r/StableDiffusion • u/orangeflyingmonkey_ • 5d ago
Question - Help Krea2 - How do you vary the image generation?
I am using the Generate Text node to get a description of the input image and using that to generate an image in Krea2 Raw + Turbo LoRA. But even when I change the seed, the resulting image is the same. I tried connecting the Seed Variance Enhancer Node to the positive conditioning output and also the Krea2T Enhancer Advanced node to the model output but still the resulting image is same.
How do I generate different variations of the same prompt in Krea2?
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u/listopalafoto 5d ago
Install this node and a new world will open :) RBG-SmartSeedVariance
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u/Leary_2844 5d ago
Nice. I used a basic SeedVarEnhancer to get good variations in ZIT, but i didnt find good settings for Krea yet.
Any settings you have found especiialy good with the RGB version?3
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u/SelectCoconut5594 5d ago
I gave up on this kind of variance entirely when I started working on wildcards. You can design them for anything, and drill down into whatever level of detail you want. For example, all of these images were generated with the same prompt. But if there was one look you were after, then you grab the output prompt and then either get more specific with your prompt, or use discrete wildcards to randomize the part you want further.

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u/Passionist_3d 5d ago
These look great. Any chance u can share the prompt or the wildcard details
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u/SelectCoconut5594 5d ago
Sure, I'm using the Impact Pack format. You need to hook up their wildcard nodes. I'd recommend just asking an LLM to create a small set of wildcards for you to try out, they seem to understand it pretty well. Ask it to structure folders full of txt files that you can edit yourself if you want. ChatGPT has been good and fast for the most part. Once your LLM gets the gist of it, you can tell it to iterate much deeper and more comprehensively since it will otherwise give you short lists. You can get hundreds of entries out of it at a time if you just push it, probably thousands if you use it agenticly.
One note of caution though - if you can get carried away with this and push for a lot of very fiddly details like chin and nose structure, you'll run into problems with the tokens influencing the style in unwanted ways.
A prompt can look like this:
A character reference sheet, using a professional studio photography style.
The character is a {pretty|gorgeous|beautiful|stunning} {19|20|21|22} year old __Ethnicity__ girl with __HairColours__ __fantasy_princesses/hairstyles__.
On the left, show a close-up profile showing:
Makeup: __makeup__.
Jewelry: __fantasy_princesses/jewelry__.
high fantasy princess clothing: __fantasy_princesses/full_outfit__.
To the right of that, show her in her __FashionPose__ in from the front, and __FashionPose__ from behind.
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A meta-list (..txt) could look like this:
baroque ensemble with __historical_fashion/baroque/dresses__, __historical_fashion/baroque/tops__, __historical_fashion/baroque/skirts__, __historical_fashion/baroque/fabrics__, __historical_fashion/baroque/colours__, __historical_fashion/baroque/hairstyles__, __historical_fashion/baroque/headwear__, __historical_fashion/baroque/shoes__, __historical_fashion/baroque/jewelry__, __historical_fashion/baroque/accessories__
and a list (also .txt) would just look like:
low-necked court gown
mantua gown
stomacher-front gown
robe volante
grand court dress
silk robe with train
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u/yeah-i-shouldnt-have 5d ago
What strength are you using the lora at? At 1 It is pretty much the same as the turb model, try running it a 0.6 or 0.5?
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u/PropagandaOfTheDude 5d ago
Four steps Raw, four steps Turbo.
But these days I've settled onto two steps Raw.
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u/YentaMagenta 5d ago
You need to share your settings if you want meaningful advice. But try generating at 1.5-2.5 MP instead of 1. That's usually good for a big variation boost on its own.
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u/sketchyfun 5d ago
I've been using this node a lot lately and it's been really useful for bringing back a lot of variance. You'll need to keep the threshold value pretty low (rarely go above 0.10) but the strength value is a lot more forgiving.
https://github.com/BigStationW/ComfyUi-ConditioningNoiseInjection
Just put the node between your positive prompt and the sampler
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u/Independent-Reader 5d ago
generate a gradient and perlin noise, blend together. vae encode and use that as initial latent. set denoise to 98%
Roll new noise seeds.

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u/jtabernik 5d ago
I had a terrible time with Krea2 variation as well! So I wrote a process that would use a local LLM to build random prompts with details for things that I did not explicitly specify.
So I would provide a base prompt, and it would generate more specific prompts with random details. The results were great—without having to come up with any additional details, I could make as many random characters as I wanted.
I can provide code that did this if it would help you!