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< h1 align = "center" > IOPaint< / h1 >
< p align = "center" > A free and open-source inpainting & outpainting tool powered by SOTA AI model.< / p >
< p align = "center" >
< a href = "https://github.com/Sanster/IOPaint" >
< img alt = "total download" src = "https://pepy.tech/badge/iopaint" / >
< / a >
< a href = "https://pypi.org/project/iopaint" >
< img alt = "version" src = "https://img.shields.io/pypi/v/iopaint" / >
< / a >
< a href = "" >
< img alt = "python version" src = "https://img.shields.io/pypi/pyversions/iopaint" / >
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< / p >
## Quick Start
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IOPaint provides a convenient webui for using the latest AI models to edit your images.
The installation process for IOPaint is also simple, requiring just two commands:
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```bash
# In order to use GPU, install cuda version of pytorch first.
# pip3 install torch==2.1.2 torchvision==0.16.2 --index-url https://download.pytorch.org/whl/cu118
pip3 install iopaint
iopaint start --model=lama --device=cpu --port=8080
```
That's it, you can start using IOPaint by visiting http://localhost:8080 in your web browser.
You can also use IOPaint in the command line to batch process images:
```bash
iopaint run --model=lama --device=cpu \
--input=/path/to/image_folder \
--mask=/path/to/mask_folder \
--output=output_dir
```
`--input` is the folder containing input images, `--mask` is the folder containing corresponding mask images.
When `--mask` is a path to a mask file, all images will be processed using this mask.
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You can see more information about the available models and plugins supported by IOPaint below.
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## Features
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- Completely free and open-source, fully self-hosted, support CPU & GPU & Apple Silicon
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- Supports various AI models:
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- Erase models: These models are usually used to remove people or objects from images.
- Stable Diffusion models: You can use any Stable Diffusion Inpainting(or normal) models from [Huggingface ](https://huggingface.co/models?other=stable-diffusion ) in IOPaint.
Some popular used models include:
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- [runwayml/stable-diffusion-inpainting ](https://huggingface.co/runwayml/stable-diffusion-inpainting )
- [diffusers/stable-diffusion-xl-1.0-inpainting-0.1 ](https://huggingface.co/diffusers/stable-diffusion-xl-1.0-inpainting-0.1 )
- [andregn/Realistic_Vision_V3.0-inpainting ](https://huggingface.co/andregn/Realistic_Vision_V3.0-inpainting )
- [Lykon/dreamshaper-8-inpainting ](https://huggingface.co/Lykon/dreamshaper-8-inpainting )
- [Sanster/anything-4.0-inpainting ](https://huggingface.co/Sanster/anything-4.0-inpainting )
- [Sanster/PowerPaint-V1-stable-diffusion-inpainting ](https://huggingface.co/Sanster/PowerPaint-V1-stable-diffusion-inpainting )
- Other Diffusion models:
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- [Sanster/AnyText ](https://huggingface.co/Sanster/AnyText )
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- [timbrooks/instruct-pix2pix ](https://huggingface.co/timbrooks/instruct-pix2pix )
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- [Fantasy-Studio/Paint-by-Example ](https://huggingface.co/Fantasy-Studio/Paint-by-Example )
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- [kandinsky-community/kandinsky-2-2-decoder-inpaint ](https://huggingface.co/kandinsky-community/kandinsky-2-2-decoder-inpaint )
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- [Plugins ](https://iopaint.com/plugins ):
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- [Segment Anything ](https://iopaint.com/plugins/interactive_seg ): Accurate and fast interactive object segmentation
- [RemoveBG ](https://iopaint.com/plugins/rembg ): Remove image background or generate masks for foreground objects
- [Anime Segmentation ](https://iopaint.com/plugins/anime_seg ): Similar to RemoveBG, the model is specifically trained for anime images.
- [RealESRGAN ](https://iopaint.com/plugins/RealESRGAN ): Super Resolution
- [GFPGAN ](https://iopaint.com/plugins/GFPGAN ): Face Restoration
- [RestoreFormer ](https://iopaint.com/plugins/RestoreFormer ): Face Restoration
- [FileManager ](https://iopaint.com/features/file_manager ): Browse your pictures conveniently and save them directly to the output directory.
- [Native macOS app ](https://opticlean.io/ ) for erase task
- More features at [IOPaint Docs ](https://iopaint.com/ )