Segment Anything Model in QuPath

All credit goes to Ko Sugawara for developing this extension; I'm just playing around with it: https://forum.image.sc/t/qupath-exten...
QuPath SAM extension: https://github.com/ksugar/qupath-exte...
Web API for SAM: https://github.com/ksugar/samapi
BioRxIV citation:
```
@article {Sugawara2023.06.13.544786,
author = {Ko Sugawara},
title = {Training deep learning models for cell image segmentation with sparse annotations},
elocation-id = {2023.06.13.544786},
year = {2023},
doi = {10.1101/2023.06.13.544786},
publisher = {Cold Spring Harbor Laboratory},
abstract = {Deep learning is becoming more prominent in cell image analysis. However, collecting the annotated data required to train efficient deep-learning models remains a major obstacle. I demonstrate that functional performance can be achieved even with sparsely annotated data. Furthermore, I show that the selection of sparse cell annotations significantly impacts performance. I modified Cellpose and StarDist to enable training with sparsely annotated data and evaluated them in conjunction with ELEPHANT, a cell tracking algorithm that internally uses U-Net based cell segmentation. These results illustrate that sparse annotation is a generally effective strategy in deep learning-based cell image segmentation. Finally, I demonstrate that with the help of the Segment Anything Model (SAM), it is feasible to build an effective deep learning model of cell image segmentation from scratch just in a few minutes.Competing Interest StatementKS is employed part-time by LPIXEL Inc.},
URL = {https://www.biorxiv.org/content/early...},
eprint = {https://www.biorxiv.org/content/early...},
journal = {bioRxiv}
}
```