/ComfyUI_CustomNet

A CustomNet node for ComfyUI

Primary LanguagePythonApache License 2.0Apache-2.0

A CustomNet node for ComfyUI

A CustomNet node for ComfyUI

CustomNet: Object Customization with Variable-Viewpoints in Text-to-Image Diffusion Models. CustomNet From: CustomNet

Update

2024/08/11 --同步官方的内绘模型及代码,优化模型加载方式,现在模型跟常规的SD模型在一个地方,优化模型加载方式,

1.Installation

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

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

2.requirements

每个人的环境不同,但是carvekit-colab是必须装的,是内置的脱底工具包,懒得去掉了,你可以先用其他sam节点处理物体图。首次运行,会安装carvekit-colab的模型文件,无梯子的注意。
need carvekit-colab==4.1.0

3 Download the model

3.1 normal:
下载customnet_v1.pth模型,并放在ComfyUI/models/checkpoints/目录下:
Download the weights of Customnet “customnet_v1.pth” and put it to “ComfyUI/models/checkpoints/” link

└── ComfyUI/models/checkpoints/
    ├── customnet_v1.pth

3.2 inpainting:
下载customnet_inpaint_v1.pt模型,并放在ComfyUI/models/checkpoints/目录下:
Download the weights of Customnet “customnet_inpaint_v1.pt” and put it to “ComfyUI/models/checkpoints/” link

└── ComfyUI/models/checkpoints/
    ├── customnet_inpaint_v1.pt

3.3 clip and carvekit: 首次使用会下载3个的模型文件,须连外网:,分别是
clip:文件目录一般在C:/User/你的用户名/.cache/clip/ViT-L-14.pt
carvekit的2个脱底模型:
目录C:/User/你的用户名/.cache/carvekit/checkpoints/fba/fba_matting.pth
目录C:/User/你的用户名/.cache/carvekit/checkpoints/tracer_b7/tracer_b7.pth

6 Tips

---白底的物体图得到最好的效果; ---底模训练就是256的,所以没法做大图,除非腾讯把大图的模型放出来。
---The object image with a white background achieves the best effect;

5 Example

normal 常规脱底置于提示测的背景前面,最新的演示; Latest Presentation

inpainting 内绘模型,最新的演示; Latest Presentation

polar 主体上下视角 既往的演示, Previous demonstrations

zaimuth 主体左右视角 既往的演示, Previous demonstrations

position X0 Y0 主体在背景中的位置 既往的演示, Previous demonstrations

6 Citation

@misc{yuan2023customnet,
    title={CustomNet: Zero-shot Object Customization with Variable-Viewpoints in Text-to-Image Diffusion Models}, 
    author={Ziyang Yuan and Mingdeng Cao and Xintao Wang and Zhongang Qi and Chun Yuan and Ying Shan},
    year={2023},
    eprint={2310.19784},
    archivePrefix={arXiv},
    primaryClass={cs.CV}
}
}