test_hand.py

import cv2
import mediapipe as mp

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

hands = mp_hands.Hands(
    min_detection_confidence=0.7, min_tracking_confidence=0.5)
cap = cv2.VideoCapture(0)
while cap.isOpened():
    success, image = cap.read()
    if not success:
        break

    # Flip the image horizontally for a later selfie-view display, and 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
    results = hands.process(image)

    # Draw the hand annotations on the image.
    image.flags.writeable = True
    image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
    if results.multi_hand_landmarks:
        for hand_landmarks in results.multi_hand_landmarks:
            mp_drawing.draw_landmarks(
                image, hand_landmarks, mp_hands.HAND_CONNECTIONS)
    cv2.imshow('MediaPipe Hands', image)
    if cv2.waitKey(5) & 0xFF == 27:
        break
hands.close()
cap.release()