face

 # Import Libraries

import cv2

import time

import mediapipe as mp

# Grabbing the Holistic Model from Mediapipe and

# Initializing the Model

mp_holistic = mp.solutions.holistic

holistic_model = mp_holistic.Holistic(

    min_detection_confidence=0.5,

    min_tracking_confidence=0.5

)

# Initializing the drawing utils for drawing the facial landmarks on image

mp_drawing = mp.solutions.drawing_utils

# (0) in VideoCapture is used to connect to your computer's default camera

capture = cv2.VideoCapture(0)

# Initializing current time and precious time for calculating the FPS

previousTime = 0

currentTime = 0

while capture.isOpened():

    # capture frame by frame

    ret, frame = capture.read()

    # resizing the frame for better view

    frame = cv2.resize(frame, (800, 600))

    # Converting the from BGR to RGB

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

    # Making predictions using holistic model

    # To improve performance, optionally mark the image as not writeable to

    # pass by reference.

    image.flags.writeable = False

    results = holistic_model.process(image)

    image.flags.writeable = True

    # Converting back the RGB image to BGR

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

    # Drawing the Facial Landmarks

    mp_drawing.draw_landmarks(

    image,

    results.face_landmarks,

    mp_holistic.FACEMESH_CONTOURS,

    mp_drawing.DrawingSpec(

        color=(255,0,255),

        thickness=1,

        circle_radius=1

    ),

    mp_drawing.DrawingSpec(

        color=(0,255,255),

        thickness=1,

        circle_radius=1

    )

    )

    # Drawing Right hand Land Marks

    mp_drawing.draw_landmarks(

    image,

    results.right_hand_landmarks,

    mp_holistic.HAND_CONNECTIONS

    )

    # Drawing Left hand Land Marks

    mp_drawing.draw_landmarks(

    image,

    results.left_hand_landmarks,

    mp_holistic.HAND_CONNECTIONS

    )

   

    # Calculating the FPS

    currentTime = time.time()

    fps = 1 / (currentTime-previousTime)

    previousTime = currentTime

   

    # Displaying FPS on the image

    cv2.putText(image, str(int(fps))+" FPS", (10, 70), cv2.FONT_HERSHEY_COMPLEX, 1, (0,255,0), 2)

    # Display the resulting image

    cv2.imshow("Facial and Hand Landmarks", image)

    # Enter key 'q' to break the loop

    if cv2.waitKey(5) & 0xFF == ord('q'):

        break

# When all the process is done

# Release the capture and destroy all windows

capture.release()

cv2.destroyAllWindows()

# Code to access landmarks

for landmark in mp_holistic.HandLandmark:

    print(landmark, landmark.value)

print(mp_holistic.HandLandmark.WRIST.value)