Comments (2)
The model is a simple U-Net and should work with 128x128 inputs if you retrain it.
It seems that there are some problems in your code when loading the retrained parsing network. Possibly because you save the network without DataParallel
while the default load_weight
function expect a model wrapped with DataParallel
.
I am not sure what is the exact problem. Sorry that I am not supposed to help you with the problem, you may use some debug tools like pdb
to fix the bugs by yourself.
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Thank you! I have successfully solved the problem. It was indeed caused by the mismatch of the network name saved in the pre-trained model. Currently, I am able to generate mask images with a shape of 128. Sincerely appreciate your reply!
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Related Issues (20)
- Segmentation fault (core dumped) HOT 3
- Cuda ran out of memory. HOT 2
- Enhanced face not blending properly(?) HOT 2
- did you train more big input HOT 1
- some question HOT 2
- about the ground truth images HOT 2
- About CelebAHQ-Test HOT 1
- A question about training the FPN HOT 3
- what's F0 in the paper? HOT 3
- 测试FPN时遇到了一个问题 HOT 1
- where can I download the dataset “PSFR-RealTest”? HOT 1
- Thank you for your work. After I retrained netG, there are obvious boundaries on the edges of the face HOT 1
- 测试FPN时需要psfrgan_epoch15_net_G.pth吗 HOT 1
- Is there a method to obtain '.mat' semantic segmentation files from this code instead of 'jpg' files HOT 3
- obtain '.mat' semantic segmentation files from this code instead of 'jpg' files. Here I get the output '.mat' file as a 4-D Uint8 output. Is there a way to get a 2-D int32 output ".mat" file.
- 您好,请问怎么把generate_mask的过程中的LR的图像保存下来 HOT 1
- 你好,该方法与其他超分辨率方法比较时是如何设置的。
- FID code HOT 1
- CelebAHQ-Test HOT 1
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