It crops along spatial dimensions, i.e. width and height.
layer_cropping_2d(
object,
cropping = list(c(0L, 0L), c(0L, 0L)),
data_format = NULL,
batch_size = NULL,
name = NULL,
trainable = NULL,
weights = NULL
)
What to call the new Layer
instance with. Typically a keras
Model
, another Layer
, or a tf.Tensor
/KerasTensor
. If object
is
missing, the Layer
instance is returned, otherwise, layer(object)
is
returned.
int, or list of 2 ints, or list of 2 lists of 2 ints.
If int: the same symmetric cropping is applied to width and height.
If list of 2 ints: interpreted as two different symmetric cropping values for
height and width: (symmetric_height_crop, symmetric_width_crop)
.
If list of 2 lists of 2 ints: interpreted as ((top_crop, bottom_crop), (left_crop, right_crop))
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, height, width, channels)
while channels_first
corresponds to inputs with shape (batch, 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".
Fixed batch size for layer
An optional name string for the layer. Should be unique in a model (do not reuse the same name twice). It will be autogenerated if it isn't provided.
Whether the layer weights will be updated during training.
Initial weights for layer.
4D tensor with shape:
If data_format
is "channels_last"
: (batch, rows, cols, channels)
If data_format
is "channels_first"
: (batch, channels, rows, cols)
4D tensor with shape:
If data_format
is "channels_last"
: (batch, cropped_rows, cropped_cols, channels)
If data_format
is "channels_first"
: (batch, channels, cropped_rows, cropped_cols)
Other convolutional layers:
layer_conv_1d_transpose()
,
layer_conv_1d()
,
layer_conv_2d_transpose()
,
layer_conv_2d()
,
layer_conv_3d_transpose()
,
layer_conv_3d()
,
layer_conv_lstm_2d()
,
layer_cropping_1d()
,
layer_cropping_3d()
,
layer_depthwise_conv_2d()
,
layer_separable_conv_1d()
,
layer_separable_conv_2d()
,
layer_upsampling_1d()
,
layer_upsampling_2d()
,
layer_upsampling_3d()
,
layer_zero_padding_1d()
,
layer_zero_padding_2d()
,
layer_zero_padding_3d()