Today, I set up my new Birdnet-Pi,a raspberry Pi, running an app that detects and identifies birds by their calls. This is my first half day of recording birds.
Image description: A screenshot of the Birdnet Pi web interface. At the top, it shows a breakdown of birds from that day, sorted by species and time. In order of total number of occurrences, the birds listed are Torresian Crow, Australasian Figbird, Noisy Miner, Barn Owl, Rainbow Lorikeet and Blue-faced Honeyeater. Beneath the list of birds, it shows a waveform graphic for the audio of the latest bird call identitied by the system. In this instance, a Torresian Crow.
This uses the same detection model as the whoBIRD android app. I’ve used it in a side by side test with Merlin and they do not give consistent results. They’re in the same ball park, but really every detection (for both apps) should be verified with human ears. And I’m not sure that’s possible with a 24/7 setup.
IT’S STILL AWESOME AND FUN! I hope the talented people that made this continue to develop it. I’m glad this was posted, but like OP said, not super practical.
I found both whoBIRD and Birdnet-Pi to give good results, as long as you dismiss the low confidence results. For results with a confidence of 80 % or higher I very rarely have incorrect results. Every once in a while it confuses one kind of thrush with another, but they do sound similar to my human ears as well.
In two days, I’ve had one incorrect ID, and one that may or may not be accurate.
Both resolved by increasing the certainty threshold from its default of 70%, up to 80%.