Face recognition backend (#14495)

* Add basic config and face recognition table

* Reconfigure updates processing to handle face

* Crop frame to face box

* Implement face embedding calculation

* Get matching face embeddings

* Add support face recognition based on existing faces

* Use arcface face embeddings instead of generic embeddings model

* Add apis for managing faces

* Implement face uploading API

* Build out more APIs

* Add min area config

* Handle larger images

* Add more debug logs

* fix calculation

* Reduce timeout

* Small tweaks

* Use webp images

* Use facenet model

frigate/comms/embeddings_updater.py

@@ -12,6 +12,7 @@ class EmbeddingsRequestEnum(Enum):
     embed_description = "embed_description"
     embed_thumbnail = "embed_thumbnail"
     generate_search = "generate_search"
+    register_face = "register_face"
 
 
 class EmbeddingsResponder:
@@ -22,7 +23,7 @@ class EmbeddingsResponder:
 
     def check_for_request(self, process: Callable) -> None:
         while True:  # load all messages that are queued
-            has_message, _, _ = zmq.select([self.socket], [], [], 0.1)
+            has_message, _, _ = zmq.select([self.socket], [], [], 0.01)
 
             if not has_message:
                 break