ifresnel.py 文件源码

def modeling_1(self, input_shape, nb_classes):
        print("Modeling_1")
        nb_filters = 8
        # size of pooling area for max pooling
        pool_size_l = [(4, 4), (4,4)] # 160 --> 40, 40 --> 10
        # convolution kernel size
        kernel_size = (20, 20)

        model = Sequential()

        model.add(Convolution2D(nb_filters, kernel_size[0], kernel_size[1],
                                border_mode='valid',
                                input_shape=input_shape))
        model.add(Activation('relu'))
        model.add(MaxPooling2D(pool_size=pool_size_l[0])) # 160 --> 40
        model.add(Dropout(0.25))

        model.add(Convolution2D(nb_filters, kernel_size[0], kernel_size[1],
                                border_mode='valid'))
        model.add(Activation('relu'))
        model.add(MaxPooling2D(pool_size=pool_size_l[1])) # 40 --> 10
        model.add(Dropout(0.25))

        model.add(Convolution2D(nb_filters, 2, 2,
                                border_mode='valid'))
        model.add(Activation('relu'))
        model.add(UpSampling2D(pool_size_l[1])) # 10 --> 40
        model.add(Dropout(0.25))

        model.add(Flatten())
        model.add(Dense(4))
        model.add(Activation('relu'))
        model.add(Dropout(0.5))
        model.add(Dense(nb_classes))
        model.add(Activation('softmax'))

        return model