class_docstr: ImageDatabase can be used to load images in MMF.
  This goes either in conjunction with AnnotationDatabase or
  can be separately used with function such as `from_path`.
  MMFDataset initializes its own copy of ImageDatabase if `use_images`
  is True. Rest everything works same as a normal torch Dataset if
  you pass the annotation_db as a parameter. For example for item
  1 from annotation db, you can pass same id to ImageDatabase to loads
  its image. If you don't pass it, you have two options. Either use
  .get which takes in an annotation db item or .from_path which directly
  takes in an image path. You are free to use your own dataset instead
  of image database or free to update or ignore MMFDataset's ImageDataset
  initialization. You can either reinitialize with transform and other
  params or use any of torchvision's datasets.
code: def get(self, item):
      possible_images = self._get_attrs(item)
      return self.from_path(possible_images)
  
imports: import collections
  import os
  import torch
  import torchvision
  import torchvision.datasets.folder
  from mmf.utils.file_io import PathManager
  from mmf.utils.general import get_absolute_path
  from PIL import Image
label_desc: Use image node_id 9 for calling the ImageDatabase obj's underlying member method code with example usage: obj.get(item) and returns: self