From edcef02511d6c789734842693e787655951fbdb4 Mon Sep 17 00:00:00 2001
From: Nat Lee <natlee.work@gmail.com>
Date: Tue, 31 Dec 2024 17:30:28 +0800
Subject: [PATCH] [update] remove dummy functions

---
 deepface/models/demography/Age.py    | 26 --------------------------
 deepface/models/demography/Gender.py | 21 ---------------------
 2 files changed, 47 deletions(-)

diff --git a/deepface/models/demography/Age.py b/deepface/models/demography/Age.py
index 236bbdf..57ffbcf 100644
--- a/deepface/models/demography/Age.py
+++ b/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:
diff --git a/deepface/models/demography/Gender.py b/deepface/models/demography/Gender.py
index 2ef4cc2..1c06a76 100644
--- a/deepface/models/demography/Gender.py
+++ b/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: