tf.keras.preprocessing.image.NumpyArrayIterator

Class NumpyArrayIterator

Inherits From: Iterator

Defined in tensorflow/python/keras/_impl/keras/preprocessing/image.py.

Iterator yielding data from a Numpy array.

Arguments:

• x: Numpy array of input data.
• y: Numpy array of targets data.
• image_data_generator: Instance of ImageDataGenerator to use for random transformations and normalization.
• batch_size: Integer, size of a batch.
• shuffle: Boolean, whether to shuffle the data between epochs.
• seed: Random seed for data shuffling.
• data_format: String, one of channels_first, channels_last.
• save_to_dir: Optional directory where to save the pictures being yielded, in a viewable format. This is useful for visualizing the random transformations being applied, for debugging purposes.
• save_prefix: String prefix to use for saving sample images (if save_to_dir is set).
• save_format: Format to use for saving sample images (if save_to_dir is set).
• subset: Subset of data ("training" or "validation") if validation_split is set in ImageDataGenerator.

Methods

__init__

__init__(
    x,
    y,
    image_data_generator,
    batch_size=32,
    shuffle=False,
    seed=None,
    data_format=None,
    save_to_dir=None,
    save_prefix='',
    save_format='png',
    subset=None
)

Initialize self. See help(type(self)) for accurate signature.

__getitem__

__getitem__(idx)

Gets batch at position index.

Arguments:

• index: position of the batch in the Sequence.

Returns:

A batch

__iter__

__iter__()

Creates an infinite generator that iterate over the Sequence.

Yields:

Sequence items.

__len__

__len__()

Number of batch in the Sequence.

Returns:

The number of batches in the Sequence.

__next__

__next__(
    *args,
    **kwargs
)

next

next()

For python 2.x.

Returns:

The next batch.

on_epoch_end

on_epoch_end()

Method called at the end of every epoch.

reset

reset()