Ditto, though the LoRA might explain it.
The base model, Pony Diffusion, doesn’t normally act like that in my experience. Maybe if you generated an enormous number of images and culled them.
The simplicity of the style might also help – less to change.
Honestly, that looks pretty tasty, even with the keys.
If you’ve got a local Stable Diffusion setup and a GPU that can handle it, sure.
Some other folks might be able to give recommendations for sites.
I’d try doing upscaling using the upscaler models, probably SwinIR_4x, which I use for general-purpose upscaling.
I’d do so using the SD Ultimate Upscale extension, which can do the upscaling in tiles so that it doesn’t use VRAM proportional to the size of the image you want to upscale.
I don’t know what you have installed. I tend to use ComfyUI, which is more powerful, but I’m pretty sure more people have the older and somewhat-simpler Automatic1111 installed.
Once you’ve got Automatic1111 up and running:
If you don’t have the SD Ultimate Upscale extension installed:
Go to the Extensions tab.
Click the “available” tab.
Click the “Load from” button.
Install “ultimate-upscale-for-automatic1111”
Restart Automatic1111.
Click the img2img tab.
Either drag the image you want to upscale to the “Drag image here” square or click on it and select the image.
Click the little yellow right triangle next to the “Resize to” area, which will copy your image dimensions to the image size fields.
Set “Denoising strength” from what I think is 0.75 by default to 0.16. The 0.16 is a bit arbitrary, but it’s roughly what you want when upscaling an image rather than regenerating it; 0.75 is too high. Feel free to try playing with it if you want.
Go down to the “Script” drop-down menu and choose “Ultimate SD upscale”
Check the “SwinIR_4x” upscaler. You can play with others, but this is one that should be reasonable for photographs.
Change “Target size type” to “Scale from image size”. Set “Scale” to “4”.
Click “Generate”.
Eventually your image will show up in the right hand square.
ComfyUI works pretty much the same way: I’d also use the SwinIR_4x upscaler with the SD Ultimate Upscale node there. Can walk you through if you want, but at a high level:
I’d install the ComfyUI Extension Manager. ComfyUI doesn’t have the built-in ability to automatically download nodes, so you gotta manually install this one. You can also manually install and update nodes, but I’d recommend having the manager to make updates easier.
Use the ComfyUI Extension Manager to install the SD Ultimate Upscale node.
Set up a workflow that loads the image and runs it through the SD Ultimate Upscale node and then saves the image.
I haven’t set up batch image processing of pre-existing images with either Automatic1111 or ComfyUI; my only batch-processing has been on generated prompts. However, I believe that that’s also possible, so you can just feed it a large number of images and then let it run until completion. I couldn’t off-the-cuff give directions to do batch upscaling, though.
We whitened them.
Well, time and nature did.
We kind of adopted the idea of them being white as normal.
That’s a pretty good AK. The models I’ve used have pretty consistently done poorly with firearms, though I’ve not tried specialized models.
EDIT: And military hardware. I was thinking about trying an F-22 Flux LoRA that I saw on civitai. Vanilla Flux can’t do much by way of accurate military ships, vehicles, or aircraft.
6900
kagis
If that’s 16GB, that should be more than fine for SDXL.
So, I haven’t done much with the base Stable Diffusion XL model. I could totally believe that it has very little Sailor Moon training data. But I am confident that there are models out there that do know about Sailor Moon. In fact, I’ll bet that there are LoRAs – like, little “add-on” models that add “knowledge” to a checkpoint model on Civitai specifically for generating Sailor Moon images.
Looks like I don’t have vanilla SDXL even installed at the moment to test.
downloads vanilla
Here’s what I get from vanilla SDXL for “Sailor Moon, anime”. Yeah, doesn’t look great, probably isn’t trained on Sailor Moon:
Sailor Moon, anime
Steps: 20, Sampler: DPM++ 2M, Schedule type: Karras, CFG scale: 7, Seed: 2, Size: 1024x1024, Model hash: 31e35c80fc, Model: sd_xl_base_1.0, Token merging ratio: 0.5, Version: v1.9.4-169-ga30b19dd
searches civitai
Yeah. There are. Doing a model search just for SDXL-based LoRA models:
75 results for ‘sailor moon’
goes to investigate
Trying out Animagine, which appears to be a checkpoint model aimed at anime derived from SDXL, with a Sailor Moon LoRA that targets that to add Sailor Moon training.
