class_docstr: Rotate a boxes by 90 degrees in the plane specified by `axes`.
  See box_ops.rot90_boxes for additional details
  
  Args:
      k: number of times to rotate by 90 degrees.
      spatial_axes: 2 int numbers, defines the plane to rotate with 2 spatial axes.
          Default: (0, 1), this is the first two axis in spatial dimensions.
          If axis is negative it counts from the last to the first axis.
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docstr: Args:
      img: channel first array, must have shape: (num_channels, H[, W, ..., ]),
docstr_tok: ["Args",":","img",":","channel","first","array",",","must","have","shape",":","(","num_channels",",","H","[",",","W",",","...",",","]",")",","]
code: def __call__(self, boxes: NdarrayTensor, spatial_size: Sequence[int] | int) -> NdarrayTensor:  # type: ignore[override]
      """
      Args:
          img: channel first array, must have shape: (num_channels, H[, W, ..., ]),
      """
      return rot90_boxes(boxes, spatial_size, self.k, self.spatial_axes)
  
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 for calling the RotateBox90 obj's underlying member method code with example usage: obj.__call__(boxes, spatial_size) and returns: rot90_boxes