class_docstr: Class encapsulating a batch during the augmentation process.
  
  Data within the batch is already verified and normalized, similar to
  :class:`Batch`. Data within the batch may be changed in-place. No initial
  copy is needed.
  
  Added in 0.4.0.
  
  Parameters
  ----------
  images : None or (N,H,W,C) ndarray or list of (H,W,C) ndarray
      The images to augment.
  
  heatmaps : None or list of imgaug.augmentables.heatmaps.HeatmapsOnImage
      The heatmaps to augment.
  
  segmentation_maps : None or list of imgaug.augmentables.segmaps.SegmentationMapsOnImage
      The segmentation maps to augment.
  
  keypoints : None or list of imgaug.augmentables.kps.KeypointOnImage
      The keypoints to augment.
  
  bounding_boxes : None or list of imgaug.augmentables.bbs.BoundingBoxesOnImage
      The bounding boxes to augment.
  
  polygons : None or list of imgaug.augmentables.polys.PolygonsOnImage
      The polygons to augment.
  
  line_strings : None or list of imgaug.augmentables.lines.LineStringsOnImage
      The line strings to augment.
class_docstr_tok: ["Class","encapsulating","a","batch","during","the","augmentation","process",".","Data","within","the","batch","is","already","verified","and","normalized",",","similar","to",":","class",":","`","Batch","`",".","Data","within","the","batch","may","be","changed","in-place",".","No","initial","copy","is","needed",".","Added","in","0.4.0",".","Parameters","--","--","--","--","--","images",":","None","or","(","N",",","H",",","W",",","C",")","ndarray","or","list","of","(","H",",","W",",","C",")","ndarray","The","images","to","augment",".","heatmaps",":","None","or","list","of","imgaug.augmentables.heatmaps.HeatmapsOnImage","The","heatmaps","to","augment",".","segmentation_maps",":","None","or","list","of","imgaug.augmentables.segmaps.SegmentationMapsOnImage","The","segmentation","maps","to","augment",".","keypoints",":","None","or","list","of","imgaug.augmentables.kps.KeypointOnImage","The","keypoints","to","augment",".","bounding_boxes",":","None","or","list","of","imgaug.augmentables.bbs.BoundingBoxesOnImage","The","bounding","boxes","to","augment",".","polygons",":","None","or","list","of","imgaug.augmentables.polys.PolygonsOnImage","The","polygons","to","augment",".","line_strings",":","None","or","list","of","imgaug.augmentables.lines.LineStringsOnImage","The","line","strings","to","augment","."]
docstr: Get the names of types of augmentables that contain data.
  
  This method is intended for situations where one wants to know which
  data is contained in the batch that has to be augmented, visualized
  or something similar.
  
  Added in 0.4.0.
  
  Returns
  -------
  list of str
      Names of types of augmentables. E.g. ``["images", "polygons"]``.
docstr_tok: ["Get","the","names","of","types","of","augmentables","that","contain","data",".","This","method","is","intended","for","situations","where","one","wants","to","know","which","data","is","contained","in","the","batch","that","has","to","be","augmented",",","visualized","or","something","similar",".","Added","in","0.4.0",".","Returns","--","--","--","-","list","of","str","Names","of","types","of","augmentables",".","E.g",".","``","[","``","images","''",",","``","polygons","''","]","``","."]
code: def get_column_names(self):
      """Get the names of types of augmentables that contain data.
  
      This method is intended for situations where one wants to know which
      data is contained in the batch that has to be augmented, visualized
      or something similar.
  
      Added in 0.4.0.
  
      Returns
      -------
      list of str
          Names of types of augmentables. E.g. ``["images", "polygons"]``.
  
      """
      return _get_column_names(self, "")
  
imports: from __future__ import print_function, division, absolute_import
  import collections
  import numpy
  from ..None import imgaug
  from .None import normalization
  from .None import utils
label_desc: Use image node_id 5 for calling the _BatchInAugmentation obj's underlying member method code with example usage: obj.get_column_names() and returns: _get_column_names