ComfyUI InvSR

This project is a ComfyUI wrapper for InvSR (Arbitrary-steps Image Super-resolution via Diffusion Inversion)

Last tested: 2 January 2026 (ComfyUI v0.7.0@f2fda02 | Torch 2.9.1 | Python 3.10.12 | RTX4090 | CUDA 13.0 | Debian 12)

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Installation

Navigate to the ComfyUI /custom_nodes directory

git clone https://github.com/yuvraj108c/ComfyUI_InvSR
cd ComfyUI_InvSR

pip install -r requirements.txt

Usage

• Load example workflow
• Diffusers model (stabilityai/sd-turbo) will download automatically to ComfyUI/models/diffusers
• InvSR model (noise_predictor_sd_turbo_v5.pth) will download automatically to ComfyUI/models/invsr
• To deal with large images, e.g, 1k---->4k, set chopping_size 256
• If your GPU memory is limited, please set chopping_batch_size to 1

Parameters

• num_steps: number of inference steps
• cfg: classifier-free guidance scale
• batch_size: Controls how many complete images are processed simultaneously
• chopping_batch_size: Controls how many patches from the same image are processed simultaneously
• chopping_size: Controls the size of patches when splitting large images
• color_fix: Method to fix color shift in processed images

Updates

28 April 2025

• Update diffusers versions in requirements.txt to fix https://github.com/yuvraj108c/ComfyUI_InvSR/issues/26, https://github.com/yuvraj108c/ComfyUI_InvSR/issues/21, https://github.com/yuvraj108c/ComfyUI_InvSR/issues/15
• Add support for noise_predictor_sd_turbo_v5_diftune.pth

03 February 2025

• Add cfg parameter
• Make image divisible by 16
• Use mm to set torch device

31 January 2025

• Merged https://github.com/yuvraj108c/ComfyUI_InvSR/pull/5 by wfjsw
  • Compatibility with diffusers>=0.28
  • Massive code refactoring & cleanup

Citation

@article{yue2024InvSR,
  title={Arbitrary-steps Image Super-resolution via Diffusion Inversion},
  author={Yue, Zongsheng and Kang, Liao and Loy, Chen Change},
  journal = {arXiv preprint arXiv:2412.09013},
  year={2024},
}

License

This project is licensed under NTU S-Lab License 1.0

Acknowledgments

Thanks to simplepod.ai for providing GPU servers

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