python opencv —— 背景提取（MOG、KNN）、识别与检测（Haar Cascade）

• 注意 opencv 的坐标轴，x 轴向右，和 width 对应，y 轴向下，和 height 对应；

1. MOG2 与 KNN

• MOG：Mixture of Gaussian

  import cv2
  
  cap = cv2.VideoCapture('./data/video/768x576.avi')
  
  knn_sub = cv2.createBackgroundSubtractorKNN()
  
  mog2_sub = cv2.createBackgroundSubtractorMOG2()
  
  while True:
  
      ret, frame = cap.read()
  
      if not ret:
  
          break
  
      mog_sub_mask = mog2_sub.apply(frame)
  
      knn_sub_mask = knn_sub.apply(frame)
  
      cv2.imshow('original', frame)
  
      cv2.imshow('MOG2', mog_sub_mask)
  
      cv2.imshow('KNN', knn_sub_mask)
  
      key = cv2.waitKey(30) & 0xff
  
      if key == 27 or key == ord('q'):
  
          break
  
  cap.release()
  
  cv2.destroyAllWindows()

2. 识别与检测

• Haar Cascade

  import cv2
  
  import numpy as np
  
  # haar 级联分类器，opencv 源文件中data文件夹下会有
  
  # https://github.com/opencv/opencv/tree/master/data/haarcascades
  
  face_cascade = cv2.CascadeClassifier(
  
      './data/classifiers/haarcascade_frontalface_default.xml')
  
  eye_cascade = cv2.CascadeClassifier('./data/classifiers/haarcascade_eye.xml')
  
  cap = cv2.VideoCapture(0)
  
  while True:
  
      ret, img = cap.read()
  
      if not ret:
  
          break
  
      gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
  
      faces = face_cascade.detectMultiScale(gray, 1.3, 5)
  
      for (x, y, w, h) in faces:
  
          cv2.rectangle(img, (x, y), (x+w, y+h), color=(255, 0, 0), thickness=2)
  
          roi_gray = gray[y:y+h, x:x+w]
  
          roi_color = img[y:y+h, x:x+w]
  
          eyes = eye_cascade.detectMultiScale(roi_gray)
  
          try:
  
              ex, ey, ew, eh = eyes[0]
  
              cv2.rectangle(roi_color, (ex, ey), (ex+ew, ey+eh),
  
                  color=(0, 255, 0), thickness=2)
  
              ex1, ey1, ew1, eh1 = eyes[1]
  
              cv2.rectangle(roi_color, (ex1, ey1), (ex1+ew1, ey1+eh1),
  
                  color=(0, 255, 0), thickness=2)
  
          except IndexError:
  
              print('')
  
      cv2.imshow('me', img)
  
      key = cv2.waitKey(30)
  
      if key == 27 or key == ord('q'):
  
          break
  
  cap.release()
  
  cv2.destroyAllWindows()