For every input query descriptor, retrieve the best k matching ones from a dataset provided from user or from the one internal to class

matches = matcher.knnMatch(queryDescriptors, trainDescriptors, k)
matches = matcher.knnMatch(queryDescriptors, k)
[...] = matcher.knnMatch(..., 'OptionName', optionValue, ...)

Input

• queryDescriptors query descriptors.
• trainDescriptors dataset of descriptors furnished by user.
• k number of the closest descriptors to be returned for every input query.

Output

• matches vector to host retrieved matches.

Options

• Mask mask to select which input descriptors must be matched to ones in dataset. A vector of masks in the second variant (the i-th mask in vector indicates whether each input query can be matched with descriptors in dataset relative to i-th image). Not set by default.
• CompactResult flag to obtain a compact result (if true, a vector that doesn't contain any matches for a given query is not inserted in final result). default false

For every input descriptor, find the best k matching descriptors:

• in the first variant, for a pair of images
• in the second variant, from one image to a set