model = Sequential()
model.add(vgg_model)
model.add(Conv2D(filters = 512, kernel_size = 3, padding = "same", activation = "relu"))
model.add(UpSampling2D())
model.add(Conv2DTranspose(filters = 256, kernel_size = 3, padding = "same", activation = "relu"))
model.add(UpSampling2D())
model.add(Conv2DTranspose(filters = 128, kernel_size = 3, padding = "same", activation = "relu"))
model.add(UpSampling2D())
model.add(Conv2DTranspose(filters = 64, kernel_size = 3, padding = "same", activation = "relu"))
model.add(UpSampling2D())
model.add(Conv2DTranspose(filters = 32, kernel_size = 3, padding = "same", activation = "relu"))
model.add(UpSampling2D())
model.add(Conv2D(filters = 1, kernel_size = 3, padding = "same", activation = "relu"))
model.summary()