Visualize images (and labels) from an image classification dataset.
View aliases
Main aliases
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 |
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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 | |
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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.
|