class_docstr: Object detection dataset for non-textual elements in documents.
  The dataset includes a variety of synthetic document pages with non-textual elements.
  
  .. image:: https://doctr-static.mindee.com/models?id=v0.5.0/artefacts-grid.png&src=0
      :align: center
  
  >>> from doctr.datasets import DocArtefacts
  >>> train_set = DocArtefacts(train=True, download=True)
  >>> img, target = train_set[0]
  
  Args:
  ----
      train: whether the subset should be the training one
      use_polygons: whether polygons should be considered as rotated bounding box (instead of straight ones)
      **kwargs: keyword arguments from `VisionDataset`.
code: def extra_repr(self) -> str:
      return f"train={self.train}"
  
file_path: doctr/doctr/datasets/doc_artefacts.py
imports: import json
  import os
  from typing import Any, Dict, List, Tuple
  import numpy
  from .datasets import VisionDataset
label_desc: Use image node_id 2 for calling the DocArtefacts obj's underlying member method code with example usage: obj.extra_repr() and returns: str, self