MediaPipe is a cross-platform framework for building multimodal applied machine learning pipelines. MediaPipe Python package is available on PyPI for Linux, macOS, and Windows.

Today we will write a simple code for hand joint detection using OpenCV.

At first, import the necessary packages –

import cv2
import mediapipe as mp
import time

Initialize the classes-

cap = cv2.VideoCapture(0)
mpHands =
hands = mpHands.Hands()
mpDraw =

Final code-

pTime = 0
cTime = 0

while True:
    success, image =
    imgRGB = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
    results = hands.process(imgRGB)

    if results.multi_hand_landmarks:
        for handLms in results.multi_hand_landmarks:
            for id, lm in enumerate (handLms.landmark):
                h, w, c = image.shape
                cx, cy = int(lm.x*w), int(lm.y*h)
                print(id, cx, cy)
                if id == 4:
          ,(cx,cy),15, (255,0,255),cv2.FILLED)

            mpDraw.draw_landmarks(image, handLms, mpHands.HAND_CONNECTIONS)

    cTime = time.time()
    fps = 1/(cTime-pTime)
    pTime = cTime

    cv2.putText(image, str(int(fps)),(10,60), cv2.FONT_HERSHEY_PLAIN,3, (255,0,255),4)
    cv2.imshow("Results", image)
    if cv2.waitKey(1) & 0XFF == ord('q'):

And the final output-

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