Cover others

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 = None
         self.sub_label_publisher = sub_label_publisher
         self.tensor_input_details: dict[str, Any] = None
         self.tensor_output_details: dict[str, Any] = None
@@ -79,6 +74,11 @@ 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

@@ -7,7 +7,6 @@ from typing import Any
 
 import cv2
 import numpy as np
-from tflite_runtime.interpreter import Interpreter
 
 from frigate.comms.embeddings_updater import EmbeddingsRequestEnum
 from frigate.comms.event_metadata_updater import (
@@ -44,7 +43,7 @@ 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 = None
         self.tensor_input_details: dict[str, Any] = None
         self.tensor_output_details: dict[str, Any] = None
         self.labelmap: dict[int, str] = {}
@@ -57,6 +56,11 @@ 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
+
         self.interpreter = Interpreter(
             model_path=os.path.join(self.model_dir, "model.tflite"),
             num_threads=2,
@@ -193,7 +197,7 @@ 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 = None
         self.sub_label_publisher = sub_label_publisher
         self.tensor_input_details: dict[str, Any] = None
         self.tensor_output_details: dict[str, Any] = None
@@ -207,6 +211,11 @@ 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
+
         self.interpreter = Interpreter(
             model_path=os.path.join(self.model_dir, "model.tflite"),
             num_threads=2,

frigate/embeddings/onnx/face_embedding.py

@@ -14,11 +14,6 @@ from frigate.util.downloader import ModelDownloader
 from ...config import FaceRecognitionConfig
 from .base_embedding import BaseEmbedding
 
-try:
-    from tflite_runtime.interpreter import Interpreter
-except ModuleNotFoundError:
-    from tensorflow.lite.python.interpreter import Interpreter
-
 logger = logging.getLogger(__name__)
 
 ARCFACE_INPUT_SIZE = 112
@@ -62,6 +57,11 @@ class FaceNetEmbedding(BaseEmbedding):
             if self.downloader:
                 self.downloader.wait_for_download()
 
+            try:
+                from tflite_runtime.interpreter import Interpreter
+            except ModuleNotFoundError:
+                from tensorflow.lite.python.interpreter import Interpreter
+
             self.runner = Interpreter(
                 model_path=os.path.join(MODEL_CACHE_DIR, "facedet/facenet.tflite"),
                 num_threads=2,

frigate/events/audio.py

@@ -40,12 +40,6 @@ from frigate.util.builtin import get_ffmpeg_arg_list
 from frigate.util.process import FrigateProcess
 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
-
-
 logger = logging.getLogger(__name__)
 
 
@@ -369,6 +363,11 @@ class AudioEventMaintainer(threading.Thread):
 class AudioTfl:
     @redirect_output_to_logger(logger, logging.DEBUG)
     def __init__(self, stop_event: threading.Event, num_threads=2):
+        try:
+            from tflite_runtime.interpreter import Interpreter
+        except ModuleNotFoundError:
+            from tensorflow.lite.python.interpreter import Interpreter
+
         self.stop_event = stop_event
         self.num_threads = num_threads
         self.labels = load_labels("/audio-labelmap.txt", prefill=521)