Unfortunately they did not include a one-click uninstaller! Besides removing the .app, you also need to delete the 4GB+ model that it downloads and other files that it scatters about:

  $HOME/.diffusionbee
  $HOME/Library/Application\ Support/DiffusionBee

To be fair, this is a long standing issue between how Apple wants people to uninstall their app (by throwing them in the trash) and how modern apps really work in practice (some apps need/generate temp data in AppSupport, and sometimes it's a non trivial amount).

As a developer the best you can usually do is put some instructions somewhere (website, somewhere in a menu in UI), or do a package install that puts an uninstaller somewhere (more of the Windows way, but it breaks many expectations from users like having your app be one icon in `Applications`, and not it's own folder with your app and maybe a "Uninstall" app there too). For Aerial I give uninstall instructions on the website, but there's not much of a standard on how to handle this (that I know of, at least).

Not quite sure why this couldn't sit in the Application bundle itself.

As far as I understand this is downloaded data and they may offer model selection later on? If so they have little choice and putting your data in the user `/Library/Application Support` (or maybe `/Library/Caches` but that's a mess in itself) is what you're supposed to do.

With the various security changes in "recent" macOS, you can't modify your bundle and download files inside it, as it would change its signature and break the notarisation system.

Do you mean that it should be distributed with it, or that it should write it in there when it downloads it at runtime?

The latter. A model update would then just be an application update. To answer my own question - if they want to allow a choice of downloadable models, then Application Support is the perfect place.

And also to allow updating the app independently of the model, without a 4GB download every time.

for those with stable diffusion running, an acquaintance and I have been working on another GUI https://github.com/breadthe/sd-buddy/

which offers custom seed and batches of images (we are also working on parametric prompting https://github.com/breadthe/sd-buddy/discussions/12#discussi... )

i'd love to get to img2img and alt models next.

A note that this appears to be, at the time of writing, shared source and not strictly "open source" as it claims to be.

"Stable Diffusion Buddy is open source and free for personal use.

You may not use Stable Diffusion Buddy for any commercial purpose. That means you may not sell or profit in any way from the compiled app, from compiling the app yourself, from the source code, or a fork of it. The images generated by using this app do not fall under these limitations for obvious reasons."

Hey, that's very nice. However I wasn't able to actually generate images because I need to have a specific conda environment enabled first.

A couple of suggestions, maybe you can implement:

1) option to switch the conda environment since I had setup the dependencies in a specific environment (for me, the command is "conda activate ldm")

2) It would be nice to know what was the error when there is an error.

Looking good over here too: M1 Max.

God I would hate to be whoever OpenAI blames this on.

I’m going to leave that DALL-E beta approval email unread like a food delivery recruiter email.

> This really is a one-click installer, which is excellent. As far as I know it's the first and only one for M1.

There's https://www.charl-e.com/

That's a very pretty landing page, but it entirely avoids describing any features, or showing what it looks like beyond a thumbnail-sized image. Do you have any insights?

Unfortunately, no, haven't had time to try it yet, bookmarked it few days ago. Just wanted to comment that there are others and probably will be many more coming shortly.

I'm used to troubleshoot all kinds of stuff but I'm not a Python guy and wrangling with dependencies and virtual environments is not fun in my book. I've got lstein repo working but can't wait to have cleaner way of doing things.

I've tried it. The first time it did generate an image, albeit missing one of the few elements I mentioned.

Now it only generates black frames, even after being restarted. Not impressed at this point.

The options are sizes up to 768 x 768, "steps," and "guidance scale." You can do text-to-image or image-to-image.

I tried Charl-E and got Python errors. (Maybe because I don't have Python installed?)

`mkdir ~/Desktop/charl-e/samples` to fix that.

Why do you need a folder on the desktop? I never put files there and it seems like a strange requirement.

It’s just a bug in the code that assumes that folder is there. (Not my app)

I just tried it as well. I also got errors. Well, for a one-click install app, you don't need python preinstalled.

Can it be built from source? (Am thinking if yes, then the seed feature should be easy to add).

The seed problem is in upstream GPU libraries provided by Apple. The community is working on solutions, but they are not easy.

Can you elaborate? Isn’t the seed a simple int (or long int)?

Currently reusing the same seed dose not produce repeatable results on Apple silicon. I assume this UI hides it as missleading.

The logs for the app (logs tab) state it's just repeatedly using the number 42 as a seed. But yes in the UI the results are different each run, even with an unchanged prompt. Didn't quite parse your last but if you're saying it's misleading, yeah kind of, because you can't share or save a prompt to redo the same result.

Weird that it's considered a big challenge to fix… something in Metal? Core ML? SIMD libraries? Some translation layer? Something is not being said here.

has anyone got a frok with img2img working for M1? I keep getting errors no matter what I try.

The WebUI from https://github.com/lstein/stable-diffusion works well.

I will add it to diffusion bee soon.

PRs welcome!