Launch: Auto Label Images with Roboflow

Roboflow has introduced Auto Label, a beta tool designed to streamline the data annotation process for computer vision projects by automatically labeling images through text prompts, significantly reducing the time and cost associated with manual annotation. This tool utilizes foundation models like Grounding DINO and GroundingSAM, which are zero-shot models capable of working without custom data fine-tuning, making it effective from the onset of a project. Users can test various prompts to optimize labeling accuracy, with Auto Label capable of cutting human labeling efforts by 50% when it labels half of the images accurately. Accessible through the Roboflow project dashboard, Auto Label supports different image upload methods and offers features such as prompt experimentation, batch labeling, and annotation review to ensure high-quality results. Currently in beta, Auto Label is available for all Roboflow users, with ongoing improvements and feedback encouraged through the Roboflow User Forum.