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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