Rewrite build model task to be asynchronous so it doesn't block the pipeline

frigate/data_processing/common/face/model.py

@@ -1,5 +1,7 @@
 import logging
 import os
+import queue
+import threading
 from abc import ABC, abstractmethod
 
 import cv2
@@ -206,15 +208,15 @@ class ArcFaceRecognizer(FaceRecognizer):
         super().__init__(config)
         self.mean_embs: dict[int, np.ndarray] = {}
         self.face_embedder: ArcfaceEmbedding = ArcfaceEmbedding()
+        self.model_builder_queue: queue.Queue | None = None
 
     def clear(self) -> None:
         self.mean_embs = {}
 
-    def build(self):
-        if not self.landmark_detector:
-            self.init_landmark_detector()
-            return None
+    def run_build_task(self) -> None:
+        self.model_builder_queue = queue.Queue()
 
+        def build_model():
             face_embeddings_map: dict[str, list[np.ndarray]] = {}
             idx = 0
 
@@ -241,10 +243,33 @@ class ArcFaceRecognizer(FaceRecognizer):
 
                 idx += 1
 
+            self.model_builder_queue.put(face_embeddings_map)
+
+        thread = threading.Thread(target=build_model)
+        thread.start()
+
+    def build(self):
+        if not self.landmark_detector:
+            self.init_landmark_detector()
+            return None
+
+        if self.model_builder_queue is not None:
+            try:
+                face_embeddings_map: dict[str, list[np.ndarray]] = (
+                    self.model_builder_queue.get(timeout=0.1)
+                )
+                self.model_builder_queue = None
+            except queue.Empty:
+                return
+        else:
+            self.run_build_task()
+            return
+
         if not face_embeddings_map:
             return
 
         for name, embs in face_embeddings_map.items():
+            if embs:
                 self.mean_embs[name] = stats.trim_mean(embs, 0.15)
 
         logger.debug("Finished building ArcFace model")