layer_cropping_2d {keras} | R Documentation

## Cropping layer for 2D input (e.g. picture).

### Description

It crops along spatial dimensions, i.e. width and height.

### Usage

    layer_cropping_2d(object, cropping = list(c(0L, 0L), c(0L, 0L)),
      data_format = NULL, batch_size = NULL, name = NULL,
      trainable = NULL, weights = NULL)

### Arguments

`object` | Model or layer object
`cropping` | 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))`
`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, 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".
`batch_size` | Fixed batch size for layer
`name` | 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.
`trainable` | Whether the layer weights will be updated during training.
`weights` | Initial weights for layer.

### Input shape

4D tensor with shape:

- If `data_format` is `"channels_last"`: `(batch, rows, cols, channels)`

- If `data_format` is `"channels_first"`: `(batch, channels, rows, cols)`

### Output shape

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)`

### See Also

Other convolutional layers: `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`

[Package keras version 2.2.4 Index]