text: """
  PNG formatter for various Image objects (PIL, OpenCV, numpy arrays that look like image data)
  
  Usage:  %load_ext pil_display
  
  Now when displayhook gets an image, it will be drawn in the browser.
  
  """
  
  from io import BytesIO
  import os
  import tempfile
  
  def pil2imgdata(img, format='PNG'):
      """convert a PIL Image to png bytes"""
      fp = BytesIO()
      img.save(fp, format=format)
      return fp.getvalue()
  
  def array2imgdata_pil(A, format='PNG'):
      """get png data from array via converting to PIL Image"""
      from PIL import Image
      if A.shape[2] == 3:
          mode = 'RGB'
      elif A.shape[2] == 4:
          mode = 'RGBA'
      else:
          mode = 'L'
      img = Image.frombytes(mode, A.shape[:2][::-1], A.tostring())
      return pil2imgdata(img, format)
  
  def array2imgdata_fs(A, format='PNG'):
      """get png data via filesystem, using cv2.imwrite
      
      This is much faster than in-memory conversion with PIL on the rPi for some reason.
      """
      import cv2
      fname = os.path.join(tempfile.gettempdir(), "_ipdisplay.%s" % format)
      cv2.imwrite(fname, A)
      with open(fname) as f:
          data = f.read()
      os.unlink(fname)
      return data
  
  def display_image_array(a):
      """If an array looks like RGB[A] data, display it as an image."""
      import numpy as np
      if len(a.shape) != 3 or a.shape[2] not in {3,4} or a.dtype != np.uint8:
          return
      md = {
          'width': a.shape[1] // 2
      }
      return (array2imgdata_pil(a), md)
  
  def display_cv_image(cvimg):
      """display an OpenCV cvmat object as an image"""
      import numpy as np
      return array2imgdata_fs(np.asarray(cvimg))
  
  def load_ipython_extension(ip):
      png_formatter = ip.display_formatter.formatters['image/png']
      # both, in case of pillow or true PIL
      png_formatter.for_type_by_name('PIL.Image', 'Image', pil2imgdata)
      png_formatter.for_type_by_name('Image', 'Image', pil2imgdata)
      png_formatter.for_type_by_name('cv2.cv', 'iplimage', display_cv_image)
      png_formatter.for_type_by_name('cv2.cv', 'cvmat', display_cv_image)
      png_formatter.for_type_by_name("numpy", "ndarray", display_image_array)
  