Python_code

import cv2
import mediapipe as mp
import pyautogui
cam = cv2.VideoCapture(0)
face_mesh = mp.solutions.face_mesh.FaceMesh(refine_landmarks=True)
screen_w, screen_h = pyautogui.size()

while True :
    _, frame = cam.read()
    frame = cv2.flip(frame, 1)
    rgb_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
    output= face_mesh.process(rgb_frame)               #for detecting face
    landmark_points = output.multi_face_landmarks
    frame_h, frame_w, _ = frame.shape
    if landmark_points:
        landmarks = landmark_points[0].landmark          #for one face only
        for id, landmark in enumerate(landmarks[474 : 478]):                      #only for landmarks in 2d not 3d(z)
            x= int(landmark.x * frame_w)
            y = int(landmark.y * frame_h)
            cv2.circle(frame , (x,y), 3, (0,0,255))
            if id ==1:
                screen_x = (screen_w+3*frame_w/2)/ frame_w * x
                screen_y = (screen_h +3*frame_h/2) /frame_h * y
                if screen_x < screen_w + frame_w/4 and screen_y < screen_h + frame_h/4:

                    pyautogui.moveTo(screen_x-frame_w/4, screen_y-frame_h/4)

        left = [landmarks[145], landmarks[159]]
        for landmark in left:
            x = int(landmark.x * frame_w)
            y = int(landmark.y * frame_h)
            cv2.circle(frame, (x, y), 3, (0, 255, 0))
        if(left[0].y - left[1].y) < 0.009:

           pyautogui.click()
           pyautogui.sleep(1)

    cv2.imshow('eye controlled mouse', frame)   #to show somw image.
    cv2.waitKey(1)                              #to make cv2 to wait for 1 sec for key