NVIDIA Docs Hub NVIDIA Holoscan NVIDIA Clara Deploy SDK User Guide

1. Introduction
- 1.1. Architecture
2. Installation
- 2.1. System Requirements
- 2.2. Ansible Installation
  - 2.2.1. Steps to Install
- 2.3. Verify Installation
- 2.4. Installation on a Cloud Service Provider (CSP)
- 2.5. Installing Clara in a system protected by a firewall
3. Uninstallation
- 3.1. Steps to uninstall Clara
4. Clara Administration
- 4.1. Configuration
- 4.2. Start/Stop/Restart the platform
  - 4.2.1. Restarting the Operating System
- 4.3. Network Configuration
- 4.4. AI models for TensorRT Inference Server
- 4.5. Key Commands
5. Core Concepts
- 5.1. Directed Acyclic Graph (DAG)
- 5.2. Data Source
- 5.3. Operator
- 5.4. Pipeline
- 5.5. Service
- 5.6. Job
- 5.7. Triggering a Pipeline
- 5.8. Data Sink
6. How to Run a Reference Pipeline
- 6.1. Select a Reference Pipeline
- 6.2. Run Reference Pipelines by Sending DICOM Instances Over Network
- 6.3. Run Reference Pipelines using Local Input Files
7. How to Run a Reference Pipeline using Model Repository
- 7.1. Select a Reference Pipeline
- 7.2. Run Reference Pipelines by Sending DICOM Instances Over Network
8. Clara Pipeline Driver API
- 8.1. Clara Pipeline Driver Overview
- 8.2. Clara Pipeline Callbacks
- 8.3. Clara Pipeline Driver
- 8.4. NVIDIA Clara Pipeline Driver Guidance
- 8.5. Clara Pipeline Fast I/O Allocations
- 8.6. Clara Pipeline Fast I/O Context
- 8.7. Clara Pipeline Fast I/O Entries
- 8.8. Clara Pipeline Payload
- 8.9. Clara Pipeline Payload Entry
  - 8.9.1. Name
  - 8.9.2. Path
- 8.10. Clara Pipeline Driver Callbacks
- 8.11. Clara Pipeline Fast I/O Allocations
- 8.12. Clara Pipeline Fast I/O Context
- 8.13. Clara Pipeline FastIO Entry
- 8.14. Pipeline Stage Payload
- 8.15. Pipeline Payload Entry
  - 8.15.1. Name
  - 8.15.2. Path
- 8.16. Clara Pipeline Callbacks
- 8.17. Clara Pipeline Driver
  - 8.17.1. Clara Operator Life-Cycle
- 8.18. Clara Pipeline Payload
  - 8.18.1. Input Entries
  - 8.18.2. Output Entries
- 8.19. Clara Pipeline Payload Entry
  - 8.19.1. Name
  - 8.19.2. Path
9. Pipeline Definition Language
- 9.1. Clara Pipeline Definition Language Overview
  - 9.1.1. Features
- 9.2. Clara Deploy SDK Pipeline Glossary
  - 9.2.1. Clara Deploy SDK PLatform
  - 9.2.2. Container
  - 9.2.3. Containerized Application
  - 9.2.4. Directed Acyclic Graph (DAG)
  - 9.2.5. Payload
  - 9.2.6. Pipeline
  - 9.2.7. Pipeline Application
  - 9.2.8. Pipeline Job
  - 9.2.9. Operator
  - 9.2.10. Service
- 9.3. Operators
- api-version 0.7.0
- api-version 0.5.0
- 9.6. The Anatomy of an Operator
  - 9.6.1. Disk-based I/O
  - 9.6.2. Shared Memory I/O
- 9.7. Argo vs. Clara Orchestration
- 9.8. Pipelines
  - 9.8.1. A simple pipeline example
  - 9.8.2. Pipelines with Untyped Operators
  - 9.8.3. Pipelines with Typed Operators for Performance and Explicit Data Typing
    - 9.8.3.1. Implicit Semantics, Explicit Types
    - 9.8.3.2. Operator Reuse Across Pipelines
  - 9.8.4. Pipelines with Operators in Private Registries
    - ngc-clara
    - 9.8.4.2. Custom Docker Registry Secrets
- 9.9. Services
- 9.10. Connections
  - 9.10.1. Properties
    - 9.10.1.1. http
- 9.11. Container
  - 9.11.1. Properties
- 9.12. Document
  - 9.12.1. Properties
- 9.13. Import
  - 9.13.1. Properties
    - 9.13.1.1. path
    - 9.13.1.2. args
  - 9.13.2. Overriding Values on Import
    - 9.13.2.1. Example
- 9.14. Input
