hands.py

import cv2
import mediapipe as mp
mp_drawing = mp.solutions.drawing_utils
mp_drawing_styles = mp.solutions.drawing_styles
mp_hands = mp.solutions.hands
 
# Webカメラから入力
cap = cv2.VideoCapture(0)
with mp_hands.Hands(
    model_complexity=0,
    min_detection_confidence=0.5,
    min_tracking_confidence=0.5) as hands:
  while cap.isOpened():
    success, image = cap.read()
    if not success:
      print("Ignoring empty camera frame.")
      continue
    image.flags.writeable = False
    image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
    results = hands.process(image)
 
    # 検出された手の骨格をカメラ画像に重ねて描画
    image.flags.writeable = True
    image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
    if results.multi_hand_landmarks:
      width=cap.get(cv2.CAP_PROP_FRAME_WIDTH)
      height=cap.get(cv2.CAP_PROP_FRAME_HEIGHT)
     # print("width"+str(cap.get(cv2.CAP_PROP_FRAME_WIDTH)))
    # print("height"+str(cap.get(cv2.CAP_PROP_FRAME_HEIGHT)))
     # print("aaaaaaaaaaaaaaaaaaaaaaa")
      print(results.multi_hand_landmarks[0].landmark[1].x)
    #  x=results.multi_hand_landmarks[0].landmark.x
     # y=results.multi_hand_landmarks[0].landmark.y
    #  print(x,y)
      for hand_landmarks in results.multi_hand_landmarks:
        mp_drawing.draw_landmarks(
            image,
            hand_landmarks,
            mp_hands.HAND_CONNECTIONS,
            mp_drawing_styles.get_default_hand_landmarks_style(),
            mp_drawing_styles.get_default_hand_connections_style())
        cv2.drawMarker(image,(100,100),(0,0,0),markerType=cv2.MARKER_STAR, markerSize=10)
    #cv2.imshow('MediaPipe Hands', cv2.flip(image, 1))
    cv2.imshow('MediaPipe Hands', image)
    if cv2.waitKey(5) & 0xFF == 27:
      break
cap.release()