Key point detection of human hand based on mediapipe

MediaPipe It is an open source algorithm framework of Google , Integrated face recognition , Human posture evaluation and hand detection model .
windows Under the MediaPipe install

pip install mediapipe

Be careful ：ARM Architecture doesn't have python Under the mediapipe, at present mediapipe Only support x86 framework , I won't support it arm framework , As shown in the figure below .

The code is as follows ：

"""  Key point detection of hand  """

import cv2
import mediapipe as mp
import time

cap = cv2.VideoCapture(0)
mpHands = mp.solutions.hands
hands = mpHands.Hands(static_image_mode=False,
                      max_num_hands=2,
                      min_detection_confidence=0.5,
                      min_tracking_confidence=0.5)

mpDraw = mp.solutions.drawing_utils
pTime = 0
cTime = 0
while True:
    success, img = cap.read()
    img = cv2.flip(img, 1)
    imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
    results = hands.process(imgRGB)
    #print(results.multi_hand_landmarks)
    if results.multi_hand_landmarks:
        for handLms in results.multi_hand_landmarks:
            for id, lm in enumerate(handLms.landmark):
                #print(id,lm)
                h, w, c = img.shape
                cx, cy = int(lm.x *w), int(lm.y*h)
                print(cx,cy)
                #if id ==0:
                cv2.circle(img, (cx,cy), 3, (255,0,255), cv2.FILLED)
            mpDraw.draw_landmarks(img, handLms, mpHands.HAND_CONNECTIONS)
    cTime = time.time()
    fps = 1/(cTime-pTime)
    pTime = cTime
    cv2.putText(img,str(int(fps)), (10,70), cv2.FONT_HERSHEY_PLAIN, 3, (255,0,255), 3)
    cv2.imshow("Image", img)
    cv2.waitKey(1)