ivpy: Iconographic Visualization Inside Computational Notebooks

ivpy: Iconographic Visualization Inside Computational Notebooks. Crockett, D. International Journal for Digital Art History, 2019. Number: 4

Paper doi abstract bibtex

Iconographic Visualization in Python, or ivpy, is a software module, written in the Python programming language, that provides a set of functions for organizing iconographic representations of data, including images and glyphs. The module also provides methods for extracting visual features from images; generating and hand-tuning clusters of data points; and embedding high-dimensional data in 2D coordinate spaces. It is designed for use inside computational notebooks, so that users working with data needn't leave the notebook environment in order to generate visualizations. The software is designed primarily for those researchers working with large image datasets in fields where human visual expertise cannot be replaced with or superseded by machine vision, such as art history and media studies.

@article{crockett_ivpy_2019,
	title = {ivpy: {Iconographic} {Visualization} {Inside} {Computational} {Notebooks}},
	copyright = {Copyright (c) 2019},
	issn = {2363-5401},
	shorttitle = {ivpy},
	url = {https://journals.ub.uni-heidelberg.de/index.php/dah/article/view/66401},
	doi = {10.11588/dah.2019.4.66401},
	abstract = {Iconographic Visualization in Python, or ivpy, is a software module, written in the Python programming language, that provides a set of functions for organizing iconographic representations of data, including images and glyphs. The module also provides methods for extracting visual features from images; generating and hand-tuning clusters of data points; and embedding high-dimensional data in 2D coordinate spaces. It is designed for use inside computational notebooks, so that users working with data needn't leave the notebook environment in order to generate visualizations. The software is designed primarily for those researchers working with large image datasets in fields where human visual expertise cannot be replaced with or superseded by machine vision, such as art history and media studies.},
	language = {en},
	number = {4},
	urldate = {2021-08-17},
	journal = {International Journal for Digital Art History},
	author = {Crockett, Damon},
	year = {2019},
	note = {Number: 4},
	keywords = {art history},
	pages = {3.60--3.79},
}

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