Update landmarks.py

landmarks.py

@@ -1,7 +1,7 @@
 import cv2
 import numpy as np
 from typing import List, Iterable, Optional
-from mediapipe import solutions as mp_solutions  # Updated import
+from mediapipe.python.solutions.face_mesh import FaceMesh  # Correct import
 
 
 def detect_landmarks(src: np.ndarray, is_stream: bool = False) -> Optional[List]:
@@ -9,27 +9,21 @@ def detect_landmarks(src: np.ndarray, is_stream: bool = False) -> Optional[List]
     Given an image `src`, retrieves the facial landmarks associated with it.
     Works with Mediapipe 0.10+.
     """
-    # Initialize FaceMesh
-    with mp_solutions.face_mesh.FaceMesh(
+    with FaceMesh(
         static_image_mode=not is_stream,
         max_num_faces=1,
-        refine_landmarks=True,  # optional, provides iris landmarks if needed
+        refine_landmarks=True,
         min_detection_confidence=0.5,
         min_tracking_confidence=0.5
     ) as fm:
-        # Convert BGR to RGB as Mediapipe expects RGB
         results = fm.process(cv2.cvtColor(src, cv2.COLOR_BGR2RGB))
     
-    # Return the landmarks if found
     if results.multi_face_landmarks:
         return results.multi_face_landmarks[0].landmark
     return None
 
 
 def normalize_landmarks(landmarks, height: int, width: int, mask: Iterable = None) -> np.ndarray:
-    """
-    Converts normalized Mediapipe landmark coordinates to pixel coordinates.
-    """
     normalized_landmarks = np.array([
         (int(landmark.x * width), int(landmark.y * height)) for landmark in landmarks
     ])
@@ -39,12 +33,9 @@ def normalize_landmarks(landmarks, height: int, width: int, mask: Iterable = Non
 
 
 def plot_landmarks(src: np.ndarray, landmarks: List, show: bool = False) -> np.ndarray:
-    """
-    Given a source image and a list of landmarks, plots them onto the image.
-    """
     dst = src.copy()
     for x, y in landmarks:
-        cv2.circle(dst, (x, y), 2, (0, 255, 0), cv2.FILLED)  # green dots for visibility
+        cv2.circle(dst, (x, y), 2, (0, 255, 0), cv2.FILLED)
     if show:
         print("Displaying image plotted with landmarks")
         cv2.imshow("Plotted Landmarks", dst)