samstars

samstars is a Python library for instance segmentation of individual trees using high-resolution imagery and lidar-derived rasters.

Installation

For users, install the published library from PyPI:

python -m pip install samstars

samstars supports Python 3.10 through 3.12 on Linux x86-64 and Apple Silicon macOS. CPU execution is the baseline. Apple Silicon users can install optional TensorFlow Metal support with python -m pip install "samstars[metal]"; Linux CUDA users should install a matched PyTorch/Torchvision build using the official PyTorch selector before installing samstars.

samstars does not bundle trained model files. See docs/training.md and docs/segmentation.md to train a model bundle and run segmentation.

Developer setup

For local development from a clone:

python -m pip install -e .

Install the test dependencies and run the functional suite with:

python -m pip install -e ".[test]"
python -m pytest

For documentation development:

python -m pip install -e ".[docs]"
mkdocs serve

For platform-specific development environments, use the Conda environment files in this repository:

conda env create -f environment.ubuntu.samstars.yml
conda activate samstars
python -m pip install -e .

On Apple Silicon macOS, use environment.macos.samstars.yml instead. These environment files provide Python 3.10 CPU baselines; accelerator setup is described in docs/installation.md.

Notes

  • Python 3.10 through 3.12 is supported on Linux x86-64 and Apple Silicon macOS.
  • CPU execution is the default; CUDA, MPS, and TensorFlow Metal are opt-in accelerators.
  • Segmentation runs require a trained samstars model bundle.
  • The intended workflow is to train a model bundle for your data and then use it for segmentation.

Project links

Data verified by PyPI on Jul 23, 2026
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Credits

Author: Iosefa Percival

GitHub Statistics

Data verified by PyPI on Jul 23, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License expression

MIT
View SPDX License List

Requires

Python <3.13, >=3.10

Provides Extra

metal test docs

Tags

segmentation remote-sensing lidar imagery geospatial

Classifiers

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