  - 9.14.1. Properties
- 9.15. Operator
  - 9.15.1. Properties
- 9.16. Output
  - 9.16.1. Properties
- 9.17. Pipeline
  - 9.17.1. Properties
- 9.18. Requests
  - 9.18.1. Properties
- 9.19. Service
  - 9.19.1. Properties
- 9.20. Syntax & Grammar
  - 9.20.1. YAML Basics
  - 9.20.2. Operator Definitions
  - 9.20.3. Service Definitions
- 9.21. Template
  - 9.21.1. Properties
    - 9.21.1.1. parameters
    - 9.21.1.2. Example:
  - 9.21.2. Placeholders
- 9.22. Clara Structures and Primitives
  - 9.22.1. Clara Structures
  - 9.22.2. Clara Primitive Types
  - 9.22.3. Examples of Valid Declarations
- 9.23. Variables
10. Bundled Operators
- 10.1. Clara DICOM Reader
  - 10.1.1. Requirements
  - 10.1.2. Running the DICOM Reader
- 10.2. Clara DICOM Writer
  - 10.2.1. Requirements
  - 10.2.2. Running the DICOM Writer
- 10.3. Clara Deploy DICOM Parser Operator
  - 10.3.1. Overview
  - 10.3.2. Inputs
  - 10.3.3. Outputs
  - 10.3.4. Directory Structure
  - 10.3.5. Parameters
  - 10.3.6. Executing Operator Locally
  - 10.3.7. Executing Operator in Docker
  - 10.3.8. License
  - 10.3.9. Suggested Reading
- 10.4. Clara Deploy Base Inference Operator V2
  - 10.4.1. Overview
    - 10.4.1.1. Version information
  - 10.4.2. Inputs
  - 10.4.3. Outputs
  - 10.4.4. Environment Variables
  - 10.4.5. AI Model
    - 10.4.5.1. NVIDIA Triton Inference Server
  - 10.4.6. Directory Structure
  - 10.4.7. Executing Operator as Docker Container
  - 10.4.8. Executing Operator Docker Container Interactively
  - 10.4.9. Creating Model Specific Application
    - 10.4.9.1. Prerequisites
    - 10.4.9.2. Steps
  - 10.4.10. License
  - 10.4.11. Suggested Reading
- 10.5. Clara AI Liver Tumor Segmentation Operator
  - 10.5.1. Overview
  - 10.5.2. Inputs
  - 10.5.3. Outputs
  - 10.5.4. AI Model
    - 10.5.4.1. NVIDIA TensorRT Inference Server (TRTIS)
  - 10.5.5. Directory Structure
  - 10.5.6. Executing Operator as Docker Container
  - 10.5.7. Executing Operator Docker Container Interactively
- 10.6. Clara Deploy SDK VNet Segmentation Operator
  - 10.6.1. Overview
  - 10.6.2. Data Input
  - 10.6.3. Data Output
  - 10.6.4. Parameters
  - 10.6.5. Dependencies
  - 10.6.6. Execution of VNet Segmentation Operator
- 10.7. Clara AI Brain Tumor Segmentation Operator
  - 10.7.1. Overview
  - 10.7.2. Inputs
  - 10.7.3. Outputs
  - 10.7.4. AI Model
    - 10.7.4.1. NVIDIA TensorRT Inference Server (TRTIS)
  - 10.7.5. Directory Structure
  - 10.7.6. Executing Operator Locally
  - 10.7.7. Executing Operator in Docker
- 10.8. Clara AI Hippocampus Segmentation Operator
  - 10.8.1. Overview
  - 10.8.2. Inputs
  - 10.8.3. Outputs
  - 10.8.4. AI Model
    - 10.8.4.1. NVIDIA TensorRT Inference Server (TRTIS)
  - 10.8.5. Directory Structure
  - 10.8.6. Executing Operator Locally
  - 10.8.7. Executing Operator in Docker
- 10.9. Clara AI Spleen Segmentation
  - 10.9.1. Overview
  - 10.9.2. Inputs
  - 10.9.3. Outputs
  - 10.9.4. AI Model
    - 10.9.4.1. NVIDIA Triton Inference Server
  - 10.9.5. Directory Structure
  - 10.9.6. Executing Operator as Docker Container
  - 10.9.7. Executing Operator Docker Container Interactively
- 10.10. Malaria Microscopy Classification Operator
  - 10.10.1. Overview
  - 10.10.2. Inputs
  - 10.10.3. Outputs
  - 10.10.4. AI Model
    - 10.10.4.1. NVIDIA TensorRT Inference Server (TRTIS)
  - 10.10.5. Directory Structure
  - 10.10.6. Executing the Operator Locally
