editor. You’ll see a BIRDNET_COMMAND variable. This tells the container what to do.

For an RTSP Stream (like an IP Camera):

BIRDNET_COMMAND="birdnet-go realtime --rtsp 'rtsp://username:password@192.168.0.13/live'"

For a Local Microphone (Linux):

BIRDNET_COMMAND="birdnet-go realtime --source \"sysdefault\""

3. Launch It!

Once your configuration is set, start the application with:

docker-compose up --build

That’s it! Docker will pull the necessary images and start the service. You can now access the BirdNET web interface by opening your browser and going to:

http://localhost:8080 (or http://<your-ip-address>:8080 if accessing from another device)

Exploring the Interface

Once you load the dashboard, you’ll see why Birdnet-Go is such a great customized client. It provides a clean, web-based UI that gives you instant insight into what’s happening around you:

• Real-time Spectrogram: You can watch the live visual representation of the audio feed as it comes in. It’s fascinating to see the visual signature of a bird call scrolling by.
• Live Detections: As soon as BirdNET identifies a sound, it pops up in the detection log with the common name, scientific name, and a confidence score.
• Audio Playback: Missed a call? You can click on any detection in the list to replay the specific audio snippet that triggered the identification.

Advanced: Using a Local Microphone on macOS

If you’re on a Mac, accessing the local microphone from a Docker container is a bit tricky due to macOS security restrictions. However, we can work around this by streaming the microphone audio to an RTSP server (included in the docker-compose file) using FFmpeg.

1. Install FFmpeg

If you don’t have it, install FFmpeg via Homebrew:

brew install ffmpeg

2. Prepare the Stream

Make sure your terminal has permission to access the microphone (System Settings > Privacy & Security > Microphone).

Then, in a separate terminal window, run this command to stream your mic to the RTSP server:

ffmpeg -f avfoundation -i ":0" -acodec aac -b:a 128k -ar 44100 -ac 1 -f rtsp -rtsp_transport tcp rtsp://localhost:8554/mic

Note: You may need to change ":0" to the correct index for your microphone. Run ffmpeg -f avfoundation -list_devices true -i "" to see your devices.

3. Update Configuration

In your .env file, point BirdNET to this local stream:

BIRDNET_COMMAND="birdnet-go realtime --rtsp 'rtsp://host.docker.internal:8554/mic'"

Now, when you run docker-compose up, BirdNET will be listening to your Mac’s microphone!

Conclusion

By using Docker and Birdnet-Go, you can skip the tedious installation steps and jump straight to the fun part: identifying the birds around you.

One of the best things about this setup is that it’s designed to run 24/7. You can leave the container running in the background, constantly monitoring your environment day and night. Whether it’s catching the first calls of the dawn chorus or identifying an elusive owl at midnight, your automated bird station will capture it all without you lifting a finger.

Whether you’re using an existing IP camera stream or just your laptop’s microphone, this setup provides a robust and reliable way to run BirdNET anywhere. It’s the perfect addition to any Smart Home or nature-focused Home Lab.

Happy birdwatching!