tf.keras.utils.array_to_img

Converts a 3D NumPy array to a PIL Image instance.

Main aliases

tf.keras.preprocessing.image.array_to_img

tf.keras.utils.array_to_img(
    x, data_format=None, scale=True, dtype=None
)

Used in the tutorials
Image segmentation Semantic Segmentation with Model Garden Adversarial regularization for image classification

from PIL import Image
img = np.random.random(size=(100, 100, 3))
pil_img = keras.utils.array_to_img(img)

Args
`x`	Input data, in any form that can be converted to a NumPy array.
`data_format`	Image data format, can be either `"channels_first"` or `"channels_last"`. Defaults to `None`, in which case the global setting `keras.backend.image_data_format()` is used (unless you changed it, it defaults to `"channels_last"`).
`scale`	Whether to rescale the image such that minimum and maximum values are 0 and 255 respectively. Defaults to `True`.
`dtype`	Dtype to use. `None` means the global setting `keras.backend.floatx()` is used (unless you changed it, it defaults to `"float32"`). Defaults to `None`.

Returns
A PIL Image instance.

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Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/keras/utils/array_to_img