  - 10.10.7. Executing the Operator in Docker
- 10.11. Clara AI Lung Tumor Segmentation Operator
  - 10.11.1. Overview
  - 10.11.2. Inputs
  - 10.11.3. Outputs
  - 10.11.4. AI Model
    - 10.11.4.1. NVIDIA Triton Inference Server
  - 10.11.5. Directory Structure
  - 10.11.6. Executing Operator as Docker Container
  - 10.11.7. Executing Operator Docker Container Interactively
- 10.12. Colon Tumor Segmentation Operator
  - 10.12.1. Overview
  - 10.12.2. Inputs
  - 10.12.3. Outputs
  - 10.12.4. AI Model
    - 10.12.4.1. NVIDIA Triton Inference Server
  - 10.12.5. Directory Structure
  - 10.12.6. Executing Operator as Docker Container
  - 10.12.7. Executing Operator Docker Container Interactively
- 10.13. Clara AI Pancreas Tumor Segmentation
  - 10.13.1. Overview
  - 10.13.2. Inputs
  - 10.13.3. Outputs
  - 10.13.4. AI Model
    - 10.13.4.1. NVIDIA Triton Inference Server (formerly known as TRTIS)
  - 10.13.5. Directory Structure
  - 10.13.6. Executing Operator as Docker Container
  - 10.13.7. Executing Operator Docker Container Interactively
- 10.14. Chest X-ray Classification Operator
  - 10.14.1. Overview
  - 10.14.2. Inputs
  - 10.14.3. Outputs
  - 10.14.4. AI Model
    - 10.14.4.1. NVIDIA TensorRT Inference Server (TRTIS)
  - 10.14.5. Directory Structure
  - 10.14.6. Executing Operator Locally
  - 10.14.7. Executing Operator in Docker
- 10.15. Breast Microscopy Classification Operator
  - 10.15.1. Overview
  - 10.15.2. Inputs
  - 10.15.3. Outputs
  - 10.15.4. AI Model
    - 10.15.4.1. NVIDIA TensorRT Inference Server (TRTIS)
  - 10.15.5. Directory Structure
  - 10.15.6. Executing the Operator Locally
  - 10.15.7. Executing the Operator in Docker
- 10.16. Clara AI Prostate Segmentation
  - 10.16.1. Overview
  - 10.16.2. Inputs
  - 10.16.3. Outputs
  - 10.16.4. AI Model
    - 10.16.4.1. NVIDIA Triton Inference Server
  - 10.16.5. Directory Structure
  - 10.16.6. Executing Operator as Docker Container
  - 10.16.7. Executing Operator Docker Container Interactively
- 10.17. CT Recon Operator
  - 10.17.1. Overview
  - 10.17.2. Data Input
  - 10.17.3. Data Output
  - 10.17.4. Parameters
  - 10.17.5. Dependencies
  - 10.17.6. Directory Structure
  - 10.17.7. Optimization
- 10.18. Clara Register Results
  - 10.18.1. Requirements/Dependencies
  - 10.18.2. Source Code & Pipeline Example
  - 10.18.3. Inputs
  - 10.18.4. Outputs
  - 10.18.5. Directory Structure
  - 10.18.6. Executing the Operator Within a Container
    - 10.18.6.1. Steps
    - 10.18.6.2. Example
- 10.19. Clara Genomics Analysis
  - 10.19.1. Overview
    - 10.19.1.1. Components in the toolset:
      - 10.19.1.1.1. cudamapper
      - 10.19.1.1.2. racon
    - 10.19.1.2. 3rd party tools:
      - 10.19.1.2.1. minimap2
      - 10.19.1.2.2. miniasm
  - 10.19.2. Directory Structure
- 10.20. FastIO-ITK Operator
  - 10.20.1. Overview
  - 10.20.2. Commands
- 10.21. DICOM RTSTRUCT Writer Operator
  - 10.21.1. Overview
  - 10.21.2. Inputs
  - 10.21.3. Outputs
  - 10.21.4. Environment Variables
  - 10.21.5. Directory Structure
  - 10.21.6. Executing the Operator Locally
  - 10.21.7. Executing Operator in Docker
  - 10.21.8. License
  - 10.21.9. Suggested Reading
- 10.22. Clara FastIO Variable Passthrough - Nifti to FastIO Variable Conveter Operator
  - 10.22.1. Overview
  - 10.22.2. Inputs
  - 10.22.3. Outputs
  - 10.22.4. Directory Structure
