ComfyUI_LucidFlux
ComfyUI_LucidFlux:Caption-Free Universal Image Restoration with a Large-Scale Diffusion Transformer，you can use it in ComfyUI
Nodes (8)
LucidFlux's one-input LoRA merge — mostly the Turbo shortcut, and entirely optional
Turning the restored latent back into pixels — and why 'wavelet' should stay on
The DiffBIR preprocessor that decides what your restoration actually sees
LucidFlux's conditioning stage — and the OOM trap everyone hits first
The custom denoiser that actually runs the restoration (no, a stock KSampler won't do)
This is where a photo becomes a restoration task
PiD pushes the restored latent up to the wall
NVIDIA's PiD decoder, loaded for the 4K leg of LucidFlux
ComfyUI_LucidFlux（comfy 原生 DiT 链版本）
LucidFlux: Caption-Free Universal Image Restoration with a Large-Scale Diffusion Transformer，you can use it in ComfyUI
Update
- 更改封装方式，使用comfyUI的核心复现方法/ change the encapsulation method to use the core method of comfyUI
1.Installation
In the ./ComfyUI/custom_nodes directory, run the following:
git clone https://github.com/smthemex/ComfyUI_LucidFlux
2.checkpoints
2.1 any flux dit / 任意flux模型， KJ的 或者官方封装的
2.2 lucid checkpoints/ links /lucidflux.pth 和prompt_embeddings.pt 和gemma_prompt_embedding.pt
2.3 siglip512 links / model.safetensors 只下单体模型
2.4 DiffBIR links / general_swinir_v1.ckpt
2.5 turbo lora links #optional 可选，8 步起
2.6 lucid_connector.pthlinks
2.7 ultravaelinks ,rename or not
2.8 PIDlinks / PiD_res2kto4k_sr4x_official_flux_distill_4step.pth or PiD_res2k_sr4x_official_flux_distill_4step.pth
2.9 null_caption_embs.ptlinks #PID use
ComfyUI/models/
├── diffusion_models/flux1-dev-fp8.safetensors # 任意 flux-dev（bf16/fp8 均可）
├── PiD_v1pt5_res2kto4k_sr4x_official_flux_distill_4step.pth # v1.5 的 4K 模型（使用PID必需）
├── clip_vision/siglip2-so400m-patch16-512.safetensors
├── vae/UltraFlux.safetensors # 2K 用；1K 可换 ae.safetensors
└── LucidFlux/
├── lucidflux.pth # 双条件分支（必需）
├── lucid_connector.pth # SigLIP→4096 的 redux connector（必需）
├── general_swinir_v1.ckpt # DiffBIR 先验（必需）
├── prompt_embeddings.pt # 官方预计算文本 embedding（**必需**，替代 CLIP/T5）
└── gemma_prompt_embedding.pt / null_caption_embs.pt # 仅 PiD 阶段用
3 Example
- 256 to 4K
4 Citation
LucidFlux
@article{fei2025lucidflux,
title={LucidFlux: Caption-Free Universal Image Restoration via a Large-Scale Diffusion Transformer},
author={Fei, Song and Ye, Tian and Wang, Lujia and Zhu, Lei},
journal={arXiv preprint arXiv:2509.22414},
year={2025}
}