tds-face-land-4.py

# IMPORTING LIBRARIES
import cv2
import mediapipe as mp

# INITIALIZING OBJECTS
mp_drawing = mp.solutions.drawing_utils
mp_drawing_styles = mp.solutions.drawing_styles
mp_face_mesh = mp.solutions.face_mesh

drawing_spec = mp_drawing.DrawingSpec(thickness=1, circle_radius=1)
cap = cv2.VideoCapture(0)

# DETECT THE FACE LANDMARKS
with mp_face_mesh.FaceMesh(min_detection_confidence=0.5, min_tracking_confidence=0.5) as face_mesh:
  while True:
    success, image = cap.read()

    # Flip the image horizontally and convert the color space from BGR to RGB
    image = cv2.cvtColor(cv2.flip(image, 1), cv2.COLOR_BGR2RGB)

    # To improve performance
    image.flags.writeable = False
    
    # Detect the face landmarks
    results = face_mesh.process(image)

    # To improve performance
    image.flags.writeable = True

    # Convert back to the BGR color space
    image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
    
    # Draw the face mesh annotations on the image.
    if results.multi_face_landmarks:
      for face_landmarks in results.multi_face_landmarks:
        mp_drawing.draw_landmarks(
            image=image,
            landmark_list=face_landmarks,
            connections=mp_face_mesh.FACEMESH_TESSELATION,
            landmark_drawing_spec=None,
            connection_drawing_spec=mp_drawing_styles
            .get_default_face_mesh_tesselation_style())

    # Display the image
    cv2.imshow('MediaPipe FaceMesh', image)
    
    # Terminate the process
    if cv2.waitKey(5) & 0xFF == 27:
      break

cap.release()