Data Labeller
- 2 Devlogs
- 4 Total hours
Three-step process that utilises AI to arrive at accurate labels for images, videos and audio.
Three-step process that utilises AI to arrive at accurate labels for images, videos and audio.
Added a text area for labellers to input their names, and updated the “submit labels” button so that it now collects labels from ticked checkboxes and other descriptive labels, and sends them to the database.
So now the labeller’s name and the labels can be recorded in the database! Next step is to integrate AI for checking.
Admin page (and connected to backend) done, where “admins” insert urls to be labelled as requested by clients and identify possible categories all urls might fall under, and submit urls and categories to the database. Labeller page partially done, where labellers “get a new task” that renders a url and lists categories as checkboxes to be ticked off and an additional textbox for any additional identifiable labels. To-do next: connect label submission buttons to endpoint in backend.