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synced 2026-02-05 10:45:21 +03:00
Only run audio detection when audio is above noise threshold
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@ -145,6 +145,12 @@ audio:
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enabled: False
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# Optional: Configure the amount of seconds without detected audio to end the event (default: shown below)
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max_not_heard: 30
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# Optional: Configure the min rms volume required to run audio detection (default: shown below)
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# As a rule of thumb:
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# - 200 - high sensitivity
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# - 500 - medium sensitivity
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# - 1000 - low sensitivity
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min_volume: 500
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# Optional: Types of audio to listen for (default: shown below)
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listen:
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- bark
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@ -393,6 +393,9 @@ class AudioConfig(FrigateBaseModel):
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max_not_heard: int = Field(
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default=30, title="Seconds of not hearing the type of audio to end the event."
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)
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min_volume: int = Field(
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default=500, title="Min volume required to run audio detection."
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)
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listen: List[str] = Field(
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default=DEFAULT_LISTEN_AUDIO, title="Audio to listen for."
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)
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@ -169,14 +169,18 @@ class AudioEventMaintainer(threading.Thread):
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if not self.feature_metrics[self.config.name]["audio_enabled"].value:
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return
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waveform = (audio / AUDIO_MAX_BIT_RANGE).astype(np.float32)
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model_detections = self.detector.detect(waveform)
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rms = np.sqrt(np.mean(np.absolute(audio.astype(np.float32)**2)))
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for label, score, _ in model_detections:
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if label not in self.config.audio.listen:
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continue
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# only run audio detection when volume is above min_volume
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if rms >= self.config.audio.min_volume:
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waveform = (audio / AUDIO_MAX_BIT_RANGE).astype(np.float32)
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model_detections = self.detector.detect(waveform)
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self.handle_detection(label, score)
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for label, score, _ in model_detections:
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if label not in self.config.audio.listen:
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continue
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self.handle_detection(label, score)
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self.expire_detections()
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