class_docstr: Custom Pascal VOC detection Dataset.
  Classes are generated from dataset
  generate_classes : bool, default False
      If True, generate class labels base on the annotations instead of the default classe labels.
class_docstr_tok: ["Custom","Pascal","VOC","detection","Dataset",".","Classes","are","generated","from","dataset","generate_classes",":","bool",",","default","False","If","True",",","generate","class","labels","base","on","the","annotations","instead","of","the","default","classe","labels","."]
code: def _generate_classes(self):
      classes = set()
      all_xml = glob.glob(
          os.path.join(self._root, "Annotations", "*.xml")
      )
      for each_xml_file in all_xml:
          tree = ET.parse(each_xml_file)
          root = tree.getroot()
          for child in root:
              if child.tag == "object":
                  for item in child:
                      if item.tag == "name":
                          classes.add(item.text)
      classes = sorted(list(classes))
      return classes
  
imports: from __future__ import absolute_import
  from __future__ import division
  import glob
  import logging
  import os
  import warnings
  import numpy
  import mxnet
  from ..base import VisionDataset
label_desc: Use image node_id 2 for calling the CustomVOCDetection obj's underlying member method code with example usage: obj._generate_classes() and returns: classes