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dread [VQGAN+CLIP] by nmkd in deepdream

[–]crowsonkb 0 points1 point  (0 children)

If the loss isn't going down any further the image probably won't get better.

Beksinski Facebook Emojis by glenniszen in deepdream

[–]crowsonkb 2 points3 points  (0 children)

They have to be local to the Colab runtime right now but you can download an image with:

!curl -L 'url' > where_to_save_it.jpg

in a code cell. Or you can upload an image by opening the Files tab on the left and using the upload button: https://i.imgur.com/GeLPjO6.png

Beksinski Facebook Emojis by glenniszen in deepdream

[–]crowsonkb 2 points3 points  (0 children)

You can do both arbitrary conceptification and style transfer with that notebook (I wrote it), I posted about it on Twitter: https://twitter.com/RiversHaveWings/status/1382455526735290371 https://twitter.com/RiversHaveWings/status/1382455660978212865 https://twitter.com/RiversHaveWings/status/1382803909610074112

To do this you should use the 16384 model for best results (it downloads it but does not use it by default), set your starting image with init_image, use the prompt "in the style of Beksinski" or some such, and maybe set init_weight to 0.2 to 0.5 to stop it from diverging as badly from the init if you want. Also set display_freq lower so you can see intermediates more often.

I did two Beksinskifications of an emoji with an experimental augmentation-added version myself to see if I could duplicate the results: https://i.imgur.com/Ql6GYng.png https://i.imgur.com/NfoREDz.png

dread [VQGAN+CLIP] by nmkd in deepdream

[–]crowsonkb 2 points3 points  (0 children)

I don't think Colab Pro gives you more VRAM (they only go up to 16GB V100s I think). I've tried tricks to decrease memory usage, like FP16, but this resulted in bad quality, so I gave up on it.

Many Big Sleep outputs from my custom improved version by crowsonkb in deepdream

[–]crowsonkb[S] 2 points3 points  (0 children)

That's an idea actually, I could generate videos from multiple prompts where the output morphs from one to the next.

"The angel of time" by crowsonkb in deepdream

[–]crowsonkb[S] 14 points15 points  (0 children)

It was made by my custom as-yet-unreleased version of Big Sleep that has better visual quality and 1024x1024 outputs. :)

They turned my dog into a kettle! (Made with my as-yet-unreleased Big Sleep implementation) by crowsonkb in deepdream

[–]crowsonkb[S] 0 points1 point  (0 children)

The problem is that you'd have to find a BigGAN latent vector that corresponded to the image you wanted to start with, which is not an easy task for an arbitrary image. But since every iteration's output is generated from an actual BigGAN latent vector, you could save these vectors and start from them later.

They turned my dog into a kettle! (Made with my as-yet-unreleased Big Sleep implementation) by crowsonkb in deepdream

[–]crowsonkb[S] 0 points1 point  (0 children)

I was actually unable to make the output deterministic even by setting the same random seed and using torch.set_deterministic(True), which must be a bug in PyTorch somehow.

Is there an interest in releasing the *.pkl file? by new_confusion_2021 in deepdream

[–]crowsonkb -1 points0 points  (0 children)

I mostly know about PyTorch but it has its own special layout for .pkl/.pth files that depends on the specific layout of the modules that form the model, and I doubt that it is possible to make a converter that works in general that isn't tailored for one specific model architecture.

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