I guess you were going for an angelic Sailor Moon? Or angelic money, not sure there…doing an angelic Sailor Moon:
Doing a batch of 20 and grabbing my personal favorite:
(masterpiece, best quality, very aesthetic, ultra detailed), intricate details, 4k, aausagi, long hair, double bun, twintails, hair ornament, parted bangs, tiara, earrings, blue eyes, heart choker, blue sailor collar, red bow, white shirt, see-through, elbow gloves, white gloves, multicolored skirt, white skirt, lora:sailor_moon_animaginexl_v1:0.9, standing, angel, halo
Negative prompt: (worst quality, low quality, very displeasing, lowres), (interlocked fingers, badly drawn hands and fingers, anatomically incorrect hands), blurry, watermark, 3d
Steps: 30, Sampler: Euler a, Schedule type: Automatic, CFG scale: 7, Seed: 11, Size: 1024x1024, Model hash: 1449e5b0b9, Model: animagineXLV31_v30, Token merging ratio: 0.5, Lora hashes: “sailor_moon_animaginexl_v1: e658577df088”, Version: v1.9.4-169-ga30b19dd
Time taken: 8 min. 18.0 sec. (to do a batch of 20, and with 30 steps, whereas I typically use 20…used 30 because the LoRA example image did, don’t wanna go experiment a bunch).
I grabbed some of those prompt terms from the example images for the Sailor Moon LoRA on Civitai. Haven’t really tried experimenting with what works well. I dunno what’s up with those skirt colors, but it looks like the “multicolored skirt, white skirt” does it – maybe there are various uniforms that Sailor Moon wears in different series or something, since it looks like this LoRA knows about them and can use specific ones, as they have those different skirts and different prompt terms on the example images.
I just dropped the Animagine model in the models/Stable-diffusion directory in Automatic1111, and the Sailor Moon Tsukino Usagi LoRA in the models/Lora directory, chose the checkpoint model, included that <lora:sailor_moon_animaginexl_v1:0.9> prompt term to make the render use that LoRA and some trigger terms.
That’s 1024x1024. Then doing a 4x upscale to a 16GB 4096x4096 PNG using SwinIR_4x in img2img using the SD Ultimate Upscale script (which does a tiled upscale, so memory shouldn’t be an issue):
The above should be doable with an Automatic1111 install and your hardware and the above models.
EDIT: On Civitai, when you view example images, you can click the little “i” in a circle on the image to view what settings they used to create them.
EDIT2: It looks like the same guy that made a LoRA for Sailor Moon also did LoRAs for the other characters in her series, so if you want, like, training on Sailor Mars or whatever, looks like you could grab that and also add knowledge about her in.
Thanks for trying it out! Both the inpainting and outpainting – the expansion – worked better than I’d expected, though I dunno if that’s exactly what M0oP0o’s after.
Lots of odd artifacting, slow creation time and yes it had some issues with sailormoon.
It probably isn’t worth the effort for most things, but one option might also be – and I’m not saying that this will work well, but a thought – using both. That is, if Bing Image Creator can generate images with content that you want but gets some details wrong and can’t do inpainting, but Midjourney can do inpainting, it might be possible to take a Bing-generated image that’s 90% of what you want and then inpaint the particular detail at issue using Midjourney. The inpainting will use the surrounding image as an input, so it should tend to try to generate similar image.
I’d guess that the problem is that an image generated with one model probably isn’t going to be terribly stable in another model – like, it probably won’t converge on exactly the same thing – but it might be that surrounding content is enough to hint it to do the right thing, if there’s enough of that context.
I mean, that’s basically – for a limited case – how AI upscaling works. It gets an image that the model didn’t generate, and then it tries to generate a new image, albeit with only slight “pressure” to modify rather than retain the existing image.
It might produce total garbage, too, but might be worth an experiment.
