tf.keras.preprocessing.image.Iterator
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Base class for image data iterators.
Inherits From: Sequence
tf.keras.preprocessing.image.Iterator( n, batch_size, shuffle, seed )
Every Iterator
must implement the _get_batches_of_transformed_samples
method.
Arguments
n: Integer, total number of samples in the dataset to loop over. batch_size: Integer, size of a batch. shuffle: Boolean, whether to shuffle the data between epochs. seed: Random seeding for data shuffling.
Methods
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()
__getitem__
__getitem__( idx )
Gets batch at position index
.
Arguments | |
---|---|
index | position of the batch in the Sequence. |
Returns | |
---|---|
A batch |
__iter__
__iter__()
Create a generator that iterate over the Sequence.
__len__
__len__()
Number of batch in the Sequence.
Returns | |
---|---|
The number of batches in the Sequence. |
Class Variables
-
white_list_formats
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/keras/preprocessing/image/Iterator