谷歌开源姿态识别mediapipe-python安装配置

软件需求（win10系统）

 

配置python软件：anaconda（带python和相关第三方包）      https://anaconda.org/

编译器：vscode

其他环境软件：jdk10以上，VC_redist.x64（重要，不然出现找不到模块问题）

 

安装

1、安装完上述软件后，运行cmd     输入  python 出现版本号，python安装正常

2、输入 pip install  mediapipe  安装软件包

3、配置jdk 环境变量。

4、VS code 安装python插件。

运行

1、在谷歌https://mediapipe.dev/网站上查看demon。

2、在VS code运行官方手部视频识别例子，要有摄像头。

import sys
from cv2 import cv2
import mediapipe as mp
mp_face_detection = mp.solutions.face_detection
mp_drawing = mp.solutions.drawing_utils
mp_drawing = mp.solutions.drawing_utils
mp_hands = mp.solutions.hands
# For webcam input:
cap = cv2.VideoCapture(0)
with mp_hands.Hands(
    min_detection_confidence=0.9,
    min_tracking_confidence=0.9) as hands:
  while cap.isOpened():
    success, image = cap.read()
    if not success:
      print("Ignoring empty camera frame.")
      # If loading a video, use 'break' instead of 'continue'.
      continue

    # 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
cap.release()

识别如下