code: def central_zoom(img: np.ndarray, zoom_factor: int) -> np.ndarray:
      h, w = img.shape[:2]
      h_ch, w_ch = ceil(h / zoom_factor), ceil(w / zoom_factor)
      h_top, w_top = (h - h_ch) // 2, (w - w_ch) // 2
  
      img = scale(
          img[h_top : h_top + h_ch, w_top : w_top + w_ch],
          zoom_factor,
          cv2.INTER_LINEAR,
      )
      h_trim_top, w_trim_top = (img.shape[0] - h) // 2, (
          img.shape[1] - w
      ) // 2
      return img[
          h_trim_top : h_trim_top + h, w_trim_top : w_trim_top + w
      ]
  
file_path: albumentations/albumentations/augmentations/blur/functional.py
imports: from itertools import product
  from math import ceil
  from typing import Sequence, Union
  import cv2
  import numpy
  from albumentations.augmentations.functional import convolve
  from albumentations.augmentations.geometric.functional import scale
  from albumentations.augmentations.utils import _maybe_process_in_chunks, clipped, preserve_shape
label_desc: Use image node_id 6 for calling a global function with example usage: central_zoom(img, zoom_factor) and returns: img