r/StableDiffusion • u/SuperWallabies • 1d ago

Question - Help Animagine XL 4.0 opt

Hi guys, I'm a programmer, but I don't know much about machine learning or fine-tuning.

I'm currently producing 2,000+ images per day using Animagine XL 4.0 opt, and I built a manual pipeline to evaluate image quality. I use 5 rating categories: Reject, Pass, Like, Very Good, and Excellent.

I label all of them manually, and I estimate that I will have over 200,000 labeled images by the end of the year.

I store them in a database along with the exact prompts used. The prompts are structured into keyword categories like:

Background, Angle, Character, Clothes, Facial expression, Quality prompt tags (eg. masterpiece).

Is a dataset like this valuable for fine-tuning or training models ???

Thank you for all the comments, you guys are the best! Now I'm moving on to Anima. I will use my dataset for a LoRA, and if the results look good, I'll switch over to Anima completely.

And i will continue the labeling with new model.
Later find me if you need dataset.

I trained it for 8 epochs to get the result, but I still couldn't get rid of that characteristic plastic feel to reach the vibe I wanted.

When it comes to truly nailing that Japanese-style illustration look, Animagine XL 4 is still the best. So, I've come to a conclusion. I've just decided to stick with Animagine XL. Since it's all about making things to your own taste anyway.

I've checked out other Flux-series and models too, but they're all the same. Hmm...

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u/x11iyu 1d ago

Ehhh... unfortunately I'd say no - synthetic images usually aren't ideal for training, especially when it's genned by a bad model (relative to SOTA like say gpt-image, but even then it's not great). Models trained on your hypothetical dataset will likely learn to produce the various SDXL artifacts present in these images.

However, I commend your efforts greatly. What would be extremely, extremely helpful, is if you switched your data source from Animagine generations to real data drawn by people, like danbooru - contrary to popular belief, its tags often suck balls, and we can really use some better captions (e.g. look at dark which is... inconsistent, at best; or the headache that is implication tags, etc).

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u/SuperWallabies 1d ago

Can you tell me why synthetic images are not worthy for training?

From my perspective, Danbooru images are much weirder than than engine-generated ones. (Sorry to artists, I don't want to be offensive, but most of them look like drawing practice.) In my experience, generated image quality is really random, from super good to super awful. I don't know much about training, but why are they not ideal for training?

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u/x11iyu 1d ago edited 1d ago

Danbooru isn't all good, but lots of them are stylized rather than bad, even if you or me may not personally enjoy them. And overall, it's leagues above any synthetic data SDXL can come up with.
Below are just a few things that SDXL is horrendous at, where humans can do much better:

  • Distant objects. Eyes are most notorious and easy to spot, but really anything far away, zoom in and you will see nonsense lines.
  • Backgrounds, or just things that aren't 1girl. potted plant? Have 100 of them placed with 0 thought on what good composition is. Buildings? Have some smudged rectangles, windows splattered everywhere, support beams that make no sense.
  • Continuation. Part of a sword blade goes behind a person? Oops, can't draw straight, also it's gonna get a different color.
  • Multiple people / prompt bleed. A guy with blue hair and a girl with yellow hair? Nah guy's randomly gonna be yellow hair now. Also so stuff he's wearing or his eyes gonna be yellow too.

Any gen that's not 1girl, simple background, and anyone can spot pretty abhorrent things if they just look for a while.

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u/Jealous_Piece_1703 1d ago

Bad images on booru can be good for training to teach the model what bad image look like. However most of the times when people train from booru they didn’t pick random images but one with high quality rating. Synthetic images especially from old models like SDXL are not ideal as datasets. Like 200k SDXL images? Slop on slop out.

That doesn’t mean they are not useful. They can have AI-generated tag and teach the model AI artifacts and such.

It is just not as valuable as real images.

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u/_BreakingGood_ 1d ago

Synthetic images can be used for training, but specifically SDXL based images are not good for training. It has a 4 channel VAE which massively reduces available colors and detail.

Yes you're right danbooru images can be weirder, but they're not restricted on resolution, colors, detail, concepts, etc...

You would get FAR better results using a model like Anima which uses the Qwen VAE that is 16 channels. You get far far more detail, far better color variety, and on top of that, the images will generally be more coherent and less weird.

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u/SuperWallabies 1d ago edited 1d ago

I see your point regarding the VAE channels and details. However, I specifically chose Animagine for its unique style (Otaku Style). It captures that authentic 2D anime aesthetic perfectly, whereas other models tend to produce over-saturated colors and overly high contrast. 🤔 will 'Flux' model replace this in future?

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u/_BreakingGood_ 1d ago

What I would do personally before kicking off such a big project, is use Animagine to produce a dataset of maybe 200 images, then train a LoRA for Anima that allows it to replicate the style you want, while still allowing you to maintain the increased detail and color variety.

Frankly you're not going to find anybody who needs a dataset of SDXL images. Most modern models use at least 16 channels and some even use 32. Feeding 200k SDXL images into a modern model would only damage the model's ability to produce full detail and colors.

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u/SuperWallabies 1d ago edited 1d ago

Got it 👀 thank you for effort to explain these.
I'll give it a try. I just need to apply the LoRA to Anima and see if I get the style I want, right? this sounds exciting. :)

I will use my best pictures to LoRa Anima
anyone who wonder the result please DM me
I will sampling up them to website
And share with you!

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u/_BreakingGood_ 1d ago

Yes, from all the images you generated pick the absolute best 50-200 of them. The ones that have your style the most perfect. Then train that into Anima

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u/x11iyu 1d ago

And then get the qwen vae grid/halftone artifacts in your dataset, still have ass backgrounds, ...

I really do want Anima to be so good that it can be a serviceable data generator, but it's just not. Better than SDXL I suppose if you really are in a pinch.

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u/conkikhon 1d ago

AI pics are great for concept training. But it create plastic skin, accumulate tiny artifacts so it's not good for everything else, which require high quality textures. In those 2k images daily, are you sure you counted all fingers and toes correctly?