Iterator yielding data from a Numpy array.
Inherits From: Iterator, Sequence
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 ImageDataGeneratorto 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_diris set). | 
| save_format | Format to use for saving sample images (if save_to_diris
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') |