Windows下如何运行mediapipe（极简版）

硬件准备：一个USB摄像头

必备库：

1.安装opencv-python库（win下安装opencv非常简单，此处不再赘述）

2.安装mediapipe库

pip install mediapipe

打开vscode，新建空python文件，将示例代码复制进去，这里以face_detection举例：

示例代码网址 ：Face Detection | mediapipe (google.github.io)

代码内容如下：

import cv2
import mediapipe as mp
mp_face_detection = mp.solutions.face_detection
mp_drawing = mp.solutions.drawing_utils

# For static images:
IMAGE_FILES = []
with mp_face_detection.FaceDetection(
    model_selection=1, min_detection_confidence=0.5) as face_detection:
  for idx, file in enumerate(IMAGE_FILES):
    image = cv2.imread(file)
    # Convert the BGR image to RGB and process it with MediaPipe Face Detection.
    results = face_detection.process(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))

    # Draw face detections of each face.
    if not results.detections:
      continue
    annotated_image = image.copy()
    for detection in results.detections:
      print('Nose tip:')
      print(mp_face_detection.get_key_point(
          detection, mp_face_detection.FaceKeyPoint.NOSE_TIP))
      mp_drawing.draw_detection(annotated_image, detection)
    cv2.imwrite('/tmp/annotated_image' + str(idx) + '.png', annotated_image)

# For webcam input:
cap = cv2.VideoCapture(0)
with mp_face_detection.FaceDetection(
    model_selection=0, min_detection_confidence=0.5) as face_detection:
  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

    # To improve performance, optionally mark the image as not writeable to
    # pass by reference.
    image.flags.writeable = False
    image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
    results = face_detection.process(image)

    # Draw the face detection annotations on the image.
    image.flags.writeable = True
    image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
    if results.detections:
      for detection in results.detections:
        mp_drawing.draw_detection(image, detection)
    # Flip the image horizontally for a selfie-view display.
    cv2.imshow('MediaPipe Face Detection', cv2.flip(image, 1))
    if cv2.waitKey(5) & 0xFF == 27:
      break
cap.release()

注意中间需要选择摄像头（这是唯一可能需要修改的地方）

（括号内参数默认为0，表示第一个视频设备），如果代码运行后显示如下图所示，说明需要改，改成1大概率可以解决（其顺序为电脑设备管理器中的视频设备的顺序）：

 

完成，选择合适的解释器运行该Python文件即可（Run Python file）

文档地址如下：Python只能运行所选的7个应用

Solutions | mediapipe (google.github.io)