faceMesh.py

import cv2
import mediapipe as mp
import time

# Face mesh detection
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()

        start = time.time()

        # Flip the image horizontally for a later selfie-view display
        # 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

        # Process the image
        results = face_mesh.process(image)

        image.flags.writeable = True

        # Convert the image color back so it can be displayed
        image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)


        if results.multi_face_landmarks:
          for face_landmarks in results.multi_face_landmarks:
                #print(face_landmarks)
                #print(face_landmarks.landmark.x)
                # Draw the face mesh annotations on the image.
                mp_drawing.draw_landmarks(
                    image=image,
                    landmark_list=face_landmarks,
                    connections=mp_face_mesh.FACEMESH_TESSELATION,
                    landmark_drawing_spec=drawing_spec,
                    connection_drawing_spec=drawing_spec)



        end = time.time()
        totalTime = end - start

        fps = 1 / totalTime

        cv2.putText(image, f'FPS: {int(fps)}', (20,70), cv2.FONT_HERSHEY_SIMPLEX, 1.5, (0,255,0), 2)

        cv2.imshow('MediaPipe FaceMesh', image)



        if cv2.waitKey(5) & 0xFF == 27:
            break

cap.release()