TensorFlow 1 version | View source on GitHub |
Zero-padding layer for 2D input (e.g. picture).
tf.keras.layers.ZeroPadding2D(
padding=(1, 1), data_format=None, **kwargs
)
Used in the notebooks
Used in the tutorials |
---|
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)
Arguments | |
---|---|
padding
|
Int, or tuple of 2 ints, or tuple of 2 tuples of 2 ints.
|
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) .
It defaults to the image_data_format value found in your
Keras config file at ~/.keras/keras.json .
If you never set it, then it will be "channels_last".
|
Input shape:
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)