ComfyUI Extension: ComfyUI_AnyDoor

Authored by smthemex

Created

Updated

51 stars

you can using anydoor ,change clothes,object

Custom Nodes (0)

    README

    ComfyUI_AnyDoor

    You can using AnyDoor in comfyUI,you can change the clothes of the characters and move the position of the objects in the picture

    AnyDoor origin From: AnyDoor

    Tips:
    At present, there is no good adaptation node for the injection of object mask positions, so we will add one later.
    If you have pre downloaded the model, you don't need to install the modelscope library

    英文阅读慢的,请看中文说明

    My ComfyUI node list:

    1、ParlerTTS node:ComfyUI_ParlerTTS
    2、Llama3_8B node:ComfyUI_Llama3_8B
    3、HiDiffusion node:ComfyUI_HiDiffusion_Pro
    4、ID_Animator node: ComfyUI_ID_Animator
    5、StoryDiffusion node:ComfyUI_StoryDiffusion
    6、Pops node:ComfyUI_Pops
    7、stable-audio-open-1.0 node :ComfyUI_StableAudio_Open
    8、GLM4 node:ComfyUI_ChatGLM_API
    9、CustomNet node:ComfyUI_CustomNet
    10、Pipeline_Tool node :ComfyUI_Pipeline_Tool
    11、Pic2Story node :ComfyUI_Pic2Story
    12、PBR_Maker node:ComfyUI_PBR_Maker
    13、ComfyUI_Streamv2v_Plus node:ComfyUI_Streamv2v_Plus
    14、ComfyUI_MS_Diffusion node:ComfyUI_MS_Diffusion
    15、ComfyUI_AnyDoor node: ComfyUI_AnyDoor
    16、ComfyUI_Stable_Makeup node: ComfyUI_Stable_Makeup
    17、ComfyUI_EchoMimic node: ComfyUI_EchoMimic
    18、ComfyUI_FollowYourEmoji node: ComfyUI_FollowYourEmoji

    1.Installation

    In the ./ComfyUI /custom_node directory, run the following:

    git clone https://github.com/smthemex/ComfyUI_AnyDoor.git
    

    or using ComfyUI-Manager

    2.requirements

    pip install -r requirements.txt
    

    if miss any modules,rename "for_modules_miss_requirements.txt" to requirements.txt
    and pip install -r requirements.txt
    or just "pip install missing module"

    3 Required models

    model 1:

    <online> The first use will automatically download the model, but the "Pruned" model is not on the huggingface server, so there is a "modelscope" (魔搭)library in the requirements, which will reference the use of the modelscope library to download the corresponding "Pruned" model <offline>

    --using "origin" model download "epoch=1-step=8687.ckpt"(16.8G) : link
    or
    --using "pruned" model download "epoch=1-step=8687-pruned.ckpt"(4.9G) : link

    model 2:

    <online> The model is not stored on the huggingface, you can find it at the following two URLs.The first use will automatically download the model from “modelscope” <offline>

    --download "dinov2_vitg14_pretrain.pth"(4.5G) :link
    or
    --download "dinov2_vitg14_pretrain.pth"(4.5G) :link

    --The file storage address is as follows:

    ├── ComfyUI/models/
    |      ├──anydoor/
    |             ├── dinov2_vitg14_pretrain.pth
    |             ├── epoch=1-step=8687.ckpt  (origin)
    |             ├── epoch=1-step=8687-pruned.ckpt  (pruned)
    

    4 Using

    4.1 Image and image_mask are the objects you want to transfer, while bg_image and bg_mask are the background of the image, which is the main image;
    4.2 Seed is currently invalid;
    Although the built-in mask of comfyUI can also be used, I still recommend using Seg or Sam;
    4.4 If there is not enough graphics memory, you can consider enabling save_memory;
    4.5 useInteractive_seg will process the mask again, unless you are a hand animation mask, it is generally not recommended to open it;
    4.6 The maximum model training size is 768 * 768, so it is not recommended to use oversized images for image training;
    4.7 The workflow file is located in the examples folder;
    4.8 When inputting the mask image, please make sure that the selection you want to replace is whiter.

    5 Example

    change cloth using SAM...

    change cloth using normal mask...

    Citation

    特别致谢: 青龍聖者@bdsqlsz 的“poch=1-step=8687-pruned.ckpt” 模型

    AnyDoor

    @article{chen2023anydoor,
      title={Anydoor: Zero-shot object-level image customization},
      author={Chen, Xi and Huang, Lianghua and Liu, Yu and Shen, Yujun and Zhao, Deli and Zhao, Hengshuang},
      journal={arXiv preprint arXiv:2307.09481},
      year={2023}
    }
    

    Citing DINOv2

    @misc{oquab2023dinov2,
      title={DINOv2: Learning Robust Visual Features without Supervision},
      author={Oquab, Maxime and Darcet, Timothée and Moutakanni, Theo and Vo, Huy V. and Szafraniec, Marc and Khalidov, Vasil and Fernandez, Pierre and Haziza, Daniel and Massa, Francisco and El-Nouby, Alaaeldin and Howes, Russell and Huang, Po-Yao and Xu, Hu and Sharma, Vasu and Li, Shang-Wen and Galuba, Wojciech and Rabbat, Mike and Assran, Mido and Ballas, Nicolas and Synnaeve, Gabriel and Misra, Ishan and Jegou, Herve and Mairal, Julien and Labatut, Patrick and Joulin, Armand and Bojanowski, Piotr},
      journal={arXiv:2304.07193},
      year={2023}
    }
    
    @misc{darcet2023vitneedreg,
      title={Vision Transformers Need Registers},
      author={Darcet, Timothée and Oquab, Maxime and Mairal, Julien and Bojanowski, Piotr},
      journal={arXiv:2309.16588},
      year={2023}
    }