What I’d probably try to do if I were doing this locally is to feed my starting image into the thing to generate prompt terms that my local model can use to generate a similar-looking image, and include those when doing inpainting, since those prompt terms will be adapted to trying to create a reasonably-similar image using the different model. On Automatic1111, there’s an extension called Clip Interrogator that can do this (“image to text”).
Searching online, it looks like Midjourney has similar functionality, the /describe command.
https://docs.midjourney.com/docs/describe
It’s not magic – I mean, end of the day, the model can only do what it’s been trained on – but I’ve found that to be helpful locally, since I’d bet that Bing and Midjourney expect different prompt terms for a given image.
Oh I also tried local generation (forgot the name) and wooooow is my local PC bad at pictures (clearly can’t be my lack of ability it setting it up).
Hmm. Well, that I’ve done. Like, was the problem that it was slow? I can believe it, but just as a sanity check, if you run on a CPU, pretty much everything is mind-bogglingly slow. Do you know if you were running it on a GPU, and if so, how much VRAM it has? And what you were using (like, Stable Diffusion 1.5, Stable Diffusion XL, Flux, etc?)
@M0oP0o@mander.xyz, as far as I can tell, you always use Bing Image Creator.
And as far as I can tell, @Thelsim@sh.itjust.works always uses Midjourney.
I don’t use either. But as far as I know, neither service currently charges for generation of images. I don’t know if there’s some sort of different rate-limit that favors one over the other, or another reason to use Bing (perhaps Midjourney’s model is intentionally not trained on Sailor Moon?), but I do believe that Midjourney can do a few things that Bing doesn’t.
One of those is inpainting. Inpainting, for those who haven’t used it, lets one start with an existing image, create a mask that specifies that only part of the image should be regenerated, and then regenerate that part of the image using a specified prompt (which might differ from the prompt used to generate the image as a whole). I know that Thelsim’s used this feature before with Midjourney, because she once used it to update an image with some sort of poison witch image with hands over a green glowing pot, so I’m pretty sure that it’s available to Midjourney general users.
I know that you recently expressed frustration with Bing’s Image Creator’s current functionality, wanted more.
Inpainting’s time-consuming, but it can let a lot of images be rescued, rather than having to just re-reroll the whole image. Have you tried using Midjourney? Was there anything there that you found made it not acceptable?
it’s just ComfyUI behaving this way. Nothing is loaded, no LLMs
Oh, okay, then I’m probably wrong on VRAM, then. On my system, it needs to actually run the nodes before the VRAM gets allocated. Sorry! I thought I had it…
Just realized that I was dyslexic with the ordering directive, which worked well with Flux apparently not understanding it, since I wound up with the desired ordering; I’d intended to write “left to right”.
Not yet! One thing that AI generated images right now are not so good at is maintaining a consistent portrayal of a character from image to image, which is something you want for illustrating a story.
You might be able to do something like that with a 3d modeler to pose characters, generate a wireframe, and then feed that wireframe into ControlNet. Or if you have a huge corpus of existing images of a particular character portrayed in a particular way, you could maybe create new images with them in new situations. But without that, it’s hard to go from a text description to many images portrayed in a consistent way. For one image, it works, and for some things, that’s fine. But you’d have a hard time doing, say, a graphic novel that way.
I suspect that doing something like that is going to require having models that are actually working with 3D internal representations of the world, rather than 2D, at a bare minimum.
it starts flipping frames between the nodes and a different set of nodes.
Yeah, I don’t know what would cause that. I use it in Firefox.
Maybe try opening it in Chromium or a private window to disable addons (if you have your Firefox install set up not to run addons in private windows?)
I’m still suspicious of resource consumption, either RAM or VRAM. I don’t see another reason that you’d suddenly smack into problems when running ComfyUI.
