Add vggface2 to extraction pipeline

lib/align/detected_face.py

@@ -104,7 +104,7 @@ def __init__(self,
         self.top = top
         self.height = height
         self._landmarks_xy = landmarks_xy
-        self._identity: Dict[Literal["vggface2"], np.ndarray] = {}
+        self._identity: Dict[str, np.ndarray] = {}
         self.thumbnail: Optional[np.ndarray] = None
         self.mask = {} if mask is None else mask
         self._training_masks: Optional[Tuple[bytes, Tuple[int, int, int]]] = None
@@ -137,7 +137,7 @@ def bottom(self) -> int:
         return self.top + self.height
 
     @property
-    def identity(self) -> Dict[Literal["vggface2"], np.ndarray]:
+    def identity(self) -> Dict[str, np.ndarray]:
         """ dict: Identity mechanism as key, identity embedding as value. """
         return self._identity
 
@@ -191,7 +191,7 @@ def add_landmarks_xy(self, landmarks: np.ndarray) -> None:
         logger.trace("landmarks shape: '%s'", landmarks.shape)  # type: ignore
         self._landmarks_xy = landmarks
 
-    def add_identity(self, name: Literal["vggface2"], embedding: np.ndarray, ) -> None:
+    def add_identity(self, name: str, embedding: np.ndarray, ) -> None:
         """ Add an identity embedding to this detected face. If an identity already exists for the
         given :attr:`name` it will be overwritten
 

lib/cli/args.py

@@ -495,6 +495,13 @@ def get_optional_arguments() -> List[Dict[str, Any]]:
                    "more faces at the cost of extraction speed. Pass in a single number to use "
                    "increments of that size up to 360, or pass in a list of numbers to enumerate "
                    "exactly what angles to check.")))
+        argument_list.append(dict(
+            opts=("-I", "--identity"),
+            action="store_true",
+            default=False,
+            group=_("Plugins"),
+            help=_("Obtain and store face identity encodings from VGGFace2. Slows down extract a "
+                   "little, but will save time if using 'sort by face'")))
         argument_list.append(dict(
             opts=("-min", "--min-size"),
             action=Slider,