Add strength input to Differential Diffusion #5709
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Wouldn't it be better to skip the blending logic when the strength is set to 1.0? |
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@ltdrdata The blend operation is nearly instantaneous either way (at least at 1024x1024), but you're right, a conditional check is probably smarter. 🙂 Updated the code. |
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Any reason why this is not merged? |
comfyanonymous
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Sep 21, 2025
* Update nodes_differential_diffusion.py * Update nodes_differential_diffusion.py * Make strength optional to avoid validation errors when loading old workflows, adjust step --------- Co-authored-by: ThereforeGames <[email protected]>
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The commits are now in via #9957! Closing this PR 🫡 thanks! |
Thor-ATX
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Sep 26, 2025
…e-update * commit '2b7f9a8196304badb5fe58e5c734e4b182ad0fdf': (91 commits) Fix the failing unit test. (comfyanonymous#10037) Make LatentCompositeMasked work with basic video latents. (comfyanonymous#10023) Fix memory leak by properly detaching model finalizer (comfyanonymous#9979) Fix issue with .view() in HuMo. (comfyanonymous#10014) Add new audio nodes (comfyanonymous#9908) Rodin3D - add [Rodin3D Gen-2 generate] api-node (comfyanonymous#9994) ComfyUI version 0.3.60 feat(api-nodes): add wan t2i, t2v, i2v nodes (comfyanonymous#9996) update template to 0.1.86 (comfyanonymous#9998) Fix bug with WanAnimateToVideo. (comfyanonymous#9990) Fix bug with WanAnimateToVideo node. (comfyanonymous#9988) add offset param (comfyanonymous#9977) Support for qwen edit plus model. Use the new TextEncodeQwenImageEditPlus. (comfyanonymous#9986) Set some wan nodes as no longer experimental. (comfyanonymous#9976) Lower wan memory estimation value a bit. (comfyanonymous#9964) Fix LoRA Trainer bugs with FP8 models. (comfyanonymous#9854) [Reviving comfyanonymous#5709] Add strength input to Differential Diffusion (comfyanonymous#9957) Add inputs for character replacement to the WanAnimateToVideo node. (comfyanonymous#9960) Update WanAnimateToVideo to more easily extend videos. (comfyanonymous#9959) fix(seedream4): add flag to ignore error on partial success (comfyanonymous#9952) ...
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Hi,
The Differential Diffusion node from #2876 is awesome for inpainting tasks, but the effect is too strong at times. It is challenging to use when generating a subject that has little in common with the original.
Even at a denoising strength of 100%, Differential Diffusion often overwhelms the prompt. But if we blend the adjusted binary mask with the original, we can find a sweet spot. The example below was performed with Euler/Beta, 4 steps, 100% denoising strength. Model is flux1-dev.sft with distillation LoRAs for speed.
50-75% Differential Diffusion strength feels a lot more usable in practice than 100%. Here's one more comparison if you'll indulge me:
The prompt was "Donald Trump." That guy in the middle looks like he'd be fun at parties, but he's definitely not Trump.