code: def bbreg(boundingbox, reg):
      if reg.shape[1] == 1:
          reg = torch.reshape(reg, (reg.shape[2], reg.shape[3]))
  
      w = boundingbox[:, 2] - boundingbox[:, 0] + 1
      h = boundingbox[:, 3] - boundingbox[:, 1] + 1
      b1 = boundingbox[:, 0] + reg[:, 0] * w
      b2 = boundingbox[:, 1] + reg[:, 1] * h
      b3 = boundingbox[:, 2] + reg[:, 2] * w
      b4 = boundingbox[:, 3] + reg[:, 3] * h
      boundingbox[:, :4] = torch.stack([b1, b2, b3, b4]).permute(1, 0)
  
      return boundingbox
  
imports: import torch
  from torch.nn.functional import interpolate
  from torchvision.transforms import functional
  from torchvision.ops.boxes import batched_nms
  from PIL import Image
  import numpy
  import os
  import math
label_desc: Use image node_id 3 for calling a global function with example usage: bbreg(boundingbox, reg) and returns: boundingbox