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Why does knnMatch return a list of tuples instead of a list of DMatch?

asked 2018-05-31 08:50:57 -0500

prinsherbert gravatar image

This stitching example

https://docs.opencv.org/3.0-beta/doc/...

pipes the output of flann.knnMatch to cv2.drawMatchesKnn. Since the reference pages do not come close to properly documenting the output of knnMatch:

I decided to look at the implementation of drawMatchesKnn, but found something strange. In the python-code, the output of knnMatch is a list of lists of two DMatch objects:

matches[:3] == (
[[<DMatch 0x7ff57f981710>, <DMatch 0x7ff57f981130>],
 [<DMatch 0x7ff57f981330>, <DMatch 0x7ff57f981290>],
 [<DMatch 0x7ff57f981310>, <DMatch 0x7ff57f9816f0>]]
)

However drawMatchesKnn, to which matches is passed, these two line suggest it is a list of DMatches, instead of a list of lists of DMatches, since there is only one index [m] not two [m][n],

https://github.com/opencv/opencv/blob...

Moreover, this loop for i,(m,n) in enumerate(matches): in the first link also seems to ignore the second DMatch n in each sublist.

What is this second DMatch in each item of matches? Why is matches a list of tuples of DMatches, and not a list of 'DMatch`es?

It seems as if I can ignore the second DMatch, yet I don't feel comfortable blindly doing so.

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answered 2018-05-31 09:25:30 -0500

berak gravatar image

updated 2018-05-31 09:34:04 -0500

if you use knnMatch, it will return a list of (the best) K matches instead of a single DMatch. (K=2 was chosen in your example)

using match instead will return a single list of matches. (that's probably, what you expected)

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In the first link of the OP, they test whether the best test is at least 1.0/0.7 times better than the second best, and that is why they use knnMatch instead of match (to also get the second bests)?

prinsherbert gravatar imageprinsherbert ( 2018-05-31 09:57:46 -0500 )edit
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Asked: 2018-05-31 08:43:23 -0500

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Last updated: May 31 '18