class_docstr: When indexed, loads images from disk, resizes to consistent size, then returns image.
  Since the returned images will consist of 3 dimensions, the model ivis uses must be capable
  of dealing with this dimensionality of data (for example, a Convolutional Neural Network).
  Such a model can be constructed externally and then passed to ivis as the argument for 'model'.
  
  :param list filepath_list: All image filepaths in dataset.
  :param tuple img_shape: A tuple (height, width) containing desired dimensions to resize the
      images to.
  :param color_mode str: Either "rgb", "rgba" or "grayscale". Determines how many channels present
      in images that are read in - 3, 4, or 1 respectively.
  :param resize_method str: Interpolation method to use when resizing image. Must be one of:
      "area", "bicubic", "bilinear", "gaussian", "lanczos3", "lanczos5", "mitchellcubic", "nearest".
  :param preserve_aspect_ratio boolean: Whether to preserve the aspect ratio when resizing images.
      If True, will maintain aspect ratio by padding the image.
  :param dtype tf.dtypes.DType: The dtype to read the image into. One of tf.uint8 or tf.uint16.
  :param preprocessing_function Callable: A function to apply to every image. Will be called
      at the end of the pipeline, after image reading and resizing.
      If None (default), no function will be applied.
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docstr: Returns a batch of data points based on the index sequence provided.
docstr_tok: ["Returns","a","batch","of","data","points","based","on","the","index","sequence","provided","."]
code: def get_batch(self, idx_seq):
      """Returns a batch of data points based on the index sequence provided."""
      if self.workers is not None:
          return list(self.workers.map(self.__getitem__, idx_seq))
      return super().get_batch(idx_seq)
  
file_path: ivis/ivis/data/sequence/image.py
imports: import os
  from concurrent.futures import ThreadPoolExecutor
  import numpy
  import tensorflow
  from .sequence import IndexableDataset
label_desc: Use image node_id 6 for calling the ImageDataset obj's underlying member method code with example usage: obj.get_batch(idx_seq) and returns: super, list