nvidia clara+slicer3

server side:

ref. https://docs.nvidia.com/clara/tlt-mi/

get container

export workspace=/tmp/clara-experiments
mkdir -p $workspace
export dockerImage=nvcr.io/nvidia/clara-train-sdk:v3.1.01
docker pull $dockerImage
docker run --gpus=1 --shm-size=1G --ulimit memlock=-1 --ulimit stack=67108864 -it --rm -v $workspace:/workspace/clara-experiments $dockerImage /bin/bash

# check if container has `ngc` command.

ngc registry model list nvidia/med/*
MODEL_NAME=clara_mri_seg_brain_tumors_br16_full_amp
VERSION=1
ngc registry model download-version nvidia/med/$MODEL_NAME:$VERSION --dest /var/tmp

setup server

# https://docs.nvidia.com/clara/tlt-mi/aiaa/installation.html
export workspace=/tmp/clara-experiments
mkdir -p $workspace
export SOURCE_DIR=$workspace
export MOUNT_DIR=/aiaa-experiments
export LOCAL_PORT=80
export REMOTE_PORT=80
export DOCKER_IMAGE=nvcr.io/nvidia/clara-train-sdk:v3.1.01

docker run $OPTIONS --gpus=1 -it --rm \
       -p $LOCAL_PORT:$REMOTE_PORT \
       -v $SOURCE_DIR:$MOUNT_DIR \
       --ipc=host \
       $DOCKER_IMAGE \
       /bin/bash

# https://docs.nvidia.com/clara/tlt-mi/aiaa/quickstart.html
start_aas.sh --workspace /aiaa-experiments/aiaa-1

# https://docs.nvidia.com/clara/tlt-mi/aiaa/quickstart.html#monitor

docker exec -it into container to download models.

# https://docs.nvidia.com/clara/tlt-mi/nvmidl/installation.html#downloading-the-models
ngc registry model list nvidia/med/*
MODEL_NAME=clara_mri_seg_brain_tumors_br16_full_amp
VERSION=1
ngc registry model download-version nvidia/med/$MODEL_NAME:$VERSION --dest /var/tmp

# https://docs.nvidia.com/clara/tlt-mi/aiaa/loading_models.html


export LOCAL_PORT=80
curl -X PUT "http://127.0.0.1:$LOCAL_PORT/admin/model/clara_ct_seg_spleen_amp" \
     -H "accept: application/json" \
     -H "Content-Type: application/json" \
     -d '{"path":"nvidia/med/clara_ct_seg_spleen_amp","version":"1"}'

curl -X PUT "http://127.0.0.1:$LOCAL_PORT/admin/model/clara_mri_seg_brain_tumors_br16_full_amp" \
     -H "accept: application/json" \
     -H "Content-Type: application/json" \
     -d '{"path":"nvidia/med/clara_mri_seg_brain_tumors_br16_full_amp","version":"1"}'

curl -X PUT "http://127.0.0.1:$LOCAL_PORT/admin/model/clara_mri_annotation_brain_tumors_t1ce_tc_amp" \
     -H "accept: application/json" \
     -H "Content-Type: application/json" \
     -d '{"path":"nvidia/med/clara_mri_annotation_brain_tumors_t1ce_tc_amp","version":"1"}'

client side:

ref. https://github.com/NVIDIA/ai-assisted-annotation-client/blob/master/slicer-plugin/README.md

go to https://download.slicer.org and download tar.gz
tar -xvf Slicer-4.11.20210226-linux-amd64.tar.gz
cd Slicer-4.11.20210226-linux-amd64
./Slicer
follow "Tutorials and examples" section in below link
remember to install  Nvidia AIAA extension and ** restart slicer **.
input `http://server-ip:port` in AIAA settings.

https://github.com/NVIDIA/ai-assisted-annotation-client/blob/master/slicer-plugin/README.md

pangyuteng/README.md