A python api for BirdNET-Analyzer and BirdNET-Lite
birdnetlib provides a common interface for BirdNET-Analyzer and BirdNET-Lite.
Documentation is at https://joeweiss.github.io/birdnetlib.
See Getting Started for a quick introduction.
birdnetlib requires Python 3.9+ and prior installation of Tensorflow Lite, librosa and ffmpeg. See BirdNET-Analyzer for more details on installing the Tensorflow-related dependencies.
pip install birdnetlibTo use the latest BirdNET-Analyzer model, use the Analyzer class.
from birdnetlib import Recording from birdnetlib.analyzer import Analyzer from datetime import datetime # Load and initialize the BirdNET-Analyzer models. analyzer = Analyzer() recording = Recording( analyzer, "sample.mp3", lat=35.4244, lon=-120.7463, date=datetime(year=2022, month=5, day=10), # use date or week_48 min_conf=0.25, ) recording.analyze() print(recording.detections)recording.detections contains a list of detected species, along with time ranges and confidence value.
[{'common_name': 'House Finch', 'confidence': 0.5744, 'end_time': 12.0, 'scientific_name': 'Haemorhous mexicanus', 'start_time': 9.0, 'label': 'Haemorhous mexicanus_House Finch'}, {'common_name': 'House Finch', 'confidence': 0.4496, 'end_time': 15.0, 'scientific_name': 'Haemorhous mexicanus', 'start_time': 12.0, 'label': 'Haemorhous mexicanus_House Finch'}]The Recording class takes a file path as an argument. You can also use RecordingFileObject to analyze an in-memory object, or RecordingBuffer for handling an array buffer.
birdnetlib uses models provided by BirdNET-Lite and BirdNET-Analyzer under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International Public License.
BirdNET-Lite and BirdNET-Analyzer were developed by the K. Lisa Yang Center for Conservation Bioacoustics at the Cornell Lab of Ornithology.
For more information on BirdNET analyzers, please see the project repositories below:
birdnetlib is not associated with BirdNET-Lite, BirdNET-Analyzer or the K. Lisa Yang Center for Conservation Bioacoustics.
birdnetlib is maintained by Joe Weiss. Contributions are welcome.
- Establish a unified API for interacting with Tensorflow-based BirdNET analyzers
- Enable python-based test cases for BirdNET analyzers
- Make it easier to use BirdNET in python-based projects
- Make it easier to migrate to new BirdNET versions/models as they become available