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.

Extraordinary platform for labeling Fully satisfied with SuperAnnotate's platform. Obvious advantages over other platforms particularly moving very fast and smooth during annotation work. From where I come from, the network tends to be a problem with frequent dips that rendered other platforms in the space along with image labeling work very hard. SuperAnnotate is amazing in the sense that it caches both server-side and individual machine data which saves me a lot of time.

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.

Extremely helpful and convenient Extremely helpful and convenient was looking for a tool to annotate documents for my master-thesis - found this via open-cv. good examples, easy to learn, and covers all my use-cases (separate folders for separate documents for instance). the webservice is top-notch, uploads work fast, and the entire project can be stored in one place and accessed from anywhere. Since i reached the limit for the free version, i reached out to the team, which got back to me instantly and gave me an appointment on the following day. the staff is very friendly, understanding and supportive! now i can conduct my research exactly the way i need - big thanks and a clear recommendation for anyone with a use case :)

Convenient, easy to capture edges, cool workflow. SuperAnnotate is very adaptable. All the tools are very reliable and helps a project run smoothly. I love the frequent updates the comfortable shift to a new UI or feature immersion. Their smart segmentation work is awesome and reduces work for semantic-tier labeling more than 50% by my account.