tfds.visualization.show_examples
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Visualize images (and labels) from an image classification dataset.
tfds.visualization.show_examples(
ds: _Dataset,
ds_info: dataset_info.DatasetInfo,
is_batched: bool = False,
**options_kwargs
)
Used in the notebooks
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
|
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Last updated 2024-04-26 UTC.
[null,null,["Last updated 2024-04-26 UTC."],[],[],null,["# tfds.visualization.show_examples\n\n\u003cbr /\u003e\n\n|----------------------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/datasets/blob/v4.9.3/tensorflow_datasets/core/visualization/show_examples.py#L94-L150) |\n\nVisualize images (and labels) from an image classification dataset.\n\n#### View aliases\n\n\n**Main aliases**\n\n[`tfds.show_examples`](https://www.tensorflow.org/datasets/api_docs/python/tfds/visualization/show_examples)\n\n\u003cbr /\u003e\n\n tfds.visualization.show_examples(\n ds: _Dataset,\n ds_info: dataset_info.DatasetInfo,\n is_batched: bool = False,\n **options_kwargs\n )\n\n### Used in the notebooks\n\n| Used in the tutorials |\n|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| - [TensorFlow Datasets](https://www.tensorflow.org/datasets/overview) - [Fine tuning models for plant disease detection](https://www.tensorflow.org/hub/tutorials/cropnet_on_device) |\n\nThis function is for interactive use (Colab, Jupyter). It displays and return\na plot of (rows\\*columns) images from a tf.data.Dataset.\n\n#### Usage:\n\n ds, ds_info = tfds.load('cifar10', split='train', with_info=True)\n fig = tfds.show_examples(ds, ds_info)\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|--------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `ds` | [`tf.data.Dataset`](https://www.tensorflow.org/api_docs/python/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. |\n| `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` |\n| `is_batched` | Whether the data is batched. |\n| `**options_kwargs` | Additional display options, specific to the dataset type to visualize. Are forwarded to [`tfds.visualization.Visualizer.show`](../../tfds/visualization/Visualizer#show). See the [`tfds.visualization`](../../tfds/visualization) for a list of available visualizers. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|-------|--------------------------------|\n| `fig` | The `matplotlib.Figure` object |\n\n\u003cbr /\u003e"]]
View source on GitHub