class_docstr: Eurosat remote sensing benchmarking dataset.
code: def _info(self):
      if self.builder_config.selection == "rgb":
          features = tfds.features.FeaturesDict(
              {
                  "image": tfds.features.Image(shape=[64, 64, 3]),
                  "label": tfds.features.ClassLabel(names=_LABELS),
                  "filename": tfds.features.Text(),
              }
          )
          supervised_keys = ("image", "label")
      elif self.builder_config.selection == "all":
          features = tfds.features.FeaturesDict(
              {
                  "sentinel2": tfds.features.Tensor(
                      shape=[64, 64, 13], dtype=np.float32
                  ),
                  "label": tfds.features.ClassLabel(names=_LABELS),
                  "filename": tfds.features.Text(),
              }
          )
          supervised_keys = ("sentinel2", "label")
  
      return tfds.core.DatasetInfo(
          builder=self,
          description=_DESCRIPTION,
          features=features,
          supervised_keys=supervised_keys,
          homepage=_URL,
          citation=_CITATION,
      )
  
file_path: datasets/tensorflow_datasets/image_classification/eurosat.py
imports: import io
  import os
  import numpy
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
  import tensorflow_datasets.public_api
label_desc: Use image node_id 1 for calling the Eurosat obj's underlying member method code with example usage: obj._info() and returns: tfds