README.md

Running with TorchServe

Create a virtual environment

python -m venv .venv
source .venv/bin/activate

Install dependencies

pip install -r seggpt_requirements.txt

Build and deploy the model

./create_mar.sh
./serve.sh

In another terminal session, send a request

python request.py --input_dir {directory of input images} --prompt_dir {directory of prompt images} --target_dir {directory of target images} --output_dir {desired output directory}

Running with dockerized TorchServe

Build the TorchServe docker image

docker build -t seggpt-ts:latest .

Run the docker container

docker run --rm --name seggpt -p 127.0.0.1:8080:8080 -p 127.0.0.1:8081:8081 seggpt-ts:latest

Send a request

python request.py --input_dir {directory of input images} --prompt_dir {directory of prompt images} --target_dir {directory of target images} --output_dir {desired output directory}