  - 10.22.5. License
  - 10.22.6. Suggested Reading
- 10.23. Clara FastIO Variable Passthrough - Fastio to Npz Converter Operator
  - 10.23.1. Overview
  - 10.23.2. Inputs
  - 10.23.3. Outputs
  - 10.23.4. Directory Structure
  - 10.23.5. License
  - 10.23.6. Suggested Reading
- 10.24. Clara FastIO Variable Passthrough - Compare Operator
  - 10.24.1. Overview
  - 10.24.2. Inputs
  - 10.24.3. Outputs
  - 10.24.4. Directory Structure
  - 10.24.5. License
  - 10.24.6. Suggested Reading
- 10.25. DeepStream App Operator
  - 10.25.1. Quick Start
  - 10.25.2. Inputs & Outputs
  - 10.25.3. Sample AI model (Organ Object Detector)
- 10.26. Digital Pathology Image Processing Operator
  - 10.26.1. Overview
  - 10.26.2. Commands
- 10.27. Clara Deploy AI Lung Segmentation Operator
  - 10.27.1. Overview
  - 10.27.2. Inputs
  - 10.27.3. Outputs
  - 10.27.4. AI Model
    - 10.27.4.1. NVIDIA Triton Inference Server (formerly known as TRTIS)
  - 10.27.5. Directory Structure
  - 10.27.6. Executing Operator Locally
  - 10.27.7. Executing Operator in Docker
  - 10.27.8. License
  - 10.27.9. Suggested Reading
- 10.28. Clara Deploy AI COVID-19 Classification Operator
  - 10.28.1. DISCLAIMER
  - 10.28.2. Overview
  - 10.28.3. Inputs
  - 10.28.4. Outputs
  - 10.28.5. Environment Variables
  - 10.28.6. AI Model
    - 10.28.6.1. NVIDIA Triton Inference Server (formerly known as TRTIS)
  - 10.28.7. Directory Structure
  - 10.28.8. Executing Operator Locally
  - 10.28.9. Executing Operator in Docker
  - 10.28.10. License
  - 10.28.11. Suggested Reading
- 10.29. Clara Deploy AI COVID-19 Lesion Segmentation Operator
  - 10.29.1. Overview
  - 10.29.2. AI Model
    - 10.29.2.1. References
  - 10.29.3. Operator Inputs
  - 10.29.4. Operator Outputs
    - 10.29.4.1. NVIDIA Triton Inference Server (formerly known as TRTIS)
  - 10.29.5. Directory Structure
  - 10.29.6. Executing Operator as Docker Container
  - 10.29.7. Executing Operator Docker Container Interactively
- 10.30. Clara Deploy Series Selector
  - 10.30.1. Overview
  - 10.30.2. Inputs
  - 10.30.3. Outputs
  - 10.30.4. Directory Structure
  - 10.30.5. Executing Operator in Docker
  - 10.30.6. Executing Operator Locally
  - 10.30.7. Customizing Series Matching Rules
- 10.31. Copy customized rules file overwriting the default one.
  - 10.31.1. License
  - 10.31.2. Suggested Reading
- 10.32. Digital Pathology Nuclei Segmentation Operator
  - 10.32.1. Overview
  - 10.32.2. Commands
    - segmentation
      - 10.32.2.1.1. Input
      - 10.32.2.1.2. Output
- 10.33. Clara Deploy DICOM Segmentation Writer Operator
  - 10.33.1. Overview
  - 10.33.2. Inputs
  - 10.33.3. Outputs
  - 10.33.4. Environment Variables
  - 10.33.5. Directory Structure
  - 10.33.6. Executing the Operator Docker Image
  - 10.33.7. Executing the Operator Docker Image Interactively
  - 10.33.8. License
  - 10.33.9. Suggested Reading
- 10.34. Clara Deploy DICOM Report Object Writer
  - 10.34.1. Overview
  - 10.34.2. Inputs
  - 10.34.3. Outputs
  - 10.34.4. Environment Variables
  - 10.34.5. Directory Structure
  - 10.34.6. Executing the Operator Docker Image
  - 10.34.7. Executing the Operator Docker Image Interactively
  - 10.34.8. License
  - 10.34.9. Suggested Reading
- 10.35. Registration Operator
  - 10.35.1. Overview
  - 10.35.2. Data Input
  - 10.35.3. Data Output
  - 10.35.4. Parameters
  - 10.35.5. Execution steps.
