Simplify detect faces code

eye_tracking/gaze/head_pose_estimation/face_landmark_estimator.py

@@ -1,7 +1,5 @@
 from typing import List
 
-import face_alignment
-import face_alignment.detection.sfd
 import mediapipe
 import numpy as np
 from omegaconf import DictConfig
@@ -19,21 +17,14 @@ def __init__(self, config: DictConfig):
         )
 
     def detect_faces(self, image: np.ndarray) -> List[Face]:
-        return self._detect_faces_mediapipe(image)
-
-    def detect_faces_raw(self, image: np.ndarray) -> List[np.ndarray]:
-        if self.mode == "mediapipe":
-            return self._detect_faces_mediapipe_raw(image)
-        else:
-            raise ValueError
-
-    def _detect_faces_mediapipe(self, image: np.ndarray) -> List[Face]:
         """
         Calculated landmarks scaled to the image size with a bounding box
+        :param image: RGB image
+        :return: List of faces
         """
 
         h, w = image.shape[:2]
-        faces_landmarks = self._detect_faces_mediapipe_raw(image)
+        faces_landmarks = self._detect_faces_raw(image)
         detected = []
         if faces_landmarks:
             for face in faces_landmarks:
@@ -43,9 +34,17 @@ def _detect_faces_mediapipe(self, image: np.ndarray) -> List[Face]:
                 detected.append(Face(bbox, pts))
         return detected
 
-    def _detect_faces_mediapipe_raw(self, image: np.ndarray) -> List[np.ndarray]:
+    def detect_faces_raw(self, image: np.ndarray) -> List[np.ndarray]:
+        if self.mode == "mediapipe":
+            return self._detect_faces_raw(image)
+        else:
+            raise ValueError
+
+    def _detect_faces_raw(self, image: np.ndarray) -> List[np.ndarray]:
         """
-        Returns landmarks as they come from the mediapipe model
+        Returns landmarks as they come from the mediapipe model (not scaled to the image size)
+        :param image: RGB image
+        :return: List of faces landmarks
         """
         predictions = self.detector.process(self._get_bgr_frame(image))
         faces_landmarks = []