tensorflow-wavelets 1.0.23

Tensorflow wavelet Layers

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!