58 lines
2.6 KiB
Markdown
58 lines
2.6 KiB
Markdown
# ComfyUI_ObjectClear
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[ObjectClear](https://github.com/zjx0101/ObjectClear):Complete Object Removal via Object-Effect Attention,you can try it in ComfyUI
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# New
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* 此方法优势在于内绘不仅限于主体，比如去除物体，物体的影子也会去掉，表现优异。
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# 1 . Installation /安装
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In the ./ComfyUI /custom_node/ directory, run the following:
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```
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git clone https://github.com/smthemex/ComfyUI_ObjectClear.git
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```
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---
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# 2 . Requirements
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* 通常不需要安装，因为没什么特别的库
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```
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pip install -r requirements.txt
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```
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# 3 . Model/模型
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* [jixin0101/ObjectClear](https://huggingface.co/jixin0101/ObjectClear/tree/main) download files as below /下载下方列出的模型:
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```
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├── your comfyUI path/models/checkpoints/
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| ├──diffusion_pytorch_model.safetensors # unet dir/ 目录，rename or not 重命名或者随你，可以下fp16的
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├── your comfyUI path/models/vae/
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| ├──diffusion_pytorch_model.safetensors # vae dir/目录，rename or not 重命名或者随你
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├── models/clip_vision/
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| ├── diffusion_pytorch_model.safetensors # image_prompt_encoder 目录，其实就是这个： clip-vit-large-patch14.safetensors
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├── models/clip/
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| ├── model.safetensors # postfuse_module dir /目录 rename or not 重命名或者随你 ，可以下fp16
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| ├── clip_l.safetensors # normal comfyUI clip 常规comfy的clip
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| ├── clip_g.safetensors # normal comfyUI clip 常规comfy的clip
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```
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* seg /遮罩没有内置，随便用其他的吧。
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# 4 . Example
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# 5 .Tips/使用说明
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* 支持单图或多图，遮罩合并用插件带的batch节点，512是垫图最小短边尺寸（会自动裁切），模型用512*512训练的，按理此尺寸是最好的。
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* Support single or multiple images, use batch nodes with plugins for mask merging, 512 is the input image ‘s minimum short edge size, and the model is trained with 512 * 512, which is theoretically the best size.
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# 6. Citation
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```
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@InProceedings{zhao2025ObjectClear,
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title = {{ObjectClear}: Complete Object Removal via Object-Effect Attention},
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author = {Zhao, Jixin and Zhou, Shangchen and Wang, Zhouxia and Yang, Peiqing and Loy, Chen Change},
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booktitle = {arXiv preprint arXiv:2505.22636},
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year = {2025}
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}
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```
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