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v0.1.1 - Documentation and CI/CD Improvements

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@fmegahed fmegahed released this 06 Nov 17:46
· 3 commits to main since this release
v0.1.1
d6dd153

Release Notes - v0.1.1

Overview

This patch release improves the package documentation, adds automated CI/CD workflows, and establishes the package as a companion to the upcoming clip-conformal package.

What's New

Documentation Improvements

  • Enhanced README: Repositioned the package as a companion data package for clip-conformal
  • Installation Guide: Added clear pip installation instructions
  • Quick Start Example: Included Python code snippet for immediate usage
  • Relationship Section: Explained the complementary nature with clip-conformal package
  • Proper Citations: Added BibTeX format citations with correct author information
  • Improved Table Formatting: Fixed dataset summary table to render properly in Markdown

Automation & Infrastructure

  • GitHub Actions CI: Automated testing across Python 3.9-3.12
  • Automated PyPI Publishing: Push a version tag to automatically release to PyPI
  • Release Instructions: Comprehensive guide for maintainers (RELEASE.md)
  • Development Setup: Added .gitignore for cleaner repository management

Installation

pip install conformal-clip-data==0.1.1

Quick Start

from conformal_clip_data import get_data_path

# Access the textile dataset
data_path = get_data_path("textile")
print(f"Dataset location: {data_path}")

Dataset Contents

The textile image dataset remains unchanged from v0.1.0:

Class Count
Nominal images 1,000
Local defects 500
Global defects 500

All images are 250 × 250 px, generated using the spc4sts R package.

Citation

If you use this dataset, please cite:

@misc{megahed2025adaptingopenaisclipmodel,
      title={Adapting OpenAI's CLIP Model for Few-Shot Image Inspection in Manufacturing Quality Control: An Expository Case Study with Multiple Application Examples},
      author={Fadel M. Megahed and Ying-Ju Chen and Bianca Maria Colosimo and Marco Luigi Giuseppe Grasso and L. Allison Jones-Farmer and Sven Knoth and Hongyue Sun and Inez Zwetsloot},
      year={2025},
      eprint={2501.12596},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2501.12596},
}

Coming Soon

The clip-conformal package will be released to PyPI shortly, providing full implementation of conformal prediction methods for CLIP models, with complete examples using this dataset.

Full Changelog

See CHANGELOG.md for complete details.

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