11. User Defined Operators
- 11.1. Developing Clara Pipeline Operators Using the Operator Development Kit
- 11.2. Developing Clara Operators Using the Operator Development Kit
12. Bundled Pipelines
- 12.1. Liver Segmentation Pipeline
  - 12.1.1. Pipeline Definition
  - 12.1.2. Executing the Pipeline
- 12.2. CT Reconstruction Pipeline
  - 12.2.1. Overview
  - 12.2.2. Data
  - 12.2.3. Operators
  - 12.2.4. Execution of Reconstruction docker
    - 12.2.4.1. Reconstruction Operator Docker Image
  - 12.2.5. Execute of Reconstruction Pipeline within Clara
  - 12.2.6. CT Recon Perf pipeline
  - 12.2.7. CT Recon Liver segmentation pipeline
- 12.3. Multi AI Pipeline
  - 12.3.1. Overview
  - 12.3.2. Data
  - 12.3.3. Execution Steps on Clara Platform
- 12.4. Vnet Segmentation pipeline
  - 12.4.1. Overview
  - 12.4.2. Data
  - 12.4.3. Operators
- 12.5. Clara AI Brain Tumor Segmentation Pipeline
  - 12.5.1. Pipeline Definition
  - 12.5.2. Executing the Pipeline
- 12.6. Hippocampus Segmentation Pipeline
  - 12.6.1. Pipeline Definition
  - 12.6.2. Executing the Pipeline
- 12.7. Spleen Segmentation Pipeline
  - 12.7.1. Pipeline Definition
  - 12.7.2. Executing the Pipeline
- 12.8. Malaria Microscopy Classification Pipeline
  - 12.8.1. Pipeline Definition
  - 12.8.2. Executing the Pipeline
- 12.9. Lung Tumor Segmentation Pipeline
  - 12.9.1. Pipeline Definition
  - 12.9.2. Executing the Pipeline
- 12.10. Colon Tumor Segmentation Pipeline
  - 12.10.1. Pipeline Definition
  - 12.10.2. Executing the Pipeline
- 12.11. Pancreas Tumor Segmentation Pipeline
  - 12.11.1. Pipeline Definition
  - 12.11.2. Executing the Pipeline
- 12.12. Chest X-ray Classification Pipeline
  - 12.12.1. Pipeline Definition
  - 12.12.2. Executing the Pipeline
  - 12.12.3. Datasets
- 12.13. Breast Pathology Image Classification Pipeline
  - 12.13.1. Pipeline Definition
  - 12.13.2. Executing the Pipeline
- 12.14. Clara AI Prostate Segmentation Pipeline
  - 12.14.1. Overview
  - 12.14.2. Pipeline Definition
  - 12.14.3. Executing the Pipeline
- 12.15. De Novo Sequence Assembly - Clara Genomics Analysis
  - 12.15.1. Pipeline Definition
  - 12.15.2. Executing the Pipeline
  - 12.15.3. Data Input
  - 12.15.4. Data Output
- 12.16. 3D Image Processing Pipeline using FastIO
  - 12.16.1. Pipeline Definition
  - 12.16.2. Executing the Pipeline
  - 12.16.3. Data Input
  - 12.16.4. Data Output
  - 12.16.5. Viewing the Output Volume Image
- 12.17. FastIO Passthrough Pipeline Using FastIO Variable API
  - 12.17.1. Pipeline Definition
  - 12.17.2. Data Input
  - 12.17.3. Data Output
  - 12.17.4. Executing the Pipeline
  - 12.17.5. Check Job Status and Download/View Payloads in Clara Console/Dashboard
  - 12.17.6. Download and Verify the Outputs
- 12.18. Suggested Reading
- 12.19. DeepStream Batch Pipeline
  - 12.19.1. Pipeline Definition
  - 12.19.2. Executing the Pipeline
  - 12.19.3. Data Input
  - 12.19.4. Data Output
  - 12.19.5. Viewing the Output Video
  - 12.19.6. Performance Implications
- 12.20. Digital Pathology Image Processing Pipeline
  - 12.20.1. Pipeline Definition
    - 12.20.1.1. dp-sample-pipeline-no-optimization.yaml
    - 12.20.1.2. dp-sample-pipeline.yaml
  - 12.20.2. Executing the Pipeline
  - 12.20.3. Data Input
  - 12.20.4. Data Output
  - 12.20.5. Viewing the Output Volume Image
- 12.21. Clara Deploy AI COVID-19 Classification Pipeline
