Metadata-Version: 2.2
Name: bioimage-cpp
Version: 0.8.0
Summary: Dependency-light C++ bioimage analysis algorithms with Python bindings
Author: bioimage-cpp contributors
License: MIT
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: C++
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
Classifier: Topic :: Scientific/Engineering :: Image Processing
Project-URL: Homepage, https://github.com/computational-cell-analytics/bioimage-cpp
Project-URL: Repository, https://github.com/computational-cell-analytics/bioimage-cpp
Project-URL: Issues, https://github.com/computational-cell-analytics/bioimage-cpp/issues
Requires-Python: >=3.10
Requires-Dist: numpy
Provides-Extra: test
Requires-Dist: pytest; extra == "test"
Requires-Dist: pooch; extra == "test"
Requires-Dist: scipy; extra == "test"
Provides-Extra: data
Requires-Dist: pooch; extra == "data"
Description-Content-Type: text/markdown

# bioimage-cpp

[![Documentation](https://img.shields.io/badge/docs-pdoc-blue)](https://computational-cell-analytics.github.io/bioimage-cpp/)
[![Build Status](https://github.com/computational-cell-analytics/bioimage-cpp/actions/workflows/tests.yml/badge.svg)](https://github.com/computational-cell-analytics/bioimage-cpp/actions/workflows/tests.yml)
[![PyPI](https://img.shields.io/pypi/v/bioimage-cpp)](https://pypi.org/project/bioimage-cpp/)
[![conda-forge](https://img.shields.io/conda/vn/conda-forge/bioimage-cpp)](https://anaconda.org/conda-forge/bioimage-cpp)

Image processing and segmentation functionality in C++ with light-weight python bindings through nanobind and minimal dependencies to enable distribution via pip.

The package includes dependency-free triangle-mesh extraction from 3D volumes
and segmentation masks, plus Laplacian mesh smoothing, under `bioimage_cpp.mesh`.
It also includes exact masked-grid Dijkstra paths under `bioimage_cpp.distance`
and binary-forest plus semantic multi-label 3D TEASAR skeletonization under
`bioimage_cpp.skeleton`.

The `bioimage_cpp` python library can be installed via pip:
```bash
pip install bioimage-cpp
```

Or via conda-forge:
```bash
conda install -c conda-forge bioimage-cpp
```

Please refer to [the documentation](https://computational-cell-analytics.github.io/bioimage-cpp/) for details.

**Disclaimer:** The functionality of this library was implemented mainly by coding agents (Claude Code and OpenAI Codex).
We have made our best efforts to test the implementations thoroughly and are already using it heavily in our day-to-day research and have integrated with other software tools.
Nevertheless, it may contain bugs or unintended behavior (as most software does).
If you find such a problem, please [open an issue on github](https://github.com/computational-cell-analytics/bioimage-cpp/issues).
We are committed to improving and mainting this software.
