How it's works

1. First import the library that we need

import cv2
import numpy as np
import mediapipe as mp

2. Make the program to connect to the webcam

import cv2
import numpy as numpy

cap = cv2.VideoCapture(0)
while True:
    _, frame = cap.read()
    cv2.imshow('Hand Tracking', frame)
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break

cap.release()
cv2.destroyAllWindows()

3. Load the module of hands and drawing_utils

mp_drawing = mp.solutions.drawing_utils
mp_hands = mp.solutions.hands

4. Determine the minimum percentage

with mp_hands.Hands(
    min_detection_confidence=0.8,
    min_tracking_confidence=0.8) as hands:

5. Chanfe BGR to RGB

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

6. To optimize the program change writeable to False

image.flags.writeable = False

7. processing

results = hands.process(image)

8. Change RGB to BGR

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

9. Make a loop and draw the landmark

if results.multi_hand_landmarks:
    for hand_landmarks in results.multi_hand_landmarks:
        mp_drawing.draw_landmarks(
            	image, hand_landmarks, mp_hands.HAND_CONNECTIONS,mp_drawing.DrawingSpec(color=(0, 0, 255 )),
                mp_drawing.DrawingSpec(color=(255, 255, 255 )))

Demo

Clik the picture to see the Video