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Upscaling and Face Fix
MooshieUI upscales with MultiDiffusion tiled diffusion, the same approach used by SwarmUI. There is no slow tile-by-tile processing; all tiles are denoised together each step for seamless results.
The tiled diffusion node is also published as a standalone ComfyUI custom node for use outside MooshieUI: ComfyUI-MooshieTiledDiffusion. It is the same node MooshieUI uses, so it supports Anima (COSMOS) and 5D latents, MultiDiffusion and SpotDiffusion, and txt2img, img2img, and inpainting, and it works above 2.4 MP where a single pass shows artifacts. Install it with ComfyUI-Manager (search Mooshie Tiled Diffusion), the Comfy Registry (comfyui-mooshietileddiffusion), or by cloning into custom_nodes. It is a one-off export with no promise of ongoing maintenance; the canonical source stays in MooshieUI.
- Model-based - uses a dedicated upscale model (for example Omni-SR). Scale is fixed by the model (2x, 4x, etc.).
- Algorithmic (Lanczos) - fast pixel-space upscaling with an adjustable 1 to 4x scale.
When you pick a recommended model that is not installed, MooshieUI downloads it to ComfyUI's models/upscale_models/:
| Model | Scale | Source |
|---|---|---|
| Omni 2x | 2x | Acly/Omni-SR |
| Omni 4x | 4x | Acly/Omni-SR |
Any other models in models/upscale_models/ also appear in the dropdown.
- Toggle per generation. Recommended for large images and required for Anima (COSMOS) models.
- Adjustable tile size (256 to 2048px).
- Cosine-feathered blending for seamless boundaries.
- Supports both MultiDiffusion and SpotDiffusion algorithms.
- Soft Guidance (CFG Rescale) - toggle in Upscale Settings to reduce extra hands/objects at low denoise. Adjustable multiplier (0.0 to 1.0, default 0.4).
- Smart Guidance (positive-biased adaptive) - toggle in Sampler Settings to bias the model toward positive conditioning across all passes.
These are custom nodes (MooshieSoftGuidance, MooshieSmartGuidance) installed automatically.
- Denoise - 0 to 1 (lower preserves more of the original).
- Steps - 1 to 50.
Hover any generated image and click Upscale to upscale the last output without changing your settings.
Enable a post-generation pass that detects faces and re-denoises them at higher resolution, then composites them back with smooth cosine-falloff blending. No Impact Pack dependency; it is a self-contained node.
Controls in Face Fix Settings:
-
Detector model - choose from recommended detectors (for example an Anzhc face segmentation model or
face_yolov8n). Missing models are auto-downloaded with SHA256 verification, and theultralyticsPython package is installed automatically. - Denoise - 0 to 1.
- Steps - 1 to 50.
- Guide size - 256 to 1024px.
- Auto-prompt toggle.
Getting started
Prompting
Generation features
Models and output
Deployment
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