Integrate TM Docker plug-in changes to enable passing UID:GID as argu…

…ment.

- add new liver tumor 2.0 sample

Signed-off-by: Victor Chang <[email protected]>

deploy/monai-deploy-express/.env

@@ -1,13 +1,13 @@
 # Container Images
 INFORMATICS_GATEWAY_IMAGE=ghcr.io/project-monai/monai-deploy-informatics-gateway:0.4.1
 INFORMATICS_GATEWAY_CONFIG_IMAGE=dwdraju/alpine-curl-jq:latest
-WORKFLOW_MANAGER_IMAGE=ghcr.io/project-monai/monai-deploy-workflow-manager:2023.5.0-beta.185 
-TASK_MANAGER_IMAGE=ghcr.io/project-monai/monai-deploy-task-manager:2023.5.0-beta.185 
+WORKFLOW_MANAGER_IMAGE=ghcr.io/project-monai/monai-deploy-workflow-manager:2023.5.0-beta.238
+TASK_MANAGER_IMAGE=ghcr.io/project-monai/monai-deploy-task-manager:2023.5.0-beta.238 
 
 MINIO_IMAGE=minio/minio:latest
 MONGODB_IMAGE=mongo:5.0.12
-ORTHANC_IMAGE=osimis/orthanc:23.3.4
-RABBITMQ_IMAGE=rabbitmq:3.11-management
+ORTHANC_IMAGE=osimis/orthanc:23.9.2-full
+RABBITMQ_IMAGE=rabbitmq:3.12.7-management
 
 ELK_VERSION=8.7.0
 ELASTICSEARCH_IMAGE=docker.elastic.co/elasticsearch/elasticsearch:${ELK_VERSION}

deploy/monai-deploy-express/README.md

@@ -99,7 +99,7 @@ The first time calling `docker compose up` may take longer as it needs to pull a
 
 - The following error indicates that the `docker compose` version may not be up-to-date. If the problem persists, modify the `TASK_MANAGER_DATA` variable defined in the `.env` file and change `$PWD/.md/mdtm` to a fully qualified path. E.g. `/home/monai/some/path/to/.md/mdtm/`.
     ```
-    ERROR: Named volume "$PWD/.md/mdtm:/var/lib/monai:rw" is used in service "task-manager" but no declaration was found in the volumes section. 
+    ERROR: Named volume "$PWD/.md/mdtm:/var/lib/mde:rw" is used in service "task-manager" but no declaration was found in the volumes section. 
     ```
 
     *WHY? The value of `TASK_MANAGER_DATA` is exposed to the Task Manager container as an environment variable in order for Task Manager to map the volume from the host to the MAP container correctly.*
@@ -112,7 +112,7 @@ The first time calling `docker compose up` may take longer as it needs to pull a
 
   - If you start Monai Deploy Express from within a container, you are likely to have problems when starting the system with 'docker compose up', such as:
     ```
-    ERROR: Named volume "$PWD/.md/mdtm:/var/lib/monai:rw" is used in service "task-manager" but no declaration was found in the volumes section. 
+    ERROR: Named volume "$PWD/.md/mdtm:/var/lib/mde:rw" is used in service "task-manager" but no declaration was found in the volumes section. 
     ```
 
 - If you start Monai Deploy Express from within a container, you are likely to have problems when starting the system with 'docker compose up', such as:
@@ -156,6 +156,7 @@ The **sample-workflows** directory includes the following four sample workflow d
 - `lung-seg.json`: AI Lung Segmentation MAP
 - `liver-seg.json`: AI Liver Segmentation MAP
 - `liver-lung-seg.json`: AI Lung & AI Liver Combo
+- `liver-tumor.json`: AI Liver Tumor 2.0 MAP (MONAI Deploy 0.6)
 
 *Note: in these examples, we will be using `curl` command to register MONAI Deploy workflow definitions with the Workflow Manager. To learn more about `curl`, visit the [curl Man Page](https://curl.se/docs/manpage.html).*
 
@@ -193,7 +194,7 @@ This example uses the `alpine` container image instead of a MAP to print all fil
 
