Kaya tasks semantic and instance segmentation tool

Kaya tasks semantic and instanc…

Kaya Tasks semantic and instance segmentation tool

Kaya Tasks semantic and instance segmentation tool

Kaya Tasks semantic and instance segmentation tool

Associate Product Designer @ SUPA

Associate Product Designer @ SUPA

Product Designer @ SUPA

I gave an image annotation tool for semantic and instance segmentation projects a major revamp with brand new image tools and renewed annotation tools.

I gave an image annotation tool for semantic and instance segmentation projects a major revamp with brand new image tools and renewed annotation tools.

I gave an image annotation tool for semantic and instance segmentation projects a major revamp with brand new image tools and renewed annotation tools.

About Kaya Tasks

SUPA bridges the gap between data labellers (or image annotators) and AI/ML businesses that need image data labelled.


Kaya Tasks is an image annotation tooling platform built by SUPA that allows data labellers to work on image annotation projects created by SUPA's clients.

SUPA bridges the gap between data labellers (or image annotators) and AI/ML businesses that need image data labelled.


Databolt is a B2B SaaS image annotation platform built by SUPA that allows enterprises, data engineers, and data scientists to get their image data annotated by data annotators.

About Databolt

On the demand side of things, Databolt is a B2B SaaS image annotation platform that allows enterprises, data engineers, and data scientists to create projects and get image data annotated by data labellers.

SUPA bridges the gap between data labellers (or image annotators) and AI/ML businesses that need image data labelled.


Databolt is a B2B SaaS image annotation platform built by SUPA that allows enterprises, data engineers, and data scientists to get their image data annotated by data annotators.

The problem

Project objectives

Project objectives

Project objectives

The goal of this design task is ultimately to create a better labelling experience for SUPA's image annotators who are working on semantic segmentation projects.

To improve the SS labelling experience, we are to:

Work on highly requested features

Improve the visual experience

Improve hierarchy and grouping

It was time to automate semantic segmentation projects

Databolt and Kaya Tasks had only accommodated image classification and vector annotation projects at the time of this design task.


Clients who wanted semantic segmentation services from SUPA went through a manual process where our Demand team would create leads for our annotators, and our annotators would use an older tool for image annotation.


Seeing that Databolt and Kaya Tasks were maturing as products that automated this process, the Product team decided that it was time to onboard semantic segmentation projects too.

The older tool was difficult to use

Before, semantic segmentation work would be done on SupaAnnotator, a much older platform for projects manually managed by our project managers.


At its alpha launch, this tool was built sans any design input. It functioned and had facilitated a good amount of data annotation work, but was disorienting especially to first-time users. Annotators had to go through rounds of training to understand how to get work done on the platform.

The research

Understanding semantic segmentation

Before jumping the gun, it was important for me to be clear about what semantic segmentation was and what was required to foster good semantic segmentation work.


In an initial discussion with my product manager, we pinned down the basic aspects of semantic segmentation projects and how they differ from other project types.

Semantic segmentation requires for

Semantic segmentation requires for

Semantic segmentation requires for

Every pixel on an image to be labelled

Annotations to follow the shape of an object

annotations to be able to be viewed or exported as a PNG mask

Studying existing tools in the market

I took a dive into what other semantic segmentation tools looked like, and discussed their strengths and weaknesses with my product manager.


We took note of features that we liked but might be too complex for the first launch, and agreed to keep things relatively simple in its initial phases.

Finding the gaps in our current tool

I talked to our community manager about setting up chats with some of our annotators, to learn more about what they like and dislike about the current tool.


From both the interviews and a feature request survey our team had conducted, we learned a few things.

Most highly-requested features

Most highly-requested features

Most highly-requested features

Undo and redo button

Image tools (Brightness, rotate, etc.)

A way to change the label of an existing annotation

Best rated existing features

Best rated existing features

Best rated existing features

Snapback feature

Mask toggle

Cut tool

Combine toggle

Synthesising interview and survey findings

Based on insights from the user interviews and feature request survey, I hopped onto Miro to map out a summary of the features to add, keep, and drop on the annotation tool, regrouping them into four main categories:


  1. Annotation tools

  2. Image tools

  3. Platform features

  4. Annotation and label features

The process

Starting initial explorations

While making sure I don't stray too far from the existing tooling UI on Kaya Tasks, I played around with how I can distinguish annotation tools from image tools.


I explored an image tool panel on the top right of the screen and a dynamic status bubble on the left that would show what mode the annotator is on.

Design reviews with the Product team

Over insights from many discussions with fellow designers and product managers on grouping behaviours, visual options, selecting flows and more, I iterated on the design in stages.

