GridMask layer

• Original Link : https://keras.io/api/keras_cv/layers/augmentation/grid_mask/
• Last Checked at : 2024-11-25

source

GridMask class

keras_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.src.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.

Example

(images, labels), _ = keras.datasets.cifar10.load_data()
random_gridmask = keras_cv.layers.preprocessing.GridMask()
augmented_images = random_gridmask(images)

References

• GridMask paper