# threshold below which boxes will be filtered out
conf: float = 0,
# discards all overlapping boxes with IoU > iou_threshold
iou: float = .05,
Incorporating FastSAM with parameterizable NMS would greatly increase the utility of SoM for tasks requiring high sensitivity and with many different objects.
Alternative suggestions for increasing the sensitivity with the current segmentation models would be greatly appreciated! 🙏
Segmenting images with many distinct objects results in many objects being missed, e.g.:
(Notice not all cells are marked.)
In https://github.com/OpenAdaptAI/OpenAdapt/pull/679 we have good results using Ultralytics FastSAM for segmentation with very small values for non maximum suppression
conf
andiou
:Incorporating FastSAM with parameterizable NMS would greatly increase the utility of SoM for tasks requiring high sensitivity and with many different objects.
Alternative suggestions for increasing the sensitivity with the current segmentation models would be greatly appreciated! 🙏