tfds.visualization.show_examples

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

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tfds.show_examples

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

Used in the notebooks

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.

Usage:

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