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Apply cutout (https://arxiv.org/abs/1708.04552) to images.
Number= 0, seed:
Number= None, data_format: str = 'channels_last' ) -> tf.Tensor
This operation applies a (mask_height x mask_width) mask of zeros to
a random location within
img. The pixel values filled in will be of the
replace. The located where the mask will be applied is randomly
chosen uniformly over the whole images.
images: A tensor of shape (batch_size, height, width, channels) (NHWC), (batch_size, channels, height, width)(NCHW).
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.
constant_values: What pixel value to fill in the images in the area that has the cutout mask applied to it.
seed: A Python integer. Used in combination with
tf.random.set_seedto create a reproducible sequence of tensors across multiple calls.
data_format: A string, one of
channels_first. The ordering of the dimensions in the inputs.
channels_lastcorresponds to inputs with shape
(batch_size, ..., channels)while
channels_firstcorresponds to inputs with shape
(batch_size, channels, ...).
An image Tensor.
InvalidArgumentError: if mask_size can't be divisible by 2.