code: def adjust_camera_to_bbox_crop_(
      camera: PerspectiveCameras,
      image_size_wh: torch.Tensor,
      clamp_bbox_xywh: torch.Tensor,
  ) -> None:
      if len(camera) != 1:
          raise ValueError(
              "Adjusting currently works with singleton cameras camera only"
          )
  
      focal_length_px, principal_point_px = _convert_ndc_to_pixels(
          camera.focal_length[0],
          camera.principal_point[0],
          image_size_wh,
      )
      principal_point_px_cropped = (
          principal_point_px - clamp_bbox_xywh[:2]
      )
  
      focal_length, principal_point_cropped = _convert_pixels_to_ndc(
          focal_length_px,
          principal_point_px_cropped,
          clamp_bbox_xywh[2:],
      )
  
      camera.focal_length = focal_length[None]
      camera.principal_point = principal_point_cropped[None]
  
imports: import functools
  import warnings
  from pathlib import Path
  from typing import List, Optional, Tuple, TypeVar, Union
  import numpy
  import torch
  from PIL import Image
  from pytorch3d.io import IO
  from pytorch3d.renderer.cameras import PerspectiveCameras
  from pytorch3d.structures.pointclouds import Pointclouds
label_desc: Use image node_id 23 for calling a global function with example usage: adjust_camera_to_bbox_crop_(camera, image_size_wh, clamp_bbox_xywh) without return types