import cv2

import mediapipe as mp

cap = cv2.VideoCapture(0)

with mp_face_mesh.FaceMesh(

refine_landmarks=True,

min_tracking_confidence=0.5) as face_mesh:

while cap.isOpened():

if not success:

print("Ignoring empty camera frame.")

# If loading a video, use 'break' instead of 'continue'.

continue

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

# pass by reference.

image.flags.writeable = False

# Draw the face mesh annotations on the image.

image.flags.writeable = True

if results.multi_face_landmarks:

for face_landmarks in results.multi_face_landmarks:

landmark_drawing_spec=None,

landmark_drawing_spec=None,

landmark_drawing_spec=None,

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

cv2.imshow('MediaPipe Face Mesh', cv2.flip(image, 1))

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

break

import cv2

import time

import mediapipe as mp

print('')

for landmark in mp_holistic.HandLandmark:

print(landmark, landmark.value)

print('')

capture = cv2.VideoCapture(0)

while capture.isOpened():

# capture frame by frame

# resizing the frame for better view

# Converting the from BGR to RGB

# Making predictions using holistic model

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

# pass by reference.

image.flags.writeable = False

image.flags.writeable = True

# Converting back the RGB image to BGR

# Drawing the Facial Landmarks

# Drawing Right hand Land Marks

# Drawing Left hand Land Marks

# Calculating the FPS

# 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

cv2.destroyAllWindows()