VisionAIre
  • About Nodeflux
  • Visionaire Stream
    • Overview
    • Requirements
      • Credential Keys
      • Tested Hardware
      • Bandwith Requirements
    • Installation Guide
      • Dependencies
      • Simple Installation
      • Advanced Installation
      • Clustering Installation
      • Add-ons Analytics Installation
        • People Attributes Installation
        • Vehicle Attributes Installation
        • OVOD Installation
        • OVIC Installation
        • VM Installation
        • VLM Installation
    • Analytics
      • Face Recognition
        • Additional Information
          • Overview
          • Disclaimer
          • Metrics
          • Testing
      • People Analytics
      • Crowd Estimation
      • PPE Detection
      • License Plate Recognition
      • Vehicle Analytics
      • Water Level Monitoring
        • Camera Guideline
      • Pre-Flood Monitoring
      • Person Smoking Detection
      • Person with Handphone Detection
      • Smoke and Fire Detection
      • Person Using Firearms Detection
      • Vandalism Attempt Recognition
      • ATM Burglary Incident Recognition
      • Road Crash Monitoring
      • People Fighting Recognition
      • Riot Recognition
    • Developer Guide
      • How our APIs work
      • HTTP APIs
      • Websocket
      • Database Structure
    • Changelogs
  • Visionaire Snapshot
    • Overview
    • Requirements
    • Installation Guide
      • Face Searching & Matching
        • Single Node
        • Clustering
      • Helmet Detection
      • Chicken Estimation
      • Face Detection
      • Over Dimension Over Load
      • Frontal License Plate Recognition
    • Analytics
      • Face Searching & Matching
        • Face Enrollment
          • Image Guideline
          • Face and Image Quality Assessment
            • Setup On Premise
            • API
          • Insert / Update / Delete Enrollment
          • Batch Enrollment
      • Helmet Detection
      • Chicken Estimation
      • People Demography
      • Face Detection
      • Over Dimension Over Load
      • License Plate Recognition -Frontal
    • Developer Guide
      • APIs
        • Face Searching & Matching
        • Helmet Detection
        • Chicken Estimation
        • People Demography
        • Face Detection
        • Over Dimension Over Load
        • Frontal License Plate Recognition
      • Vanilla APIs for Face Enrollment
      • Porting Enrollment Database Cluster to Docker
    • Changelogs
  • VisionAIre Dashboard
    • Introduction
    • Add Analytic Assignment
    • Accessing Vanilla Database
    • Connect to Vanilla Websocket
    • Create your own visualization
      • Migration from Old Streamer to New Streamer
      • Drawing Region of Interest
      • Additional Visualization Query
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  • How to Setup the Deployment?
  • 1. Configuration of docker-compose.yml
  • 2. Settings of config.yml
  • 3. Keep the analytics image and port addresses into .env file
  • 4. Run Image

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  1. Visionaire Stream
  2. Installation Guide
  3. Add-ons Analytics Installation

VM Installation

This page informs how to deploy the docker compose of snapshot platform as the VisionAIre Stream analytics requirements for every analytics run by VM deployment.

How to Setup the Deployment?

Create a dedicated folder for this installation to help organize your deployment.

1. Configuration of docker-compose.yml

version: '3.3'
services:
  node1:
    image: "${VM_IMAGE}"
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: 1
              capabilities: [gpu]
    pid: host
    network_mode: host
    cap_add:
      - SYS_PTRACE
    command: [
      httpserver,
      --listen-port, "${FREMIS1_LISTEN_PORT}",
      --listen-port-monitoring, "${FREMIS1_LISTEN_PORT_MONITORING}",
      --verbose,
    ]
    healthcheck:
      test: ["CMD", "curl", "-f", "http://0.0.0.0:${FREMIS1_LISTEN_PORT}/healthcheck"]
      interval: 5s
      timeout: 3s
      retries: 20
  coordinator:
    image: "${VM_IMAGE}"
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: 1
              capabilities: [gpu]
    pid: host
    network_mode: host
    cap_add:
      - SYS_PTRACE
    command: [
      coordinator,
      --listen-port, "${COORDINATOR_LISTEN_PORT}",
      --listen-port-monitoring, "${COORDINATOR_LISTEN_PORT_MONITORING}",
      --config-path, "/etc/nodeflux/config.yml",
      --verbose,
    ]
    volumes:
      - ${PWD}/config.yml:/etc/nodeflux/config.yml
    depends_on:
      node1:
        condition: service_healthy

2. Settings of config.yml

version: "v1"
nodes:
- address: "0.0.0.0:4021"
  analytic_id: "NFFS-VM"

3. Keep the analytics image and port addresses into .env file

export VM_IMAGE=registry.gitlab.com/nodefluxio/cloud/analytics/pipelines/vm-pipeline:on-premise-0.1.0

export COORDINATOR_LISTEN_PORT=4004
export COORDINATOR_LISTEN_PORT_MONITORING=5004

export FREMIS1_LISTEN_PORT=4021
export FREMIS1_LISTEN_PORT_MONITORING=5021

4. Run Image

docker-compose up -d --build
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Last updated 9 months ago

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