Image priming gives "The size of tensor a (224) must match the size of tensor b (512) at non-singleton dimension 3"

Hi, Unless I’m missing something obvious, it looks like the image priming no longer works? E.g.

imagine "A pizza on fire" --open_folder=False --start_image_path=./samples/prime-orig.jpg

siren_pytorch/siren_pytorch.py:101: UserWarning: Using a target size (torch.Size([1, 3, 512, 512])) that is different to the input size (torch.Size([1, 3, 224, 224])) … RuntimeError: The size of tensor a (224) must match the size of tensor b (512) at non-singleton dimension 3

[NotNANtoN]

I fixed the error that it does not run at all in the PR above (#103), but the generated images are completely white for large start_image_steps. When I checked out this repo first it already had the same issue - so now we are at least back to the old non-working version.

@nerdyrodent what you can do instead is to pass your image as img to the Imagine class, along with your text. Then Deepdaze will optimize for your image features too. That’s quite different from image priming, but still interesting.

[nerdyrodent]

Same error every time. It can be worked around by using “–image_width=224”. I’m not that great at coding, so I’m still looking through the rest of the code to see how it handles different image sizes.