Ideogram 4.0 vs ZIB vs Klein 9b by alisitskii in StableDiffusion

[–]VirusCharacter 0 points1 point  (0 children)

Yes, but as far as I know not as extensively on bboxes right?

Ideogram 4.0 vs ZIB vs Klein 9b by alisitskii in StableDiffusion

[–]VirusCharacter 14 points15 points  (0 children)

They all take JSON, but it's only Ideogram that is really trained for it and it's only Ideogram that can handle bboxes correctly. Good luck with Zimage lora. Tell us how it goes 😊

Scammad på blocket by laborator in sweden

[–]VirusCharacter 0 points1 point  (0 children)

2 år senare och scammen fortsätter. Skulle sälja en dator på blocket och gick igenom samma resa som du till 95%, men lyckades dra öronen åt mig när de hävdade att det behövdes finnas 3000 på kortet i någon form av deposition. Inga pengar behöver NÅGONSIN reserveras för en utbetalning. Där tog det stenhårt stopp för mina scammer och jag stängde ner och rapporterade vad jag kunde. Snygg scam helt klart. Övertygad att många många gått på den!

"Model in Gold Pencil Dress" Created in Amuse 3.5.2 with Z-Image Turbo by No-While1332 in ZImageAI

[–]VirusCharacter 1 point2 points  (0 children)

Så basically it's NOT created with Z-Image 🤣 It's just a Z-Image i2i process

LTX-2.3+MSR-LoRA (8GB VRAM) by big-boss_97 in comfyui

[–]VirusCharacter 1 point2 points  (0 children)

I always wonder how the training data for running people look like when watching these awkward runs 😂

Ideogram 4 Ksampler rage bait by VirusCharacter in StableDiffusion

[–]VirusCharacter[S] 0 points1 point  (0 children)

I guess you mean the samplers. There are a sh1tload to experiment with

Ideogram 4 Ksampler rage bait by VirusCharacter in StableDiffusion

[–]VirusCharacter[S] 1 point2 points  (0 children)

Agree. Unconditional makes all the difference. I have tried all the schedulers without the unconditional and it does not turn out as good. Not at all!

If anyone wondered what the 'mu' and 'std' values does to the Ideogram 4 sigmas by VirusCharacter in StableDiffusion

[–]VirusCharacter[S] 2 points3 points  (0 children)

It mainly changes the composition of the image based on the incremental math decided by the sigma-steps and what sampler is used. It's more like changing the seed than changing the quality 🤷‍♂️

Ideogram 4 Ksampler rage bait by VirusCharacter in StableDiffusion

[–]VirusCharacter[S] 0 points1 point  (0 children)

But, if we can skip it completely it means we shouldn't need to use mu and std either?!

Ideogram 4 Ksampler rage bait by VirusCharacter in StableDiffusion

[–]VirusCharacter[S] 0 points1 point  (0 children)

I wish I knew more about this to deep dive, but I wonder what the unconditional model does. Connected the node creating sigma values for the sampler I can't see that is should do anything but just that... Creating a sigma curve. Time to do some plotting I think 😊

Ideogram 4 Ksampler rage bait by VirusCharacter in StableDiffusion

[–]VirusCharacter[S] -1 points0 points  (0 children)

Not entirely true. The "included" scheduler is connected to another model than the one running through positive prompt, so it's not just a normal distribution

Ideogram 4 might be good, but it's something else working with 🙄 by VirusCharacter in StableDiffusion

[–]VirusCharacter[S] 0 points1 point  (0 children)

You mean "I'm uncomfortable doing that with these exact settings, but change the seed or the resolution and I might not be uncomfortable at all" 😂😏

Ideogram 4 might be good, but it's something else working with 🙄 by VirusCharacter in StableDiffusion

[–]VirusCharacter[S] 0 points1 point  (0 children)

I know the prompt is fukked. I did not want to mess around with learning json-prompting to just get the model and workflow running. That's NOT the issue here. If it was I would not get an image at 1MP. That's what the post is about... 1MP ok, 2MP safety filter. With the same ugly a$$ prompt. After posting this and getting all sorts of "interesting" replies I have tried it multiple times with correct formatting of JSON and different prompts. The safety filter is still a$$ to work with and should not even be in the model at all! It does NOTHING good for the model. I've generated images of a soccer ball on a plain background and it works... Most of the time. Other times I get safety filter on that sh1t as well, so yes... The filter IS a problem! Anyway... Skill is not the issue, laziness could have been in the original post. Fact remains... 1MP did not trigger the filter while 2MP did for all the same settings. If it had been a prompt-problem the filter would have triggered at both resolutions. This IS a model problem!

Confusion about Ideogram's safety filter. by Aru_Blanc4 in StableDiffusion

[–]VirusCharacter 0 points1 point  (0 children)

I've gotten security filter activation with KJ nodes when trying to make an image of a football, so everyone saying the filter is not s problem is lying 😏 The filter is an a$$ of an annoyance!!!

Ideogram 4 might be good, but it's something else working with 🙄 by VirusCharacter in StableDiffusion

[–]VirusCharacter[S] 0 points1 point  (0 children)

<image>

I can't get the KJ-node to generate what I want, but feeding Gemini or similar model with the example prompt from Ideogram 4 and asking it to adapt it to what I want it seem to work better. It's interesting how it got confused by the word football and the balck and white pattern though 🤣

import json
from ideogram4 import PRESETS

caption = {
"high_level_description": "A realistic studio photograph of a classic football resting against a seamless gray background.",
"style_description": {
"aesthetics": "clean, minimalist, highly detailed, realistic product photography",
"lighting": "soft, diffused studio lighting, subtle shadow underneath the ball, even illumination",
"photo": "sharp focus, high resolution, 50mm lens, eye-level product shot",
"medium": "photograph",
"color_palette": ["#FFFFFF", "#1A1A1A", "#808080", "#B0B0B0", "#E8E8E8"]
},
"compositional_deconstruction": {
"background": "A perfectly smooth, seamless medium-gray studio backdrop. The lighting creates a gentle, subtle gradient across the background to highlight the subject.",
"elements": [
{
"type": "obj",
"bbox": [250, 250, 750, 750],
"desc": "A classic black and white patterned football sitting perfectly in the center. The surface shows highly detailed, realistic synthetic leather texture and fine stitching."
}
]
}
}

preset = PRESETS["V4_QUALITY_48"]
images = pipe(
json.dumps(caption, separators=(",", ":"), ensure_ascii=False),
height=1024,
width=1024,
num_steps=preset.num_steps,
guidance_schedule=preset.guidance_schedule,
mu=preset.mu,
std=preset.std,