main.py 文件源码

def model_EES(input_col, input_row):
    _input = Input(shape=(input_col, input_row, 1), name='input')

    EES = Conv2D(nb_filter=8, nb_row=3, nb_col=3, init='he_normal',
                 activation='relu', border_mode='same', bias=True)(_input)
    EES = Deconvolution2D(nb_filter=16, nb_row=14, nb_col=14, output_shape=(None, input_col * 2, input_row * 2, 16),
                          subsample=(2, 2), border_mode='same', init='glorot_uniform', activation='relu')(EES)
    out = Conv2D(nb_filter=1, nb_row=5, nb_col=5, init='glorot_uniform', activation='relu', border_mode='same')(EES)

    model = Model(input=_input, output=out)
    # sgd = SGD(lr=0.0001, decay=0.005, momentum=0.9, nesterov=True)
    Adam = adam(lr=0.001)
    model.compile(optimizer=Adam, loss='mean_squared_error', metrics=['mean_squared_error'])
    return model