Merge 67dca94651 into ef5608a970

* Revert "Fix saving attributes for object to DB (#22000)"

This reverts commit 73c1e12faf.

* Automatically handle attributes by obj data parsing

frigate/data_processing/real_time/bird.py

@@ -22,7 +22,7 @@ from .api import RealTimeProcessorApi
 try:
     from tflite_runtime.interpreter import Interpreter
 except ModuleNotFoundError:
-    from tensorflow.lite.python.interpreter import Interpreter
+    from ai_edge_litert.interpreter import Interpreter
 
 logger = logging.getLogger(__name__)
 

frigate/data_processing/real_time/custom_classification.py

@@ -32,7 +32,7 @@ from .api import RealTimeProcessorApi
 try:
     from tflite_runtime.interpreter import Interpreter
 except ModuleNotFoundError:
-    from tensorflow.lite.python.interpreter import Interpreter
+    from ai_edge_litert.interpreter import Interpreter
 
 logger = logging.getLogger(__name__)
 
@@ -76,7 +76,7 @@ class CustomStateClassificationProcessor(RealTimeProcessorApi):
         try:
             from tflite_runtime.interpreter import Interpreter
         except ModuleNotFoundError:
-            from tensorflow.lite.python.interpreter import Interpreter
+            from ai_edge_litert.interpreter import Interpreter
 
         model_path = os.path.join(self.model_dir, "model.tflite")
         labelmap_path = os.path.join(self.model_dir, "labelmap.txt")

frigate/detectors/detector_utils.py

@@ -6,7 +6,7 @@ import numpy as np
 try:
     from tflite_runtime.interpreter import Interpreter, load_delegate
 except ModuleNotFoundError:
-    from tensorflow.lite.python.interpreter import Interpreter, load_delegate
+    from ai_edge_litert.interpreter import Interpreter, load_delegate
 
 
 logger = logging.getLogger(__name__)

frigate/detectors/plugins/cpu_tfl.py

@@ -12,7 +12,7 @@ from ..detector_utils import tflite_detect_raw, tflite_init
 try:
     from tflite_runtime.interpreter import Interpreter
 except ModuleNotFoundError:
-    from tensorflow.lite.python.interpreter import Interpreter
+    from ai_edge_litert.interpreter import Interpreter
 
 
 logger = logging.getLogger(__name__)

frigate/detectors/plugins/edgetpu_tfl.py

@@ -13,7 +13,7 @@ from frigate.detectors.detector_config import BaseDetectorConfig, ModelTypeEnum
 try:
     from tflite_runtime.interpreter import Interpreter, load_delegate
 except ModuleNotFoundError:
-    from tensorflow.lite.python.interpreter import Interpreter, load_delegate
+    from ai_edge_litert.interpreter import Interpreter, load_delegate
 
 logger = logging.getLogger(__name__)
 

frigate/embeddings/onnx/face_embedding.py

@@ -17,7 +17,7 @@ from .base_embedding import BaseEmbedding
 try:
     from tflite_runtime.interpreter import Interpreter
 except ModuleNotFoundError:
-    from tensorflow.lite.python.interpreter import Interpreter
+    from ai_edge_litert.interpreter import Interpreter
 
 logger = logging.getLogger(__name__)
 

frigate/events/audio.py

@@ -43,7 +43,7 @@ from frigate.video import start_or_restart_ffmpeg, stop_ffmpeg
 try:
     from tflite_runtime.interpreter import Interpreter
 except ModuleNotFoundError:
-    from tensorflow.lite.python.interpreter import Interpreter
+    from ai_edge_litert.interpreter import Interpreter
 
 
 logger = logging.getLogger(__name__)

frigate/track/object_processing.py

@@ -33,7 +33,6 @@ from frigate.config.camera.updater import (
     CameraConfigUpdateEnum,
     CameraConfigUpdateSubscriber,
 )
-from frigate.config.classification import ObjectClassificationType
 from frigate.const import (
     FAST_QUEUE_TIMEOUT,
     UPDATE_CAMERA_ACTIVITY,
@@ -760,16 +759,8 @@ class TrackedObjectProcessor(threading.Thread):
 
             self.update_mqtt_motion(camera, frame_time, motion_boxes)
 
-            attribute_model_names = [
-                name
-                for name, model_config in self.config.classification.custom.items()
-                if model_config.object_config
-                and model_config.object_config.classification_type
-                == ObjectClassificationType.attribute
-            ]
             tracked_objects = [
-                o.to_dict(attribute_model_names=attribute_model_names)
-                for o in camera_state.tracked_objects.values()
+                o.to_dict() for o in camera_state.tracked_objects.values()
             ]
 
             # publish info on this frame

frigate/track/tracked_object.py

@@ -376,11 +376,15 @@ class TrackedObject:
         )
         return (thumb_update, significant_change, path_update, autotracker_update)
 
-    def to_dict(
-        self,
-        attribute_model_names: list[str] | None = None,
-    ) -> dict[str, Any]:
-        event = {
+    def to_dict(self) -> dict[str, Any]:
+        # Tracking internals excluded from output (centroid, estimate, estimate_velocity)
+        _EXCLUDED_OBJ_DATA_KEYS = {
+            "centroid",
+            "estimate",
+            "estimate_velocity",
+        }
+
+        event: dict[str, Any] = {
             "id": self.obj_data["id"],
             "camera": self.camera_config.name,
             "frame_time": self.obj_data["frame_time"],
@@ -414,11 +418,11 @@ class TrackedObject:
             "path_data": self.path_data.copy(),
             "recognized_license_plate": self.obj_data.get("recognized_license_plate"),
         }
-        if attribute_model_names is not None:
-            for name in attribute_model_names:
-                value = self.obj_data.get(name)
-                if value is not None:
-                    event[name] = value
+
+        # Add any other obj_data keys (e.g. custom attribute fields) not yet included
+        for key, value in self.obj_data.items():
+            if key not in _EXCLUDED_OBJ_DATA_KEYS and key not in event:
+                event[key] = value
 
         return event