[update] remove dummy functions

deepface/models/demography/Age.py

@@ -75,32 +75,6 @@ class ApparentAgeClient(Demography):
 
         return apparent_ages
 
-
-    def predicts(self, imgs: List[np.ndarray]) -> np.ndarray:
-        """
-        Predict apparent ages of multiple faces
-        Args:
-            imgs (List[np.ndarray]): (n, 224, 224, 3)
-        Returns:
-            apparent_ages (np.ndarray): (n,)
-        """
-        # Convert list to numpy array
-        imgs_:np.ndarray = np.array(imgs)
-        # Remove batch dimension if exists
-        imgs_ = imgs_.squeeze()
-        # Check if the input is a single image
-        if len(imgs_.shape) == 3:
-            # Add batch dimension if not exists
-            imgs_ = np.expand_dims(imgs_, axis=0)
-        # Batch prediction
-        age_predictions = self.model.predict_on_batch(imgs_)
-        apparent_ages = np.array(
-            [find_apparent_age(age_prediction) for age_prediction in age_predictions]
-        )
-        return apparent_ages
-
-
-
 def load_model(
     url=WEIGHTS_URL,
 ) -> Model:

deepface/models/demography/Gender.py

@@ -70,27 +70,6 @@ class GenderClient(Demography):
 
         return predictions
 
-
-    def predicts(self, imgs: List[np.ndarray]) -> np.ndarray:
-        """
-        Predict apparent ages of multiple faces
-        Args:
-            imgs (List[np.ndarray]): (n, 224, 224, 3)
-        Returns:
-            apparent_ages (np.ndarray): (n,)
-        """
-        # Convert list to numpy array
-        imgs_:np.ndarray = np.array(imgs)
-        # Remove redundant dimensions
-        imgs_ = imgs_.squeeze()
-        # Check if the input is a single image
-        if len(imgs_.shape) == 3:
-            # Add batch dimension
-            imgs_ = np.expand_dims(imgs_, axis=0)
-        return self.model.predict_on_batch(imgs_)
-
-
-
 def load_model(
     url=WEIGHTS_URL,
 ) -> Model: