Create facemace

facemace

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+import cv2
+import mediapipe as mp
+mp_drawing = mp.solutions.drawing_utils
+mp_face_mesh = mp.solutions.face_mesh
+
+drawing_spec = mp_drawing.DrawingSpec(thickness=1, circle_radius=1)
+cap = cv2.VideoCapture(0)
+with mp_face_mesh.FaceMesh(
+    min_detection_confidence=0.5,
+    min_tracking_confidence=0.5) as face_mesh:
+  while cap.isOpened():
+    success, image = cap.read()
+    if not success:
+      print("Ignoring empty camera frame.")
+      # If loading a video, use 'break' instead of 'continue'.
+      continue
+
+    # Flip the image horizontally for a later selfie-view display, and convert
+    # the BGR image to RGB.
+    image = cv2.cvtColor(cv2.flip(image, 1), cv2.COLOR_BGR2RGB)
+    # To improve performance, optionally mark the image as not writeable to
+    # pass by reference.
+    image.flags.writeable = False
+    results = face_mesh.process(image)
+
+    # Draw the face mesh annotations on the image.
+    image.flags.writeable = True
+    image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
+    if results.multi_face_landmarks:
+      for face_landmarks in results.multi_face_landmarks:
+        #print(face_landmarks)
+        mp_drawing.draw_landmarks(
+            image=image,
+            landmark_list=face_landmarks,
+            connections=mp_face_mesh.FACE_CONNECTIONS,
+            landmark_drawing_spec=drawing_spec,
+            connection_drawing_spec=drawing_spec)
+    cv2.imshow('MediaPipe FaceMesh', image)
+    if cv2.waitKey(5) & 0xFF == 27:
+      break
+cap.release()