code: def draw_rpn_bbox_pred(pred_dict, image, top_k=5):
      """
      For each bounding box labeled object. We want to display bbox_reg_error.
  
      We display the final bounding box and the anchor. Drawing lines between the
      corners.
      """
      logger.debug(
          "RPN regression loss (bbox to original anchors, "
          "with the smoothL1Loss)"
      )
      target = pred_dict["rpn_prediction"]["rpn_cls_target"]
      bbox_pred = pred_dict["rpn_prediction"]["rpn_bbox_pred"]
      all_anchors = pred_dict["all_anchors"]
      # Get anchors with positive label.
      positive_indices = target > 0
  
      bbox_pred = bbox_pred[positive_indices]
      all_anchors = all_anchors[positive_indices]
  
      loss_per_anchor = pred_dict["rpn_prediction"][
          "reg_loss_per_anchor"
      ]
  
      top_losses_idx = np.argsort(loss_per_anchor)[::-1][:top_k]
  
      loss_per_anchor = loss_per_anchor[top_losses_idx]
      bbox_pred = bbox_pred[top_losses_idx]
      all_anchors = all_anchors[top_losses_idx]
  
      bbox_final = decode(all_anchors, bbox_pred)
  
      image_pil, draw = get_image_draw(image)
  
      for anchor, bbox, loss in zip(
          all_anchors, bbox_final, loss_per_anchor
      ):
          anchor = list(anchor)
          bbox = list(bbox)
          draw.rectangle(
              anchor, fill=(0, 255, 0, 20), outline=(0, 255, 0, 100)
          )
          draw.rectangle(
              bbox, fill=(255, 0, 255, 20), outline=(255, 0, 255, 100)
          )
          draw.text(
              tuple([anchor[0], anchor[1]]),
              text="{:.2f}".format(loss),
              font=font,
              fill=(0, 0, 0, 255),
          )
          draw.line(
              [(anchor[0], anchor[1]), (bbox[0], bbox[1])],
              fill=(0, 0, 0, 170),
              width=1,
          )
          draw.line(
              [(anchor[2], anchor[1]), (bbox[2], bbox[1])],
              fill=(0, 0, 0, 170),
              width=1,
          )
          draw.line(
              [(anchor[2], anchor[3]), (bbox[2], bbox[3])],
              fill=(0, 0, 0, 170),
              width=1,
          )
          draw.line(
              [(anchor[0], anchor[3]), (bbox[0], bbox[3])],
              fill=(0, 0, 0, 170),
              width=1,
          )
  
      return image_pil
  
imports: import io
  import numpy
  import os
  import logging
  import PIL.Image
  import PIL.ImageDraw
  import PIL.ImageFont
  import tensorflow
  from .bbox_overlap import bbox_overlap
  from .bbox_transform import decode
  from base64 import b64encode
  from sys import stdout
label_desc: Use image node_id 19 for calling a global function with example usage: draw_rpn_bbox_pred(pred_dict, image, top_k) and returns: image_pil