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digiKam
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Classes | |
class | Digikam::KDTreeBase |
Namespaces | |
namespace | Digikam |
Macros | |
#define | KDTREE_MAP_THRESHOLD 500 |
Size of the vector before we start using the tree. | |
#define KDTREE_MAP_THRESHOLD 500 |
Size of the vector before we start using the tree.
Due to sparse data density in the tree, we initially use a vector of nodes to compare the target to the samples once we have achieved a suitabe data density we delete the vector (but not the nodes) and begin using the tree. The next refactor will include replacing the tree with a more appropriate HDLSS classifier.