sd-webui-colab VS stable_diffusion.openvino

(Added Aug. 28, 2022) Colab notebook Stable Diffusion WebUi - Altryne by altryne. GitHub repo. txt2img. img2img. inpainting. Gradio user interface. Uses sd-webui repo.

you can try the colab version of hlky repo: https://github.com/altryne/sd-webui-colab, easier to setup or a one cell colab version: https://github.com/pinilpypinilpy/sd-webui-colab-simplified, everything works in one cell

For those without GPU's / not a powerful enough one. You can start the hlky stable diffusion webui (yes, web ui) in Google Colab with this notebook[0].

It's simple and it works, using colab for processing but actually giving you a URL (ngrok-style) to open the pretty web ui in your browser.

I've been using that on-the-go when not at my PC and it's been working very well for me (after trying numerous other colab-dedicated repos, trying to fix them, and failing).

[0]: https://github.com/altryne/sd-webui-colab

The code is directly adapted from the Colab notebook repo based on the hlky GitHub repo. I really don't have much experience with coding and didn't change much of the code other than the paths specific to Kaggle.

I'm running SD-webui on google colab https://github.com/altryne/sd-webui-colab/ with a colab pro account and its awesome but it does crash with attempting larger images. Is anyone using a google colab pro+ account and able to process larger images?

Based off of https://github.com/altryne/sd-webui-colab and https://github.com/hlky/stable-diffusion

it might be the --xformers flag, try getting rid of that since your not using cuda you wouldn't be able to run it with xformers and you could also try --use-cpu all ... you can also check this out .. https://github.com/bes-dev/stable_diffusion.openvino .. it's probably your best option if your using CPU, which if your PC Graphics are using Intel UHD 620 then you don't have a GPU and an optimized CPU inference would be best to run

SD can be run on a CPU without a GPU. I know for certain it can be done with OpenVINO. In fact, on some i7s, it will run at around 3 seconds per iteration. There was a reddit SD thread a while back saying it can be done with Automatic111. Also, soe recent threads on problems with AMD GPUs suggest Automatic1111 is using the CPU rather than the intended GPU. (Fortuanely, I have a GPU, so I don't have to deal with it myself!)

I'm not actually entirely convinced that it's even using the GPU. Radeontop shows 0% utilization while the images are generating. Additionally, the listed iteration speed should be impossibly slow for any GPU; it says 26.58s/it, which is slower than just running on a CPU.

iGPU's are in short not supported. There's this repo that may or may not help you, but even if it did I wouldn't expect much.

You can also run it in windows native with openvino, there is a barebones webui for it as well in one of the forks.Requires setting cpu to gpu in one the files. https://github.com/bes-dev/stable_diffusion.openvino

In https://github.com/bes-dev/stable_diffusion.openvino/blob/master/stable_diffusion_engine.py

" We ended up using three different Stable Diffusion projects for our testing, mostly because no single package worked on every GPU. For Nvidia, we opted for Automatic 1111's webui version(opens in new tab). AMD GPUs were tested using Nod.ai's Shark version(opens in new tab), while for Intel's Arc GPUs we used Stable Diffusion OpenVINO(opens in new tab). "