frigate/data_processing/real_time/bird.py

@@ -19,11 +19,6 @@ from frigate.util.object import calculate_region
 from ..types import DataProcessorMetrics
 from .api import RealTimeProcessorApi
 
-try:
-    from tflite_runtime.interpreter import Interpreter
-except ModuleNotFoundError:
-    from tensorflow.lite.python.interpreter import Interpreter
-
 logger = logging.getLogger(__name__)
 
 
@@ -35,7 +30,7 @@ class BirdRealTimeProcessor(RealTimeProcessorApi):
         metrics: DataProcessorMetrics,
     ):
         super().__init__(config, metrics)
-        self.interpreter: Interpreter = None
+        self.interpreter: Any | None = None
         self.sub_label_publisher = sub_label_publisher
         self.tensor_input_details: dict[str, Any] = None
         self.tensor_output_details: dict[str, Any] = None
@@ -82,6 +77,11 @@ class BirdRealTimeProcessor(RealTimeProcessorApi):
 
     @redirect_output_to_logger(logger, logging.DEBUG)
     def __build_detector(self) -> None:
+        try:
+            from tflite_runtime.interpreter import Interpreter
+        except ModuleNotFoundError:
+            from tensorflow.lite.python.interpreter import Interpreter
+
         self.interpreter = Interpreter(
             model_path=os.path.join(MODEL_CACHE_DIR, "bird/bird.tflite"),
             num_threads=2,

frigate/data_processing/real_time/custom_classification.py

@@ -29,11 +29,6 @@ from frigate.util.object import box_overlaps, calculate_region
 from ..types import DataProcessorMetrics
 from .api import RealTimeProcessorApi
 
-try:
-    from tflite_runtime.interpreter import Interpreter
-except ModuleNotFoundError:
-    from tensorflow.lite.python.interpreter import Interpreter
-
 logger = logging.getLogger(__name__)
 
 MAX_OBJECT_CLASSIFICATIONS = 16
@@ -52,7 +47,7 @@ class CustomStateClassificationProcessor(RealTimeProcessorApi):
         self.requestor = requestor
         self.model_dir = os.path.join(MODEL_CACHE_DIR, self.model_config.name)
         self.train_dir = os.path.join(CLIPS_DIR, self.model_config.name, "train")
-        self.interpreter: Interpreter = None
+        self.interpreter: Any | None = None
         self.tensor_input_details: dict[str, Any] | None = None
         self.tensor_output_details: dict[str, Any] | None = None
         self.labelmap: dict[int, str] = {}
@@ -350,7 +345,7 @@ class CustomObjectClassificationProcessor(RealTimeProcessorApi):
         self.model_config = model_config
         self.model_dir = os.path.join(MODEL_CACHE_DIR, self.model_config.name)
         self.train_dir = os.path.join(CLIPS_DIR, self.model_config.name, "train")
-        self.interpreter: Interpreter = None
+        self.interpreter: Any | None = None
         self.sub_label_publisher = sub_label_publisher
         self.requestor = requestor
         self.tensor_input_details: dict[str, Any] | None = None
@@ -373,6 +368,11 @@ class CustomObjectClassificationProcessor(RealTimeProcessorApi):
 
     @redirect_output_to_logger(logger, logging.DEBUG)
     def __build_detector(self) -> None:
+        try:
+            from tflite_runtime.interpreter import Interpreter
+        except ModuleNotFoundError:
+            from tensorflow.lite.python.interpreter import Interpreter
+
         model_path = os.path.join(self.model_dir, "model.tflite")
         labelmap_path = os.path.join(self.model_dir, "labelmap.txt")
 

frigate/embeddings/maintainer.py

@@ -146,6 +146,29 @@ class EmbeddingMaintainer(threading.Thread):
         self.detected_license_plates: dict[str, dict[str, Any]] = {}
         self.genai_client = get_genai_client(config)
 
+        # Pre-import TensorFlow/tflite on main thread to avoid atexit registration issues
+        # when importing from worker threads later (e.g., during dynamic config updates)
+        if (
+            self.config.classification.bird.enabled
+            or len(self.config.classification.custom) > 0
+        ):
+            try:
+                from tflite_runtime.interpreter import Interpreter  # noqa: F401
+            except ModuleNotFoundError:
+                try:
+                    from tensorflow.lite.python.interpreter import (  # noqa: F401
+                        Interpreter,
+                    )
+
+                    logger.debug(
+                        "Pre-imported TensorFlow Interpreter on main thread for classification models"
+                    )
+                except Exception as e:
+                    logger.warning(
+                        f"Failed to pre-import TensorFlow Interpreter: {e}. "
+                        "Classification models may fail to load if added dynamically."
+                    )
+
         # model runners to share between realtime and post processors
         if self.config.lpr.enabled:
             lpr_model_runner = LicensePlateModelRunner(

frigate/embeddings/onnx/jina_v1_embedding.py

@@ -186,9 +186,6 @@ class JinaV1ImageEmbedding(BaseEmbedding):
                 download_func=self._download_model,
             )
             self.downloader.ensure_model_files()
-            # Avoid lazy loading in worker threads: block until downloads complete
-            # and load the model on the main thread during initialization.
-            self._load_model_and_utils()
         else:
             self.downloader = None
             ModelDownloader.mark_files_state(

frigate/embeddings/onnx/jina_v2_embedding.py

@@ -65,9 +65,6 @@ class JinaV2Embedding(BaseEmbedding):
                 download_func=self._download_model,
             )
             self.downloader.ensure_model_files()
-            # Avoid lazy loading in worker threads: block until downloads complete
-            # and load the model on the main thread during initialization.
-            self._load_model_and_utils()
         else:
             self.downloader = None
             ModelDownloader.mark_files_state(

web/src/hooks/use-camera-live-mode.ts

@@ -54,7 +54,7 @@ export default function useCameraLiveMode(
   }>({});
 
   useEffect(() => {
-    if (!cameras || cameras.length === 0) return;
+    if (!cameras) return;
 
     const mseSupported =
       "MediaSource" in window || "ManagedMediaSource" in window;

web/src/views/live/LiveCameraView.tsx

@@ -147,11 +147,10 @@ export default function LiveCameraView({
 
   // supported features
 
-  const [streamName, setStreamName, streamNameLoaded] =
-    useUserPersistence<string>(
-      `${camera.name}-stream`,
-      Object.values(camera.live.streams)[0],
-    );
+  const [streamName, setStreamName] = useUserPersistence<string>(
+    `${camera.name}-stream`,
+    Object.values(camera.live.streams)[0],
+  );
 
   const isRestreamed = useMemo(
     () =>
@@ -160,19 +159,6 @@ export default function LiveCameraView({
     [config, streamName],
   );
 
-  // validate stored stream name and reset if now invalid
-
-  useEffect(() => {
-    if (!streamNameLoaded) return;
-
-    const available = Object.values(camera.live.streams || {});
-    if (available.length === 0) return;
-
-    if (streamName != null && !available.includes(streamName)) {
-      setStreamName(available[0]);
-    }
-  }, [streamNameLoaded, camera.live.streams, streamName, setStreamName]);
-
   const { data: cameraMetadata } = useSWR<LiveStreamMetadata>(
     isRestreamed ? `go2rtc/streams/${streamName}` : null,
     {