> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.ovalbee.com/use-cases/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.ovalbee.com/_mcp/server.

# Use cases

## Docs

- [Use cases](https://docs.ovalbee.com/use-cases/overview.md): Common computer vision jobs, the flow shape that solves each one, and a template to start from.
- [Bring data into OvalBee](https://docs.ovalbee.com/use-cases/bring-data-in.md): Upload your own images and videos, pull a public dataset, or import a Supervisely project.
- [Organize labeling](https://docs.ovalbee.com/use-cases/organize-labeling.md): Turn a pool of images into reviewed annotations, with every image's state visible on the canvas.
- [Check and clean a dataset](https://docs.ovalbee.com/use-cases/check-and-clean-data.md): Find what's wrong with a dataset before training does it for you, and fix it with rules you can rerun.
- [Try a pretrained detector](https://docs.ovalbee.com/use-cases/try-a-pretrained-detector.md): See what an off-the-shelf model finds on your own images before you spend anything on labels.
- [Train a detector](https://docs.ovalbee.com/use-cases/train-a-detector.md): Split a labeled dataset, fine-tune a detector on it and see whether training actually converged.
- [Evaluate and compare models](https://docs.ovalbee.com/use-cases/evaluate-and-compare.md): Score a detector against ground truth, and choose between several with the same evaluation.