Tensorflow wavelet Layers
Project description
tensorflow-wavelets is an implementation of
- Discrete Wavelets Transform Layer
- Duel Tree Complex Wavelets Transform Layer
- Multi Wavelets Transform Neural Networks Layer
Installation
pip install tensorflow-wavelets
Usage
import tensorflow_wavelets.Layers.DWT as DWT
import tensorflow_wavelets.Layers.DTCWT as DTCWT
import tensorflow_wavelets.Layers.DMWT as DMWT
Example
model = keras.Sequential()
model.add(keras.Input(shape=(28, 28, 1)))
model.add(DWT.DWT(name="haar",concat=0))
# name can be found in pywt.wavelist(family)
# concat=0 means to split to 4 smaller layers
# concat=1 will output 1 big layer - concat from 4 smaller layers
model.add(keras.layers.Flatten())
model.add(keras.layers.Dense(nb_classes, activation="softmax"))
model.summary()
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
dwt_9_haar (DWT) (None, 14, 14, 4) 0
_________________________________________________________________
flatten_9 (Flatten) (None, 784) 0
_________________________________________________________________
dense_9 (Dense) (None, 10) 7850
=================================================================
Total params: 7,850
Trainable params: 7,850
Non-trainable params: 0
_________________________________________________________________
Free Software, Hell Yeah!
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