Image Train Filters

---

---

Description

Let's start with this image:

Using Image Contour filter:

Using Kuwahara filter:

Using Chartizate filter:

Current running online implementation: Image train filters

NodeJs Multiproject

yarn config set workspaces-experimental true

How to use

We need to provide two form-data parameters in a Multipart Formdata request. Use curl for that please. An example follows bellow.

filename

• this is the where you load your image file in

commands

• this is where you set your commands. there are only two examples at the moment:

1. Kuwahara filter:

It smooths the image

2. Image contour filter:

Processes differences in color ranges

These requests you can apply as many times as you like using a JSON request. Read following example for more.

Command example

{
  "commands": [
    {
      "filter": "imageKuwahara",
      "settings": [
        {
          "name": "square-size",
          "value": "2"
        },
        {
          "name": "iterations",
          "value": "2"
        }
      ]
    },
    {
      "filter": "imageContour",
      "settings": [
        {
          "name": "bgColor",
          "value": "0xFFFFFF"
        },
        {
          "name": "lnColor",
          "value": "0x000000"
        },
        {
          "name": "diffThreshold",
          "value": "800000"
        },
        {
          "name": "radius",
          "value": "2"
        }
      ]
    }
  ]
}

Complete request

You can use tools like postman, but you can also use curl. This is an example of such request:

$ curl -X POST --form [email protected] http://localhost:8080/images --form commands="{ \"commands\": [ { \"filter\": \"imageKuwahara\", \"settings\": [ { \"name\": \"square-size\", \"value\": \"2\"}, { \"name\": \"iterations\", \"value\": \"2\"} ]}, { \"filter\": \"imageContour\", \"settings\": [ { \"name\": \"bgColor\", \"value\": \"0xFFFFFF\"}, { \"name\": \"lnColor\", \"value\": \"0x000000\"}, { \"name\": \"diffThreshold\", \"value\": \"800000\"}, { \"name\": \"radius\", \"value\": \"2\"} ]} ] }"

Results

Your results are stored wherever you define in your application.conf folder:

akka {
  loglevel = DEBUG
  event-handlers = ["akka.event.slf4j.Slf4jEventHandler"]
}

service {
  host = "localhost"
  port = 8080
}

image-train-filters {
  image-source-path = "/tmp/image-train-filters/sources"
  image-destination-path = "/tmp/image-train-filters/destination"
}

Only important to note here that:

• image-source-path -> This is where your original file is saved

• image-destination-path -> This is where the resulting file is saved after applying the train of filters.

DevOps

$ npm i -g npm  
$ npm install -g @angular/cli  
$ alias ng="/usr/local/lib/node_modules/@angular/cli/bin/ng"  
$ npm cache clean -f  
$ npm install -g n  
$ n stable  
$ echo "deb https://dl.bintray.com/sbt/debian /" | tee -a /etc/apt/sources.list.d/sbt.list  
$ apt-key adv --keyserver hkp://keyserver.ubuntu.com:80 --recv 2EE0EA64E40A89B84B2DF73499E82A75642AC823  
$ apt-get update  
$ apt-get install sbt 
$ apt-get install default-jre 

image-train-filters-fe Module

Make a build

$ yarn install
$ yarn build
$ service nginx reload

Resources

• Akka Configuration Reference
• SBT release 1.5.0
• nginx: multiple websites on one server
• Set up multiple websites on a Digital Ocean droplet running nginx and node.js
• Fixing 413 Request Entity Too Large Errors
• Postman
• Update all the Node dependencies to their latest version
• How to fix 'Unsupported platform for [email protected]: wanted {“os”:“darwin”,“arch”:“any”} (current: {“os”:“win32”,“arch”:“x64”})

About me