Comments (3)
taesungp
commented on May 18, 2024
Hello, do you mean you are not sure which --netG and --netD to use? Our default setting --netG resnet_9blocks --netD basic should work. The other architectures, such as stylegan2 architecture, will be used in our next release when single image translation is trained.
from contrastive-unpaired-translation.
majdzr
commented on May 18, 2024
FYI, the Unet128 and Unet256 also fail as netG.
from contrastive-unpaired-translation.
taesungp
commented on May 18, 2024
We added the support for the stylegan2-based networks, designed for the single-image translation. UNet is designed to be used for the CycleGAN baseline, and we don't have support for UNet-based models for CUT.
from contrastive-unpaired-translation.
Related Issues (20)
- doesn't work with grayscale images HOT 2
- What is the input to the PatchSampleF class? HOT 1
- CUT training stopping criterion
- Error during running train.py: ConnectionRefusedError: [Errno 111] Connection refused HOT 2
- test.py alters file names of translated images HOT 1
- About the "no_antialias"
- Weird edge pattern in generated images during training
- Model doesnt work well on unpaired data
- The geneated images from train and test are inconsistent
- Applying to a general image restoration task
- One-to-Many translation HOT 2
- 3D CUT for medical images
- I cannot find the dataset HOT 2
- Unbiased / Supervised Patch Sampling
- CUT is not working with grayscale images. HOT 2
- Diagonal masked replacement is filled with -10.0 instead of exp(-10.0)
- About epoch_number
- Training image size changes
- May I ask in networks in ResnetGenerator.networks ,this parameter: no_antialias_up, What is the purpose of up? The code is as follows:
- Model collapse from the get go on grumpycat dataset HOT 6
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