Introducing best-in-class image annotation tools for computer vision applications

Written by labelbox | Published 2018/09/29
Tech Story Tags: machine-learning | labelbox-product-updates | deep-learning | image-recognition | computer-vision

TLDRvia the TL;DR App

September brought many new features and updates to Labelbox. But most notable is that the image annotation interface has undergone a massive upgrade.

Fast & Intuitive Interface Configuration

We’ve added a much simpler way for you to customize the image labeling interface. Introducing the Form-based Interface Configuration Tool. With this new interface configurator, you can easily set up your labeling task using all of the available segmentation & classification tools using an intuitive web form instead of coding JSON. Still prefer the JSON? It’s available by switching the configuration screen from ‘FORM’ to ‘JSON’ at the top.

Annotate images with pixel level accuracy

Sometimes you need pixel perfect annotations. Labelbox now offers advanced pixel-wise annotation tools, including a blazing fast (and browser side!) superpixel tool. Also available are the complimentary brush and eraser tools. Empower your annotation team with Labelbox’s best-in-class pixel-wise annotation toolkit.

BrushA pixel accurate brush tool is also available for use. It’s mechanics are consistent with most digital brush tools available in creativity software today. The brush tool is often used to do final touch-up after using the superpixel tool.

SuperpixelsFor many pixel level annotation tasks the goal is to label a homogenous grouping (or groups) of pixels. An example of this is detecting clouds in satellite imagery. For these tasks, the superpixel tool is often an extremely efficient method for annotation. Superpixels are computed groupings of pixels, and in the case of Labelbox are computed in the browser so that you can use this tool seamlessly on your private data. For optimal performance of superpixel, we recommend using the Google Chrome Browser.

EraserThe eraser tool removes the assigned class from the pixels it is applied to.

Bounding boxes, polygons, lines, points and nested classifications

Get Started with Labelbox

Visit www.labelbox.com to explore Labelbox for free or speak to one of our team members about an enterprise solution for your business.


Published by HackerNoon on 2018/09/29