Rescaling layer
- 원본 링크 : https://keras.io/api/layers/preprocessing_layers/image_preprocessing/rescaling/
- 최종 확인 : 2024-11-25
Rescaling class
keras.layers.Rescaling(scale, offset=0.0, **kwargs)A preprocessing layer which rescales input values to a new range.
This layer rescales every value of an input (often an image) by multiplying by scale and adding offset.
For instance:
- To rescale an input in the
[0, 255]range to be in the[0, 1]range, you would passscale=1./255. - To rescale an input in the
[0, 255]range to be in the[-1, 1]range, you would passscale=1./127.5, offset=-1.
The rescaling is applied both during training and inference. Inputs can be of integer or floating point dtype, and 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).
Arguments
- scale: Float, the scale to apply to the inputs.
- offset: Float, the offset to apply to the inputs.
- **kwargs: Base layer keyword arguments, such as
nameanddtype.