class_docstr: Car Images dataset.
class_docstr_tok: ["Car","Images","dataset","."]
docstr: Generate training and testing samples.
docstr_tok: ["Generate","training","and","testing","samples","."]
code: def _generate_examples(
      self, split_name, data_dir_path, data_annotations_path
  ):
      """Generate training and testing samples."""
  
      image_dict = self.returnImageDict(data_dir_path)
      bbox_dict = self.returnBbox(data_annotations_path, image_dict)
      with tf.io.gfile.GFile(data_annotations_path, "rb") as f:
          mat = tfds.core.lazy_imports.scipy.io.loadmat(f)
      for example in mat["annotations"][0]:
          image_name = example[-1].item().split(".")[0]
          label = _NAMES[example[4].item() - 1]
          image = image_dict[image_name]
          bbox = bbox_dict[image_name]
          features = {
              "label": label,
              "image": image,
              "bbox": bbox,
          }
          if self.version > "2.0.0":
              features["id"] = image_name
          yield image_name, features
  
file_path: datasets/tensorflow_datasets/image_classification/cars196.py
imports: import os
  import urllib
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
  import tensorflow_datasets.public_api
label_desc: Use image node_id 3 for calling the Cars196 obj's underlying member method code with example usage: obj._generate_examples(split_name, data_dir_path, data_annotations_path) without return types