class_docstr: Reverses the box coordinates along the given spatial axis. Preserves shape.
  
  Args:
      spatial_axis: spatial axes along which to flip over. Default is None.
          The default `axis=None` will flip over all of the axes of the input array.
          If axis is negative it counts from the last to the first axis.
          If axis is a tuple of ints, flipping is performed on all of the axes
          specified in the tuple.
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docstr: Args:
      boxes: bounding boxes, Nx4 or Nx6 torch tensor or ndarray. The box mode is assumed to be ``StandardMode``
      spatial_size: image spatial size.
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code: def __call__(self, boxes: NdarrayOrTensor, spatial_size: Sequence[int] | int):  # type: ignore
      """
      Args:
          boxes: bounding boxes, Nx4 or Nx6 torch tensor or ndarray. The box mode is assumed to be ``StandardMode``
          spatial_size: image spatial size.
      """
  
      return flip_boxes(
          boxes, spatial_size=spatial_size, flip_axes=self.spatial_axis
      )
  
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 2 for calling the FlipBox obj's underlying member method code with example usage: obj.__call__(boxes, spatial_size) and returns: flip_boxes