class_docstr: Zooms an ND Box with same padding or slicing setting with Zoom().
  
  Args:
      zoom: The zoom factor along the spatial axes.
          If a float, zoom is the same for each spatial axis.
          If a sequence, zoom should contain one value for each spatial axis.
      keep_size: Should keep original size (padding/slicing if needed), default is True.
      kwargs: other arguments for the `np.pad` or `torch.pad` function.
          note that `np.pad` treats channel dimension as the first dimension.
class_docstr_tok: ["Zooms","an","ND","Box","with","same","padding","or","slicing","setting","with","Zoom","(",")",".","Args",":","zoom",":","The","zoom","factor","along","the","spatial","axes",".","If","a","float",",","zoom","is","the","same","for","each","spatial","axis",".","If","a","sequence",",","zoom","should","contain","one","value","for","each","spatial","axis",".","keep_size",":","Should","keep","original","size","(","padding\/slicing","if","needed",")",",","default","is","True",".","kwargs",":","other","arguments","for","the","`","np.pad","`","or","`","torch.pad","`","function",".","note","that","`","np.pad","`","treats","channel","dimension","as","the","first","dimension","."]
code: def __init__(
      self,
      zoom: Sequence[float] | float,
      keep_size: bool = False,
      **kwargs: Any,
  ) -> None:
      self.zoom = zoom
      self.keep_size = keep_size
      self.kwargs = kwargs
  
imports: from __future__ import annotations
  from typing import Any, Sequence
  import numpy
  import torch
  from monai.config.type_definitions import DtypeLike, NdarrayOrTensor, NdarrayTensor
  from monai.data.box_utils import BoxMode, clip_boxes_to_image, convert_box_mode, convert_box_to_standard_mode, get_spatial_dims, spatial_crop_boxes, standardize_empty_box
  from monai.transforms import Rotate90, SpatialCrop
  from monai.transforms.transform import Transform
  from monai.utils import ensure_tuple, ensure_tuple_rep, fall_back_tuple, look_up_option
  from monai.utils.enums import TransformBackends
  from .box_ops import apply_affine_to_boxes, convert_box_to_mask, convert_mask_to_box, flip_boxes, resize_boxes, rot90_boxes, select_labels, zoom_boxes
label_desc: Use image node_id 1 to create a new ZoomBox object from inherited base classes: Transform with example: obj = ZoomBox(zoom, keep_size)