TensorFlow 2 version
|
View source on GitHub
|
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. |
TensorFlow 2 version
View source on GitHub