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

Used in the notebooks

Used in the tutorials

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


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

ds The 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 See the tfds.visualization for a list of available visualizers.

fig The matplotlib.Figure object