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Hi, I'm having trouble with pix2pixHD model while training png images.
I fixed the code a little bit to train properly, such as normalizing part and --no_vgg_loss option.
but when the image is generated, it came out only in grey scale image.
every images in checkpoints folder is in grey scale, including input_label, real_image etc.
I found the other repo someone has the same issue but it's not solved yet.
Is there anyone who can fix this issue?
--- the code that I changed in ./data/aligned_dataset line 42/51/63 ...convert('RGB') -> convert('RGBA')
in ./data/base_dataset.py line 56, 57, 61 ...[transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))] -> [transforms.Normalize((0.5, 0.5, 0.5, 0.5), (0.5, 0.5, 0.5, 0.5))]
trained in option --nc_input 4 --nc_output 4 --no_vgg_loss --no_instance
The text was updated successfully, but these errors were encountered:
I also met this problem. and if possible, could I ask whether you have solved this problem?
Sorry, something went wrong.
no, not yet. I'm just using pix2pix model instead.
No branches or pull requests
Hi, I'm having trouble with pix2pixHD model while training png images.
I fixed the code a little bit to train properly, such as normalizing part and --no_vgg_loss option.
but when the image is generated, it came out only in grey scale image.
every images in checkpoints folder is in grey scale, including input_label, real_image etc.
I found the other repo someone has the same issue but it's not solved yet.
Is there anyone who can fix this issue?
--- the code that I changed
in ./data/aligned_dataset
line 42/51/63 ...convert('RGB') -> convert('RGBA')
in ./data/base_dataset.py
line 56, 57, 61 ...[transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))] -> [transforms.Normalize((0.5, 0.5, 0.5, 0.5), (0.5, 0.5, 0.5, 0.5))]
trained in option --nc_input 4 --nc_output 4 --no_vgg_loss --no_instance
The text was updated successfully, but these errors were encountered: