GridMask
classkeras_cv.layers.GridMask(
ratio_factor=(0, 0.5),
rotation_factor=0.15,
fill_mode="constant",
fill_value=0.0,
seed=None,
**kwargs
)
GridMask class for grid-mask augmentation.
Input shape
Int or float tensor with values in the range [0, 255].
3D (unbatched) or 4D (batched) tensor with shape:
(..., height, width, channels)
, in "channels_last"
format
Output shape
3D (unbatched) or 4D (batched) tensor with shape:
(..., height, width, channels)
, in "channels_last"
format
Arguments
ratio_factor: A float, tuple of two floats, or keras_cv.FactorSampler
.
Ratio determines the ratio from spacings to grid masks.
Lower values make the grid
size smaller, and higher values make the grid mask large.
Floats should be in the range [0, 1]. 0.5 indicates that grid and
spacing will be of equal size. To always use the same value, pass a
keras_cv.ConstantFactorSampler()
.
Defaults to (0, 0.5)
.
- rotation_factor:
The rotation_factor will be used to randomly rotate the grid_mask
during training. Default to 0.1, which results in an output rotating
by a random amount in the range [-10% * 2pi, 10% * 2pi].
A float represented as fraction of 2 Pi, or a tuple of size 2
representing lower and upper bound for rotating clockwise and
counter-clockwise. A positive values means rotating counter
clock-wise, while a negative value means clock-wise. When
represented as a single float, this value is used for both the upper
and lower bound. For instance, factor=(-0.2, 0.3) results in an
output rotation by a random amount in the range [-20% * 2pi,
30% * 2pi]. factor=0.2 results in an output rotating by a random
amount in the range [-20% * 2pi, 20% * 2pi].
- __
fill_mode__: Pixels inside the gridblock are filled according to the given
mode (one of {"constant", "gaussian_noise"}
), defaults to
"constant".
- constant: Pixels are filled with the same constant value.
- gaussian_noise: Pixels are filled with random gaussian noise.
- fill_value: an integer represents of value to be filled inside the
gridblock when fill_mode="constant"
. Valid integer range
[0 to 255]
- seed: Integer. Used to create a random seed.
Usage:
(images, labels), _ = keras.datasets.cifar10.load_data()
random_gridmask = keras_cv.layers.preprocessing.GridMask()
augmented_images = random_gridmask(images)
References