  - 12.21.1. DISCLAIMER
  - 12.21.2. Pipeline Definition
  - 12.21.3. Executing the Pipeline
  - 12.21.4. License
  - 12.21.5. Suggested Reading
- 12.22. Clara Advanced DICOM Integration Pipeline
  - 12.22.1. Overview
  - 12.22.2. Pipeline Definition
  - 12.22.3. Executing the Pipeline
  - 12.22.4. License
  - 12.22.5. Suggested Reading
- 12.23. Clara Deploy DICOM Series Selection Pipeline
  - 12.23.1. Overview
  - 12.23.2. Pipeline Definition
  - 12.23.3. Executing the Pipeline
  - 12.23.4. License
  - 12.23.5. Suggested Reading
- 12.24. Digital Pathology Nuclei Segmentation Pipeline
  - 12.24.1. Pipeline Definition
    - 12.24.1.1. dp-nuclei-segmentation-pipeline.yaml
  - 12.24.2. Executing the Pipeline
  - 12.24.3. Data Input
  - 12.24.4. Data Output
  - 12.24.5. Viewing the Output Volume Image
- 12.25. Registration Pipeline
  - 12.25.1. Overview
  - 12.25.2. Parameters
  - 12.25.3. Execution Steps on Clara Platform
13. User Defined Pipelines
- 13.1. Build Custom Operators
- 13.2. Place AI Model Files in the Right Directory
- 13.3. Start With a Reference Pipeline
- 13.4. Modify the Pipeline
- 13.5. External DICOM Sender and DICOM Receiver
- 13.6. Create the Pipeline
- 13.7. Configure the Clara DICOM Destination
- 13.8. Trigger Pipeline
- 13.9. Verify the Pipeline Execution in the Dashboard
- 13.10. Verify the External DICOM Receiver Received the Images
14. Bundled Services
- 14.1. Clara Results Service
- 14.2. Clara Dashboard Render Service
- 14.3. Clara Management Console
15. Connectivity With a PACS/DICOM Server
- 15.1. Configuring the DICOM Adapter to Receive Images
- 15.2. Configuring the DICOM Adapter to Send Images
- 15.3. Troubleshooting Connectivity
16. Clara Deploy GPU Profiler
- 16.1. Clara Deploy GPU Profiler
17. Clara CLI
- clara
- 17.2. Clara Deploy SDK Configuration
- 17.3. Getting Started
  - create model
    - 17.3.1.1. Usage
    - 17.3.1.2. Flags
  - list model
    - 17.3.2.1. Usage
    - 17.3.2.2. Flags
  - delete models
    - 17.3.3.1. Usage
    - 17.3.3.2. Arguments
  - create job
    - 17.3.4.1. Usage
    - 17.3.4.2. Flags
  - start job
    - 17.3.5.1. Usage
    - 17.3.5.2. Flags
  - create pipelines
    - 17.3.6.1. Usage
    - 17.3.6.2. Flags
  - list pipelines
    - 17.3.7.1. Usage
    - 17.3.7.2. Flags
  - describe pipeline
    - 17.3.8.1. Usage
    - 17.3.8.2. Flags
  - list jobs
    - 17.3.9.1. Usage
    - 17.3.9.2. Flags
  - cancel jobs
  - upload payload
    - 17.3.11.1. Usage
    - 17.3.11.2. Flags
  - delete payloads
    - 17.3.12.1. Usage
    - 17.3.12.2. Arguments
  - download
    - 17.3.13.1. Usage
    - 17.3.13.2. Arguments
  - describe job
    - 17.3.14.1. Usage
    - 17.3.14.2. Flags
  - config
    - 17.3.15.1. Usage
    - 17.3.15.2. Flags
  - logs
    - 17.3.16.1. Usage
    - 17.3.16.2. Flags
  - version
    - 17.3.17.1. Usage
- clara
- clara-render
  - start
    - 17.5.1.1. Usage
  - restart
    - 17.5.2.1. Usage
  - stop
    - 17.5.3.1. Usage
- clara-dicom
  - start
    - 17.6.1.1. Usage
  - 17.6.2. Flags
  - restart
    - 17.6.3.1. Usage
  - stop
    - 17.6.4.1. Usage
18. Load Generator
- 18.1. Pipeline Load Generator CLI (cpload)
  - 18.1.1. Requirement:
  - 18.1.2. Syntax:
19. Platform API
- 19.1. Clara Deploy SDK Platform API Overview
  - 19.1.1. Concepts
    - 19.1.1.1. Services
  - 19.1.2. Clara Service
