Creates a Python virtual environment and installs required packages for SAM3 inference. This only needs to be run once.
Usage
geosam_install(
envname = "geosam",
method = c("uv", "virtualenv", "conda"),
gpu = NULL,
hf_token = NULL,
python_version = "3.12"
)Arguments
- envname
Name of the virtual environment to create (default: "geosam")
- method
Installation method: "uv" (recommended, fast), "virtualenv", or "conda". uv is the default and recommended approach.
- gpu
Logical. If TRUE, installs GPU-enabled PyTorch. If NULL (default), auto-detects based on available hardware.
- hf_token
Optional HuggingFace token for accessing SAM3 model weights. Can also be set via the HF_TOKEN environment variable. Required for SAM3.
- python_version
Python version to use (default: "3.12"). SAM3 requires 3.12+.
Details
This function installs:
PyTorch 2.7+ (with MPS support on Apple Silicon, CUDA 12.6+ on NVIDIA GPUs)
SAM3 from Meta (https://github.com/facebookresearch/sam3)
rasterio, geopandas, shapely, pyproj (geospatial processing)
Installation Methods
uv (recommended): Fast, modern Python package manager. Install uv first:
# macOS/Linux
curl -LsSf https://astral.sh/uv/install.sh | sh
# Windows (PowerShell)
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
# Or via pip (any platform)
pip install uvvirtualenv: Uses Python's built-in venv via reticulate. Requires Python 3.12+ to be installed on your system.
conda: Uses conda/miniconda. Slower but handles complex dependencies well.
