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Generate image of arbitrary dimension #2
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The models are adapted towards 32x32 images. While D may technically handle other image sizes (might still perform bad or slow), G will simply continue to generate 32x32 images, no matter the parameter settings. The other parts of the scripts might be able to handle other image sizes (not tested).
which simply adds one more upsampling step to the generator model (from 32x32 to 64x64). The
I think it was only used there. Then training with 64x64 images might work. The results can still be bad, as none of the networks was optimized for that resolution. |
Great, I will try. |
D might still be able to handle this.
(Second 4 decreased to 2 in all of them.) Not sure if all of the visualization is able to handle that image shape. |
Yes, indeed the error seems related to the visualization. I have to take a look into this more carefully |
The error posted above (first post) is related to G. The visualization creates matrices according to the |
Dear,
Is it possible to generate images of arbitrary dimension?
I would like to try the framework using images of arbitrary size but I don't know what I have to change in the code. Images generated in the output grid are indeed squared.
It is sufficient for me also generate rectangular images as in the sky generator, but changing the parameters as in that files (i.e. multiplying by two the scale parameter) results in an error when running
train.lua
.Here the stacktrace:
Thanks for your help
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