  - 19.1.3. Jobs Service
  - 19.1.4. Models Service
  - 19.1.5. Payloads Service
  - 19.1.6. Pipelines Service
    - 19.1.6.1. Examples
  - 19.1.7. Create a New Pipeline
  - 19.1.8. Get a List of Existing Pipelines
  - 19.1.9. Create and Start a Job
  - 19.1.10. Get Status of a Job
  - 19.1.11. Get a File Listing from a Payload
  - 19.1.12. Download a File from a Payload
    - 19.1.12.1. Useful Links
  - 19.1.13. Introduction to GRPC and Protobuf
  - 19.1.14. GRPC Examples
- 19.2. GpuUtilization
  - 19.2.1. Properties
- 19.3. ProcessDetails
  - 19.3.1. Properties
    - 19.3.1.1. name
    - 19.3.1.2. job_id
- 19.4. Clara Stop RPC
- 19.5. ClaraStopRequest
  - 19.5.1. Properties
    - 19.5.1.1. header
- 19.6. ClaraStopResponse
  - 19.6.1. Properties
    - 19.6.1.1. header
- 19.7. Clara Stop RPC
- 19.8. ClaraUtilizationRequest
  - 19.8.1. Properties
    - 19.8.1.1. header
    - 19.8.1.2. watch
- 19.9. ClaraUtilizationResponse
  - 19.9.1. Properties
    - 19.9.1.1. header
    - 19.9.1.2. gpu_metrics
- 19.10. Clara Version RPC
- 19.11. ClaraVersionRequest
  - 19.11.1. Properties
    - 19.11.1.1. header
- 19.12. ClaraVersionResponse
  - 19.12.1. Properties
    - 19.12.1.1. header
    - 19.12.1.2. version
- 19.13. Pipelines Create RPC
  - 19.13.1. Types
- 19.14. PipelinesCreateRequest
  - 19.14.1. Properties
    - 19.14.1.1. header
    - 19.14.1.2. definition
  - 19.14.2. metadata
- 19.15. PipelinesCreateResponse
  - 19.15.1. Properties
    - 19.15.1.1. header
    - 19.15.1.2. pipeline_id
- 19.16. Pipelines Details RPC
  - 19.16.1. Messages
- 19.17. PipelinesDetailsRequest
  - 19.17.1. Properties
    - 19.17.1.1. header
    - 19.17.1.2. pipeline_id
- 19.18. PipelinesDetailsResponse
  - 19.18.1. Properties
- 19.19. Pipelines List RPC
  - 19.19.1. Messages
- 19.20. PipelinesListRequest
  - 19.20.1. Properties
    - 19.20.1.1. header
- 19.21. PipelinesListResponse
  - 19.21.1. Properties
    - 19.21.1.1. header
    - 19.21.1.2. details
- 19.22. PipelineDetails
  - 19.22.1. Properties
    - 19.22.1.1. pipeline_id
    - 19.22.1.2. name
- 19.23. Pipelines Remove RPC
- 19.24. PipelinesRemoveRequest
  - 19.24.1. Properties
    - 19.24.1.1. header
    - 19.24.1.2. pipeline_id
- 19.25. PipelinesRemoveResponse
  - 19.25.1. Properties
    - 19.25.1.1. header
- 19.26. Pipelines Update RPC
  - 19.26.1. Messages
- 19.27. PipelinesUpdateRequest
  - 19.27.1. Properties
- 19.28. PipelinesUpdateResponse
  - 19.28.1. Properties
    - 19.28.1.1. header
- 19.29. PipelineDefinitionFile
  - 19.29.1. Properties
    - 19.29.1.1. content
- 19.30. Jobs Cancel RPC
  - 19.30.1. Messages
- 19.31. JobsCancelRequest
  - 19.31.1. Properties
- 19.32. JobsCancelResponse
  - 19.32.1. Properties
- 19.33. Jobs Create RPC
  - 19.33.1. Messages
- 19.34. JobsCreateRequest
  - 19.34.1. Properties
- 19.35. JobsCreateResponse
  - 19.35.1. Properties
- 19.36. Jobs List RPC
  - 19.36.1. Messages
- 19.37. JobsListRequest
  - 19.37.1. Properties
    - 19.37.1.1. header
    - 19.37.1.2. filter
- 19.38. JobsListResponse
  - 19.38.1. Properties
    - 19.38.1.1. header
    - 19.38.1.2. job_details
- 19.39. Jobs ReadLogs RPC
  - 19.39.1. Messages
- 19.40. JobsReadLogsRequest
  - 19.40.1. Properties
- 19.41. JobsReadLogsResponse
  - 19.41.1. Properties
- 19.42. Jobs Start RPC
  - 19.42.1. Messages
- 19.43. JobsStartRequest
  - 19.43.1. Properties
