code: def plot_tensor(
      window_name: str,
      tensor: np.ndarray,
      coord_highlight: tuple[int, int] = None,
  ):
      font_size = 48
      image = np.zeros(
          (tensor.shape[1] * font_size, tensor.shape[0] * font_size, 3),
          dtype=np.uint8,
      )
  
      for y in range(tensor.shape[1]):
          for x in range(tensor.shape[0]):
              if (
                  coord_highlight
                  and x == coord_highlight[1]
                  and y == coord_highlight[0]
              ):
                  cv2.putText(
                      image,
                      str(int(tensor[y, x])),
                      (x * font_size, int((y + 0.8) * font_size)),
                      cv2.FONT_HERSHEY_TRIPLEX,
                      1.0,
                      (127, 127, 255),
                  )
              else:
                  cv2.putText(
                      image,
                      str(int(tensor[y, x])),
                      (x * font_size, int((y + 0.8) * font_size)),
                      cv2.FONT_HERSHEY_TRIPLEX,
                      1.0,
                      (255, 255, 255),
                  )
  
      cv2.imshow(window_name, image)
  
imports: from argparse import ArgumentParser
  import cv2
  import numpy
label_desc: Use image node_id 1 for calling a global function with example usage: plot_tensor(window_name, tensor, coord_highlight) without return types