I’m currently running ComfyUI and Firefox and some relatively-light other stuff, and I’m at 23GB RAM used (by processes, not disk caching), so I wouldn’t expect that you’d be running into trouble on memory unless you’ve got some other hefty stuff going on. I run it on a 128GB RAM, 128GB paging NVMe machine, so I’ve got headroom, but I don’t think that you’d need more than what you’re running if you’re generating stuff on the order of what I am.
goes investigating
Hmm. Currently all of my video memory (24GB) is being used, but I’m assuming that that’s because Wayland is caching data or something there. I’m pretty sure that I remember having a lot of free VRAM at some point, though maybe that was in X.
considers
Let me kill off ComfyUI and see how much that frees up. Operating on the assumption that nothing immediately re-grabs the memory, that’d presumably give a ballpark for VRAM consumption.
tries
Hmm. That went down to 1GB for non-ComfyUI stuff like Wayland, so ComfyUI was eating all of that.
I don’t know. Maybe it caches something.
experiments further
About 17GB (this number and others not excluding the 1GB for other stuff) while running, down to 15GB after the pass is complete. That was for a 1280x720 image, and I was loading the SwinIR upscaler; while not used, it might be resident in VRAM.
goes to set up a workflow without the upscaler to generate a 512x512 image
Hmm. 21GB while running. I’d guess that ComfyUI might be doing something to try to make use of all free VRAM, like, do more parallel processing.
Lemme try with a Stable Diffusion-based model (Realmixxl) instead of the Flux-based Newreality.
tries
About 10GB. Hmm.
kagis
https://old.reddit.com/r/comfyui/comments/1adhqgy/how_to_run_comfyui_with_mid_vram/
It sounds like ComfyUI also supports the --midvram and --lowvram flags, but that it’s supposed to automatically select something reasonable based on your system. I dunno, haven’t played with that myself.
tries --lowvram
I peak at about 14GB for ComfyUI at 512x512, was 13GB for most of generation.
tries 1280x720
Up to 15.7GB, down to 13.9GB after generation. No upscaling, just Newreality.
Hmm. So, based on that testing, I wouldn’t be incredibly surprised if you might be exhausting your VRAM if you’re running Flux on a GPU with 12GB. I’m guessing that it might be running dry on cards below 16GB (keeping in mind that it looks like other stuff is consuming about 1GB for me). I don’t think I have a way to simulate running the card with less VRAM than it physically has to see what happens.
Keep in mind that I have no idea what kind of memory management is going on here. It could be that pytorch purges stuff if it’s running low and doesn’t actually need that much, so these numbers are too conservative. Or it could be that you really do need that much.
Here’s a workflow (it generates a landscape painting, something I did a while back) using a Stable Diffusion XL-based model, Realmixxl (note: model and webpage includes NSFW content), which ran with what looked like maximum VRAM usage of about 10GB on my system using the attached workflow prompt/settings. You don’t have to use Realmixxl, if you have another model, should be able to just choose that other one. But maybe try running it, see if those problems go away? Because if that works without issues, that’d make me suspicious that you’re running dry on VRAM.
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EDIT: Keep in mind that I’m not an expert on resource consumption on this, haven’t read material about what requirements are, and there may be good material out there covering it. This is my ad-hoc, five-minutes-or-so-of testing; my own solution was mostly to just throw hardware at the problem, so I haven’t spent a lot of time optimizing workflows for VRAM consumption.
EDIT2: Some of the systems (Automatic1111 I know, dunno about ComfyUI) are also capable, IIRC, of running at reduced precision, which can reduce VRAM usage on some GPUs (though it will affect the output slightly, won’t perfectly reproduce a workflow), so I’m not saying that the numbers I give are hard lower limits; might be possible to configure a system to operate with less VRAM in some other ways. Like I said, I haven’t spent a lot of time trying to drive down ComfyUI VRAM usage.
UI: ComfyUI
Model: STOIQNewrealityFLUXSD_F1DAlpha
A cute, adorable, loveable, happy cave spider.
The image is an illustration.
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When a model is initially being loaded, I see slowdown, but once that has happened, I don’t. I see that with Automatic1111 as well. Once it’s been loaded, though, I don’t get that. I regularly do (non-GPU-using) stuff on another workspace when rendering, can’t detect any slowdown.
So I don’t know what might be the cause. Maybe memory exhaustion? A system that’s paging like mad might do that, I guess.
As to an alternative, it depends on what you want to do.
If you’ve never done local GPU-based image generation, then Automatic1111 is probably the most-widely-used UI (albeit the oldest).
