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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