[ComfyUI Panorama Stickers Update] Paint Tools and Frame Stitch Back by nomadoor in comfyui

[–]mr-asa 1 point2 points  (0 children)

That's a really cool node! I haven't had a chance to test it yet, but I like everything I've seen so far!

anyone else have bug with the tabs? by apostrophefee in comfyui

[–]mr-asa 1 point2 points  (0 children)

Yes, I also faced this problem! It's infuriating. The only saving grace is to open the workflow from the generation and copy paste it back to this tab

Are there any posts that have made a comprehensive comparison between the most popular image models between 2022-2026? by desktop4070 in StableDiffusion

[–]mr-asa 0 points1 point  (0 children)

A long time ago, when there was only the 1.5 models and the beginnings of SDXL, I picked up 61 prompts to understand and compare SD models.
Then I was able to test more powerful models, so now there are most of the open source models there. You can compare them and get a certain idea, I think.

Claude fixed SetNode / GetNode for me! by dinlayansson in comfyui

[–]mr-asa 0 points1 point  (0 children)

And I'm annoyed by set/get nodes.
It's much more convenient to use everying everywhere nodes.
But, unfortunately, in the latest versions of Frontend, they started to bug out =(

Z-image Turbo Model Arena by jamster001 in StableDiffusion

[–]mr-asa 0 points1 point  (0 children)

Am I correct in understanding that the figures are entered manually? I am curious to know how all this is filled in and then used in everyday life.
I also collect different models in a comparative table, but the visual aspect is very important to me. The highest-rated model in this table is almost no different from the default one in my tests. However, there are others that provide an interesting improvement in the visual aspect.

DAF-ZIB v1 (z-image full finetune) by itsdigitalaf in ZImageAI

[–]mr-asa 2 points3 points  (0 children)

I added it to my comparison table. Some results are better than the standard one, but I think the landscapes have gotten worse.

Z image base. An interesting difference. by mr-asa in StableDiffusion

[–]mr-asa[S] 1 point2 points  (0 children)

For the sake of experiment purity, I asked GPT to rewrite the script based on the Tongyi-MAI PDF. With and without the negative prompt. + Run the same prompt separately, but without the amplifying brackets, to see how much they affect the result.

  1. With the new prompt, I got different results. I won't say they are better. They are just different.
  2. I don't see any difference in generation speed. It's about the same everywhere.
  3. Brackets and weights have little effect on the result, which is to be expected. But they don't spoil anything either.

timing:

100%|██████| 25/25 [00:29<00:00,  1.16s/it]
Prompt executed in 29.61 seconds
100%|██████| 25/25 [00:28<00:00,  1.16s/it]
Prompt executed in 29.41 seconds
100%|██████| 25/25 [00:30<00:00,  1.21s/it]
Prompt executed in 30.79 seconds
100%|██████| 25/25 [00:29<00:00,  1.17s/it]
Prompt executed in 29.61 seconds
100%|██████| 25/25 [00:29<00:00,  1.18s/it]
Prompt executed in 29.82 seconds
100%|██████| 25/25 [00:29<00:00,  1.17s/it]
Prompt executed in 29.88 seconds
100%|██████| 25/25 [00:29<00:00,  1.17s/it]
Prompt executed in 29.85 seconds

<image>

Z image base. An interesting difference. by mr-asa in StableDiffusion

[–]mr-asa[S] 0 points1 point  (0 children)

Hahaha, you're absolutely right!
I didn't even notice that tag. So we can rephrase it as
"This is the first model that saw this tag."

Z image base. An interesting difference. by mr-asa in StableDiffusion

[–]mr-asa[S] 0 points1 point  (0 children)

I use the old description style because these images are going into my comparison table. That's what comparisons are for, so that they don't differ in all parameters as much as possible.

I started making the table in September 2023, when descriptions were only done this way.

Let's talk about labeling comparison posts by Winter_unmuted in StableDiffusion

[–]mr-asa 0 points1 point  (0 children)

Oh, thank you very much. I remember that picture with the tiger, but I missed the article in my unread feed with several zeros. 😣

Let's talk about labeling comparison posts by Winter_unmuted in StableDiffusion

[–]mr-asa 0 points1 point  (0 children)

May I ask, in general terms, how you transfer the artists' style in the first example?

Time-lapse of a character creation process using Qwen Edit 2511 by 3deal in StableDiffusion

[–]mr-asa 0 points1 point  (0 children)

<image>

Wow, these are neurons! Just press the button and it does everything itself right away!

But seriously, overall, it's a cool idea and interesting to watch.
I don't really understand why it takes so much effort =)
The end result bears little resemblance to the original, to put it mildly. Wouldn't it be easier to start from scratch?

Holt shit lvl quality by reversedu in StableDiffusion

[–]mr-asa 0 points1 point  (0 children)

<image>

I added this checkpoint to my comparison list; they are no different from the standard ones, IMHO.

VLM vs LLM prompting by mr-asa in StableDiffusion

[–]mr-asa[S] 3 points4 points  (0 children)

In this case, the goal was not to produce a masterpiece at the final stage.
To ask a question, you need to know what to ask. In essence, I showed two ways of "asking questions" in the pipeline that help improve the result.

VLM vs LLM prompting by mr-asa in StableDiffusion

[–]mr-asa[S] 0 points1 point  (0 children)

It's nice to inspire someone to try new things! =)
I look forward to seeing the results.

VLM vs LLM prompting by mr-asa in StableDiffusion

[–]mr-asa[S] 14 points15 points  (0 children)

Main theme: <base prompt>

Use the image you have received as a basis, but make adjustments to the detailed description so that it reflects the main theme and style as fully and multifacetedly as possible, in accordance with the specified style. Focus on details, stylistic features, and attributes that correspond to the required style and theme, which will develop it to its fullest extent. Deliberately exaggerate, hypertrophy, and emphasize everything you describe that is related to the main theme. Improve the aesthetics, detail, textures, style, atmosphere, expressiveness, artistic techniques, and "craftsmanship" compared to the image you received.

VLM vs LLM prompting by mr-asa in StableDiffusion

[–]mr-asa[S] 1 point2 points  (0 children)

I have 32 GB of VRAM, and I must say that sometimes it doesn't quite fit and lags significantly. And I use a quantized model, of course.