Skip to content

WildMeOrg/wbia-tpl-pyflann

 
 

Repository files navigation

Wildbook IA - PyFlann

Build and upload to PyPI (main) Latest PyPI version Documentation on ReadTheDocs

FLANN - Fast Library for Approximate Nearest Neighbors! - Part of the WildMe / Wildbook IA Project.

This is a Fork of the FLANN repo, under a different name for use in the Wildbook 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 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:

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).

Build and Installation

This package requires the following system dependencies:

  • lz4 (in debian as liblz4)
  • pkg-config (in debian as pkg-config)
  • gcc (use build-essential in debian)

For development use the run_develop_setup.sh script.

Conditions of use

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

About

Fast Library for Approximate Nearest Neighbors

Resources

License

Security policy

Stars

Watchers

Forks

Packages

No packages published

Languages

  • C++ 73.3%
  • Python 10.0%
  • Cuda 8.0%
  • C 4.3%
  • CMake 4.0%
  • Shell 0.2%
  • Other 0.2%