TFDS now supports the Croissant 🥐 format! Read the documentation to know more.

tfds.visualization.show_examples

Visualize images (and labels) from an image classification dataset.

Main aliases

tfds.show_examples

tfds.visualization.show_examples(
    ds: _Dataset,
    ds_info: dataset_info.DatasetInfo,
    is_batched: bool = False,
    **options_kwargs
)

Used in the tutorials
TensorFlow Datasets Fine tuning models for plant disease detection

This function is for interactive use (Colab, Jupyter). It displays and return a plot of (rows*columns) images from a tf.data.Dataset.

ds, ds_info = tfds.load('cifar10', split='train', with_info=True)
fig = tfds.show_examples(ds, ds_info)

Args
`ds`	`tf.data.Dataset`. The tf.data.Dataset object to visualize. Examples should not be batched. Examples will be consumed in order until (rows * cols) are read or the dataset is consumed.
`ds_info`	The dataset info object to which extract the label and features info. Available either through `tfds.load('mnist', with_info=True)` or `tfds.builder('mnist').info`
`is_batched`	Whether the data is batched.
`**options_kwargs`	Additional display options, specific to the dataset type to visualize. Are forwarded to `tfds.visualization.Visualizer.show`. See the `tfds.visualization` for a list of available visualizers.

Returns
`fig`	The `matplotlib.Figure` object

Args