Def unet_model(input_size=(96, 128, 3), n_filters=32, n_classes=23):

Course Q&A Deep Learning Specialization Convolutional Neural Networks
1

what is the meaning of Use the cblock5[0] as expansive_input and cblock4[1] as contractive_input and n_filters
so the code becomes
ublock6 = upsampling_block(cblock5[0],cblock4[1],n_filters * 8)
so similarly what we need to write for ublock7, ublock8, ublock9

2

Chain the output of the previous block as expansive_input and the corresponding contractive block output. Note that you must use the second element of the contractive block. At each step, use half the number of filters of the previous block

ublock7 = block(ublock6, cblock3[1], filters*4). similarly for others

3

yeah thanks for the response and just now issue resolved

4

Issue Resolved so post removed

5

check your computation for a_G. you need to compute the outputs for the current ‘generated image’.

6

hi i checked actually i am confused