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More mypy cleanup (#22658)
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* Halfway point for fixing data processing * Fix mixin types missing * Cleanup LPR mypy * Cleanup audio mypy * Cleanup bird mypy * Cleanup mypy for custom classification * remove whisper * Fix DB typing * Cleanup events mypy * Clenaup * fix type evaluation * Cleanup * Fix broken imports
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@@ -4,7 +4,7 @@ import logging
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import os
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import threading
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import time
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from typing import Optional
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from typing import Any, Optional
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from peewee import DoesNotExist
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@@ -17,6 +17,7 @@ from frigate.const import (
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UPDATE_EVENT_DESCRIPTION,
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)
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from frigate.data_processing.types import PostProcessDataEnum
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from frigate.embeddings.embeddings import Embeddings
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from frigate.types import TrackedObjectUpdateTypesEnum
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from frigate.util.audio import get_audio_from_recording
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@@ -31,7 +32,7 @@ class AudioTranscriptionPostProcessor(PostProcessorApi):
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self,
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config: FrigateConfig,
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requestor: InterProcessRequestor,
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embeddings,
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embeddings: Embeddings,
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metrics: DataProcessorMetrics,
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):
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super().__init__(config, metrics, None)
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@@ -40,7 +41,7 @@ class AudioTranscriptionPostProcessor(PostProcessorApi):
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self.embeddings = embeddings
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self.recognizer = None
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self.transcription_lock = threading.Lock()
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self.transcription_thread = None
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self.transcription_thread: threading.Thread | None = None
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self.transcription_running = False
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# faster-whisper handles model downloading automatically
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@@ -69,7 +70,7 @@ class AudioTranscriptionPostProcessor(PostProcessorApi):
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self.recognizer = None
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def process_data(
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self, data: dict[str, any], data_type: PostProcessDataEnum
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self, data: dict[str, Any], data_type: PostProcessDataEnum
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) -> None:
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"""Transcribe audio from a recording.
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@@ -141,13 +142,13 @@ class AudioTranscriptionPostProcessor(PostProcessorApi):
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except Exception as e:
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logger.error(f"Error in audio transcription post-processing: {e}")
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def __transcribe_audio(self, audio_data: bytes) -> Optional[tuple[str, float]]:
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def __transcribe_audio(self, audio_data: bytes) -> Optional[str]:
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"""Transcribe WAV audio data using faster-whisper."""
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if not self.recognizer:
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logger.debug("Recognizer not initialized")
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return None
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try:
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try: # type: ignore[unreachable]
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# Save audio data to a temporary wav (faster-whisper expects a file)
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temp_wav = os.path.join(CACHE_DIR, f"temp_audio_{int(time.time())}.wav")
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with open(temp_wav, "wb") as f:
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@@ -176,7 +177,7 @@ class AudioTranscriptionPostProcessor(PostProcessorApi):
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logger.error(f"Error transcribing audio: {e}")
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return None
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def _transcription_wrapper(self, event: dict[str, any]) -> None:
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def _transcription_wrapper(self, event: dict[str, Any]) -> None:
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"""Wrapper to run transcription and reset running flag when done."""
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try:
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self.process_data(
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@@ -194,7 +195,7 @@ class AudioTranscriptionPostProcessor(PostProcessorApi):
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self.requestor.send_data(UPDATE_AUDIO_TRANSCRIPTION_STATE, "idle")
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def handle_request(self, topic: str, request_data: dict[str, any]) -> str | None:
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def handle_request(self, topic: str, request_data: dict[str, Any]) -> str | None:
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if topic == "transcribe_audio":
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event = request_data["event"]
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