 #### Description
 
-In this section, we will download a DICOM dataset, upload it to Orthanc and then run the [Liver Segmentation MAP](https://github.com/Project-MONAI/monai-deploy-app-sdk/tree/main/examples/apps/ai_livertumor_seg_app) from the
+In this section, we will download a DICOM dataset, upload it to Orthanc and then run the [Liver Segmentation MAP](https://github.com/Project-MONAI/monai-deploy-app-sdk/tree/0.5.1/examples/apps/ai_livertumor_seg_app) from the
 [MONAI Deploy App SDK](https://github.com/Project-MONAI/monai-deploy-app-sdk). Finally, we can expect the AI-generated segmentation result to appear in Orthanc.
 
 
@@ -300,6 +301,45 @@ In the `liver-lung-seg.json` workflow definition, we combined the AI Lung MAP an
 
 In this example, the [Chest CT dataset](https://drive.google.com/file/d/1IGXUgZ7NQCwsix57cdSgr-iYErevqETO/view?usp=sharing) should only launch the AI Lung MAP, while the [Abdomen CT dataset](https://drive.google.com/file/d/1d8Scm3q-kHTqr_-KfnXH0rPnCgKld2Iy/view?usp=sharing) would launch the AI Liver MAP.
 
+### AI Liver Tumor 2.0 MAP
+
+#### Description
+
+In this section, we will download a DICOM dataset, upload it to Orthanc and then run the [Liver Segmentation MAP](https://github.com/Project-MONAI/monai-deploy-app-sdk/tree/0.6.0/examples/apps/ai_livertumor_seg_app) from the
+[MONAI Deploy App SDK](https://github.com/Project-MONAI/monai-deploy-app-sdk). Finally, we can expect the AI-generated segmentation result to appear in Orthanc.
+
+
+#### Steps
+
+1. Download the [Abdomen CT dataset](#running-a-monai-deploy-workflow) dataset
+2. Download the AI Liver Tumor 2.0 MAP
+   ```bash
+   docker pull ghcr.io/mmelqin/monai_ai_livertumor_seg_app_stl-x64-workstation-dgpu-linux-amd64:2.0
+   ```
+3. Upload the dataset as described in [Uploading Data](#upload-dicom-datasets)
+4. Deploy the workflow definition to MONAI Deploy Workflow Manager:
+5. 
+   ```bash
+   curl --request POST --header 'Content-Type: application/json'  --data "@sample-workflows/liver-tumor.json"  http://localhost:5001/workflows
+   ```
+
+   If the `curl` command runs successfully, expect a `workflow_id` to be returned and printed to the terminal:
+
+   ```
+   {"workflow_id":"811620da-381f-4daa-854d-600948e67228"}
+   ```
+   
+6. Navigate to Orthanc, select any study and then click *Send to DICOM Modality* from the menu on the left.
+   In the popup dialog, select **MONAI-DEPLOY** to start a C-STORE request to the Informatics Gateway.
+7. Wait for the workflow to complete; the entire workflow takes roughly one minute and thirty seconds to complete. To see the AI-generated segmentation object, reload the Orthanc study page.
+8. To see the output of the container, run the following commands:
+   ```bash
+   > docker container list -a | grep monai_ai_livertumor_seg_app_stl
+   # locate the container ID and run the following
+   > docker logs {CONTAINER ID}
+   ```
+
+
 ## Using Kibana
 
 A default dataview is imported to Kibana at startup. To load the saved search, navigate to http://localhost:5601/, click on Analytics > Discover from the 🍔 menu. From the top right click *Open* and select *MONAI-Default*.
@@ -416,7 +456,7 @@ A MONAI Deploy [workflow definition](https://github.com/Project-MONAI/monai-depl
                 "entrypoint": "/bin/bash,-c", # entrypoint of your container image; separated by commas
                 "command": "python3 -u /opt/monai/app/app.py", # commands to execute with the container image; separated by commas
                 "task_timeout_minutes": "5", # how long this task is expected to execute; terminated after the configured value
-                "temp_storage_container_path": "/var/lib/monai/", # how thd Docker plug-in maps your data from host to container - this is mapped to `$TASK_MANAGER_DATA` in the docker-compose file 
+                "temp_storage_container_path": "/var/lib/mde/", # how thd Docker plug-in maps your data from host to container - this is mapped to `$TASK_MANAGER_DATA` in the docker-compose file 
                 "env_MONAI_INPUTPATH": "/var/monai/input/", # an environment varible provided to the container to read the input data
                 "env_MONAI_OUTPUTPATH": "/var/monai/output/", # an environment variable provided to the container to write AI-genrated results
                 "env_MONAI_MODELPATH": "/opt/monai/models/", # an environment variable provided to the container to located AI models

