Posted by speckx 12 hours ago
I have a spare e-ink display and my next weekend project to follow onto this is to wire it up so it shows some faux "woodcut" images of birds detected, or something like that.
https://i.imgur.com/5XbM6bb.png
Also if anyone is interested, here is the server for the e-ink screen https://github.com/koryk/inky-impression-server
and here is a MCP for birdnet that I've been using for a bit https://github.com/koryk/birdnetpi-mcp-local-server
I’ve been unhappy with my little lcd board I’ve been using for the same here https://github.com/simonjgreen/OpenObservatory as the contrast is bad. I was considering using one of my trmnl displays, but it isn’t quite the right operating model for the frequency of updates I want.
The journey to a magical, free bird sound ID app involves some obvious steps (the NSF gave them money), but the amount of timeline offramps is really high. The NSF didn't think this app was educational ("it's just telling them the answer, they don't even have to work for it!"), the funding ran out so they were thinking of charging money, eBird happened to have five years of bird sound recordings they could use, a computer vision guy on the team happened to learn that spectrograms are basically the same as pictures...
And the result is tremendously useful! They get great signal on where birds are, and they're making people so much more interested in birds and nature and science. And I think charging $1 for the app or, shudder, some sort of subscription model might've ruined the whole thing.
Unless a species has a really, really unique call or song, I've made it my personal rule to get eyes on it and, if I'm still not convinced, to take a picture and cross reference with iNaturalist and what folks on there think of it.
I've learned to curse the species that differ from others by the sheen of the backs of the males' necks or the angle of a wingbar. Also, gulls that only differ by things like the color of their feet or beaks.
Personal best for a single session is 23 birds in my back garden over the course of a couple of coffees. I have though spent a fair bit of time making the garden as attractive to different types of bird as possible - mainly through having a variety of different shaped feeders with different feed in. I can recommend the NatureSpy camera feeder too [0] - though I have had to modify it a little to make the food hole smaller otherwise magpies empty the thing in a single day just chucking all the seed on the floor. Dickheads.
[0] https://naturespy.org/collections/wifi-solar-bird-feeder-nes...
Ended up installing a better microphone attached to a RPi3A+ and using a RaspberyPi 4 which I already owned for hosting BirdNET-Go https://maciejb.me/posts/birdnet-go-setup/
Much better sound quality now!
I made a change to the markdown card sometime ago that uses only `U+2581` through `U+ 2587` instead to avoid that issue.
It's under a collapsed block here:
https://www.kyleniewiada.org/blog/2025/05/backyard-bird-trac...
Case I used to make it portable and fit the display https://makerworld.com/en/models/1336154-portable-pi-sdr-cas...
Input is three RTSP streams from various Reolink PoE cameras around our house, and it is pretty cool to be able to find and listen to the birds/frogs that come.
Any advice on how to go about this.
My current plan is to put multiple cameras at the mouth of the chimney opening which is about 42"x42"(1mx1m).
Does this sound realistic to anyone with experience?
Here's one example: https://github.com/sammlapp/ovenbird-individual-recognition
My impression is that the hardest part is knowing whether or not you're actually doing a good job. For vocal learners (like the ovenbird example linked above), it seems to be pretty easy using embeddings from existing models (like perch or birdnet). For non-learning species (possibly including your swifts), you can use timbre clues to differentiate many individuals, but may not be able to really nail down individual identity.
