Superannote I have had the opportunity to work on the platform for 4 months and have seen first-hand how intently they respond to our feedback and provide updates that boost efficiency even further. Few features in SuperAnnotate are just a lifesaver for annotators. It provides a great deal of editing capability on existing annotated images. This has been crucial in some of the work we have performed using this platform. Also with great ease of use coming from features like auto-segmentation and the superb project-based analytics generated to keep the management side organized, it’s almost impossible not to recommend SuperAnnotate. I have found this one of the only platforms to use Neural Network training, Quality Control, and AI-Augmentation. I hope to explore more of these features further for research purposes and project requirements.

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.

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.

5* - Great efficient tool with good UX and an extremely helpful Customer service team. Our main consideration for a tool was something that could handle an extremely large data set with around a million to 2 million images. We have shortlisted a lot of tools but we ended up choosing super-annotate as it had an user friendly UX and very high rate of annotation. The way we have handled a team of 40-50 annotators was very easy and hassle free.

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.