utils.h

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// ----------------------------------------------------------------------------
// -                        CloudViewer: www.cloudViewer.org                  -
// ----------------------------------------------------------------------------
// Copyright (c) 2018-2024 www.cloudViewer.org
// SPDX-License-Identifier: MIT
// ----------------------------------------------------------------------------
 
#pragma once
 
#include <array>
#include <cmath>
 
namespace colmap {
namespace retrieval {
 
struct ImageScore {
    int image_id = -1;
    float score = 0.0f;
};
 
// Implements the weighting function used to derive a voting weight from the
// Hamming distance of two binary signatures. See Eqn. 4 in
// Arandjelovic, Zisserman. DisLocation: Scalable descriptor distinctiveness for
// location recognition. ACCV 2014.
// The template is the length of the Hamming embedding vectors.
// This class is based on an original implementation by Torsten Sattler.
template <int N, int kSigma = 16>
class HammingDistWeightFunctor {
public:
    static const size_t kMaxHammingDistance =
            static_cast<size_t>(1.5f * kSigma);
 
    HammingDistWeightFunctor() {
        // Fills the look-up table.
        const float sigma_squared = kSigma * kSigma;
        for (int n = 0; n <= N; ++n) {
            const float hamming_dist = static_cast<float>(n);
            if (hamming_dist <= kMaxHammingDistance) {
                look_up_table_.at(n) =
                        std::exp(-hamming_dist * hamming_dist / sigma_squared);
            } else {
                look_up_table_.at(n) = 0.0f;
            }
        }
    }
 
    // Returns the weight for Hamming distance h and standard deviation sigma.
    // Does not perform a range check when performing the look-up.
    inline float operator()(const size_t hamming_dist) const {
        return look_up_table_.at(hamming_dist);
    }
 
private:
    // In order to avoid wasting computations, we once compute a look-up table
    // storing all function values for all possible values of the standard
    // deviation \sigma. This is implemented as a (N + 1) vector.
    std::array<float, N + 1> look_up_table_;
};
 
}  // namespace retrieval
}  // namespace colmap