Dipper Features
Machine Learning for Bioacoustics
Get from audio datasets to verified species detection histories efficiently—without writing a line of code.
- Apply machine learning classifiers
- Stratified selection of ML detections for review
- Efficient keyboard-based annotation
- Grid-view and Focus-view annotation layouts
- Coming soon: Custom classifier training
Server Mode + Remote Access
To run Dipper on a server and access via a remote browser, see Server Mode instructions
ML Model Support
The app includes all major foundation models for bioacoustics, including BirdNET, Perch V2, and HawkEars
Linux installation
Make the AppImage executable: chmod +x Dipper*.AppImage, then run it.
Screenshots
Video Tutorials
Download demo datasets here
About Dipper
Dipper is an open-source desktop application for bioacoustics machine learning workflows.
Annotation
Binary, multi-class, and bounding-box annotation of audio clips with spectrogram visualization.
Inference
Run trained models over large audio datasets and review detections in the built-in reviewer.
Bugs and Feature Requests
Report issues or request new features on our GitHub Issues page.
All Releases
Click any asset to download directly from GitHub Releases.
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