Menipy is an alpha-stage Python toolkit for droplet and meniscus shape analysis from images. It provides a PySide6 graphical interface and a headless command line tool for running analysis pipelines from files, cameras, or image directories.

The project currently focuses on image-based workflows for sessile and pendant drop analysis, with additional experimental pipelines under active development.

• Provide a clear, extensible foundation for droplet and meniscus shape analysis from images.
• Model analysis as pipelines where each step represents a concrete stage: loading, preprocessing, segmentation, contour extraction, geometry fitting, metrics, validation, and reporting.
• Support both GUI-driven exploration and headless CLI workflows for automated or batch processing.
• Grow a toolbox of measurements, numerical methods, plugins, and utilities beyond the most common droplet-analysis metrics.
• Keep the project accessible for scientific review by documenting assumptions, limitations, result contracts, and implementation details.

Screenshot: Menipy GUI with image preview, analysis controls, overlays, and results panels.

Menipy is an alpha-stage project under active development and is not production-ready. Most of the implemented methods have not yet been tested or validated against standard measurement methods, so results may be incorrect or inaccurate. This software is not intended to replace validated commercial or non-commercial measurement tools. Use it at your own risk and verify measurements independently before relying on them.

Documentation and references may also contain errors because parts of them were generated with AI assistance. They require human curation and should be independently checked before being relied upon.

Package metadata also marks the project as alpha.

Menipy requires Python 3.10 or newer.

For local development or testing from a source checkout, uv is the preferred method:

uv sync --extra dev --extra test

Run commands in the managed environment with uv run, for example:

uv run menipy
uv run adsa --help

As an alternative, install with Python's built-in virtual environment and pip:

python -m venv .venv
source .venv/bin/activate
python -m pip install --upgrade pip
pip install -e ".[dev,test]"

For a basic editable install without development tools:

pip install -e .

On Windows PowerShell, activate the virtual environment with:

.\.venv\Scripts\Activate.ps1

After installation, start the GUI with:

menipy

Fallback module entry point:

python -m menipy.gui.app

Run the command-line interface with:

adsa --help

Single-image sessile analysis with auto-calibration:

adsa --pipeline sessile --image "data/samples/prueba sesil 2.png" --auto-calibrate --out ./out

Batch analysis of a directory:

adsa --pipeline sessile --input-dir data/samples --glob "*.png" --auto-calibrate --out ./out

The CLI also supports --camera, manual geometry options such as --roi, --needle, and --contact-line, SOP loading with --sop, and plugin database management through the plugins subcommand.

The current pipeline registry exposes these modes:

• sessile
• pendant
• oscillating
• capillary_rise
• captive_bubble

Sessile and pendant workflows are the primary documented user paths. Other pipelines are present for ongoing development and should be treated as experimental unless validated for your use case.

• User guide: DOCUMENTATION.md
• Drop analysis workflow: docs/guides/drop_analysis.md
• Image processing notes: docs/guides/image_processing.md
• Scientific background: docs/guides/base_information.md, docs/guides/physics_models.md, docs/guides/numerical_methods.md
• Developer guides: pipelines, plugins, utilities
• Result contracts: docs/contracts/
• Roadmap: PLAN.md
• Contributing: CONTRIBUTING.md

Historical cleanup notes and archived planning material are preserved under archive/2026-05-cleanup/.

Maintainer: Carlos Renaudo, PLAPIQUI - Planta Piloto de Ingenieria Quimica, Universidad Nacional del Sur/CONICET.