Cropping layer for 3D data (e.g. spatial or spatio-temporal).
Inherits From: Layer
, Operation
tf.keras.layers.Cropping3D(
cropping=((1, 1), (1, 1), (1, 1)), data_format=None, **kwargs
)
Example:
input_shape = (2, 28, 28, 10, 3)
x = np.arange(np.prod(input_shape)).reshape(input_shape)
y = keras.layers.Cropping3D(cropping=(2, 4, 2))(x)
y.shape
(2, 24, 20, 6, 3)
Args |
cropping
|
Int, or tuple of 3 ints, or tuple of 3 tuples of 2 ints.
- If int: the same symmetric cropping is applied to depth, height,
and width.
- If tuple of 3 ints: interpreted as three different symmetric
cropping values for depth, height, and width:
(symmetric_dim1_crop, symmetric_dim2_crop, symmetric_dim3_crop) .
- If tuple of 3 tuples of 2 ints: interpreted as
((left_dim1_crop, right_dim1_crop), (left_dim2_crop,
right_dim2_crop), (left_dim3_crop, right_dim3_crop)) .
|
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, spatial_dim1, spatial_dim2, spatial_dim3, channels)
while "channels_first" corresponds to inputs with shape
(batch_size, channels, spatial_dim1, spatial_dim2, spatial_dim3) .
When unspecified, uses image_data_format value found in your Keras
config file at ~/.keras/keras.json (if exists). Defaults to
"channels_last" .
|
|
5D tensor with shape:
- If
data_format is "channels_last" :
(batch_size, first_axis_to_crop, second_axis_to_crop,
third_axis_to_crop, channels)
- If
data_format is "channels_first" :
(batch_size, channels, first_axis_to_crop, second_axis_to_crop,
third_axis_to_crop)
|
Output shape |
5D tensor with shape:
- If
data_format is "channels_last" :
(batch_size, first_cropped_axis, second_cropped_axis,
third_cropped_axis, channels)
- If
data_format is "channels_first" :
(batch_size, channels, first_cropped_axis, second_cropped_axis,
third_cropped_axis)
|
Attributes |
input
|
Retrieves the input tensor(s) of a symbolic operation.
Only returns the tensor(s) corresponding to the first time
the operation was called.
|
output
|
Retrieves the output tensor(s) of a layer.
Only returns the tensor(s) corresponding to the first time
the operation was called.
|
Methods
from_config
View source
@classmethod
from_config(
config
)
Creates a layer from its config.
This method is the reverse of get_config
,
capable of instantiating the same layer from the config
dictionary. It does not handle layer connectivity
(handled by Network), nor weights (handled by set_weights
).
Args |
config
|
A Python dictionary, typically the
output of get_config.
|
Returns |
A layer instance.
|
symbolic_call
View source
symbolic_call(
*args, **kwargs
)