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@ -103,6 +103,58 @@ using ::cvflann::KL_Divergence; |
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/** @brief The FLANN nearest neighbor index class. This class is templated with the type of elements for which
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the index is built. |
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`Distance` functor specifies the metric to be used to calculate the distance between two points. |
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There are several `Distance` functors that are readily available: |
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@link cvflann::L2_Simple cv::flann::L2_Simple @endlink- Squared Euclidean distance functor. |
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This is the simpler, unrolled version. This is preferable for very low dimensionality data (eg 3D points) |
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@link cvflann::L2 cv::flann::L2 @endlink- Squared Euclidean distance functor, optimized version. |
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@link cvflann::L1 cv::flann::L1 @endlink - Manhattan distance functor, optimized version. |
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@link cvflann::MinkowskiDistance cv::flann::MinkowskiDistance @endlink - The Minkowsky distance functor. |
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This is highly optimised with loop unrolling. |
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The computation of squared root at the end is omitted for efficiency. |
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@link cvflann::MaxDistance cv::flann::MaxDistance @endlink - The max distance functor. It computes the |
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maximum distance between two vectors. This distance is not a valid kdtree distance, it's not |
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dimensionwise additive. |
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@link cvflann::HammingLUT cv::flann::HammingLUT @endlink - %Hamming distance functor. It counts the bit |
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differences between two strings using a lookup table implementation. |
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@link cvflann::Hamming cv::flann::Hamming @endlink - %Hamming distance functor. Population count is |
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performed using library calls, if available. Lookup table implementation is used as a fallback. |
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@link cvflann::Hamming2 cv::flann::Hamming2 @endlink- %Hamming distance functor. Population count is |
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implemented in 12 arithmetic operations (one of which is multiplication). |
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@link cvflann::HistIntersectionDistance cv::flann::HistIntersectionDistance @endlink - The histogram |
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intersection distance functor. |
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@link cvflann::HellingerDistance cv::flann::HellingerDistance @endlink - The Hellinger distance functor. |
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@link cvflann::ChiSquareDistance cv::flann::ChiSquareDistance @endlink - The chi-square distance functor. |
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@link cvflann::KL_Divergence cv::flann::KL_Divergence @endlink - The Kullback-Leibler divergence functor. |
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Although the provided implementations cover a vast range of cases, it is also possible to use |
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a custom implementation. The distance functor is a class whose `operator()` computes the distance |
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between two features. If the distance is also a kd-tree compatible distance, it should also provide an |
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`accum_dist()` method that computes the distance between individual feature dimensions. |
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In addition to `operator()` and `accum_dist()`, a distance functor should also define the |
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`ElementType` and the `ResultType` as the types of the elements it operates on and the type of the |
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result it computes. If a distance functor can be used as a kd-tree distance (meaning that the full |
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distance between a pair of features can be accumulated from the partial distances between the |
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individual dimensions) a typedef `is_kdtree_distance` should be present inside the distance functor. |
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If the distance is not a kd-tree distance, but it's a distance in a vector space (the individual |
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dimensions of the elements it operates on can be accessed independently) a typedef |
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`is_vector_space_distance` should be defined inside the functor. If neither typedef is defined, the |
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distance is assumed to be a metric distance and will only be used with indexes operating on |
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generic metric distances. |
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*/ |
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template <typename Distance> |
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class GenericIndex |
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@ -217,6 +269,17 @@ public: |
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std::vector<DistanceType>& dists, int knn, const ::cvflann::SearchParams& params); |
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void knnSearch(const Mat& queries, Mat& indices, Mat& dists, int knn, const ::cvflann::SearchParams& params); |
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/** @brief Performs a radius nearest neighbor search for a given query point using the index.
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@param query The query point. |
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@param indices Vector that will contain the indices of the nearest neighbors found. |
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@param dists Vector that will contain the distances to the nearest neighbors found. It has the same |
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number of elements as indices. |
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@param radius The search radius. |
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@param params SearchParams |
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This function returns the number of nearest neighbors found. |
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*/ |
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int radiusSearch(const std::vector<ElementType>& query, std::vector<int>& indices, |
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std::vector<DistanceType>& dists, DistanceType radius, const ::cvflann::SearchParams& params); |
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int radiusSearch(const Mat& query, Mat& indices, Mat& dists, |
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Alexander Alekhin
6 years ago