deploy/monai-deploy-express/docker-compose.yml

@@ -209,7 +209,7 @@ services:
     container_name: $TASK_MANAGER_CONTAINERNAME
     volumes:
       - ./configs/task-manager.json:/opt/monai/wm/appsettings.json
-      - $TASK_MANAGER_DATA:/var/lib/monai/:rw
+      - $TASK_MANAGER_DATA:/var/lib/mde/:rw
       - /var/run/docker.sock:/var/run/docker.sock
       # - $MONAI_DEPLOY_PLUGINS:/opt/monai/wm/plug-ins/
     environment:

deploy/monai-deploy-express/init.sh

@@ -18,6 +18,13 @@ RUNDIR=$PWD/.md
 echo "Initializing directories..."
 [ -d $RUNDIR ] && echo "Removing existin $RUNDIR" && sudo rm -r $RUNDIR
 mkdir -p $RUNDIR/esdata/ && echo "Created $RUNDIR/"
+mkdir -p $RUNDIR/minio/ && echo "Created $RUNDIR/minio/"
+mkdir -p $RUNDIR/rabbitmq/ && echo "Created $RUNDIR/rabbitmq/"
+mkdir -p $RUNDIR/orthanc/ && echo "Created $RUNDIR/orthanc/"
+mkdir -p $RUNDIR/mongodb/ && echo "Created $RUNDIR/mongodb/"
+mkdir -p $RUNDIR/mdwm/ && echo "Created $RUNDIR/mdwm/"
+mkdir -p $RUNDIR/mdtm/ && echo "Created $RUNDIR/mdtm/"
+mkdir -p $RUNDIR/mdig/ && echo "Created $RUNDIR/mdig/"
 sudo chown 1000:1000 -R $RUNDIR/esdata && echo "Permission updated"
 echo "Directories setup"
 echo "Ready to run docker compose up"

deploy/monai-deploy-express/sample-workflows/hello-world.json

@@ -21,7 +21,7 @@
 				"server_url": "unix:///var/run/docker.sock",
 				"entrypoint": "/bin/sh,-c",
 				"command": "/usr/bin/find /var/monai/input -type f",
-				"temp_storage_container_path": "/var/lib/monai/",
+				"temp_storage_container_path": "/var/lib/mde/",
 				"MYINPUT": "/var/monai/input/"
 			},
 			"artifacts": {

deploy/monai-deploy-express/sample-workflows/liver-lung-seg.json

@@ -37,7 +37,7 @@
 				"entrypoint": "/bin/bash,-c",
 				"command": "python3 -u /opt/monai/app/app.py",
 				"task_timeout_minutes": "5",
-				"temp_storage_container_path": "/var/lib/monai/",
+				"temp_storage_container_path": "/var/lib/mde/",
 				"env_MONAI_INPUTPATH": "/var/monai/input/",
 				"env_MONAI_OUTPUTPATH": "/var/monai/output/",
 				"env_MONAI_MODELPATH": "/opt/monai/models/",
@@ -93,7 +93,7 @@
 				"entrypoint": "/bin/bash,-c",
 				"command": "python3 -u /opt/monai/app/app.py",
 				"task_timeout_minutes": "5",
-				"temp_storage_container_path": "/var/lib/monai/",
+				"temp_storage_container_path": "/var/lib/mde/",
 				"env_MONAI_INPUTPATH": "/var/monai/input/",
 				"env_MONAI_OUTPUTPATH": "/var/monai/output/",
 				"env_MONAI_MODELPATH": "/opt/monai/models/",

