How it's works

1. First import the library that we need

import cv2
import mediapipe as mp

2. Make the program to connect to the webcam

import cv2
import numpy as numpy

cap = cv2.VideoCapture(0)
while True:
    _, frame = cap.read()
    cv2.imshow('Face Mesh', frame)
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break

cap.release()
cv2.destroyAllWindows()

3. Load the module of face_mesh and drawing_utils

mp_drawing = mp.solutions.drawing_utils
mp_face_mesh = mp.solutions.face_mesh

4. Determine the minimum percentage

with mp_face_mesh.FaceMesh(
    min_detection_confidence=0.5,
    min_tracking_confidence=0.5) as face_mesh:

5. Chanfe BGR to RGB

image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)

6. To optimize the program change writeable to False

image.flags.writeable = False

7. processing

results = hands.process(image)

8. Change RGB to BGR

image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)

9. Make a loop and draw the landmark

drawing_spec = mp_drawing.DrawingSpec(color=(0,251,251),thickness=1, circle_radius=1)

if results.multi_face_landmarks:
            for face_landmarks in results.multi_face_landmarks:
                mp_drawing.draw_landmarks(image,face_landmarks,mp_face_mesh.FACE_CONNECTIONS,drawing_spec,drawing_spec)