> For the complete documentation index, see [llms.txt](https://docs.unitlab.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.unitlab.ai/documentation/auto-labeling.md).

# AUTO-LABELING

- [Detect Anything (SAM 1–SAM 3)](https://docs.unitlab.ai/documentation/auto-labeling/detect-anything-sam-1-sam-3.md): Choose and operate Unitlab’s SAM-assisted segmentation, class-prompt detection, and supported geometry workflows.
- [Find Similar](https://docs.unitlab.ai/documentation/auto-labeling/find-similar.md): Use one verified box, polygon, mask, or cuboid to find and review similar objects in the current image or frame.
- [Prompt Labeling](https://docs.unitlab.ai/documentation/auto-labeling/prompt-labeling.md): Describe a visual concept in natural language and create editable, class-bound SAM 3 proposals.
- [Bidirectional Auto-Tracking](https://docs.unitlab.ai/documentation/auto-labeling/bidirectional-auto-tracking.md): Track objects forward, backward, or through the full video, DICOM, or NIfTI sequence from one reliable seed.
- [Batch Auto-Labeling](https://docs.unitlab.ai/documentation/auto-labeling/batch-auto-labeling.md): Run models at scale with workflow Model stages, human correction routes, queues, monitoring, and failure recovery.
- [Batch Classification](https://docs.unitlab.ai/documentation/auto-labeling/batch-classification.md): Classify project cohorts operationally by applying governed tags to selected items without confusing metadata with ontology labels.
- [Bring your own Models](https://docs.unitlab.ai/documentation/auto-labeling/bring-your-own-models.md): Register, validate, map, secure, and operate private HTTP inference models inside Unitlab workflows.