ComfyUI-DonutNodes
A ComfyUI extension with 54 custom nodes.
Nodes (54)
ComfyUI-DonutNodes
Custom nodes for ComfyUI focused on LoRA management, model merging, and image enhancement.
Features
- Block-weighted LoRA stacking with per-block strength control and CivitAI integration
- Donut Detailers for per-block model tuning and face/object enhancement
- TeaCache acceleration for faster SDXL inference
- Tiled upscaling with seamless blending
- CFG sampling with 18 curve types
- Spectral noise sharpening for reference-based detail enhancement
Installation
ComfyUI Manager
Search for "DonutNodes" in ComfyUI Manager and install.
Manual
cd ComfyUI/custom_nodes
git clone https://github.com/DonutsDelivery/ComfyUI-DonutNodes.git donutnodes
cd donutnodes
python -m pip install -r requirements.txt
Run the install command with the same Python interpreter that launches ComfyUI.
Optional companion packages
- ComfyUI-DonutLocalAutomation provides the local-only Prompt Receiver and Image Reporter nodes.
- ComfyUI-DonutCivitaiLocal provides optional local CivitAI library and workflow-recovery tools.
Install ComfyUI-DonutLocalAutomation alongside this package to keep the original
DonutPromptReceiver and DonutImageReporter node IDs in existing workflows.
Nodes
| Node | Description | |------|-------------| | DonutLoRAStack | Block-weighted LoRA stacking with presets | | DonutApplyLoRAStack | Apply stacked LoRAs to model/CLIP | | DonutLoraStackCombine | Merge two LoRA stacks | | DonutFaceDetailer | Face detection and enhancement | | DonutUniversalDetailer | Auto-detect object enhancement | | DonutDetailerZIT | ZIT-based detail enhancement | | DonutSDXLTeaCache | TeaCache acceleration for SDXL | | DonutTiledUpscale | Tiled img2img upscaling | | DonutKSamplerCFG | CFG sampling with curve control | | DonutSpectralNoiseSharpener | Reference-based spectral sharpening | | ModelMergeZIT | ZIT model merging | | DonutModelSave | Save merged models |
License
See LICENSE file.