BirdNET-Pi: A realtime acoustic bird classification system for the Raspberry Pi 4B, 3B+, and 0W2 built on the TFLite version of BirdNET.
github.com
Not the most conventional application for self-hosting, but thought it might make for a fun weekend project for someone.
BirdNET-Pi is built off the back of Cornell University's BirdNET Sound ID neural network model (https://birdnet.cornell.edu/). It can be used to classify what birds are in your vicinity by listening to their calls.
In case y'all haven't seen it: you can run similar software in a docker container and connect it to a standard security camera stream to get audio.
https://github.com/mmcc-xx/BirdCAGE
This is a very cool idea! What microphone would be well suited for this purpose?
There's a Github discussion post which is all about that topic. Worth checking it out for advice.
https://github.com/mcguirepr89/BirdNET-Pi/discussions/39
It largely depends on the surrounding environment in which you are going to place the device. In my case, I need to use a shotgun due to a highway nearby.
Careful with the birds!
Thanks. This definitely goes onto the pile of things I'll build at the new house.
BirdNet-Pi is awesome. Highly recommended for anyone who likes birds. The BirdNet app for phones is also nice.
Btw, BirdNet-Pi also works fine on the non-plus Raspberry Pi 3.
The default install instructions explicitly prevent installation on a Pi3 or Pi3+. If you have armv7l cpu architecture, the script just exits. I banged at it for a bit, but the tensorflow lite runtime install tripped me up. Going to look into the docker project mentioned elsewhere in this thread instead.
The Cornell app is magical. If i self host this is it mobile compatible? I’d love to be able to host and share this with the family if so.
Yes the website looks just fine from mobile, I have had one running for weeks and my phone is the primary way I access it.
Loving this sweet sweet, this is what this magazine is here for, new toy.
Wife and I are into birding locally around the house. "Babe, it can listen all day and ID what it hears" might just be the tipping point to get her onboard with a couple cameras for the house.
Actually sounds really cool, why not