class_docstr: Multi-Human-Parsing V1 Dataset.
  Parameters
  ----------
  root : string
      Path to MHPV1 folder. Default is '$(HOME)/.mxnet/datasets/mhp/LV-MHP-v1'
  split: string
      'train', 'val' or 'test'
  transform : callable, optional
      A function that transforms the image
  Examples
  --------
  >>> from mxnet.gluon.data.vision import transforms
  >>> # Transforms for Normalization
  >>> input_transform = transforms.Compose([
  >>>     transforms.ToTensor(),
  >>>     transforms.Normalize([.485, .456, .406], [.229, .224, .225]),
  >>> ])
  >>> # Create Dataset
  >>> trainset = gluoncv.data.MHPV1Segmentation(split='train', transform=input_transform)
  >>> # Create Training Loader
  >>> train_data = gluon.data.DataLoader(
  >>>     trainset, 4, shuffle=True, last_batch='rollover',
  >>>     num_workers=4)
docstr: Category names.
docstr_tok: ["Category","names","."]
code: def classes(self):
      """Category names."""
      return type(self).CLASSES
  
file_path: gluon-cv/gluoncv/data/mhp.py
imports: import os
  import numpy
  from PIL import Image
  from PIL import ImageFile
  import mxnet
  from .segbase import SegmentationDataset
label_desc: Use image node_id 5 for calling the MHPV1Segmentation obj's underlying member method code with example usage: obj.classes() and returns: type