Iterator yielding data from a Numpy array.
Inherits From: Iterator
, Sequence
View aliases
Compat aliases for migration
See
Migration guide for
more details.
`tf.compat.v1.keras.preprocessing.image.NumpyArrayIterator`
tf.keras.preprocessing.image.NumpyArrayIterator(
x,
y,
image_data_generator,
batch_size=32,
shuffle=False,
sample_weight=None,
seed=None,
data_format=None,
save_to_dir=None,
save_prefix='',
save_format='png',
subset=None,
ignore_class_split=False,
dtype=None
)
Args |
x
|
Numpy array of input data or tuple. If tuple, the second elements is
either another numpy array or a list of numpy arrays, each of which
gets passed through as an output without any modifications.
|
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.
|
sample_weight
|
Numpy array of sample weights.
|
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.
|
ignore_class_split
|
Boolean (default: False), ignore difference
in number of classes in labels across train and validation
split (useful for non-classification tasks)
|
dtype
|
Dtype to use for the generated arrays.
|
Methods
next
View source
next()
For python 2.x.
on_epoch_end
View source
on_epoch_end()
Method called at the end of every epoch.
reset
View source
reset()
__getitem__
View source
__getitem__(
idx
)
Gets batch at position index
.
Args |
index
|
position of the batch in the Sequence.
|
__iter__
View source
__iter__()
Create a generator that iterate over the Sequence.
__len__
View source
__len__()
Number of batch in the Sequence.
Returns |
The number of batches in the Sequence.
|
Class Variables |
white_list_formats
|
('png', 'jpg', 'jpeg', 'bmp', 'ppm', 'tif', 'tiff')
|