test.py

import cv2
import time
import mediapipe as mp
import numpy as np

# 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

    # 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,
    )
    
    print("----------------------")
    print(results.right_hand_landmarks)

    # 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()