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Critical Vulnerability in NestJS Devtools: Localhost RCE via Sandbox Escape
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mygithub.libinneed.workers.dev/tphakala/birdnet-go
BirdNET-Go is an AI solution for continuous avian monitoring and identification
Quick install script for Debian, Ubuntu and Raspberry Pi OS based systems:
curl -fsSL https://github.com/tphakala/birdnet-go/raw/main/install.sh -o install.sh
bash ./install.sh
I am seeking web developer with experience in Go HTML templating, Tailwind CSS, HTMX, Alpine.js, or similar frameworks to join in enhancing the BirdNET-Go application web UI. Your expertise can make a real difference in how users engage with this app and connect with birdlife. If you have the skills and a keen interest in contributing to a nature-focused project, I'd love to hear from you.
For detailed installation instructions, see the installation documentation. For securing your BirdNET-Go installation, see the security documentation.
For instructions on how to build the project, see the building documentation.
BirdNET-Go CLI
Usage:
birdnet [command]
Available Commands:
authors Print the list of authors
completion Generate the autocompletion script for the specified shell
directory Analyze all *.wav files in a directory
file Analyze an audio file
help Help about any command
license Print the license of Go-BirdNET
realtime Analyze audio in realtime mode
Flags:
--debug Enable debug output
-h, --help help for birdnet
--locale string Set the locale for labels. Accepts full name or 2-letter code. (default "finnish")
--overlap float Overlap value between 0.0 and 2.9
--sensitivity float Sigmoid sensitivity value between 0.0 and 1.5 (default 1)
--threshold float Confidency threshold for detections, value between 0.1 to 1.0 (default 0.8)
Use "birdnet [command] --help" for more information about a command.
There is more detailed usage documentation at wiki https://github.com/tphakala/birdnet-go/wiki
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International
Tomi P. Hakala
Contributions by Hampus Carlsson, Jan Vrska, @twt--, @aster1sk, @hoover67
Please let me know if you are missing from contributors list!
BirdNET AI model by the K. Lisa Yang Center for Conservation Bioacoustics at the Cornell Lab of Ornithology in collaboration with Chemnitz University of Technology. Stefan Kahl, Connor Wood, Maximilian Eibl, Holger Klinck.
BirdNET label translations by Patrick Levin for BirdNET-Pi project by Patrick McGuire.
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