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► Keras 3 API documentation / Layers API / Reshaping layers / ZeroPadding2D layer

ZeroPadding2D layer

[source]

ZeroPadding2D class

keras.layers.ZeroPadding2D(padding=(1, 1), data_format=None, **kwargs)

Zero-padding layer for 2D input (e.g. picture).

This layer can add rows and columns of zeros at the top, bottom, left and right side of an image tensor.

Example

>>> input_shape = (1, 1, 2, 2)
>>> x = np.arange(np.prod(input_shape)).reshape(input_shape)
>>> x
[[[[0 1]
   [2 3]]]]
>>> y = keras.layers.ZeroPadding2D(padding=1)(x)
>>> y
[[[[0 0]
   [0 0]
   [0 0]
   [0 0]]
  [[0 0]
   [0 1]
   [2 3]
   [0 0]]
  [[0 0]
   [0 0]
   [0 0]
   [0 0]]]]

Arguments

  • padding: Int, or tuple of 2 ints, or tuple of 2 tuples of 2 ints.
    • If int: the same symmetric padding is applied to height and width.
    • If tuple of 2 ints: interpreted as two different symmetric padding values for height and width: (symmetric_height_pad, symmetric_width_pad).
    • If tuple of 2 tuples of 2 ints: interpreted as ((top_pad, bottom_pad), (left_pad, right_pad)).
  • 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, height, width, channels) while "channels_first" corresponds to inputs with shape (batch_size, channels, height, width). When unspecified, uses image_data_format value found in your Keras config file at ~/.keras/keras.json (if exists). Defaults to "channels_last".

Input shape

4D tensor with shape: - If data_format is "channels_last": (batch_size, height, width, channels) - If data_format is "channels_first": (batch_size, channels, height, width)

Output shape

4D tensor with shape: - If data_format is "channels_last": (batch_size, padded_height, padded_width, channels) - If data_format is "channels_first": (batch_size, channels, padded_height, padded_width)

ZeroPadding2D layer
ZeroPadding2D class