old but relevant, it's like a production system. We can continue to tune and squeeze 1mp pictures out of it in high quality on relevant localized hardware without breaking a sweat. 1-3 seconds on a m3 system, and then cascade of tooling below stays the same.
A1111 also had its time. Comfy takes a couple hours to learn, and then it’s vastly superior. Like, if you are already on Mac there is no reason to also kick yourself in the face trying to go back to 1111.
There's also sdcpp ( https://github.com/leejet/stable-diffusion.cpp ) . It is for people that know command line shells like bash or Powershell. SDCPP is like llama.cpp but it is for using text to image AI models. Not everyone likes the node/graph programming interface in Comfy or a Webpage interface. Some people need these GUI/web interfaces and get lost and frustrated in shell scripting.
Totally and sdcpp and drawthings were inspiration for this work. It's not just about the UI, there's a whole stack of plugins, APIs etc. It would be a bigger shift, than just use other UI. Composition etc.
Plus this was fun to learn where the attention and time spent is eating up. I plan to git into the UNet, and then do some Multi-Model Memory Attention tuning as well, for Refining and Inpaint Swaps for the 8Gb Macs.
A1111 (or rather Forge Neo at this point) can still be pretty useful (for a Windows user) if somebody just want a batteries-included approach because it makes it trivial to move back and forth between masking, manual inpainting, tacking on a high‑res fix and/or upscale, and swapping things out on the fly quickly.
Caveat: No idea how well A1111 and its variants function on Mac though.
These days I mostly use ComfyUI because after building out a node‑based workflow, it’s easy to export as a JSON file with websocket outputs that I can integrate into my programs.
I'm not an editorialist, I spend my time on the software side of things, but want a detailed technical journal of what happened to achieve the gains. Also why the github link is near the top of the intro which I wrote. I'm not trying to disrespect the reader, but the time of the user of the software. Appreciate your view. I've made adjustments.
I spend all day reading AI generated text in one form or other in my day job. When I come to unwind in HN I’m not interested of more of the same. Seeing “load-bearing”, “landing things”, “it’s not x, it’s y” makes me think of work. I honestly would rather read human text with typos and warts.
Invoke AI is also really good if you prefer working in a canvas-style environment, in a more traditional graphical way. It easily has the nicest workflows for outpainting/regional/inpainting by far.
What a crazy repo. Some cyber archeologists need to do a case analysis of the entire diffusion model ecosystem circa the original Stable Diffusion up to now.
A1111 is such a throwback. It's been ages since that & AI image generation was cool. Back before the massive amount of slop and when things were just a fun experiment
Plus this was fun to learn where the attention and time spent is eating up. I plan to git into the UNet, and then do some Multi-Model Memory Attention tuning as well, for Refining and Inpaint Swaps for the 8Gb Macs.
Caveat: No idea how well A1111 and its variants function on Mac though.
These days I mostly use ComfyUI because after building out a node‑based workflow, it’s easy to export as a JSON file with websocket outputs that I can integrate into my programs.
https://github.com/Haoming02/sd-webui-forge-classic/tree/neo
It's not serious. It shows that the author doesn't care about showing what he's up to.
He cares about making content to post on a blog.
And that's disrespectful to the reader.
https://github.com/invoke-ai/invokeai