code: def _init_sticker_area(
      self, pic_in_numpy_0_255, logo_mask=None, resized_logo_mask=None
  ):
      is_saved = None
  
      # copy a new array out
      pic_in_numpy_0_255_copy = np.array(pic_in_numpy_0_255)
      _object = self.mask_list[0]
      xmin = int(_object["bndbox"]["xmin"])
      ymin = int(_object["bndbox"]["ymin"])
      xmax = int(_object["bndbox"]["xmax"])
      ymax = int(_object["bndbox"]["ymax"])
  
      if logo_mask is not None and resized_logo_mask is not None:
          ad_area_center_x = old_div((xmin + xmax), 2)
          ad_area_center_y = old_div((ymin + ymax), 2)
  
          # cv2.resize only eats integer
          resized_width = resized_logo_mask.shape[1]
          resized_height = resized_logo_mask.shape[0]
  
          paste_xmin = int(ad_area_center_x - old_div(resized_width, 2))
          paste_ymin = int(
              ad_area_center_y - old_div(resized_height, 2)
          )
          paste_xmax = paste_xmin + resized_width
          paste_ymax = paste_ymin + resized_height
  
          # can also write as np.where(cond, v1, v2)
          for i in range(paste_xmin, paste_xmax):
              for j in range(paste_ymin, paste_ymax):
                  if (
                      resized_logo_mask[
                          j - paste_ymin, i - paste_xmin, 0
                      ]
                      == self.very_small
                  ):
                      # plot logo
                      pic_in_numpy_0_255_copy[j, i] = 255
  
      # uniform base color of the ad_sticker area
      # balance between printability and constrast
      # rand = (np.random.normal(loc=0.5, scale=0.1, size=pic_in_numpy_0_255_copy[ymin:ymax, xmin:xmax].shape)/2)*255
      # rand_int = rand.astype('int')
      # pic_in_numpy_0_255_copy[ymin:ymax, xmin:xmax] = rand_int
  
      pic_in_numpy_0_255_copy[ymin:ymax, xmin:xmax] = [
          164,
          83,
          57,
      ]  # a rgb point inside CMYK color space
  
      return pic_in_numpy_0_255_copy
  
imports: from __future__ import division
  from __future__ import print_function
  from builtins import str
  from builtins import range
  from past.utils import old_div
  import numpy
  import cv2
  import tensorflow
  import time
  import os
  from EOT_simulation import transformation
  from attack_methods.base_logic import ODD_logic
  import pdb
label_desc: Use image node_id 5 for calling the EOTB_attack obj's underlying member method code with example usage: obj._init_sticker_area(pic_in_numpy_0_255, logo_mask, resized_logo_mask) and returns: pic_in_numpy_0_255_copy