Labeling data in image, text, audio so it can be recognized by machine learning model.
Define users and their key journeys
Identified important interactions and user pain points along the journey.
Conducted competitive research to assess what are the potential strengths and weaknesses of current data annotation platforms in the market.
Gather all information from stakeholders and POC reviews to come up with a structure and workflow.
Design and Prototype
Created different mock-ups and prototype to get reviewed by stakeholders.
Utilized the whole screen for the user to focus more on the workspace.
Hide notable areas like the overview and instructions and will only be shown once the project starts and the user clicked on the subheader expanded button.
Placed the annotation classes on the left sidebar with icons and colors so it'll be easier for the user to recognize what type of annotation tool is selected.
Image annotation can be zoomed in/ out for detailed selection and accessibility.
Introduce the option to hide and show classes for overlapping annotation cases.