class_docstr: The dataset for the PASCAL Visual Object Classes Challenge 2012
  (VOC2012) for the detection competition.
  
  A total of 11,540 images are included in this dataset, where each image
  contains a set of objects, out of 20 different classes, making a total of
  27,450 annotated objects.
  
  Note that, as per the official dataset, the test set of VOC2012 does not
  contain annotations.
  
  Example usage::
  
      import fiftyone as fo
      import fiftyone.zoo as foz
  
      dataset = foz.load_zoo_dataset("voc-2012", split="validation")
  
      session = fo.launch_app(dataset)
  
  Dataset size
      3.59 GB
  
  Source
      http://host.robots.ox.ac.uk/pascal/VOC/voc2012
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code: def name(self):
      return "voc-2012"
  
imports: import fiftyone.core.labels
  import fiftyone.core.utils
  import fiftyone.types
  import fiftyone.utils.imagenet
  import fiftyone.utils.data
  import fiftyone.zoo.datasets
label_desc: Use image node_id 1 for calling the VOC2012Dataset obj's underlying member method code with example usage: obj.name() and returns: str