View source: R/layers-preprocessing.R
layer_random_flip | R Documentation |
Randomly flip each image horizontally and vertically
layer_random_flip(object, mode = "horizontal_and_vertical", seed = NULL, ...)
object |
What to compose the new
|
mode |
String indicating which flip mode to use. Can be |
seed |
Integer. Used to create a random seed. |
... |
standard layer arguments. |
This layer will flip the images based on the mode
attribute.
During inference time, the output will be identical to input. Call the layer
with training = TRUE
to flip the input.
Input shape:
3D (unbatched) or 4D (batched) tensor with shape:
(..., height, width, channels)
, in "channels_last"
format.
Output shape:
3D (unbatched) or 4D (batched) tensor with shape:
(..., height, width, channels)
, in "channels_last"
format.
https://www.tensorflow.org/api_docs/python/tf/keras/layers/RandomFlip
https://keras.io/api/layers/preprocessing_layers/image_augmentation/random_flip
Other image augmentation layers:
layer_random_brightness()
,
layer_random_contrast()
,
layer_random_crop()
,
layer_random_height()
,
layer_random_rotation()
,
layer_random_translation()
,
layer_random_width()
,
layer_random_zoom()
Other preprocessing layers:
layer_category_encoding()
,
layer_center_crop()
,
layer_discretization()
,
layer_hashing()
,
layer_integer_lookup()
,
layer_normalization()
,
layer_random_brightness()
,
layer_random_contrast()
,
layer_random_crop()
,
layer_random_height()
,
layer_random_rotation()
,
layer_random_translation()
,
layer_random_width()
,
layer_random_zoom()
,
layer_rescaling()
,
layer_resizing()
,
layer_string_lookup()
,
layer_text_vectorization()
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