def main(image_filter=transformations.identity):
image_filter = Filter(image_filter, data)
image_filter.initialize()
model = Model([
keras.layers.Flatten(input_shape=data.input_shape),
keras.layers.Dense(128, activation=keras.activations.relu),
keras.layers.Dense(10, activation=keras.activations.softmax)
])
model.optimizer = keras.optimizers.SGD(lr=0.01, nesterov=True)
model.epochs = 4
model.image_filter = image_filter
model.initialize()
model.fit()
image_filter.plot()
print('Accuracy: {0}'.format(model.test_accuracy))
def main(
image_filter=transformations.identity,
filter_params={},
preprocess=True,
preprocess_params={}):
image_filter = Filter(image_filter, data)
image_filter.params = filter_params
image_filter.preprocessing = preprocess
image_filter.preprocess_params = preprocess_params
image_filter.initialize()
model = Model([
Conv2D(32, (3,3), padding='same', input_shape=data.input_shape, activation=relu),
Conv2D(32, (3,3), activation=relu),
MaxPooling2D(pool_size=(2,2)),
Dropout(0.25),
Conv2D(64, (3,3), padding='same', activation=relu),
Conv2D(64, (3,3), activation=relu),
MaxPooling2D(pool_size=(2, 2)),
Dropout(0.25),
Flatten(),
Dense(512, activation=relu),
Dropout(0.5),
Dense(data.num_classes, activation=softmax)
])
model.image_filter = image_filter
model.initialize()
model.fit()
print('Accuracy: {0}'.format(model.test_accuracy))
