ZeroPadding2D layer
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, usesimage_data_formatvalue 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)