JoyAI-Echo video model released on HF
https://huggingface.co/jdopensource/JoyAI-Echo

https://redd.it/1tx8mak
@rStableDiffusion

ComfyUI-PiD update: more backbones, workflows, and better low-VRAM support
https://redd.it/1txacn4
@rStableDiffusion

Ideogram generated a Gemini Watermark without being prompted to
https://redd.it/1txfrhw
@rStableDiffusion

I didn't expect ideogram to be so good

https://preview.redd.it/odhzj8racf5h1.png?width=1501&format=png&auto=webp&s=71dbe0a0d613fb00dc8a904cc58646b7639bf02b

Spanish speaker trying to make their first contribution, please excuse any poor writing.

With Ideogram's release on Comfy, I saw it received a lot of hate, but honestly, it's amazing (at least to me) what it can do regarding typography. I adapted a workflow that was shared in the comments and combined it with Flux image editing, and wow, the possibilities are enormous.

First, I was interested in optimizing workflows for the hypothetical creation of content to promote an e-commerce site or product. I don't know if this violates the model's usage guidelines, but it works perfectly.

Second... yes... the workflow can be other things... , and it's just a matter of using the JSON prompt correctly. Otherwise, with Flux, you can do character replacement, and it looks quite nice.

I left the workflow with 30 steps and 5 CFGs on the Ideogram side, and it works wonderfully for typography and other details (wink wink). I don't know if you've tried other values, but with these and a resolution of 1024 (I'll upscale it later), the total generation time between both models (Ideogram and Flux) is 125 seconds. My setup is a 5070 and 96GB of RAM, and considering that it basically renders the product already finished, I find it truly impressive for the time saved when adding details in an editing program.

Here's a comparison of how this layout process was before in Flux (40 steps and 4 configurations, almost 15 minutes of generation) and how it is now in Ideogram.

Image generated by Infogram

image generated by flux

image with the flux edit

product image

I've included the workflow here so you can save yourself the trouble of switching between different workflows and see what you can create. Again, I simply combined two existing workflows to save time until someone achieves an i2i.

https://pastebin.com/r6UvLyni

Note: It seems I messed up a node; just activate it for the Infogram side to work.

https://preview.redd.it/hrle6nx3if5h1.png?width=565&format=png&auto=webp&s=a60e90a11716b5fccb714909b47bae9dec369fde




https://redd.it/1txf7qe
@rStableDiffusion

PhoneDiffusion - Local AI Image Studio for your iPhone!
https://redd.it/1txhlxl
@rStableDiffusion

Lightricks to split into two companies as it cuts another 75 jobs
https://www.calcalistech.com/ctechnews/article/r1dgjt5gmg

https://redd.it/1txhfv7
@rStableDiffusion

Made a custom sampler (Akium), now available for both Forge and ComfyUI

So I've been messing around with samplers for a while and ended up building my own. Figured I'd share it since a few people in my Discord found it useful.

It's called Akium. The short version: it's a second-order stochastic sampler, but instead of treating every step in isolation it keeps a running "momentum" of where the denoising is heading, and uses that to look ahead before committing to the next step. Once it's got a confident sense of direction, it automatically dials back the stochastic noise, because past a certain point the extra randomness just fights against fine detail.

End result is sharper details than something like ER-SDE, without losing the variety you get from stochastic sampling. Does two model calls per step, same as Heun or DPM++ 2S, so it's not free but it's not crazy either.

There's also an AkiumColor variant that does a small chroma boost on the final latent for more saturated output. Bit experimental, might change it later. Heads up that the boost is tuned for 4-channel latents (SD1.5/SDXL/Illustrious) — on other VAEs it can behaves differently.

I originally built it for Forge (comes with an installer that patches the sampler dropdown), and just finished porting it to ComfyUI. On Comfy it shows up directly in the normal KSampler dropdown as akium / akium_color after you drop it in custom_nodes, so no special workflow needed — though there are custom sampler nodes too if you're into the custom_sampling pipeline.

Tested mostly on Anima and Illustrious. Recommended settings that worked for me:

Anima: 30-35 steps, CFG 4-5, Beta scheduler
Illustrious: 28-32 steps, CFG 5-7, Karras

Would love feedback if anyone gives it a spin, especially curious how it holds up on Pony or other base models I haven't tested much. Comparison grids are on the GitHub if you want to see before/after.
Comfy link: https://github.com/AkiumAI/akium-sampler-comfy.git
Forge link: https://github.com/AkiumAI/akium-sampler.git




https://redd.it/1txgszm
@rStableDiffusion

Flux.2 Klein Spectral Graft - a node for adding/removing object, clothes swapping, face swapping and more

https://redd.it/1txg5sb
@rStableDiffusion