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== Project Overview ==
== Project Overview ==


marK is a machine learning dataset annotation tool being developed that will help users annotate multiple types of data for training in supervised classification problems. The objective of the project is to add text annotation support and refactor the codebase to separate image annotation logic from the core of marK, making its codebase more extensible and easy to add new annotations types.  
marK is a machine learning dataset annotation tool being developed that will help users annotate multiple types of data for training in supervised classification problems. The objective of the project is to add text annotation support and refactor the codebase to separate image annotation logic from the core of marK, making its codebase more extensible and easy to add new annotation types.  


Mentor: [http://invent.kde.org/cdelimacarvalho Caio Jordão Carvalho]
Mentor: [http://invent.kde.org/cdelimacarvalho Caio Jordão Carvalho]
This page is still being written


== Milestones ==
== Milestones ==


* Refactor marK codebase, separating the image annotation logic from the core
* Refactor marK codebase, separating the image annotation logic from the core
** status: Pending
** Status: Doing
* Text Annotation support
* Text Annotation support
** status: Pending
** Status: Pending


== Work Report ==
== Work Report ==


=== Community Bonding Period ===
=== Community Bonding Period ===
I studied how text annotation work, also improved coding techniques, how mark should work, best practices.
blog posts:
[https://jyeno.home.blog/2020/05/12/gsoc-2020-community-bonding-introduction/ community bonding introduction]
[https://jyeno.home.blog/2020/06/01/google-summer-of-code-2020-community-bonding-a-bit-about-text-annotation/ a bit about text annotation]


=== Coding Period - First evaluation ===
=== Coding Period - First evaluation ===
In the first coding period I merged pending code to the master branch in !2. This period marK structure changed and so my plans in how to tackle text annotation. See the posts for more explanation.
blog posts:
[https://jyeno.home.blog/2020/06/22/google-summer-of-code-2020-week-1-2-and-3/ week 1, 2 and 3]


=== Coding Period - Second evaluation ===
=== Coding Period - Second evaluation ===

Revision as of 03:14, 1 July 2020

Project Overview

marK is a machine learning dataset annotation tool being developed that will help users annotate multiple types of data for training in supervised classification problems. The objective of the project is to add text annotation support and refactor the codebase to separate image annotation logic from the core of marK, making its codebase more extensible and easy to add new annotation types.

Mentor: Caio Jordão Carvalho

This page is still being written

Milestones

  • Refactor marK codebase, separating the image annotation logic from the core
    • Status: Doing
  • Text Annotation support
    • Status: Pending

Work Report

Community Bonding Period

I studied how text annotation work, also improved coding techniques, how mark should work, best practices.

blog posts:

community bonding introduction

a bit about text annotation

Coding Period - First evaluation

In the first coding period I merged pending code to the master branch in !2. This period marK structure changed and so my plans in how to tackle text annotation. See the posts for more explanation.


blog posts:

week 1, 2 and 3

Coding Period - Second evaluation

Coding Period - Third evaluation

Important Links

You can see my proposal here. For posts of GSoC 2020, check my blog.

About me

Name: Jean Lima Andrade

Invent id: jyeno

IRC Nick: jyeno

Telegram Nick: jyeno