tf.keras.preprocessing.image.apply_brightness

TensorFlow 1 version

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

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Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.keras.preprocessing.image.array_to_img

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

Used in the notebooks

Used in the guide	Used in the tutorials
Writing a training loop from scratch	Image segmentation Adversarial regularization for image classification

Usage:

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

Arguments
`x`	Input Numpy array.
`data_format`	Image data format, can be either "channels_first" or "channels_last". Defaults to `None`, in which case the global setting `tf.keras.backend.image_data_format()` is used (unless you changed it, it defaults to "channels_last").
`scale`	Whether to rescale image values to be within `[0, 255]`. Defaults to `True`.
`dtype`	Dtype to use. Default to `None`, in which case the global setting `tf.keras.backend.floatx()` is used (unless you changed it, it defaults to "float32")

Returns
A PIL Image instance.

Raises
`ImportError`	if PIL is not available.
`ValueError`	if invalid `x` or `data_format` is passed.

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tf.keras / preprocessing / preprocessing.image.apply_brightness_shift

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Used in the notebooks

Usage:

Arguments

Returns

Raises