Skip to content

Latest commit

 

History

History
32 lines (24 loc) · 1.69 KB

AWS-Deployment-Guide.md

File metadata and controls

32 lines (24 loc) · 1.69 KB
Raw

AWS-Deployment Guide

There are two ways of deploying the CVAT.

  1. On Nvidia GPU Machine: Tensorflow annotation feature is dependent on GPU hardware. One of the easy ways to launch CVAT with the tf-annotation app is to use AWS P3 instances, which provides the NVIDIA GPU. Read more about P3 instances here. Overall setup instruction is explained in main readme file, except Installing Nvidia drivers. So we need to download the drivers and install it. For Amazon P3 instances, download the Nvidia Drivers from Nvidia website. For more check Installing the NVIDIA Driver on Linux Instances link.

  2. On Any other AWS Machine: We can follow the same instruction guide mentioned in the Readme file. The additional step is to add a security group and rule to allow incoming connections.

For any of above, don't forget to add exposed AWS public IP address and port to docker-compose.override.yml:

You need at least 2 opened ports on your Amazon instance, for UI and Django apps.

version: "2.3"

services:
  cvat:
    environment:
      UI_HOST: *your Amazon AWS instance's url or IP*
      UI_PORT: *port for UI app*
    ports:
      - "REACT_APP_API_PORT specified below:8080"


  cvat_ui:
    build:
      args:
        REACT_APP_API_HOST: *your Amazon AWS instance's url or IP*
        REACT_APP_API_PORT: *port for Django app*
    ports:
      - "UI_PORT specified above":80"