Fixes (#18117)

* face library i18n fixes

* face library i18n fixes

* add ability to use ctrl/cmd S to save in the config editor

* Use datetime as ID

* Update metrics inference speed to start with 0 ms

* fix android formatted thumbnail

* ensure role is comma separated and stripped correctly

* improve face library deletion

- add a confirmation dialog
- add ability to select all / delete faces in collections

* Implement lazy loading for video previews

* Force GPU for large embedding model

* GPU is required

* settings i18n fixes

* Don't delete train tab

* webpush debugging logs

* Fix incorrectly copying zones

* copy path data

* Ensure that cache dir exists for Frigate+

* face docs update

* Add description to upload image step to clarify the image

* Clean up

---------

Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>

frigate/embeddings/onnx/face_embedding.py

@@ -23,10 +23,7 @@ FACENET_INPUT_SIZE = 160
 
 
 class FaceNetEmbedding(BaseEmbedding):
-    def __init__(
-        self,
-        device: str = "AUTO",
-    ):
+    def __init__(self):
         super().__init__(
             model_name="facedet",
             model_file="facenet.tflite",
@@ -34,7 +31,6 @@ class FaceNetEmbedding(BaseEmbedding):
                 "facenet.tflite": "https://github.com/NickM-27/facenet-onnx/releases/download/v1.0/facenet.tflite",
             },
         )
-        self.device = device
         self.download_path = os.path.join(MODEL_CACHE_DIR, self.model_name)
         self.tokenizer = None
         self.feature_extractor = None
@@ -113,10 +109,7 @@ class FaceNetEmbedding(BaseEmbedding):
 
 
 class ArcfaceEmbedding(BaseEmbedding):
-    def __init__(
-        self,
-        device: str = "AUTO",
-    ):
+    def __init__(self):
         super().__init__(
             model_name="facedet",
             model_file="arcface.onnx",
@@ -124,7 +117,6 @@ class ArcfaceEmbedding(BaseEmbedding):
                 "arcface.onnx": "https://github.com/NickM-27/facenet-onnx/releases/download/v1.0/arcface.onnx",
             },
         )
-        self.device = device
         self.download_path = os.path.join(MODEL_CACHE_DIR, self.model_name)
         self.tokenizer = None
         self.feature_extractor = None
@@ -154,7 +146,7 @@ class ArcfaceEmbedding(BaseEmbedding):
 
             self.runner = ONNXModelRunner(
                 os.path.join(self.download_path, self.model_file),
-                self.device,
+                "GPU",
             )
 
     def _preprocess_inputs(self, raw_inputs):