code: def vstack_header(
      image: np.ndarray,
      title: str,
      bg_color=(35, 41, 40),
      text_color=(242, 248, 248),
      text_thickness: int = 2,
      text_scale=1.5,
  ) -> np.ndarray:
      (rows, cols) = image.shape[:2]
  
      title_image = np.zeros((30, cols, 3), dtype=np.uint8)
      title_image[:] = bg_color
      cv2.putText(
          title_image,
          title,
          (10, 24),
          fontFace=cv2.FONT_HERSHEY_PLAIN,
          fontScale=text_scale,
          color=text_color,
          thickness=text_thickness,
          lineType=cv2.LINE_AA,
      )
  
      return vstack_autopad([title_image, image])
  
file_path: pytorch-toolbelt/pytorch_toolbelt/utils/visualization.py
imports: from __future__ import absolute_import
  import itertools
  import math
  import warnings
  from typing import List, Iterable, Tuple, Optional
  import cv2
  import numpy
  from .torch_utils import image_to_tensor
label_desc: Use image node_id 6 for calling a global function with example usage: vstack_header(image, title, bg_color, text_color, text_thickness, text_scale) and returns: vstack_autopad