ccgan.py 文件源码

def build_generator(self):


        model = Sequential()

        # Encoder
        model.add(Conv2D(64, kernel_size=4, strides=2, input_shape=self.img_shape, padding="same"))
        model.add(Activation('relu'))
        model.add(Conv2D(128, kernel_size=4, strides=2, padding="same"))
        model.add(Activation('relu'))
        model.add(Conv2D(256, kernel_size=4, strides=2, padding="same"))
        model.add(Activation('relu'))

        # Decoder
        model.add(UpSampling2D())
        model.add(Conv2D(128, kernel_size=4, padding="same"))
        model.add(Activation('relu'))
        model.add(UpSampling2D())
        model.add(Conv2D(64, kernel_size=4, padding="same"))
        model.add(Activation('relu'))
        model.add(UpSampling2D())
        model.add(Conv2D(self.channels, kernel_size=4, padding="same"))
        model.add(Activation('tanh'))

        model.summary()

        masked_img = Input(shape=self.img_shape)
        img = model(masked_img)

        return Model(masked_img, img)