deploy/monai-deploy-express/sample-workflows/liver-seg.json

@@ -33,7 +33,7 @@
 				"entrypoint": "/bin/bash,-c",
 				"command": "python3 -u /opt/monai/app/app.py",
 				"task_timeout_minutes": "5",
-				"temp_storage_container_path": "/var/lib/monai/",
+				"temp_storage_container_path": "/var/lib/mde/",
 				"env_MONAI_INPUTPATH": "/var/monai/input/",
 				"env_MONAI_OUTPUTPATH": "/var/monai/output/",
 				"env_MONAI_MODELPATH": "/opt/monai/models/",

deploy/monai-deploy-express/sample-workflows/liver-tumor.json

@@ -0,0 +1,84 @@
+{
+	"name": "ai-liver-seg",
+	"version": "1.0.0",
+	"description": "AI Liver Tumor 2.0",
+	"informatics_gateway": {
+		"ae_title": "MONAI-DEPLOY",
+		"data_origins": [
+			"ORTHANC"
+		],
+		"export_destinations": [
+			"ORTHANC"
+		]
+	},
+	"tasks": [
+		{
+			"id": "router",
+			"description": "Ensure series description contains liver",
+			"type": "router",
+			"task_destinations": [
+				{
+					"name": "liver",
+					"conditions": ["{{ context.dicom.series.any('0008','103E')}} == 'CT series for liver tumor from nii 014'"]
+				}
+			]
+		},
+		{
+			"id": "liver",
+			"description": "Execute Liver Segmentation MAP",
+			"type": "docker",
+			"args": {
+				"container_image": "ghcr.io/mmelqin/monai_ai_livertumor_seg_app_stl-x64-workstation-dgpu-linux-amd64:2.0",
+				"server_url": "unix:///var/run/docker.sock",
+				"user": "1000:1000",
+				"entrypoint": "/bin/bash,-c",
+				"command": "python3 -u /opt/holoscan/app/",
+				"task_timeout_minutes": "5",
+				"temp_storage_container_path": "/var/lib/mde/",
+				"env_HOLOSCAN_INPUT_PATH": "/var/holoscan/input/",
+				"env_HOLOSCAN_OUTPUT_PATH": "/var/holoscan/output/",
+				"env_HOLOSCAN_MODEL_PATH": "/opt/holoscan/models/",
+				"env_HOLOSCAN_WORKDIR": "/var/holoscan/"
+			},
+			"artifacts": {
+				"input": [
+					{
+						"name": "env_HOLOSCAN_INPUT_PATH",
+						"value": "{{ context.input.dicom }}"
+					}
+				],
+				"output": [
+					{
+						"name": "env_HOLOSCAN_OUTPUT_PATH",
+						"mandatory": true
+					}
+				]
+			},
+			"task_destinations": [
+				{
+					"name": "export-liver-seg"
+				}
+			]
+		},
+		{
+			"id": "export-liver-seg",
+			"description": "Export Segmentation Storage Object",
+			"type": "export",
+			"export_destinations": [
+				{
+					"Name": "ORTHANC"
+				}
+			],
+			"artifacts": {
+				"input": [
+					{
+						"name": "export-dicom",
+						"value": "{{ context.executions.liver.artifacts.env_HOLOSCAN_OUTPUT_PATH }}",
+						"mandatory": true
+					}
+				],
+				"output": []
+			}
+		}
+	]
+}

deploy/monai-deploy-express/sample-workflows/lung-seg.json

@@ -33,7 +33,7 @@
 				"entrypoint": "/bin/bash,-c",
 				"command": "python3 -u /opt/monai/app/app.py",
 				"task_timeout_minutes": "5",
-				"temp_storage_container_path": "/var/lib/monai/",
+				"temp_storage_container_path": "/var/lib/mde/",
 				"env_MONAI_INPUTPATH": "/var/monai/input/",
 				"env_MONAI_OUTPUTPATH": "/var/monai/output/",
 				"env_MONAI_MODELPATH": "/opt/monai/models/",