55 lines
1.6 KiB
Markdown
55 lines
1.6 KiB
Markdown
# Lama-cleaner: Image inpainting tool powered by [LaMa](https://github.com/saic-mdal/lama)
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This project is mainly used for selfhosting LaMa model, some interaction improvements may be added later.
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https://user-images.githubusercontent.com/3998421/153323093-b664bb68-2928-480b-b59b-7c1ee24a4507.mp4
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- [x] High resolution support
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- [x] Multi stroke support. Press and hold the `cmd/ctrl` key to enable multi stroke mode.
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- [x] Zoom & Pan
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- [ ] Keep image EXIF data
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## Quick Start
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- Install requirements: `pip3 install -r requirements.txt`
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- Start server: `python3 main.py --device=cuda --port=8080`
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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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### Fronted
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Frontend code are modified from [cleanup.pictures](https://github.com/initml/cleanup.pictures),
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You can experience their great online services [here](https://cleanup.pictures/).
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- Install dependencies:`cd lama_cleaner/app/ && yarn`
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- Start development server: `yarn dev`
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- Build: `yarn build`
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## Docker
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Run within a Docker container. Set the `CACHE_DIR` to models location path.
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Optionally add a `-d` option to the `docker run` command below to run as a daemon.
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### Build Docker image
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```
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docker build -f Dockerfile -t lamacleaner .
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```
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### Run Docker (cpu)
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```
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docker run -p 8080:8080 -e CACHE_DIR=/app/models -v $(pwd)/models:/app/models -v $(pwd):/app --rm lamacleaner python3 main.py --device=cpu --port=8080
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```
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### Run Docker (gpu)
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```
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docker run --gpus all -p 8080:8080 -e CACHE_DIR=/app/models -v $(pwd)/models:/app/models -v $(pwd):/app --rm lamacleaner python3 main.py --device=cuda --port=8080
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```
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Then open [http://localhost:8080](http://localhost:8080)
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