Miscellaneous Fixes (0.17 beta) (#21301)

* Wait for config to load before evaluating route access

Fix race condition where custom role users are temporarily denied access after login while config is still loading. Defer route rendering in DefaultAppView until config is available so the complete role list is known before ProtectedRoute evaluates permissions

* Use batching for state classification generation

* Ignore incorrect scoring images if they make it through the deletion

* Delete unclassified images

* mitigate tensorflow atexit crash by pre-importing tflite/tensorflow on main thread

Pre-import Interpreter in embeddings maintainer and add defensive lazy imports in classification processors to avoid worker-thread tensorflow imports causing "can't register atexit after shutdown"

* don't require old password for users with admin role when changing passwords

* don't render actions menu if no options are available

* Remove hwaccel arg as it is not used for encoding

* change password button text

---------

Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>

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 = 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] = {}
@@ -74,6 +69,11 @@ class CustomStateClassificationProcessor(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")
 
@@ -345,7 +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 = 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
@@ -368,6 +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")