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Train with different image size

Open puhuk opened this issue 3 years ago • 3 comments
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Hi, Thanks for the great work!

I'm trying to train with different image size and change relevant code (input size, input_nc for initializing FeatureRegression in class GMM. But the result seems like the picture.

Could you help me what should I need to correct for different image size.

  • Left image is input and right image is warped from GMM

image

puhuk avatar Apr 18 '22 15:04 puhuk

The GMM network is like: input --> correlation --> transformation parameters TPS Then output = TPS transformation (input, transformation parameters TPS ) One easy way is you can increase the resolution of 'transformation parameters TPS" so that it can transform the high-resolution input. In this way, you don't need to change the network input size. I've tried changing the image size of the input, but --> calculated correlation is broken out of memory.

thaithanhtuan avatar Aug 07 '22 10:08 thaithanhtuan

Hi can you please point out the lines of code where to make those changes as per your line that you mentioned below "One easy way is you can increase the resolution of 'transformation parameters TPS" so that it can transform the high-resolution input. In this way, you don't need to change the network input size." Detailed explanation will be welcomed

anzwolf avatar Feb 21 '23 04:02 anzwolf

The GMM network is like: input --> correlation --> transformation parameters TPS Then output = TPS transformation (input, transformation parameters TPS ) One easy way is you can increase the resolution of 'transformation parameters TPS" so that it can transform the high-resolution input. In this way, you don't need to change the network input size. I've tried changing the image size of the input, but --> calculated correlation is broken out of memory.

hii sir, did you have pretrained model with more than 2,00,000 steps. please share if you have.

sudip550 avatar Oct 04 '23 15:10 sudip550