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)

Technical

Title
LabelGPT
Requirements
  • Web App
Language
No language has been specified.
Available languages
License
  • Full
Latest update
2025-06-03
Author
labellerr
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