--- library_name: ultralytics license: agpl-3.0 pipeline_tag: image-segmentation --- # Model Card for Delineate Anything: Resolution-Agnostic Field Boundary Delineation on Satellite Imagery by [Mykola Lavreniuk](https://scholar.google.com/citations?hl=en&user=-oFR-RYAAAAJ), [Nataliia Kussul](https://scholar.google.com/citations?user=e3TWBuwAAAAJ&hl=en), [Andrii Shelestov](https://scholar.google.com/citations?user=tqoQKZAAAAAJ&hl=en), [Yevhenii Salii](https://scholar.google.com/citations?user=4jgAsBIAAAAJ&hl=en), [Volodymyr Kuzin](https://www.researchgate.net/profile/Volodymyr-Kuzin), [Sergii Skakun](https://scholar.google.com/citations?user=G9_6G6IAAAAJ&hl=en), [Zoltan Szantoi](https://scholar.google.com/citations?user=P_pyhi8AAAAJ&hl=en) **Delineate Anything Flow (DelAnyFlow)** is a resolution-agnostic methodology for fast, country-level agricultural field boundary detection from satellite imagery. It utilizes the **DelAny** instance segmentation model, which is based on a YOLOv11 backbone and trained on the large-scale Field Boundary Instance Segmentation-22M (FBIS 22M) dataset. DelAny delivers state-of-the-art accuracy, showing significantly higher mAP and faster inference than alternatives like SAM2. It supports national-scale applications, having been used to generate a complete field boundary layer for Ukraine (603,000 km²) in under six hours. ![intro](figs/intro.jpg) ## Paper [Delineate Anything Flow: Fast, Country-Level Field Boundary Detection from Any Source](https://arxiv.org/abs/2511.13417) ## Citation ```bibtex @misc{lavreniuk2025delineate, title={Delineate Anything Flow: Fast, Country-Level Field Boundary Detection from Any Source}, author={Mykola Lavreniuk and Nataliia Kussul and Andrii Shelestov and Yevhenii Salii and Volodymyr Kuzin and Sergii Skakun and Zoltan Szantoi}, year={2025}, eprint={2511.13417}, archivePrefix={arXiv}, primaryClass={cs.CV}, url={https://arxiv.org/abs/2511.13417}, } ```