/*********************************************************************** * Software License Agreement (BSD License) * * Copyright 2011-2024 Jose Luis Blanco (joseluisblancoc@gmail.com). * All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions * are met: * * 1. Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * 2. Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in the * documentation and/or other materials provided with the distribution. * * THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. * IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. *************************************************************************/ #include #include #include #include #include #include "utils.h" void kdtree_save_load_demo(const size_t N) { PointCloud cloud; // Generate points: generateRandomPointCloud(cloud, N); double query_pt[3] = {0.5, 0.5, 0.5}; // construct a kd-tree index: using my_kd_tree_t = nanoflann::KDTreeSingleIndexAdaptor< nanoflann::L2_Simple_Adaptor>, PointCloud, 3 /* dim */ >; // Construct the index and save it: // -------------------------------------------- { my_kd_tree_t index( 3 /*dim*/, cloud, nanoflann::KDTreeSingleIndexAdaptorParams(10 /* max leaf */)); std::ofstream f("index.bin", std::ofstream::binary); if (f.bad()) throw std::runtime_error("Error writing index file!"); index.saveIndex(f); f.close(); } // Load the index from disk: // -------------------------------------------- { // Important: construct the index associated to the same dataset, since // data points are NOT stored in the binary file. // Note - set KDTreeSingleIndexAdaptor::SkipInitialBuildIndex, otherwise // the tree builds an index that'll be overwritten via loadIndex my_kd_tree_t index( 3 /*dim*/, cloud, nanoflann::KDTreeSingleIndexAdaptorParams( 10 /* max leaf */, nanoflann::KDTreeSingleIndexAdaptorFlags:: SkipInitialBuildIndex)); std::ifstream f("index.bin", std::ofstream::binary); if (f.fail()) throw std::runtime_error("Error reading index file!"); index.loadIndex(f); f.close(); // do a knn search const size_t num_results = 1; size_t ret_index; double out_dist_sqr; nanoflann::KNNResultSet resultSet(num_results); resultSet.init(&ret_index, &out_dist_sqr); index.findNeighbors(resultSet, &query_pt[0]); std::cout << "knnSearch(nn=" << num_results << "): \n"; std::cout << "ret_index=" << ret_index << " out_dist_sqr=" << out_dist_sqr << std::endl; } // Stress test: try to save an empty index { PointCloud emptyCloud; my_kd_tree_t index(3 /*dim*/, emptyCloud); std::ofstream f("index2.bin", std::ofstream::binary); if (f.bad()) throw std::runtime_error("Error writing index file!"); index.saveIndex(f); f.close(); } } int main() { // Randomize Seed srand(static_cast(time(nullptr))); kdtree_save_load_demo(100000); return 0; }