Fixed AttentionCouple, NegPip(negative weights in prompts) for SDXL and FLUX, more CFG++ and SMEA DY samplers, etc.
Just a bunch of random nodes modified/fixed/created by me or others. If any node starts throwing errors after an update - try to delete and re-add the node.
You can drag-and-drop workflow images from examples/
into your ComfyUI. I'll probably add some more examples in future (but I'm kinda lazy, kek).
Supports:
Modified implementation of NegPiP by laksjdjf and hako-mikan. It uses ModelPatcher instead of monkey-patching, which should increase compatibility with other nodes.
CLIPNegPip
node allows you to use negative weights in prompts. Connect the node before other model/clip patches.
Read more about NegPiP in the original repo. I recommend to keep all dots/commas inside weight braces (i.e. (worst quality,:-1.3) (sketch:-1.1,)
instead of (worst quality:-1.3), (sketch:-1.1),
).
[!NOTE]
CLIPNegPip
is compatible with:
CLIPNegPip
is incompatible with:
- smZ Nodes by shiimizu (for now you can use ComfyUI_ADV_CLIP_emb and comfyui-prompt-control instead)
- Comfyui_Flux_Style_Adjust by yichengup (and probably some other custom nodes that modify cond tensors)
Modified implementation of AttentionCouple by laksjdjf and Haoming02. I made AttentionCouplePPM
node compatible with CLIPNegPiP
node and with default PatchModelAddDownscale (Kohya Deep Shrink)
node.
Inputs for new regions are managed automatically: when you attach cond/mask of a region to the node, a new cond_
/ mask_
input appears. Last cond_
/ mask_
inputs are always optional.
Use multiple LatentToMaskBB
nodes to set bounding box masks for AttentionCouplePPM
. The parameters are relative to your initial latent: x=0.5, y=0.0, w=0.5, h=1.0
will produce a mask covering right half of your image.
Modified samplers from Euler-Smea-Dyn-Sampler by Koishi-Star.
Contains some new samplers: euler_ancestral_dy
, dpmpp_2m_dy
and dpmpp_3m_dy
.
Tweaking s_dy_pow
may reduce blur artifacts (optimal value is 2
for euler_*
samplers and -1
for dpmpp_*
samplers, use -1
to disable this feature).
Samplers adapted to CFG++: Manifold-constrained Classifier Free Guidance for Diffusion Models by Chung et al.. Also contains converted samplers from Euler-Smea-Dyn.
Should greatly reduce overexposure effect. Use together with SamplerCustom
node. Don't forget to set CFG scale to 1.0-2.0 and PAG/SEG scale (if used) to 0.5-1.0.
Implementation of Applying Guidance in a Limited Interval Improves Sample and Distribution Quality in Diffusion Models by Kynkäänniemi et al. (also contains RescaleCFG
functionality)
Guidance Limiter is also available as a CFGLimiterGuider
guider node for SamplerCustomAdvanced
.
Empty Latent Image (Aspect Ratio)
node generates empty latent with specified aspect ratio and with respect to target resolution.
A small lightweight wrapper over ConditioningConcat
node, CLIPTextEncodeBREAK
node can split prompts by BREAK
keyword into chunks and produce a single concatenated conditioning.
Counts tokens in your prompt and returns them as a string (currently limited to clip_l). You can also print token count + individual tokens by enabling debug_print
.
Adds AlignYourSteps scheduler modified by Extraltodeus to the default list of schedulers by replacing comfy.samplers.calculate_sigmas
function. ays
is the default AYS scheduler for SDXL and ays+
is just ays
with force_sigma_min=True
.
Also adds GITS scheduler and AYS_30 scheduler (based on AYS_32 by Koitenshin)
Hijacks advanced_encode_from_tokens
method from Advanced CLIP Text Encode extension (if installed), making all weight interpretations compatible with NegPip.