Supervisely
AboutAPI ReferenceSDK Reference
  • 🤖What's Supervisely
  • 🚀Ecosystem of Supervisely Apps
  • 💡FAQ
  • 📌Getting started
    • How to import
    • How to annotate
    • How to invite team members
    • How to connect agents
    • How to train models
  • 🔁Import and Export
    • Import
      • Overview
      • Import using Web UI
      • Supported annotation formats
        • Images
          • 🤖Supervisely JSON
          • 🤖Supervisely Blob
          • COCO
          • Yolo
          • Pascal VOC
          • Cityscapes
          • Images with PNG masks
          • Links from CSV, TXT and TSV
          • PDF files to images
          • Multiview images
          • Multispectral images
          • Medical 2D images
          • LabelMe
          • LabelStudio
          • Fisheye
          • High Color Depth
        • Videos
          • Supervisely
        • Pointclouds
          • Supervisely
          • .PCD, .PLY, .LAS, .LAZ pointclouds
          • Lyft
          • nuScenes
          • KITTI 3D
        • Pointcloud Episodes
          • Supervisely
          • .PCD, .PLY, .LAS, .LAZ pointclouds
          • Lyft
          • nuScenes
          • KITTI 360
        • Volumes
          • Supervisely
          • .NRRD, .DCM volumes
          • NIfTI
      • Import sample dataset
      • Import into an existing dataset
      • Import using Team Files
      • Import from Cloud
      • Import using API & SDK
      • Import using agent
    • Migrations
      • Roboflow to Supervisely
      • Labelbox to Supervisely
      • V7 to Supervisely
      • CVAT to Supervisely
    • Export
  • 📂Data Organization
    • Core concepts
    • MLOps Workflow
    • Projects
      • Datasets
      • Definitions
      • Collections
    • Team Files
    • Disk usage & Cleanup
    • Quality Assurance & Statistics
      • Practical applications of statistics
    • Operations with Data
      • Data Filtration
        • How to use advanced filters
      • Pipelines
      • Augmentations
      • Splitting data
      • Converting data
        • Convert to COCO
        • Convert to YOLO
        • Convert to Pascal VOC
    • Data Commander
      • Clone Project Meta
  • 📝Labeling
    • Labeling Toolboxes
      • Images
      • Videos 2.0
      • Videos 3.0
      • 3D Point Clouds
      • DICOM
      • Multiview images
      • Fisheye
    • Labeling Tools
      • Navigation & Selection Tools
      • Point Tool
      • Bounding Box (Rectangle) Tool
      • Polyline Tool
      • Polygon Tool
      • Brush Tool
      • Mask Pen Tool
      • Smart Tool
      • Graph (Keypoints) Tool
      • Frame-based tagging
    • Labeling Jobs
      • Labeling Queues
      • Labeling Consensus
      • Labeling Statistics
    • Labeling with AI-Assistance
  • 🤝Collaboration
    • Admin panel
      • Users management
      • Teams management
      • Server disk usage
      • Server trash bin
      • Server cleanup
      • Server stats and errors
    • Teams & workspaces
    • Members
    • Issues
    • Guides & exams
    • Activity log
    • Sharing
  • 🖥️Agents
    • Installation
      • Linux
      • Windows
      • AMI AWS
      • Kubernetes
    • How agents work
    • Restart and delete agents
    • Status and monitoring
    • Storage and cleanup
    • Integration with Docker
  • 🔮Neural Networks
    • Overview
    • Inference & Deployment
      • Overview
      • Supervisely Serving Apps
      • Deploy & Predict with Supervisely SDK
      • Using trained models outside of Supervisely
    • Model Evaluation Benchmark
      • Object Detection
      • Instance Segmentation
      • Semantic Segmentation
      • Custom Benchmark Integration
    • Custom Model Integration
      • Overview
      • Custom Inference
      • Custom Training
    • Legacy
      • Starting with Neural Networks
      • Train custom Neural Networks
      • Run pre-trained models
  • 👔Enterprise Edition
    • Get Supervisely
      • Installation
      • Post-installation
      • Upgrade
      • License Update
    • Kubernetes
      • Overview
      • Installation
      • Connect cluster
    • Advanced Tuning
      • HTTPS
      • Remote Storage
      • Single Sign-On (SSO)
      • CDN
      • Notifications
      • Moving Instance
      • Generating Troubleshoot Archive
      • Storage Cleanup
      • Private Apps
      • Data Folder
      • Firewall
      • HTTP Proxy
      • Offline usage
      • Multi-disk usage
      • Managed Postgres
      • Scalability Tuning
  • 🔧Customization and Integration
    • Supervisely .JSON Format
      • Project Structure
      • Project Meta: Classes, Tags, Settings
      • Tags
      • Objects
      • Single-Image Annotation
      • Single-Video Annotation
      • Point Cloud Episodes
      • Volumes Annotation
    • Developer Portal
    • SDK
    • API
  • 💡Resources
    • Changelog
    • GitHub
    • Blog
    • Ecosystem
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On this page
  • Installation instructions for different operating systems:
  • Agent

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  1. Agents

Installation

PreviousSharingNextLinux

Last updated 9 months ago

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Installation instructions for different operating systems:

Agent

Learn how Supervisely agent works and how to maintain it in the section.

🖥️
Unix-based
Windows WSL
Agent
About Supervisely Agent
Adding, Restarting, and Deleting Nodes
How the Agent Works
Agent Storage
Leveraging Amazon AMI for Agent Deployment
Efficient Cleanup and Resource Management
Custom Docker Registry Integration
Management
Status, and Troubleshooting

Installation Linux

Everything you need to know about deploying Supervisely agent on Unix-based operating systems.

Installation Windows

Everything you need to know about deploying Supervisely agent on Windows WSL.

Installation AMI AWS

If, for some reason, your computer doesn't meet the requirements, hardware (no GPU) or software (no CUDA or nvidia-docker), there is a quick way to try training & inference with Supervisely on Amazon EC2.

Installation Kubernetes

Follow these steps to deploy Supervisely in Kubernetes cluster