Zero-padding layer for 2D input (e.g. picture).
Inherits From: Layer
, Module
tf.keras.layers.ZeroPadding2D(
padding=(1, 1), data_format=None, **kwargs
)
This layer can add rows and columns of zeros
at the top, bottom, left and right side of an image tensor.
Examples:
input_shape = (1, 1, 2, 2)
x = np.arange(np.prod(input_shape)).reshape(input_shape)
print(x)
[[[[0 1]
[2 3]]]]
y = tf.keras.layers.ZeroPadding2D(padding=1)(x)
print(y)
tf.Tensor(
[[[[0 0]
[0 0]
[0 0]
[0 0]]
[[0 0]
[0 1]
[2 3]
[0 0]]
[[0 0]
[0 0]
[0 0]
[0 0]]]], shape=(1, 3, 4, 2), dtype=int64)
Args |
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) else 'channels_last'.
Defaults to 'channels_last'.
|
|
4D tensor with shape:
- If
data_format is "channels_last" :
(batch_size, rows, cols, channels)
- If
data_format is "channels_first" :
(batch_size, channels, rows, cols)
|
Output shape |
4D tensor with shape:
- If
data_format is "channels_last" :
(batch_size, padded_rows, padded_cols, channels)
- If
data_format is "channels_first" :
(batch_size, channels, padded_rows, padded_cols)
|