• Support multiple model architectures
  1. LaMa
  2. LDM
• High resolution support
• Multi stroke support. Press and hold the cmd/ctrl key to enable multi stroke mode.
• Zoom & Pan
• Keep image EXIF data

1. Install requirements: pip3 install -r requirements.txt
2. Start server: python3 main.py, open http://localhost:8080

Available commands for main.py

Diffusion model(ldm) is MUCH MORE slower than GANs(lama)(1080x720 image takes 8s on 3090), but it's possible to get better result, see below example:

Original Image	LaMa	LDM

Blogs about diffusion models:

• https://lilianweng.github.io/posts/2021-07-11-diffusion-models/
• https://yang-song.github.io/blog/2021/score/

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

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

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.

docker build -f Dockerfile -t lamacleaner .

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

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