<reponame>roychanmeliaz/bachelor-thesis-report-latex
def model_base_64x3_CNN(input_shape):
    model = Sequential()

    model.add(Conv2D(64, (3, 3), input_shape=input_shape, padding='same'))
    model.add(Activation('relu'))
    model.add(AveragePooling2D(pool_size=(5, 5), strides=(3, 3), padding='same'))

    model.add(Conv2D(64, (3, 3), padding='same'))
    model.add(Activation('relu'))
    model.add(AveragePooling2D(pool_size=(5, 5), strides=(3, 3), padding='same'))

    model.add(Conv2D(64, (3, 3), padding='same'))
    model.add(Activation('relu'))
    model.add(AveragePooling2D(pool_size=(5, 5), strides=(3, 3), padding='same'))

    model.add(Flatten())
    return model.input, model.output

def model_base_64x3_CNN(input_shape):
    model = Sequential()

    model.add(Conv2D(64, (3, 3), input_shape=input_shape, padding='same'))
    model.add(Activation('relu'))
    model.add(AveragePooling2D(pool_size=(5, 5), strides=(3, 3), padding='same'))

    model.add(Conv2D(64, (3, 3), padding='same'))
    model.add(Activation('relu'))
    model.add(AveragePooling2D(pool_size=(5, 5), strides=(3, 3), padding='same'))

    model.add(Conv2D(64, (3, 3), padding='same'))
    model.add(Activation('relu'))
    model.add(AveragePooling2D(pool_size=(5, 5), strides=(3, 3), padding='same'))

    model.add(Flatten())
    return model.input, model.output