docstr: Gets the data object at index :obj:`idx` and transforms it (in case
  a :obj:`self.transform` is given).
  In case :obj:`idx` is a slicing object, *e.g.*, :obj:`[2:5]`, a list, a
  tuple, a  LongTensor or a BoolTensor, will return a subset of the
  dataset at the specified indices.
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code: def __getitem__(self, idx):
      r"""Gets the data object at index :obj:`idx` and transforms it (in case
      a :obj:`self.transform` is given).
      In case :obj:`idx` is a slicing object, *e.g.*, :obj:`[2:5]`, a list, a
      tuple, a  LongTensor or a BoolTensor, will return a subset of the
      dataset at the specified indices."""
      data = torch.load(
          osp.join(self.path_table, "fragment_{:06d}.pt".format(idx))
      )
      if self.transform is not None:
          data = self.transform(data)
      if self.num_random_pt > 0:
          detector = RandomDetector(self.num_random_pt)
          data = detector(data)
      return data
  
imports: import numpy
  import os
  import os.path
  import torch
  import json
  from torch_points3d.datasets.base_dataset import BaseDataset
  from torch_points3d.datasets.registration.basetest import Base3DMatchTest
  from torch_points3d.datasets.registration.basetest import SimplePatch
  from torch_points3d.datasets.registration.utils import PatchExtractor
  from torch_points3d.datasets.registration.detector import RandomDetector
  from torch_points3d.datasets.registration.pair import Pair, MultiScalePair
  from torch_points3d.datasets.registration.utils import tracked_matches
  from torch_points3d.datasets.registration.base_siamese_dataset import GeneralFragment
  from torch_points3d.datasets.registration.base_siamese_dataset import BaseSiameseDataset
label_desc: Use image node_id 2 for calling the Test3DMatch obj's underlying member method code with example usage: obj.__getitem__(idx) and returns: data