Compare Ango Hub vs. Scalabel

Ango Hub is an all-in-one, quality-oriented data annotation platform that AI teams can use. Ango Hub is available on-premise and in the cloud. It allows AI teams and their data annotation workforces to quickly and efficiently annotate their data without compromising quality. Ango Hub is the only data annotation platform that focuses on quality. It features features that enhance the quality of your annotations. These include a centralized labeling system, a real time issue system, review workflows and sample label libraries. There is also consensus up to 30 on the same asset. Ango Hub is versatile as well. It supports all data types that your team might require, including image, audio, text and native PDF. There are nearly twenty different labeling tools that you can use to annotate data. Some of these tools are unique to Ango hub, such as rotated bounding box, unlimited conditional questions, label relations and table-based labels for more complicated labeling tasks.

Facilitate a variety of annotation types for both images and videos through a flexible, open-source web-based tool. This tool is designed to scale and supports user-friendly “click and drag” functionalities, allowing for the addition of multiple attributes with ease. It incorporates features that enable the fitting of boundaries using Bezier curves and the ability to duplicate shared boundaries. Users can annotate the specific areas where a driver is operating and mark lane lines to enhance vision-based vehicle localization and trajectory planning. An intuitive four-click method is employed to accurately encapsulate objects of interest, while advanced algorithms predict annotations across frames by utilizing object tracking and interpolation techniques for bounding boxes. It also offers prediction capabilities for individual object instances, with 2D tracking functionalities expanded into a three-dimensional context, enhancing the overall annotation process. This comprehensive tool aims to streamline the workflow for users involved in image and video annotation tasks.