class_docstr: Importer for YOLOv5 datasets stored on disk.
  
  See :ref:`this page <YOLOv5Dataset-import>` for format details.
  
  Args:
      dataset_dir (None): the dataset directory. If omitted, ``yaml_path``
          must be provided
      yaml_path (None): an optional parameter that enables explicit control
          over the location of the dataset YAML file. Can be any of the
          following:
  
          -   a filename like ``"dataset.yaml"`` specifying the name of the
              YAML file in ``dataset_dir``
          -   an absolute path to the YAML file. In this case,
              ``dataset_dir`` has no effect
  
          If None, the parameter will default to ``dataset.yaml``
      split ("val"): the split to load. Typical values are
          ``("train", "val")``
      include_all_data (False): whether to generate samples for all images in
          the data directory (True) rather than only creating samples for
          images with labels (False)
      shuffle (False): whether to randomly shuffle the order in which the
          samples are imported
      seed (None): a random seed to use when shuffling
      max_samples (None): a maximum number of samples to import. By default,
          all samples are imported
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code: def label_cls(self):
      return fol.Detections
  
imports: import logging
  import os
  import warnings
  import yaml
  import eta.core.utils
  import fiftyone.core.labels
  import fiftyone.core.storage
  import fiftyone.utils.data
label_desc: Use image node_id 7 for calling the YOLOv5DatasetImporter obj's underlying member method code with example usage: obj.label_cls() and returns: fol