I'm trying to get main.py to run, fresh out the box, after I've set up the conda environment as suggested.
In generator.py UNETGenerator I get errors that the combined net works are not compatible size, so I have to resize each decoder to have the same size as the encoder layer, e.g.
from
de_6 = Convolution2D(nb_filter=512, nb_row=4, nb_col=4, border_mode='same')(de_6)
to
de_6 = Convolution2D(nb_filter=128, nb_row=4, nb_col=4, border_mode='same')(de_6)
otherwise this fails:
de_6 = merge([de_6, en_2], mode=merge_mode, concat_axis=1)
Then once adjusted I get an error with
DCGAN
telling me:
"ValueError: Dimensions must be equal, but are 1 and 64 for 'Conv2D_168' (op: 'Conv2D') with input shapes: [?,510,64,1], [4,4,64,64]."
Hi!
I'm trying to get main.py to run, fresh out the box, after I've set up the conda environment as suggested.
In generator.py UNETGenerator I get errors that the combined net works are not compatible size, so I have to resize each decoder to have the same size as the encoder layer, e.g. from de_6 = Convolution2D(nb_filter=512, nb_row=4, nb_col=4, border_mode='same')(de_6) to de_6 = Convolution2D(nb_filter=128, nb_row=4, nb_col=4, border_mode='same')(de_6)
otherwise this fails: de_6 = merge([de_6, en_2], mode=merge_mode, concat_axis=1)
Then once adjusted I get an error with DCGAN
telling me: "ValueError: Dimensions must be equal, but are 1 and 64 for 'Conv2D_168' (op: 'Conv2D') with input shapes: [?,510,64,1], [4,4,64,64]."
Could you suggest what I'm doing wrong?
Thanks,
Ben