diff --git a/frigate/detectors/detector_utils.py b/frigate/detectors/detector_utils.py
new file mode 100644
index 000000000..d6445d5c0
--- /dev/null
+++ b/frigate/detectors/detector_utils.py
@@ -0,0 +1,36 @@
+import numpy as np
+
+
+def tflite_init(self, interpreter):
+    self.interpreter = interpreter
+
+    self.interpreter.allocate_tensors()
+
+    self.tensor_input_details = self.interpreter.get_input_details()
+    self.tensor_output_details = self.interpreter.get_output_details()
+
+
+def tflite_detect_raw(self, tensor_input):
+    self.interpreter.set_tensor(self.tensor_input_details[0]["index"], tensor_input)
+    self.interpreter.invoke()
+
+    boxes = self.interpreter.tensor(self.tensor_output_details[0]["index"])()[0]
+    class_ids = self.interpreter.tensor(self.tensor_output_details[1]["index"])()[0]
+    scores = self.interpreter.tensor(self.tensor_output_details[2]["index"])()[0]
+    count = int(self.interpreter.tensor(self.tensor_output_details[3]["index"])()[0])
+
+    detections = np.zeros((20, 6), np.float32)
+
+    for i in range(count):
+        if scores[i] < 0.4 or i == 20:
+            break
+        detections[i] = [
+            class_ids[i],
+            float(scores[i]),
+            boxes[i][0],
+            boxes[i][1],
+            boxes[i][2],
+            boxes[i][3],
+        ]
+
+    return detections
diff --git a/frigate/detectors/plugins/cpu_tfl.py b/frigate/detectors/plugins/cpu_tfl.py
index 8a54363e1..fc8db0f4b 100644
--- a/frigate/detectors/plugins/cpu_tfl.py
+++ b/frigate/detectors/plugins/cpu_tfl.py
@@ -1,12 +1,13 @@
 import logging
 
-import numpy as np
 from pydantic import Field
 from typing_extensions import Literal
 
 from frigate.detectors.detection_api import DetectionApi
 from frigate.detectors.detector_config import BaseDetectorConfig
 
+from ..detector_utils import tflite_detect_raw, tflite_init
+
 try:
     from tflite_runtime.interpreter import Interpreter
 except ModuleNotFoundError:
@@ -27,39 +28,12 @@ class CpuTfl(DetectionApi):
     type_key = DETECTOR_KEY
 
     def __init__(self, detector_config: CpuDetectorConfig):
-        self.interpreter = Interpreter(
+        interpreter = Interpreter(
             model_path=detector_config.model.path,
             num_threads=detector_config.num_threads or 3,
         )
 
-        self.interpreter.allocate_tensors()
-
-        self.tensor_input_details = self.interpreter.get_input_details()
-        self.tensor_output_details = self.interpreter.get_output_details()
+        tflite_init(self, interpreter)
 
     def detect_raw(self, tensor_input):
-        self.interpreter.set_tensor(self.tensor_input_details[0]["index"], tensor_input)
-        self.interpreter.invoke()
-
-        boxes = self.interpreter.tensor(self.tensor_output_details[0]["index"])()[0]
-        class_ids = self.interpreter.tensor(self.tensor_output_details[1]["index"])()[0]
-        scores = self.interpreter.tensor(self.tensor_output_details[2]["index"])()[0]
-        count = int(
-            self.interpreter.tensor(self.tensor_output_details[3]["index"])()[0]
-        )
-
-        detections = np.zeros((20, 6), np.float32)
-
-        for i in range(count):
-            if scores[i] < 0.4 or i == 20:
-                break
-            detections[i] = [
-                class_ids[i],
-                float(scores[i]),
-                boxes[i][0],
-                boxes[i][1],
-                boxes[i][2],
-                boxes[i][3],
-            ]
-
-        return detections
+        return tflite_detect_raw(self, tensor_input)