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Build KD-Trees and perform Nearest Neighbor searches

License: MIT License

C++ 99.92% Makefile 0.08%
kd-tree nn nearest-neighbor-search nearest-neighbors nearest-neighbours kdtrees bsp bsp-tree

kd-tree's Introduction

KD-Tree Library

This library provides an implementation for building KD-Trees and performing nearest-neighbor searches. It is templated such that it supports float and double precision types for any set of k-dimensional points.

Directory Structure

kd-tree/

  • data/                   Sample input, query and tree data
  • include/              External header files to be used
  • src/                     All source files (*.cpp, *.h)
  • LICENSE.txt       MIT License boilerplate
  • Makefile              To build the package
  • README.txt       This file

Build Instructions

This library uses C++11 features and was tested on Ubuntu 14.04.05 LTS (trusty) 64-bit using the compiler: g++ (Ubuntu 4.8.4-2ubuntu1~14.04.3) 4.8.4

To build, clone the package and run the Makefile in the kd-tree folder:

usr@host:kd-tree$ make

Usage Instructions

  1. Build KD-Tree:
$ ./KDTree --build <path/input_file.csv>

Sample data can be found in ./data/ Output file "tree.json" is generated

  1. Query KD-Tree for Nearest Neighbors:
$ ./KDTree --query <path/query_file.csv> <path/tree.json>(optional)

If tree file is not entered, the default "./data/sample_tree.json" is used. Output files "query_results.csv" and "query_results_truth.csv" are generated.

  1. Help:
$ ./KDTree --help

Usage instructions can be viewed here.

kd-tree's People

Contributors

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