RandomHeight layer

RandomHeight class

tf.keras.layers.experimental.preprocessing.RandomHeight(
    factor, interpolation="bilinear", seed=None, **kwargs
)

Randomly vary the height of a batch of images during training.

Adjusts the height of a batch of images by a random factor. The input should be a 4-D tensor in the "channels_last" image data format.

By default, this layer is inactive during inference.

Arguments

  • factor: A positive float (fraction of original height), or a tuple of size 2 representing lower and upper bound for resizing vertically. 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 with height changed by a random amount in the range [20%, 30%]. factor=(-0.2, 0.3) results in an output with height changed by a random amount in the range [-20%, +30%].factor=0.2results in an output with height changed by a random amount in the range[-20%, +20%]`.
  • interpolation: String, the interpolation method. Defaults to bilinear. Supports bilinear, nearest, bicubic, area, lanczos3, lanczos5, gaussian, mitchellcubic
  • seed: Integer. Used to create a random seed.

Input shape

4D tensor with shape: (samples, height, width, channels) (data_format='channels_last').

Output shape

4D tensor with shape: (samples, random_height, width, channels).