birdnetlib 0.13.2

A python api for BirdNET-Lite and BirdNET-Analyzer

birdnetlib

A python api for BirdNET-Analyzer and BirdNET-Lite

birdnetlib provides a common interface for BirdNET-Analyzer and BirdNET-Lite.

Documentation

Documentation is at https://joeweiss.github.io/birdnetlib.

See Getting Started for a quick introduction.

Installation

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 birdnetlib

Basic usage

To 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.

About BirdNET-Lite and BirdNET-Analyzer

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:

BirdNET-Analyzer

BirdNET-Lite

birdnetlib is not associated with BirdNET-Lite, BirdNET-Analyzer or the K. Lisa Yang Center for Conservation Bioacoustics.

About birdnetlib

birdnetlib is maintained by Joe Weiss. Contributions are welcome.

Project Goals

• 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