awesome-data-labeling

Why we included this project

Choosing an annotation tool is usually the first step in building a training dataset, and this list gathers dozens of the main options in one place. It covers image, video, audio, and 3D/LiDAR labeling projects, from simple desktop bounding-box editors like labelImg to collaborative web platforms and semi-automatic tools that suggest annotations from pretrained models. Entries are grouped by data type, so you can compare tools for your specific modality without hunting across separate repositories. The list is maintained by the team behind Label Studio, so the selection reflects hands-on experience with labeling data at scale. It is a reference index rather than software you run yourself, but it saves real time when you are evaluating annotation workflows.