It does detection on the backend and then feeds those bounding boxes into SAM running in the browser. This is a little slow on the first pass but allows the user the adjust the bboxes and get new segmentations in nearly real time, without putting a ton of load on the server. Saved me having to label a bunch of holds with precise masks/polygons (I labeled 10k for the detection model and that was quite enough). I might try using SAM's output to train a smaller model in the future, haven't gotten around to it.
(Site is early in development and not ready for actual users, but feel free to mess around.)
It does detection on the backend and then feeds those bounding boxes into SAM running in the browser. This is a little slow on the first pass but allows the user the adjust the bboxes and get new segmentations in nearly real time, without putting a ton of load on the server. Saved me having to label a bunch of holds with precise masks/polygons (I labeled 10k for the detection model and that was quite enough). I might try using SAM's output to train a smaller model in the future, haven't gotten around to it.
(Site is early in development and not ready for actual users, but feel free to mess around.)