If you want to run Flux and Flux-derived models – which I’m using to generate my above image – I believe I recall reading that while Automatic1111 cannot run them – and maybe that’s changed, have not been monitoring the situation – the Forge UI can do so as well. But I’ve never used it, so I can’t provide any real guidance as to setup.
kagis
Yeah, looks like Automatic1111 can’t do Flux:
https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/16311
And it looks like Forge can indeed run Flux:
https://sandner.art/flux1-in-forge-ui-setup-guide-with-sdsdxl-tips/
If you’re short of VRAM or RAM or something, though, I don’t know if Forge will do better than ComfyUI. I think that I might at least try to diagnose what is causing the issue first, as there are some things that can be done to reduce resource usage, like generating images at lower resolution and relying more-heavily on tile-based upscaling. With at least some of the systems, haven’t played around with ComfyUI here, there are also some command-line options to reduce VRAM usage in exchange for longer compute time, like --medvram or --lowvram in Automatic1111.
I don’t think that there’s a platform-agnostic way to see VRAM usage. I use a Radeon card on Linux, and there, the radeontop command will show VRAM usage. But I don’t know what tools one would use in, say, Windows to look up the same numbers.
On Linux, top will show regular memory usage, can hit “M” to sort by memory usage. I’m pretty out of date in Windows or MacOS – probably Task Manager or mmc on Windows and maybe top on MacOS as well? You may know better then me if you’re accustomed to that platform.
I can maybe try to give some better suggestions if you can list any of the OS being used, what GPU you’re running it on, and if you can, how much VRAM and RAM is on the system and if you can determine how much is being used.
I think that it’s worse than that, more catastrophic. They’ve got bread and tea…but no jam.
Ah, okay, I thought that they might have started throttling generation or something.
If I understand aright, they and ChatGPT use DALL-E 3 – I don’t really understand the relationship between Bing and ChatGPT’s image generation. I see vague references to a DALL-E 4 coming out at some point online, so I assume that it’s gonna get some kinda big functionality bump then.
I have been – if you’ve been reading my posts – pretty impressed by the natural-language parsing in Flux, and I would be willing to wager that the next iteration of most of the models out there is probably gonna improve on natural-language parsing.
I also see some stuff talking about improving text rendering, which would be nice.
I don’t know whether the functionality there is shared between ChatGPT and Bing or will be or what. But that example on ChatGPT is showing both a lot of text generation (better than I’m seeing in Flux, at any rate), and what looks kinda like that natural-language description stuff.
tries it
Yeah, that’s stubborn.
pokes a bit
There’s this, but it’s not very good.
The image is a photograph.
The body of a cow with its head replaced by a human head.
We also had a post some time back where people tried getting centaurs. Models did not like it, though you’d think that there’d be lots of models trained on fantasy images of centaurs.
I also remember someone trying to get car tires with non-black treads (not the sidewalls, but the treads). I couldn’t do it either (at least at the time, haven’t tried recently).
And I have had a long-running battle across multiple models to try to get images using cross-hatching shading.
I did manage to finally get engravings going under the Flux-derived NewReality, which is something that I wanted to do and had been driving me bonkers in Stable Diffusion for a long time.
An engraving of a raccoon.
An engraving of Sailor Moon
UI: ComfyUI
Model: STOIQNewrealityFLUXSD_F1DAlpha
The image is an illustration.
A raccoon sitting on a stool at a desk. The viewer is looking at the raccoon from behind.
On top of the desk, on the left-hand side of the desk, is a blue tray named In.
In contains a tall stack of papers.
In is labeled “In”.
On top of the desk, on the right-hand side of the desk, is a red tray named Moon.
Moon contains a small stack of papers.
Moon is labeled “Moon”.
Next to the desk, there is a metal garbage can labeled “Non-Moon”. The garbage can is heaping high with crumpled wads of paper. There are crumpled wads of paper on the floor by the trash can.
The raccoon is holding and looking intently at a piece of paper with an anime picture of Sailor Moon on it.
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They’re pretty large. I’m thinking butter-drenched hominy.
EDIT: Now I want hominy with butter.
EDIT2: https://cookpad.com/us/recipes/16952451-hominy-simmered-in-butter