knn.hpp

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#pragma once
 
#include <cpp-toolbox/pcl/knn/base_knn.hpp>
#include <cpp-toolbox/pcl/knn/bfknn.hpp>
#include <cpp-toolbox/pcl/knn/bfknn_parallel.hpp>
#include <cpp-toolbox/pcl/knn/kdtree.hpp>
 
namespace toolbox::pcl
{
 
template<typename T>
inline auto create_default_knn(size_t num_points = 0) {
    if (num_points > 10000) {
        return std::make_unique<kdtree_t<T>>();
    } else if (num_points > 1000) {
        return std::make_unique<bfknn_parallel_t<T>>();
    } else {
        return std::make_unique<bfknn_t<T>>();
    }
}
 
template<typename KNN>
double benchmark_knn(KNN& knn, 
                     const std::vector<typename KNN::element_type>& queries,
                     size_t k) {
    using namespace std::chrono;
    
    std::vector<std::size_t> indices;
    std::vector<typename KNN::distance_type> distances;
    
    auto start = high_resolution_clock::now();
    
    for (const auto& query : queries) {
        knn.kneighbors(query, k, indices, distances);
    }
    
    auto end = high_resolution_clock::now();
    auto duration = duration_cast<microseconds>(end - start);
    
    return static_cast<double>(duration.count()) / 1000.0 / queries.size();
}
 
 
}  // namespace toolbox::pcl