code: def mask_from_bbox(img, bbox):
      """Create binary mask from bounding box
  
      Args:
          img (numpy.ndarray): input image
          bbox: A bounding box tuple `(x_min, y_min, x_max, y_max)`
  
      Returns:
          mask (numpy.ndarray): binary mask
  
      """
  
      mask = np.zeros(img.shape[:2], dtype=np.uint8)
      x_min, y_min, x_max, y_max = bbox
      mask[y_min:y_max, x_min:x_max] = 1
      return mask
  
imports: from __future__ import division
  from typing import Optional, Sequence, Union
  from warnings import warn
  import cv2
  import numpy
  import skimage
  from albumentations import random_utils
  from albumentations.augmentations.utils import MAX_VALUES_BY_DTYPE, _maybe_process_in_chunks, clip, clipped, ensure_contiguous, is_grayscale_image, is_rgb_image, non_rgb_warning, preserve_channel_dim, preserve_shape
label_desc: Use image node_id 47 for calling a global function with example usage: mask_from_bbox(img, bbox) and returns: mask