{ "info": { "author": "Laurent Perrinet INT - CNRS", "author_email": "Laurent.Perrinet@univ-amu.fr", "bugtrack_url": null, "classifiers": [ "Development Status :: 3 - Alpha", "Environment :: Console", "Intended Audience :: Science/Research", "License :: OSI Approved :: GNU General Public License (GPL)", "Operating System :: POSIX", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.6", "Topic :: Scientific/Engineering", "Topic :: Scientific/Engineering :: Image Recognition", "Topic :: Scientific/Engineering :: Medical Science Apps.", "Topic :: Scientific/Engineering :: Visualization", "Topic :: Utilities" ], "description": "[![PyPI version](https://badge.fury.io/py/SparseEdges.svg)](https://badge.fury.io/py/SparseEdges)\n[![Research software impact](http://depsy.org/api/package/pypi/SparseEdges/badge.svg)](http://depsy.org/package/python/SparseEdges)\n\nWhat is the SparseEdges package?\n================================\n\nOur goal here is to build practical algorithms of sparse coding for computer vision.\n\nThis class exploits the [SLIP](https://pythonhosted.org/SLIP/) and [LogGabor](https://pythonhosted.org/LogGabor/) libraries to provide with a sparse representation of edges in images.\n\nThis algorithm was presented in the following paper:\n\n~~~~{.bibtex}\n@inbook{Perrinet15bicv,\n author = {Perrinet, Laurent U.},\n booktitle = {Biologically-inspired Computer Vision},\n chapter = {13},\n citeulike-article-id = {13566753},\n editor = {Keil, Matthias and Crist\\'{o}bal, Gabriel and Perrinet, Laurent U.},\n keywords = {anr-trax, bicv-sparse},\n posted-at = {2015-03-31 14:21:35},\n priority = {2},\n publisher = {Wiley, New-York},\n title = {Sparse models},\n year = {2015}\n}\n~~~~\n\nThis package gives a python implementation.\n\nMoreover, it gives additional tools to compute useful stistics in images; first- and second order statistics of co-occurences in images.\nMore information is available @ 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