code: def load_cell_counting(
      splitter: Union[dc.splits.Splitter, str, None] = None,
      transformers: List[Union[TransformerGenerator, str]] = [],
      reload: bool = True,
      data_dir: Optional[str] = None,
      save_dir: Optional[str] = None,
      **kwargs,
  ) -> Tuple[
      List[str], Tuple[Dataset, ...], List[dc.trans.Transformer]
  ]:
      """Load Cell Counting dataset.
  
      Loads the cell counting dataset from http://www.robots.ox.ac.uk/~vgg/research/counting/index_org.html.
  
      Parameters
      ----------
      splitter: Splitter or str
          the splitter to use for splitting the data into training, validation, and
          test sets.  Alternatively you can pass one of the names from
          dc.molnet.splitters as a shortcut.  If this is None, all the data
          will be included in a single dataset.
      transformers: list of TransformerGenerators or strings
          the Transformers to apply to the data.  Each one is specified by a
          TransformerGenerator or, as a shortcut, one of the names from
          dc.molnet.transformers.
      reload: bool
          if True, the first call for a particular featurizer and splitter will cache
          the datasets to disk, and subsequent calls will reload the cached datasets.
      data_dir: str
          a directory to save the raw data in
      save_dir: str
          a directory to save the dataset in
      """
      featurizer = dc.feat.UserDefinedFeaturizer(
          []
      )  # Not actually used
      loader = _CellCountingLoader(
          featurizer,
          splitter,
          transformers,
          CELL_COUNTING_TASKS,
          data_dir,
          save_dir,
          **kwargs,
      )
      return loader.load_dataset("cell_counting", reload)
  
file_path: deepchem/deepchem/molnet/load_function/cell_counting_datasets.py
imports: import os
  import deepchem
  from deepchem.molnet.load_function.molnet_loader import TransformerGenerator, _MolnetLoader
  from deepchem.data import Dataset
  from typing import List, Optional, Tuple, Union
label_desc: Use image node_id 1 for calling a global function with example usage: load_cell_counting(splitter, transformers, reload, data_dir, save_dir) and returns: loader