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synced 2026-08-07 03:11:15 +03:00
Miscellaneous fixes (#23335)
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* stabilize chart options to stop ApexCharts updateOptions running on every stats tick * constrain height of export dialog * stop audio maintainer when deleting a camera * run face register and recognize API handlers in threadpool
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@@ -280,7 +280,7 @@ async def create_face(request: Request, name: str):
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success response with details about the registration, or an error if face recognition
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is not enabled or the image cannot be processed.""",
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)
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async def register_face(request: Request, name: str, file: UploadFile):
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def register_face(request: Request, name: str, file: UploadFile):
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if not request.app.frigate_config.face_recognition.enabled:
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return JSONResponse(
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status_code=400,
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@@ -288,7 +288,7 @@ async def register_face(request: Request, name: str, file: UploadFile):
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)
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context: EmbeddingsContext = request.app.embeddings
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result = None if context is None else context.register_face(name, await file.read())
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result = None if context is None else context.register_face(name, file.file.read())
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if not isinstance(result, dict):
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return JSONResponse(
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@@ -313,7 +313,7 @@ async def register_face(request: Request, name: str, file: UploadFile):
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registered faces in the system. Returns the recognized face name and confidence score,
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or an error if face recognition is not enabled or the image cannot be processed.""",
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)
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async def recognize_face(request: Request, file: UploadFile):
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def recognize_face(request: Request, file: UploadFile):
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if not request.app.frigate_config.face_recognition.enabled:
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return JSONResponse(
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status_code=400,
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@@ -321,7 +321,7 @@ async def recognize_face(request: Request, file: UploadFile):
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)
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context: EmbeddingsContext = request.app.embeddings
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result = context.recognize_face(await file.read())
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result = context.recognize_face(file.file.read())
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if not isinstance(result, dict):
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return JSONResponse(
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+43
-9
@@ -94,9 +94,21 @@ class AudioProcessor(FrigateProcess):
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self.camera_metrics = camera_metrics
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self.config = config
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def __stop_audio_thread(self, camera: str) -> None:
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thread = self.audio_threads.pop(camera, None)
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if thread is None:
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return
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thread.stop()
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thread.join(10)
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if thread.is_alive():
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self.logger.warning(f"Audio maintainer thread for {camera} is still alive")
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else:
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self.logger.info(f"Audio maintainer stopped for {camera}")
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def run(self) -> None:
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self.pre_run_setup(self.config.logger)
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audio_threads: dict[str, AudioEventMaintainer] = {}
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self.audio_threads: dict[str, AudioEventMaintainer] = {}
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threading.current_thread().name = "process:audio_manager"
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@@ -120,12 +132,13 @@ class AudioProcessor(FrigateProcess):
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CameraConfigUpdateEnum.add,
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CameraConfigUpdateEnum.audio,
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CameraConfigUpdateEnum.ffmpeg,
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CameraConfigUpdateEnum.remove,
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],
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)
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def spawn_if_needed(camera: CameraConfig) -> None:
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name = camera.name
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if name is None or name in audio_threads:
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if name is None or name in self.audio_threads:
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return
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if not camera.enabled or not camera.audio.enabled:
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return
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@@ -139,7 +152,7 @@ class AudioProcessor(FrigateProcess):
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self.transcription_model_runner,
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self.stop_event, # type: ignore[arg-type]
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)
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audio_threads[name] = thread
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self.audio_threads[name] = thread
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thread.start()
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self.logger.info(f"Audio maintainer started for {name}")
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@@ -148,21 +161,31 @@ class AudioProcessor(FrigateProcess):
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self.logger.info(f"Audio processor started (pid: {self.pid})")
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# poll for newly added cameras or cameras flipped to audio.enabled at runtime
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# poll for newly added/removed cameras or cameras flipped to
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# audio.enabled at runtime
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while not self.stop_event.wait(timeout=1.0):
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config_subscriber.check_for_updates()
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updated_topics = config_subscriber.check_for_updates()
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# stop maintainers for removed cameras so their ffmpeg process is
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# torn down and they stop touching camera_metrics (which the camera
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# maintainer has already popped for the removed camera)
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for removed_camera in updated_topics.get(
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CameraConfigUpdateEnum.remove.name, []
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):
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self.__stop_audio_thread(removed_camera)
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for camera in self.config.cameras.values():
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spawn_if_needed(camera)
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config_subscriber.stop()
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for thread in audio_threads.values():
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for thread in self.audio_threads.values():
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thread.join(1)
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if thread.is_alive():
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self.logger.info(f"Waiting for thread {thread.name:s} to exit")
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thread.join(10)
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for thread in audio_threads.values():
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for thread in self.audio_threads.values():
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if thread.is_alive():
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self.logger.warning(f"Thread {thread.name} is still alive")
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@@ -184,6 +207,9 @@ class AudioEventMaintainer(threading.Thread):
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self.camera_config = camera
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self.camera_metrics = camera_metrics
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self.stop_event = stop_event
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# per-camera stop signal so a single maintainer can be torn down at
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# runtime (e.g. on camera removal) without stopping the whole process
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self.camera_stop_event = threading.Event()
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self.detector = AudioTfl(stop_event, self.camera_config.audio.num_threads)
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self.shape = (int(round(AUDIO_DURATION * AUDIO_SAMPLE_RATE)),)
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self.chunk_size = int(round(AUDIO_DURATION * AUDIO_SAMPLE_RATE * 2))
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@@ -233,7 +259,11 @@ class AudioEventMaintainer(threading.Thread):
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self.was_audio_enabled = camera.audio.enabled
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def detect_audio(self, audio: np.ndarray) -> None:
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if not self.camera_config.audio.enabled or self.stop_event.is_set():
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if (
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not self.camera_config.audio.enabled
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or self.stop_event.is_set()
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or self.camera_stop_event.is_set()
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):
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return
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audio_as_float: np.ndarray = audio.astype(np.float32)
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@@ -352,11 +382,15 @@ class AudioEventMaintainer(threading.Thread):
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self.logger.error(f"Error reading audio data from ffmpeg process: {e}")
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log_and_restart()
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def stop(self) -> None:
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"""Signal this maintainer to exit its run loop and clean up."""
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self.camera_stop_event.set()
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def run(self) -> None:
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if self.camera_config.enabled:
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self.start_or_restart_ffmpeg()
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while not self.stop_event.is_set():
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while not self.stop_event.is_set() and not self.camera_stop_event.is_set():
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# check if there is an updated config
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self.config_subscriber.check_for_updates()
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