LabelGPT for Web

Quick summary

LabelGPT is a browser-based image annotation platform that uses a generative AI backbone to speed up labeling for computer vision projects. By producing automatic labels for raw images, it shortens data-preparation time and lowers the manual effort needed for training vision models.

Where you can bring data from

• Through programmatic access (APIs)
• Microsoft Azure storage
• Google Cloud Storage
• Amazon S3
• Local folders and drives

How labels are produced

The system employs a zero-shot generation approach: you provide class or object names as plain-text prompts and the model predicts bounding boxes and segmentation masks without prior per-class training. This generative pipeline supports both detection and pixel-level segmentation tasks.

Quality control and pipeline output

LabelGPT provides a built-in review workflow that:

• Lets you screen and sort annotations by confidence values
• Shows visual previews so you can validate or correct results manually
• Exports annotations in standard formats for seamless ingestion into model training pipelines

These capabilities help accelerate model iteration and reduce labeling expenses.

Other options to consider

• RegexBot (commercial)