cie-utils 1.0.0

Image processing based on CIELAB color space.

🌈 cie-utils

Advanced image processing in Python using the CIELAB color space.

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cie-utils is a Python library for image preprocessing and color analysis using the perceptually uniform CIELAB color space.

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✨ Features

✅ RGB ➡️ LAB / Lch conversion
✅ CLAHE, PCA, false color filters
✅ Background removal via pixel std deviation
✅ Cluster-based segmentation: KMeans, GaussianMixture, Agglomerative
✅ Histogram, PDF, and scatter plot visualization
✅ CSV export of processed image stats
✅ Clean and modular structure for reuse

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📦 Installation

From PyPI

pip install cie-utils

From GitHub

pip install git+https://github.com/jarh1992/cie-utils.git

From local source (for development)

# Using Poetry (recommended for development)
poetry install

# Or using pip
pip install .

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🧪 Example Usage

from cie-utils import normalize_img, rgb2lab

lab_img = rgb2lab(normalize_img(img, ref_img))

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🧰 Development & Code Style

This project uses Poetry for dependency management:

• 🖤 black for code formatting
• 🔠 isort for import sorting
• 🧼 flake8 for linting
• ✅ pytest for testing
• 🧪 pre-commit hooks enabled in .pre-commit-config.yaml

To install dev dependencies:

poetry install
poetry run pre-commit install

Run tests:

poetry run pytest

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📚 Documentation

Documentation is automatically generated with Sphinx and hosted via GitHub Pages:

👉 https://jarh1992.github.io/cie-utils/

Documentation is automatically rebuilt and deployed on every release.

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🚀 Release Process

Releases are automated via GitHub Actions. To create a new release:

./release_workflow.sh [patch|minor|major]

This will:

1. Bump the version in pyproject.toml
2. Commit and push a version tag
3. GitHub Actions automatically:
   • Runs tests on Python 3.11 and 3.12
   • Publishes the package to PyPI
   • Deploys updated documentation to GitHub Pages

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📝 License

MIT License. See LICENSE for details.