Apply cutout (https://arxiv.org/abs/1708.04552) to images.
img_cutout( images, mask_size, offset = list(0, 0), constant_values = 0, data_format = "channels_last" )
| 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. |
| offset | A list 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. |
| data_format | A string, one of `channels_last` (default) or `channels_first`. The ordering of the dimensions in the inputs. `channels_last` corresponds to inputs with shape `(batch_size, ..., channels)` while `channels_first` corresponds to inputs with shape `(batch_size, channels, ...)`. |
An image Tensor.
This operation applies a (mask_height x mask_width) mask of zeros to a location within `img` specified by the offset. The pixel values filled in will be of the value `replace`. The located where the mask will be applied is randomly chosen uniformly over the whole images.
InvalidArgumentError: if mask_size can't be divisible by 2.