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/util/downloader.py

@@ -101,7 +101,7 @@ class ModelDownloader:
         self.download_complete.set()
 
     @staticmethod
-    def download_from_url(url: str, save_path: str, silent: bool = False):
+    def download_from_url(url: str, save_path: str, silent: bool = False) -> Path:
         temporary_filename = Path(save_path).with_name(
             os.path.basename(save_path) + ".part"
         )
@@ -125,6 +125,8 @@ class ModelDownloader:
         if not silent:
             logger.info(f"Downloading complete: {url}")
 
+        return Path(save_path)
+
     @staticmethod
     def mark_files_state(
         requestor: InterProcessRequestor,