62 lines
2.2 KiB
Markdown
62 lines
2.2 KiB
Markdown
# ComfyUI-MooshieTiledDiffusion
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Standalone export of the tiled diffusion node from MooshieUI, published by
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request (issue #338). Provided as is, with no promise of maintenance or support.
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## What it does
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Adds one node, Apply Tiled Diffusion, that patches a model to denoise in tiles
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and blend the tiles back together. This lets you generate and upscale above a
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model's native resolution without the seams and artifacts you get from a single
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large pass.
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Two methods:
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- MultiDiffusion: overlapping tiles with cosine feathered blending. Best quality.
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- SpotDiffusion: random tile shift per denoising step, no overlap. Fastest.
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It supports 4D and 5D latents, so it works with Anima (COSMOS based) models as
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well as standard diffusion models. It works in txt2img, img2img, and inpainting,
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and crops spatial conditioning (inpaint masks and ControlNet) per tile.
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The only dependencies are torch and the ComfyUI API, both of which ComfyUI
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already provides. There are no extra packages to install.
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## Install
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Pick one.
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- ComfyUI-Manager: search for Mooshie Tiled Diffusion and install.
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- Comfy Registry: install comfyui-mooshietileddiffusion.
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- Manual: clone this repo into ComfyUI/custom_nodes and restart ComfyUI.
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```
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cd ComfyUI/custom_nodes
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git clone https://github.com/Mooshieblob1/ComfyUI-MooshieTiledDiffusion
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```
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## Usage
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1. Add the Apply Tiled Diffusion node (category: model_patches/unet).
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2. Connect your model into the node and the node MODEL output into your KSampler.
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3. Set tile_width and tile_height to the model native resolution (for example
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1024 for SDXL or Flux, 512 for SD1.5).
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4. Set tile_overlap for MultiDiffusion. Higher overlap means smoother seams and
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slower generation. Overlap is ignored by SpotDiffusion.
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Use MultiDiffusion when you want the cleanest result. Use SpotDiffusion when you
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want speed and can accept an experimental method.
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This is useful above about 2.4 MP, where a single pass tends to show artifacts.
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## License
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GPL-3.0-or-later. The node is derived from ComfyUI, which is GPL-3.0.
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## Credits
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- ComfyUI by Comfy Org.
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- MultiDiffusion: Bar-Tal et al., MultiDiffusion: Fusing Diffusion Paths for
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Controlled Image Generation, ICML 2023. arxiv.org/abs/2302.08113
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- SpotDiffusion: Ding et al., 2024. arxiv.org/abs/2407.15507
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