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