Metadata-Version: 2.1
Name: pyflann-ibeis
Version: 2.3.0
Summary: FLANN (for IBEIS) - Fast Library for Approximate Nearest Neighbors
Home-page: https://github.com/Erotemic/pyflann_ibeis
Author: Jon Crall, Marius Muja
Author-email: erotemic@gmail.com
License: BSD
Platform: UNKNOWN
Classifier: Development Status :: 6 - Mature
Classifier: License :: OSI Approved :: BSD License
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Unix
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Image Recognition
Requires-Python: >=3.7
Description-Content-Type: text/x-rst
Provides-Extra: all
Provides-Extra: build
Provides-Extra: runtime
Provides-Extra: tests
License-File: COPYING

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This is a Fork of the FLANN repo, under a different name for use in the IBEIS
project. The main difference is that it has a few more helper function calls
and it should be easier build wheels and to pip install.


FLANN - Fast Library for Approximate Nearest Neighbors
======================================================

FLANN is a library for performing fast approximate nearest neighbor searches in high dimensional spaces. It contains a collection of algorithms we found to work best for nearest neighbor search and a system for automatically choosing the best algorithm and optimum parameters depending on the dataset.
FLANN is written in C++ and contains bindings for the following languages: C, MATLAB, Python, and Ruby.


Documentation
-------------

Check FLANN web page [here](http://www.cs.ubc.ca/research/flann).

Documentation on how to use the library can be found in the doc/manual.pdf file included in the release archives.

More information and experimental results can be found in the following paper:

  * Marius Muja and David G. Lowe, "Fast Approximate Nearest Neighbors with Automatic Algorithm Configuration", in International Conference on Computer Vision Theory and Applications (VISAPP'09), 2009 [(PDF)](http://people.cs.ubc.ca/~mariusm/uploads/FLANN/flann_visapp09.pdf) [(BibTex)](http://people.cs.ubc.ca/~mariusm/index.php/FLANN/BibTex)


Getting FLANN
-------------

If you want to try out the latest changes or contribute to FLANN, then it's recommended that you checkout the git source repository: `git clone git://github.com/mariusmuja/flann.git`

If you just want to browse the repository, you can do so by going [here](https://github.com/mariusmuja/flann).


Conditions of use
-----------------

FLANN is distributed under the terms of the [BSD License](https://github.com/mariusmuja/flann/blob/master/COPYING).

Bug reporting
-------------

Please report bugs or feature requests using [github's issue tracker](http://github.com/mariusmuja/flann/issues).


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