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CURART LOGO

pipeline status coverage report

Intro

This project is written in python 3 to attempt to match images and artworks. The purpose of this is to attempt to find people who are using images that are copywright, modified from original or find the source of an artwork. This is implemented using the OpenCV version of the SIFT algorithm. Therefore it is not for comercial use and purely a research project.

The second aim of the project is to work fast as scale.

Dependencies

  • This project depends on the following packages:
    • opencv
      • This is an image processing libraray, we are using the SIFT algorithm in the contrib_modules. This library is precompiled in the docker image
    • tlsh_hash
      • This is a locally sensitive hashing library. This allows us to hash keypoints and the resulting hashes will be similar if they are in fact similar key points
    • flask
      • This is the webframe work that is used to create the application
    • gunicorn
      • This is the production web server that is used to server the flask application
    • psycopg2-binary
      • A library to connect and query the postgres database

How To Deploy Localy

  • This application comes as part of a docker container

  • All you will need is docker and docker-compose

    • Install
      • Ubuntu18.0+
      # Run with admin privileges i.e sudo
      apt-get install docker.io
      curl -L "https://github.com/docker/compose/releases/download/1.24.0/docker-compose-$(uname -s)-$(uname -m)" -o /usr/local/bin/docker-compose
      chmod +x /usr/local/bin/docker-compose
      
  • To deploy create a docker compose with configuration similar to

    version: '3'
    
    networks:
      proxy:
        external: true
      internal:
        external: false
    
    services:
        curart:
            restart: always
            build:
                context: .
            environment:
                # These should be set in the local environment
                DBUSER: ${DBUSER:-latest}
                DBPASSWORD: ${DBPASSWORD:-latest}
                DBHOST: ${DBHOST:-latest}
                DBNAME: ${DBNAME:-latest}
                DBPORT: 5432 # This is default postgresql port
            labels:
                - traefik.backend=upload
                # Change host to your domain name to work
                - traefik.frontend.rule=Host:upload.dtom.dev
                - traefik.docker.network=proxy
                - traefik.port=8080
            networks:
                - internal
                - proxy
        traefik:
            image: traefik:alpine
            container_name: traefik
            restart: always
            command: --docker
            ports:
                - "443:443"
                - "80:80"
            networks:
                - proxy
            volumes:
                - "/var/run/docker.sock:/var/run/docker.sock:ro"
                # Make sure these point to the config files that you have 
                # Already created on the server
                - "/etc/containers/traefik/traefik.toml:/traefik.toml:ro"
                - "/etc/containers/traefik/acme.json:/acme.json:rw"
            labels:
                - "traefik.frontend.rule=Host:monitor.dtom.dev"
                - "traefik.port=8080"
    
    
  • Once you have this saved as a docker-compose.yml file then you can run the command :

    docker-compose up -d --scale curart=$instances_required 
    

What does this do?

  • This is the configuration file to create two docker containers.
    • The first is this application.

      • The restart section we tell the container to restart every time it is stopped unless stopped by the command docker stop
      • The build section we give the path where it will fine the files to build into the container
      • The environment section we pass in environment variable that we have in the system into the docker containers environment. We are doing this to pass secrets.
      • The labels section is for working with traefik.
        • We give the backend a name, here we call it upload
        • We give it a domain name to route to the container
        • We tell it what docker network to use to connect the traefik container and the curart container
        • Then we give the traefik port to the container
      • In networks section we declare what docker networks this container should be running on
    • The other configuration is for traefik (A reverse proxy)

      • image: Because this is not our own image we will pull the image from dockerhub and we specify the image we want here
      • container_name: We name the container
      • restart: section we tell the container to restart every time it is stopped unless stopped by the command docker stop
      • command: Once the container starts running we will give it a subcommand to tell it what to run and in what context it is running
      • ports: We need to tell the container what to map internal ports to on external ports. Traefik is our only web proxy in this case so we are using 80 and 433
      • networks: We declare what docker networks this container should be running on
      • volumes: We map directories in the host system to inside the container.
        • Here we are mapping docker.sock so that traefik can see other containers that are stopping and starting and automatically route traffic to them in real time.
        • The next two volume mappings are config files that are independent of the container. So we have created them on the host system and passed them in by mounting the volumes. We don't put these in the repo because they contain secrets and keys for traefik.
      • labels: Passes in the traefik port and give a url to route the main monitoring page to.

Verify

  • By Running docker ps on the host system you should see output similar to the following: Docker ps output display

If you cannot read this image click here

Scaling

  • If you need more application instances simply place that in the docker-compose command as so
docker-compose up -d --scale curart=2
  • This will create 2 versions of curart and traefik will automatically recogise there are two and load balance between them
  • The load balance method is round robin
  • There is no need to stop the containers to anything to scale this and there will be no downtime when scaling up

TODO How to configure and deploy database

How To Use

Once you have the containers running you can navigate to your url, mine was upload.dtom.dev

You should see the upload screen as so: Image of upload screen of curart

Click the Choose File button and navigate your system for images: Image of choosing a file from system

Once the file is chosen click the submit button

An image will be returned that is the original found image Image of resulting image being returned