RandomFlip layer
- 원본 링크 : https://keras.io/api/layers/preprocessing_layers/image_augmentation/random_flip/
- 최종 확인 : 2024-11-25
RandomFlip
class
keras.layers.RandomFlip(
mode="horizontal_and_vertical", seed=None, data_format=None, **kwargs
)
A preprocessing layer which randomly flips images during training.
This layer will flip the images horizontally and or vertically 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 pixel values can be of any range (e.g. [0., 1.)
or [0, 255]
) and of integer or floating point dtype. By default, the layer will output floats.
Note: This layer is safe to use inside a tf.data
pipeline (independently of which backend you’re using).
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.
Arguments
- mode: String indicating which flip mode to use. Can be
"horizontal"
,"vertical"
, or"horizontal_and_vertical"
."horizontal"
is a left-right flip and"vertical"
is a top-bottom flip. Defaults to"horizontal_and_vertical"
- seed: Integer. Used to create a random seed.
- **kwargs: Base layer keyword arguments, such as
name
anddtype
.