    - 19.43.1.1. header
    - 19.43.1.2. job_id
      - 19.43.1.2.1. Variables
- 19.44. JobsStartResponse
  - 19.44.1. Properties
- 19.45. NamedValue
  - 19.45.1. Properties
    - 19.45.1.1. name
    - 19.45.1.2. value
- 19.46. Jobs Status RPC
  - 19.46.1. Messages
- 19.47. JobsStatusRequest
  - 19.47.1. Properties
    - 19.47.1.1. header
    - 19.47.1.2. job_id
- 19.48. JobsStatusResponse
  - 19.48.1. Properties
- 19.49. JobsDetails
  - 19.49.1. Properties
- 19.50. JobFilter
  - 19.50.1. Properties
- 19.51. JobOperatorDetails
  - 19.51.1. Properties
- 19.52. JobOperatorStatus
- 19.53. JobPriority
- 19.54. JobState
- 19.55. JobStatus
- 19.56. Payloads Create RPC
  - 19.56.1. Messages
- 19.57. PayloadsCreateRequest
  - 19.57.1. Properties
    - 19.57.1.1. header
  - 19.57.2. metadata
    - 19.57.2.1. PayloadsCreateResponse
  - 19.57.3. Properties
- 19.58. Payloads Details RPC
  - 19.58.1. Messages
- 19.59. PayloadsDetailsRequest
  - 19.59.1. Properties
    - 19.59.1.1. header
    - 19.59.1.2. payload_id
- 19.60. PayloadsDetailsResponse
  - 19.60.1. Properties
- 19.61. Payloads Download RPC
  - 19.61.1. Messages
- 19.62. PayloadsDownloadRequest
- 19.63. PayloadsDownloadResponse
  - 19.63.1. Properties
- 19.64. Payloads Create RPC
  - 19.64.1. Messages
- 19.65. PayloadsCreateRequest
  - 19.65.1. Properties
    - 19.65.1.1. header
    - 19.65.1.2. PayloadsCreateResponse
  - 19.65.2. Properties
- 19.66. Payloads Upload RPC
  - 19.66.1. Messages
- 19.67. PayloadsUploadRequest
  - 19.67.1. Properties
- 19.68. PayloadsUploadResponse
  - 19.68.1. Properties
    - 19.68.1.1. details
- 19.69. PayloadFileDetails Message
  - 19.69.1. Properties
    - 19.69.1.1. mode
    - 19.69.1.2. size
      - 19.69.1.2.1. name
- 19.70. PayloadType
- 19.71. RPC Error Codes
  - 19.71.1. Pipeline Service Errors
  - 19.71.2. Jobs Service Errors
  - 19.71.3. Payloads Service Errors
- 19.72. Identifier
  - 19.72.1. Properties
    - 19.72.1.1. value
- 19.73. RequestHeader
  - 19.73.1. Properties
    - 19.73.1.1. api_version
    - 19.73.1.2. user_agent
- 19.74. ResponseHeader
  - 19.74.1. Properties
    - 19.74.1.1. code
    - 19.74.1.2. messages
- 19.75. Timestamp
  - 19.75.1. Properties
    - 19.75.1.1. value
- 19.76. Version
  - 19.76.1. Properties
20. Third Party Tools
- 20.1. Orthanc
  - 20.1.1. Overview
  - 20.1.2. How to Install
- 20.2. DCM4CHE
  - 20.2.1. Overview
  - 20.2.2. How to Install
- 20.3. 3D Slicer
  - 20.3.1. Overview
  - 20.3.2. How to Install
- 20.4. OHIF Viewer
  - 20.4.1. Overview
  - 20.4.2. How to Install
- 20.5. Oviyam
  - 20.5.1. Overview
  - 20.5.2. How to Install
- 20.6. Horos
  - 20.6.1. Overview
  - 20.6.2. How to Install
21. Release Notes
- 21.1. Version 0.8.1 (R8)
- 21.2. Version 0.7.4 (R7)
- 21.3. Version 0.7.3 (R7)
- 21.4. Version 0.7.2 (R7)
- 21.5. Version 0.7.1 (R7)
- 21.6. Version 0.6.1 (R6)
- 21.7. Version 0.6.0 (R6)
- 21.8. Version 0.5.0 (R5)
- 21.9. Version 0.4.1 (hotfix)
- 21.10. Version 0.4.0 (R4)
- 21.11. Version 0.2.0 (R2)
- 21.12. Version 0.1.7 (Deprecated)
- 21.13. Version 0.1.6 (Deprecated)
- 21.14. Pre-alpha (Deprecated)
- 21.15. Known Issues
- 21.16. Support
22. License
- 22.1. Third-Party Licenses

Intelligent Machines Developer / Engineer Healthcare & Life Sciences AI and Deep Learning Computer Vision / Video Analytics Developer / Engineer Dev / IT Operations