The geosam R package brings Meta's Segment Anything Model 3 (SAM3) to R for detecting objects in satellite imagery and photos. Describe what you're looking for in plain text—no training data or model fine-tuning required. The package is inspired by the Python package segment-geospatial by Qiusheng Wu, and aims to bring similar functionality to R users.

Install the development version from GitHub:

remotes::install_github("walkerke/geosam")

Then set up the Python environment:

library(geosam)
geosam_install()

You'll need a HuggingFace account with access to the SAM3 model.

Read through these vignettes to learn how to use the package:

• Getting started with geosam

• Satellite imagery detection

• Regular image detection

• Interactive workflows

If you find this project useful in your work and would like to ensure continued development of the package, you can provide support in the following ways:

• Chip in some funds to support package development via PayPal;
• Set up a consulting engagement or workshop through Walker Data to help you implement geosam in your project. Send a note to kyle@walker-data.com if you are interested;
• File an issue - or even better, a pull request - at https://github.com/walkerke/geosam/issues.

To stay on top of package updates / new features and to get information about trainings, be sure to sign up for the Walker Data mailing list here.