contrib.keras.preprocessing.image.DirectoryIterator

tf.contrib.keras.preprocessing.image.DirectoryIterator

class tf.contrib.keras.preprocessing.image.DirectoryIterator

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

Iterator capable of reading images from a directory on disk.

Arguments:

directory: Path to the directory to read images from.
    Each subdirectory in this directory will be
    considered to contain images from one class,
    or alternatively you could specify class subdirectories
    via the `classes` argument.
image_data_generator: Instance of `ImageDataGenerator`
    to use for random transformations and normalization.
target_size: tuple of integers, dimensions to resize input images to.
color_mode: One of `"rgb"`, `"grayscale"`. Color mode to read images.
classes: Optional list of strings, names of sudirectories
    containing images from each class (e.g. `["dogs", "cats"]`).
    It will be computed automatically if not set.
class_mode: Mode for yielding the targets:
    `"binary"`: binary targets (if there are only two classes),
    `"categorical"`: categorical targets,
    `"sparse"`: integer targets,
    `None`: no targets get yielded (only input images are yielded).
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).

Methods

__init__

__init__(
    directory,
    image_data_generator,
    target_size=(256, 256),
    color_mode='rgb',
    classes=None,
    class_mode='categorical',
    batch_size=32,
    shuffle=True,
    seed=None,
    data_format=None,
    save_to_dir=None,
    save_prefix='',
    save_format='jpeg',
    follow_links=False
)

__iter__

__iter__()

__next__

__next__(
    *args,
    **kwargs
)

next

next()

For python 2.x.

Returns:

The next batch.

reset

reset()