When I use my own dataset whose width and height is not the same. I noticed that there is a small mistake in the codes.
Because the data you used has the same width and height, so it's ok for your current version. But when data with different height and width is used, it can not work.
In file "dagan_architectures.py",
line 270, it should be
w = concat_shape[len(encoder_layers) - 1 - i][2]
line 318, it should be
w_size=upscale_shape[2],
line 319, it shoule be
h_size=upscale_shape[1]
line 355, it should be
dim_upscale=True, local_inner_layers=decoder_inner_layers, w_size=upscale_shape[2],
line 336, it shoule be
h_size=upscale_shape[1], dropout_rate=dropout_rate)
Hi,
When I use my own dataset whose width and height is not the same. I noticed that there is a small mistake in the codes.
Because the data you used has the same width and height, so it's ok for your current version. But when data with different height and width is used, it can not work.
In file "dagan_architectures.py",
line 270, it should be
w = concat_shape[len(encoder_layers) - 1 - i][2]
line 318, it should be w_size=upscale_shape[2],
line 319, it shoule be h_size=upscale_shape[1]
line 355, it should be dim_upscale=True, local_inner_layers=decoder_inner_layers, w_size=upscale_shape[2],
line 336, it shoule be h_size=upscale_shape[1], dropout_rate=dropout_rate)