Calculate the angle between the 2 given floating-point points (in degrees).

Calculate the angle between the 2 given floating-point points (in degrees).

Calculate the angle between the 2 given integer points (in degrees).

Calculate the angle between the 2 given integer points (in degrees).

Calculate the distance between the 2 given points.

Calculate the distance between the 2 given points.

* Function the performs exact nearest neighbor search by traversing the entire tree. */

* Find set of nearest neighbors to vec. Their indices are stored inside * the result object. * * Params: * result = the result

* Find set of nearest neighbors to vec. Their indices are stored inside * the result object. * * Params: * result = the result

* \brief Method that searches for nearest-neighbours */

* Method that searches for nearest-neighbors */

* \brief Method that searches for nearest-neighbours */

* Find set of nearest neighbors to vec. Their indices are stored inside * the result object. * * Params: * result = the result

* Find set of nearest neighbors to vec. Their indices are stored inside * the result object. * * Params: * result = the result

(2^32-1)^-1

* Convenience function for deallocating the storage data. */

* Helper function */

Check the status of the set * @return true if we have k NN */

Check the status of the set * @return alwys false */

* Helper function. * * I computes the order in which to traverse the child nodes of a particular node. */

* Method that computes the squared distance from the query point q * from inside region with center c to the border between this * region an

* Performs an exact nearest neighbor search. The exact search performs a full * traversal of the tree. */

TODO: deprecated in favor of getSignature overload, remove

* \brief Returns actual index */

* \brief Returns index parameters. * \deprecated use getParameters() instead. */

Compute the sub-signature of a feature */

* Helper function the descends in the hierarchical k-means tree by spliting those clusters that minimize * the overall variance of the clustering

Performs the approximate nearest-neighbor search. * @param vec the feature to analyze * @param do_radius flag indicating if we check the rad

* Performs the approximate nearest-neighbor search. The search is approximate * because the tree traversal is abandoned after a given number of d

* \returns The index parameters */

* \returns The index parameters */

protected functions

* \brief Get sampling step T at pyramid_level. */

* @return The index type */

* \returns The index type (kdtree, kmeans,...) */

Retrieving internal data *******************************/ get back project image