poseDetection.py

import cv2
import mediapipe as mp
import time


mp_drawing = mp.solutions.drawing_utils
mp_pose = mp.solutions.pose


cap = cv2.VideoCapture(0)


with mp_pose.Pose(
    min_detection_confidence=0.5,
    min_tracking_confidence=0.5) as pose:


    while cap.isOpened():

        success, image = cap.read()

        start = time.time()


        # Flip the image horizontally for a later selfie-view display 
        # Convert the BGR image to RGB.
        image = cv2.cvtColor(cv2.flip(image, 1), cv2.COLOR_BGR2RGB)
       
        # To improve performance, optionally mark the image as not writeable to
        # pass by reference.
        image.flags.writeable = False

        # Process the image and detect the pose
        results = pose.process(image)

        image.flags.writeable = True

        # Convert the image color back so it can be displayed
        image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)



        # Draw the pose annotation on the image.
        mp_drawing.draw_landmarks(
            image, results.pose_landmarks, mp_pose.POSE_CONNECTIONS)



        end = time.time()
        totalTime = end - start

        fps = 1 / totalTime

        cv2.putText(image, f'FPS: {int(fps)}', (20,70), cv2.FONT_HERSHEY_SIMPLEX, 1.5, (0,255,0), 2)

        cv2.imshow('MediaPipe Pose', image)


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

cap.release()