Nodes Browser
ComfyDeploy: How ComfyUI_PhotoDoodle works in ComfyUI?
What is ComfyUI_PhotoDoodle?
PhotoDoodle: Learning Artistic Image Editing from Few-Shot Pairwise Data,you can use it in comfyUI
How to install it in ComfyDeploy?
Head over to the machine page
- Click on the "Create a new machine" button
- Select the
Edit
build steps - Add a new step -> Custom Node
- Search for
ComfyUI_PhotoDoodle
and select it - Close the build step dialig and then click on the "Save" button to rebuild the machine
PhotoDoodle
PhotoDoodle it a method about 'Learning Artistic Image Editing from Few-Shot Pairwise Data',you can use it in comfyUI
Update
- add fp8 nf4 transformer and T5 quantinaze chocie,add seed,增加量化菜单,和T5量化选项,用于repo模式,增加seed。
1.Installation
In the ./ComfyUI /custom_node directory, run the following:
git clone https://github.com/smthemex/ComfyUI_PhotoDoodle
2.requirements
pip install -r requirements.txt
- If OOM try pip install mmgp ,如果OOM ,试一下用mmgp
3.checkpoints
- 3.1 mode use 'flux dev single checkpoints(fp8 or fp16)' or 'repo' or 'unet+ae+comfyui T5XXX' ,三种选择,使用flux dev的fp8或fp16单体模型 或者使用repo,或者使用flux unet+ae+comfy的T5双clip
├── ComfyUI/models/diffusion_models/
| ├── flux1-kj-dev-fp8.safetensors # if use fp8 unet 11G unet+vae+clip方法不推荐,因为更容易爆显存
| ├── flux1-dev-fp8.safetensors # if use fp8 single 16G comfy官方单体fp8模型或者flux官方单体模型,正常12G能跑,不用开mmgp
- 3.2 more lora download from here
├── ComfyUI/models/loras/
| ├── pretrain.safetensors # 必须要
| ├── skscloudsketch.safetensors # 选你喜欢的lora
4 Example
- if use single files,vae must choice "none" #flux1-dev-fp8.safetensors 16G 单体16G模型,内置clip和vae那种,vae必须选择"none",不开启mmgp,次要推荐使用
- if use repo 'black-forest-labs/FLUX.1-dev' or C:/youpath/black-forest-labs/FLUX.1-dev 如果使用repo可以用自动下载或本地,不开启mmgp,第一推荐使用
- if use unet #11G 单体unet模型,没有内置clip和vae的,所以必须要连双clip和选vae,可以不开启mmgp,12G可能会OOM
5. Acknowledgments
- Thanks to Yuxuan Zhang and Hailong Guo for providing the code base.
- Thanks to Diffusers for the open-source project.
Citation
@misc{huang2025photodoodlelearningartisticimage,
title={PhotoDoodle: Learning Artistic Image Editing from Few-Shot Pairwise Data},
author={Shijie Huang and Yiren Song and Yuxuan Zhang and Hailong Guo and Xueyin Wang and Mike Zheng Shou and Jiaming Liu},
year={2025},
eprint={2502.14397},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2502.14397},
}