This article was contributed to the Roboflow blog by Abirami Vina.
Measuring changes to our environment is an important part of understanding progress made toward a more sustainable world. Historically,
Labeling large datasets can be a time-consuming and labor-intensive task. However, with advancements in deep learning and natural language processing, it is now possible to automate the labeling process.
In this comprehensive tutorial, discover how to speed up your image annotation process using Grounding DINO and Segment Anything Model. Learn how to convert object detection datasets into instance segmentation datasets, and use these models to automatically annotate your images.
Roboflow’s Collaborative Annotation
[https://blog.roboflow.com/annotation-workflow/] and Label Only User
[https://blog.roboflow.com/labeler-access/] features have helped over 100,000
users annotate more than 100 million
Computer vision and image processing are used widely in sports to significantly
influence athletes and team performance. Implementing computer vision techniques
is a turning point in the transformation and development
This is a guest post by Kristen Kehrer
, Developer Advocate at CometML [https://www.comet.com/site/]. Since
Roboflow now supports semantic segmentation projects end-to-end allowing you to use Roboflow Annotate to label data, Roboflow Train to build models, and Roboflow Deploy for inference.
This release, alongside support