Example 1: keras image data generator
tf.keras.preprocessing.image_dataset_from_directory(
directory,
labels="inferred",
label_mode="int",
class_names=None,
color_mode="rgb",
batch_size=32,
image_size=(256, 256),
shuffle=True,
seed=None,
validation_split=None,
subset=None,
interpolation="bilinear",
follow_links=False,
)
Example 2: what should I do when the keras image datagenerato is nit working
>>> k = np.random.randn(10,10)
>>> import dask.array as da
>>> k2 = da.from_array(k,chunks = 3)
dask.array<array, shape=(10, 10), dtype=float64, chunksize=(3, 3)>
>>> k2.to_delayed()
array([[Delayed(('array-a08c1d25b900d497cdcd233a7c5aa108', 0, 0)),
Delayed(('array-a08c1d25b900d497cdcd233a7c5aa108', 0, 1)),
Delayed(('array-a08c1d25b900d497cdcd233a7c5aa108', 0, 2)),
Delayed(('array-a08c1d25b900d497cdcd233a7c5aa108', 0, 3))],
[Delayed(('array-a08c1d25b900d497cdcd233a7c5aa108', 1, 0)),
Delayed(('array-a08c1d25b900d497cdcd233a7c5aa108', 1, 1)),
Delayed(('array-a08c1d25b900d497cdcd233a7c5aa108', 1, 2)),
Delayed(('array-a08c1d25b900d497cdcd233a7c5aa108', 1, 3))],
[Delayed(('array-a08c1d25b900d497cdcd233a7c5aa108', 2, 0)),
Delayed(('array-a08c1d25b900d497cdcd233a7c5aa108', 2, 1)),
Delayed(('array-a08c1d25b900d497cdcd233a7c5aa108', 2, 2)),
Delayed(('array-a08c1d25b900d497cdcd233a7c5aa108', 2, 3))],
[Delayed(('array-a08c1d25b900d497cdcd233a7c5aa108', 3, 0)),
Delayed(('array-a08c1d25b900d497cdcd233a7c5aa108', 3, 1)),
Delayed(('array-a08c1d25b900d497cdcd233a7c5aa108', 3, 2)),
Delayed(('array-a08c1d25b900d497cdcd233a7c5aa108', 3, 3))]],
dtype=object)