docstr: Run the model to obtain a heatmap tensor from a image tensor. The heatmap
  tensor indicates the probability of each pixel being a part of text area.
  
  Parameters
  ----------
  image_tensor : torch.tensor
      Image tensor.
  
  Returns
  -------
  torch.tensor
      Probability heatmap tensor.
docstr_tok: ["Run","the","model","to","obtain","a","heatmap","tensor","from","a","image","tensor",".","The","heatmap","tensor","indicates","the","probability","of","each","pixel","being","a","part","of","text","area",".","Parameters","--","--","--","--","--","image_tensor",":","torch.tensor","Image","tensor",".","Returns","--","--","--","-","torch.tensor","Probability","heatmap","tensor","."]
code: def image2hmap(self, image_tensor):
      """
      Run the model to obtain a heatmap tensor from a image tensor. The heatmap
      tensor indicates the probability of each pixel being a part of text area.
  
      Parameters
      ----------
      image_tensor : torch.tensor
          Image tensor.
  
      Returns
      -------
      torch.tensor
          Probability heatmap tensor.
      """
      return self.model.forward(image_tensor, training=False)
  
imports: import os
  import math
  import yaml
  from shapely.geometry import Polygon
  import PIL.Image
  import numpy
  import cv2
  import pyclipper
  import torch
  from .model.constructor import Configurable
label_desc: Use image node_id 19 for calling the DBNet obj's underlying member method code with example usage: obj.image2hmap(image_tensor) and returns: self