Internal tests with colleagues at SUPA

I had some of the engineers give the prototype a hands-on try to observe a first-time user's interaction with the interface.


This is when I learned that some potential behaviours hadn't been considered and that I had more exploration work to do.

The outcome

Features snapshot

Features snapshot

Features snapshot

Regrouping and renaming existing annotation tools

Converting draw toggles into draw modes with custom icons

Enabling grouping and combining post-selection

Creating a select mode toolbar variant for post-select action items

Enabling multiple ways to group annotations

Creating new components for annotations

Introducing new image tools

Regrouping and renaming existing annotation tools

The existing tools were lumped together with no visual distinction between — whether they were toggles, image tools, or annotation tools.


Reassessing the grouping of these tools, there were essentially 1 draw tool, 1 cut tool, 1 image tool, and 2 draw toggles (Combine and Overlap).

Decision summary

Decision summary

Decision summary

Retained Draw and Cut as main annotation tools

Turned Combine and Overlap toggles into draw modes

Renamed "Overlap-on" Draw over

Renamed "Combine-on" Draw and combine

Moved the Mask toggle to the image tool panel

Converting draw toggles into draw modes with custom icons

Turning the Combine-on and Overlap-on toggles into draw modes also meant having to re-educate our annotators. To aid that process, I created custom icons to visualise each draw mode.


I initially explored renaming the default draw mode "Draw under", seeing that it was essentially the opposite of "Draw over" with the snapback feature.


However, after considering that our users were already accustomed to the behaviour of the default draw tool, we decided that this would present unnecessary confusion.


In the end, we agreed on retaining the default draw tool as Draw and keeping its icon easily distinguishable from Draw over.

Enabling grouping and combining post-selection

On the old tool, a user could only group or combine annotations by first toggling the Group or Combine toggle on before annotating.


Rethinking their make-up, Combine-on was essentially a draw mode, and Group-on was a select-and-apply feature.To solve this discrepancy in behaviour, I had to reposition these features where they belong.

Decision summary

Decision summary

Decision summary

Turned Combine-on into a draw mode

Included Group and Combine as post-select action items

Renamed the Combine tool in the post-select flow Unite to distinguish it from the draw mode

Creating a select mode toolbar variant for post-select action items

Seeing that users won't be needing to use post-select buttons (such as Group and Combine) before selecting any annotation, I created a select mode toolbar variant for only post-select action items.


By only showing users the Group and Combine buttons in select mode, we save screen real estate on the default toolbar and avoid presenting distractions with disabled buttons.

Enabling multiple ways to group annotations

While conducting internal tests, I asked participants to show me what they would do to group multiple annotations together as one instance. Some interactions I observed had inspired the outcome of the tool.


I decided to include 3 ways to group annotations for more flexibility.

Group button

Selecting more than one annotation and clicking the Group button on the toolbar.

Right-click

Selecting more than one annotation, right clicking, and selecting the Group option.

Drag-to-group

Dragging one or more annotations into another.

Creating new components for annotations

While designing the annotations panel, I kept in mind the basic tasks that our users must be able to perform.

Features to include

Hide and show annotations

Delete annotations

Select single annotation

Select multiple annotations

Change an annotation's label

To show users what they can do with an annotation on an individual level, I enabled a hover state that displays the Hide, Delete, and Select icons upon hover, along with a dropdown for changing an annotation's label.


In select mode, the Hide and Delete buttons only show on the master action bar. This is to make it clear that post-select actions will apply to all selected items.

Introducing new image tools

Image tools are tools that temporarily alter the user's view of the image to aid annotation.


Seeing that the Mask toggle from the old tool served that purpose, I included it as part of the image tool panel along with the Zoom In / Zoom Out buttons, and 2 new features — Rotate and Brighten, which were among the most highly requested features.

Introducing new keyboard shortcuts

Keyboard shortcuts are among our users' best rated features. This prompted us to include shortcuts for all existing and new annotation tools and image tools.


I sectioned the Keyboard Shortcuts modal into two parts — General and Image tools — to make scanning easier for users.

Reflections

Fresh eyes and second opinions go a long way

Apart from internal tests with my colleagues at SUPA that helped me uncover blindspots — weekly reviews, check-ins and consistent moral and technical support from the Product team sustained me throughout the 4-week design process and helped me arrive at a well-rounded outcome.

Handover docs are worth the pain

It was worth putting in a little more work and attention to detail to help engineers understand my designs better. It helped not only engineers but also product managers and designers in finding information about the behaviour of my design elements.

The prototype

View Prototype

© Zoe Chin 2023