If you upload an image with 2:1 aspect ratio it squishes it to 1:1 instead of letting you crop it. Seems like a basic thing they could add.
Try Stable Diffusion's Img2Img Mode
41–50 of 166 posts
Re: Try Stable Diffusion's Img2Img Mode
#42Re: Try Stable Diffusion's Img2Img Mode
#43Some amazing examples of what people have done with img2img with Stable Diffusion: https://old.reddit.com/r/StableDiffusion/comments/wy7oa5/img... https://old.reddit.com/r/StableDiffusion/comments/wyq04v/usi... https://old.reddit.com/r/StableDiffusion/comments/wzlmty/its...
If i ran the same input image several times, would it produce the same output?
Re: Try Stable Diffusion's Img2Img Mode
#44NOTE: for some reason this is NOT using huggingface for inference, resulting in huge queues, slow performance, etc. It is sending requests to https://sdb.pcuenca.net/i2i (https://huggingface.co/spaces/huggingface/diffuse-the-rest/b...)
Re: Try Stable Diffusion's Img2Img Mode
#45I guess documentation and clarity of UX design are not big strengths of Hugging Face.
its like github pages - the repo owner is responsible for the UI: https://huggingface.co/spaces/huggingface/diffuse-the-rest/t...
Re: Try Stable Diffusion's Img2Img Mode
#46Some amazing examples of what people have done with img2img with Stable Diffusion: https://old.reddit.com/r/StableDiffusion/comments/wy7oa5/img... https://old.reddit.com/r/StableDiffusion/comments/wyq04v/usi... https://old.reddit.com/r/StableDiffusion/comments/wzlmty/its...
If i ran the same input image several times, would it produce the same output?
if you use the same parameters (e.g. image, seed, noise strength, guidance scale, sample count - which are not exposed on this UI), yes.
Re: Try Stable Diffusion's Img2Img Mode
#47Looks pretty hard to get it to run. Queue full every time.
It is super easy to install and use locally: clone repo, create conda env, run.
there are a number of forks and auxilliary repos available that add UI, reduce memory requirements, etc.
Re: Try Stable Diffusion's Img2Img Mode
#48Can't help but see this as a friendly herald for a dystopian future.
There you go. We were promised quite far fetched things like 'flying cars', 'time travel', 'life extension' and 'universal basic income'.
Instead we get Deep Learning AI's being used for generating and faking sentences, images, videos, voices, code and digital art all being trained on mountains of data in data centers all significantly contributing to the already burning up of the planet to no benefit and no efficient alternatives.
A dystopian future with deepfakes and easy fake news creation thanks to the technologists who helped create those things for others to create a new griftopia on top of that.
So you will own nothing, believe everything that you see on the internet, and be very happy.
Re: Try Stable Diffusion's Img2Img Mode
#49If you have a GPU with >4GB of VRAM and you want to run this locally, here's a fork of the Stable Diffusion repo with a convenient web UI: https://github.com/hlky/stable-diffusion It supports both txt2img and img2img. (Not affiliated.) Edit: Incidentally, I tried running it on a CPU. It is possible, but it took 3 minutes instead of 10 seconds to produce an image. It also required me to hack up the script in a really…
Just tried it on Ubuntu 22.04. And it's working! Had to install python-is-python3 and conda, but it's up now. Fun, thanks.
Re: Try Stable Diffusion's Img2Img Mode
#50If you have a GPU with >4GB of VRAM and you want to run this locally, here's a fork of the Stable Diffusion repo with a convenient web UI: https://github.com/hlky/stable-diffusion It supports both txt2img and img2img. (Not affiliated.) Edit: Incidentally, I tried running it on a CPU. It is possible, but it took 3 minutes instead of 10 seconds to produce an image. It also required me to hack up the script in a really…
I'm impressed that running it on CPU only made it ~20x slower. How did you do it?