80 lines
2.9 KiB
Markdown
80 lines
2.9 KiB
Markdown
<h1 align="center">Lama Cleaner</h1>
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<p align="center">A free and open-source inpainting tool powered by SOTA AI model.</p>
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<p align="center">
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<a href="https://github.com/Sanster/lama-cleaner">
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<img alt="total download" src="https://pepy.tech/badge/lama-cleaner" />
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</a>
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<a href="https://pypi.org/project/lama-cleaner/">
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<img alt="version" src="https://img.shields.io/pypi/v/lama-cleaner" />
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</a>
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<a href="https://colab.research.google.com/drive/1e3ZkAJxvkK3uzaTGu91N9TvI_Mahs0Wb?usp=sharing">
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<img alt="Open in Colab" src="https://colab.research.google.com/assets/colab-badge.svg" />
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</a>
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<a href="https://huggingface.co/spaces/Sanster/Lama-Cleaner-lama">
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<img alt="Hugging Face Spaces" src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue" />
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</a>
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<a href="">
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<img alt="python version" src="https://img.shields.io/pypi/pyversions/lama-cleaner" />
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</a>
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<a href="https://hub.docker.com/r/cwq1913/lama-cleaner">
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<img alt="version" src="https://img.shields.io/docker/pulls/cwq1913/lama-cleaner" />
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</a>
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</p>
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https://user-images.githubusercontent.com/3998421/196976498-ba1ad3ab-fa18-4c55-965f-5c6683141375.mp4
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## Sponsor
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<table>
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<tr>
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<td >
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<img src="./assets/GitHub_Copilot_logo.svg" style="background: white;padding: 8px;"/>
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</td>
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<td >
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<a href="https://ko-fi.com/Z8Z1CZJGY/tiers" target="_blank" >
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❤️ Your logo
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</a>
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</td>
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</tr>
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</table>
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## Features
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- Completely free and open-source, fully self-hosted, support CPU & GPU
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- [Windows 1-Click Installer](https://lama-cleaner-docs.vercel.app/install/windows_1click_installer)
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- Classical image inpainting algorithm powered by [cv2](https://docs.opencv.org/3.4/df/d3d/tutorial_py_inpainting.html)
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- Multiple SOTA AI [models](https://lama-cleaner-docs.vercel.app/models)
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- Various inpainting [strategy](https://lama-cleaner-docs.vercel.app/features/inpainting_strategy)
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- Run as a [desktop application](https://lama-cleaner-docs.vercel.app/features/desktop_app)
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- [Interactive Segmentation](https://lama-cleaner-docs.vercel.app/features/Interactive_segmentation) on any object.
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- More features at [lama-cleaner-docs](https://lama-cleaner-docs.vercel.app/)
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## Quick Start
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Lama Cleaner make it easy to use SOTA AI model in just two commands:
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```bash
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pip install lama-cleaner
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lama-cleaner --model=lama --device=cpu --port=8080
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```
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That's it, Lama Cleaner is now running at http://localhost:8080
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See all command line arguments at [lama-cleaner-docs](https://lama-cleaner-docs.vercel.app/install/pip)
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## Development
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Only needed if you plan to modify the frontend and recompile yourself.
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### Frontend
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Frontend code are modified from [cleanup.pictures](https://github.com/initml/cleanup.pictures), You can experience their
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great online services [here](https://cleanup.pictures/).
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- Install dependencies:`cd lama_cleaner/app/ && pnpm install`
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- Start development server: `pnpm start`
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- Build: `pnpm build`
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