OAK-D deploy tool This annotation platform is so much trustworthy for development of computer vision on the edge tasks. Actually I'm working on deploying a detection model on the LUXONIS OAK-D, and has been a magnificent tool.

Excellent annotation tool I tried the free desktop tool. It works really well! Pleasant, intuitive, fast, it can definitely serve for small to medium size projects, as advertised. The annotations are accurate, the .json format to save them is perfectly appropriate. I'll give it 5 stars when it is possible to annotate videos rather than just images. Great tool anyway! [EDIT September 2021] Video annotation is now available, it really is a perfect tool, 5 stars without doubt!

Keywords: Fast, Updates, Reliability SuperAnnotate is fast, have frequent updates, and easy to use. Wholeheartedly recommend this individuals and/or data labeling outfits. Users could literally feel how far the tool has come just months-in use due to the frequency of the updates they deploy. Two of their integral features require special note. The first is the Smart Segmentation tool which helped us speed up our work signfiicantly - particularly useful for geospatial images and other semantic/panoptic segmentation work. The second feature is its workflow, enabling a step-by-step guide for annotators. Its amazing how such a simple tool minimized the time and potential for errors in labeling operations.

Great team, great product, great support We needed an experienced team with great software to help us develop a new pose detection algorithm. We needed to find the right model for our project which required experimentation and iteration with the annotation team. The Superannotate team has the right team at the right price. Their software, customer support and annotators did a great job of executing on our model.

SuperAnnotate: A great tool for data annotation SuperAnnotate is an awesome tool for the researchers/students who are working with the dataset preparation for computer vision related applications such as environment perception including object detection and semantic segmentation. It helped me a lot in my Masters' thesis. Recommended.