code: def create_xml_test():
      objects = []
      ob = {
          "name": "person",
          "pose": "Unspecified",
          "truncated": "0",
          "difficult": "0",
          "xmin": "174",
          "ymin": "101",
          "xmax": "349",
          "ymax": "351",
      }
      objects.append(ob)
      objects.append(copy.deepcopy(ob))
  
      years = "VOC2012"
      filename = "test.jpg"
      source_dict = {
          "database": "The VOC2007 Database",
          "annotation": "PASCAL VOC2007",
          "image": "flickr",
      }
      im_width = "500"
      im_height = "700"
      im_depth = "3"
      im_shape = (im_width, im_height, im_depth)
      create_pascal_voc_xml(
          filename=filename,
          years=years,
          source_dict=source_dict,
          objects_list=objects,
          im_shape=im_shape,
      )
  
file_path: deep-learning-for-image-processing/others_project/trans_widerface_to_xml/create_xml.py
imports: import copy
  import os
  from xml.dom import minidom
label_desc: Use image node_id 2 for calling a global function with example usage: create_xml_test() without return types