incerrrr

#encoder
l1 = Conv2D(16, (3,3),strides = 1 , activation = 'relu',padding='same')(input_img)
l1 = MaxPooling2D((2,2))(l1)
l1 = Conv2D(8,(3,3),strides = 1, activation='relu',padding='same')(l1)
l1 = MaxPooling2D((2,2),padding = 'same')(l1)
#
l1 = Conv2D(8,(3,3),strides = 1,activation = 'relu',padding='same')(l1)
#decoder network
l1 = Conv2DTranspose(8,(3,3),strides = 1,activation='relu',padding='same')(l1)
l1 = UpSampling2D((2,2))(l1)
l1 = Conv2DTranspose(16,(3,3),strides = 1,activation='relu',padding = 'same')(l1)
l1 = UpSampling2D((2,2))(l1)
l2 = Conv2DTranspose(1,(3,3),strides = 1, activation='sigmoid',padding  ='same')(l1)

model2 = Model(input_img, l2)
model2.compile(optimizer='Adam', loss='binary_crossentropy')
model2.summary()