Warning: This project is deprecated. TensorFlow Addons has stopped development,
The project will only be providing minimal maintenance releases until May 2024. See the full
announcement here or on
github.
tfa.image.cutout
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Apply cutout to images.
tfa.image.cutout(
images: tfa.types.TensorLike
,
mask_size: tfa.types.TensorLike
,
offset: tfa.types.TensorLike
= (0, 0),
constant_values: tfa.types.Number
= 0
) -> tf.Tensor
This operation applies a (mask_height x mask_width)
mask of zeros to
a location within images
specified by the offset.
The pixel values filled in will be of the value constant_values
.
The location where the mask will be applied is randomly
chosen uniformly over the whole images.
Args |
images
|
A tensor of shape (batch_size, height, width, channels) (NHWC).
|
mask_size
|
Specifies how big the zero mask that will be generated is that
is applied to the images. The mask will be of size
(mask_height x mask_width) . Note: mask_size should be divisible by 2.
|
offset
|
A tuple of (height, width) or (batch_size, 2)
|
constant_values
|
What pixel value to fill in the images in the area that has
the cutout mask applied to it.
|
Returns |
A Tensor of the same shape and dtype as images .
|
Raises |
InvalidArgumentError
|
if mask_size can't be divisible by 2.
|
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Last updated 2023-05-25 UTC.
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