code: def crop_bbox_by_coords(
      bbox: BoxInternalType,
      crop_coords: Tuple[int, int, int, int],
      crop_height: int,
      crop_width: int,
      rows: int,
      cols: int,
  ):
      """Crop a bounding box using the provided coordinates of bottom-left and top-right corners in pixels and the
      required height and width of the crop.
  
      Args:
          bbox (tuple): A cropped box `(x_min, y_min, x_max, y_max)`.
          crop_coords (tuple): Crop coordinates `(x1, y1, x2, y2)`.
          crop_height (int):
          crop_width (int):
          rows (int): Image rows.
          cols (int): Image cols.
  
      Returns:
          tuple: A cropped bounding box `(x_min, y_min, x_max, y_max)`.
  
      """
      bbox = denormalize_bbox(bbox, rows, cols)
      x_min, y_min, x_max, y_max = bbox[:4]
      x1, y1, _, _ = crop_coords
      cropped_bbox = x_min - x1, y_min - y1, x_max - x1, y_max - y1
      return normalize_bbox(cropped_bbox, crop_height, crop_width)
  
imports: from typing import Optional, Sequence, Tuple
  import cv2
  import numpy
  from albumentations.augmentations.utils import _maybe_process_in_chunks, preserve_channel_dim
  from ...core.bbox_utils import denormalize_bbox, normalize_bbox
  from ...core.transforms_interface import BoxInternalType, KeypointInternalType
  from ..geometric import functional
label_desc: Use image node_id 3 for calling a global function with example usage: crop_bbox_by_coords(bbox, crop_coords, crop_height, crop_width, rows, cols) and returns: normalize_bbox