code: def _get_buffer(self):
      if not self.pynb:
          s, (width, height) = self.canvas.print_to_buffer()
          if (width, height) != (self.width, self.height):
              img = Image.fromarray(self.img)
              img = img.resize((width, height), Image.NEAREST)
          else:
              img = self.img
      else:
          buf = io.BytesIO()  # works for cairo backend
          self.canvas.print_rgba(buf)
          width, height = self.width, self.height
          s = buf.getvalue()
          img = self.img
  
      buffer = np.frombuffer(s, dtype="uint8")
      img_rgba = buffer.reshape(height, width, 4)
      rgb, alpha = np.split(img_rgba, [3], axis=2)
  
      try:
          import numexpr as ne  # fuse them with numexpr
  
          visualized_image = ne.evaluate(
              "img * (1 - alpha / 255.0) + rgb * (alpha / 255.0)"
          )
      except ImportError:
          alpha = alpha.astype("float32") / 255.0
          visualized_image = img * (1 - alpha) + rgb * alpha
  
      return visualized_image.astype("uint8")
  
imports: import colorsys
  import io
  import os
  from typing import Union
  import matplotlib
  import matplotlib.colors
  import matplotlib.figure
  import numpy
  import requests
  import torch
  from matplotlib.backends.backend_agg import FigureCanvasAgg
  from mmf.datasets.processors.frcnn_processor import img_tensorize
  from PIL import Image
label_desc: Use image node_id 10 for calling the SingleImageViz obj's underlying member method code with example usage: obj._get_buffer() and returns: visualized_image