title: how to delete objects in image using opencv
body: <p>I'm relatively new to openCV, my requirement is to delete smaller island (could not attach image because of post limitation)
  I have followed below code:
  (1)Applied background subtraction to keep only moving objects
  (2)Applied Erosion Dilation to fill the holes
  (3)calculated the Average area of objects (contours)
  (4)Now I want to keep only objects which is greater than Average area(Here is where i need literally help, i tried online but could not find a solution)</p>
  <pre><code>from __future__ import print_function
  import cv2 as cv
  import argparse
  import numpy as np
  
  array = [None] * 100
  parser = argparse.ArgumentParser(description='')
  parser.add_argument('--input', type=str, help='Path to a video or a sequence of image.', default='vtest.avi')
  # parser.add_argument('--algo', type=str, help='Background subtraction method (KNN, MOG2).', default='MOG2')
  parser.add_argument('--algo', type=str, help='Background subtraction method (KNN, MOG2).', default='KNN')
  args = parser.parse_args()
  
  # create Background Subtractor objects
  if args.algo == 'MOG2':
      backSub = cv.createBackgroundSubtractorMOG2()
  else:
      backSub = cv.createBackgroundSubtractorKNN()
  
  capture = cv.VideoCapture(&quot;test.mp4&quot;)
  if not capture.isOpened():
      print('Unable to open: ' + args.input)
      exit(0)
  
  while True:
      ret, frame = capture.read()
      if frame is None:
          break
  
      # update the background model
      fgMask = backSub.apply(frame)
      # Erosion and Dilation
      kernel = np.ones((3, 3), np.int8)
      erosion = cv.erode(fgMask, kernel, iterations=1)
      dilation = cv.dilate(erosion, kernel, iterations=2)
      ## [apply]
      # contours, hierarchy = cv2.findContours(dilation, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
      contours, hierarchy = cv.findContours(dilation, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)
      print(&quot;Number of Contours = &quot; + str(len(contours)))
      # Find max contours
      # contour = max(contours, key=len)
      '''contourImg = cv.drawContours(frame, contour, -1, (0, 255, 0), 3)
      cv.imshow(&quot;Contours&quot;, contourImg)'''
  
      Contour_Cnts = 0
      Total_Area_Of_all_Contour = 0
      Average_Area_Of_Contour = 0
      for cnt in contours:
          area = cv.contourArea(cnt)
          Total_Area_Of_all_Contour = Total_Area_Of_all_Contour + area
          Contour_Cnts = Contour_Cnts + 1
      Average_Area_Of_Contour = Total_Area_Of_all_Contour // Contour_Cnts
      print(&quot;Number of contours&quot;, Contour_Cnts)
  
      Contour_Cnts = 0
      index = 0
      for cnt in contours:
          Contour_Cnts = Contour_Cnts + 1
          area = cv.contourArea(cnt)
          if area &gt; Average_Area_Of_Contour:
              index = int(index) + 1
              # array[index] = contours[Contour_Cnts]
      # cv.drawContours(frame, array, -1, (0,0,255), 2)
  
      cv.imshow('Frame', frame)
      cv.imshow('FG Mask', fgMask)
      cv.imshow('Dilation', dilation)
  
  capture.release()
  cv.destroyAllWindows()
  </code></pre>