Lama-cleaner: Image inpainting tool powered by LaMa

This project is mainly used for selfhosting LaMa model, some interaction improvements may be added later.

https://user-images.githubusercontent.com/3998421/153323093-b664bb68-2928-480b-b59b-7c1ee24a4507.mp4

High resolution support
Multi stroke support. Press and hold the cmd/ctrl key to enable multi stroke mode.
Zoom & Pan
Keep image EXIF data

Quick Start

Install requirements: pip3 install -r requirements.txt
Start server: python3 main.py --device=cuda --port=8080

Development

Only needed if you plan to modify the frontend and recompile yourself.

Fronted

Frontend code are modified from cleanup.pictures, You can experience their great online services here.

Install dependencies:cd lama_cleaner/app/ && yarn
Start development server: yarn dev
Build: yarn build

Docker

Run within a Docker container. Set the CACHE_DIR to models location path. Optionally add a -d option to the docker run command below to run as a daemon.

Build Docker image

docker build -f Dockerfile -t lamacleaner .

Run Docker (cpu)

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

Run Docker (gpu)

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

Then open http://localhost:8080

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