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Bird Classification

Bird classification identifies known birds using a quantized Tensorflow model. When a known bird is recognized, its common name will be added as a sub_label. This information is included in the UI, filters, as well as in notifications.

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Bird classification requires a one-time internet connection to download the classification model and label map from GitHub. Once cached, models work fully offline. See Network Requirements for details.

Minimum System Requirements​

Bird classification runs a lightweight tflite model on the CPU, there are no significantly different system requirements than running Frigate itself.

Model​

The classification model used is the MobileNet INat Bird Classification, available identifiers can be found here.

Configuration​

Bird classification is disabled by default and must be enabled before it can be used. Bird classification is a global configuration setting.

Navigate to Settings→Enrichments→Object classification.

  • Set Bird classification config > Bird classification to on
  • Set Bird classification config > Minimum score to the desired confidence score (default: 0.9)

Advanced Configuration​

Fine-tune bird classification with these optional parameters:

  • threshold: Classification confidence score required to set the sub label on the object.
    • Default: 0.9.