code: def __init__(self, root, set, transform=None, target_transform=None):
      self.root = root
      self.path_devkit = os.path.join(root, "VOCdevkit")
      self.path_images = os.path.join(
          root, "VOCdevkit", "VOC2007", "JPEGImages"
      )
      self.set = set
      self.transform = transform
      self.target_transform = target_transform
  
      # download dataset
      download_voc2007(self.root)
  
      # define path of csv file
      path_csv = os.path.join(self.root, "files", "VOC2007")
      # define filename of csv file
      file_csv = os.path.join(
          path_csv, "classification_" + set + ".csv"
      )
  
      # create the csv file if necessary
      if not os.path.exists(file_csv):
          if not os.path.exists(path_csv):  # create dir if necessary
              os.makedirs(path_csv)
          # generate csv file
          labeled_data = read_object_labels(
              self.root, "VOC2007", self.set
          )
          # write csv file
          write_object_labels_csv(file_csv, labeled_data)
  
      self.classes = object_categories
      self.images = read_object_labels_csv(file_csv)
  
      print(
          "[dataset] VOC 2007 classification set=%s number of classes=%d  number of images=%d"
          % (set, len(self.classes), len(self.images))
      )
  
imports: from __future__ import print_function, division, absolute_import
  import csv
  import os
  import os.path
  import tarfile
  from six.moves.urllib.parse import urlparse
  import numpy
  import torch
  import torch.utils.data
  from PIL import Image
  from .None import utils
label_desc: Use image node_id 1 to create a new Voc2007Classification object from inherited base classes: data with example: obj = Voc2007Classification(root, set, transform, target_transform)