resolve #11855

[alexevans]

Merge with extra: opencv/opencv_extra#543

resolves #11855

allow_multiple_commits=1

[alalek]

Please add test for this patch (code from answers doesn't expect empty entries).

[alexevans]

@alalek
Here's what I used, based on the tests in the original issue and answers post.

#include <iostream>
#include <opencv2/core.hpp>
#include <opencv2/features2d.hpp>

using namespace cv;
using namespace std;

int main()
{
Mat targets = (Mat_<uchar>(2, 3) <<  1, 1, 0, 1, 1, 1);
Mat sources = (Mat_<uchar>(2, 3) << 1, 1, 1, 0,0,0);
cout << sources << "\n";
cout << targets << "\n";
cout << "SOURCES TARGETS\n";
    for (int i = 0; i < sources.rows; i++)
        for (int j = 0; j < targets.rows; j++)
            cout << i << " -> " << j << " = " << norm(sources.row(i), targets.row(j), NORM_HAMMING) << "\n";
    cout << "TARGETS SOURCES\n";
    for (int i = 0; i < targets.rows; i++)
        for (int j = 0; j < sources.rows; j++)
            cout << i << " -> " << j << " = " << norm(targets.row(i), sources.row(j), NORM_HAMMING) << "\n";

Ptr<BFMatcher> bf = BFMatcher::create(NORM_HAMMING, true);
vector<vector<DMatch>> match;
cout << "Match with crosscheck TRUE\n";
bf->knnMatch(sources, targets, match, 1);

for (auto m : match)
    if(m.size() > 0)
        cout << m[0].queryIdx << " -> " << m[0].trainIdx << " = " << m[0].distance << "\n";

Ptr<BFMatcher> bf2 = BFMatcher::create(NORM_HAMMING, false);
cout << "Match with crosscheck FALSE \n";
match.clear();
bf2->knnMatch(sources, targets, match, 1);

for (auto m : match)
    cout << m[0].queryIdx << " -> " << m[0].trainIdx << " = " << m[0].distance << "\n";
return 0;
}

import numpy
import cv2

targets = numpy.array([[1, 1, 0], [1, 1, 1]], dtype=numpy.uint8)
sources = numpy.array([[1, 1, 1], [0, 0, 0]], dtype=numpy.uint8)
for si, source in enumerate(sources):
    for ti, target in enumerate(targets):
        print('%d -> %d: %d' % (si, ti, cv2.norm(source, target, cv2.NORM_HAMMING)))

bf = cv2.BFMatcher(cv2.NORM_HAMMING, crossCheck=True)
matches = bf.knnMatch(sources, targets, k=1)
print('-- crosscheck=True')
for match in matches:
    if match:
        print('%d -> %d: %f' % (match[0].queryIdx, match[0].trainIdx, match[0].distance))

bf_nocc = cv2.BFMatcher(cv2.NORM_HAMMING, crossCheck=False)
matches_nocc = bf_nocc.knnMatch(sources, targets, k=1)
print('-- crosscheck=False')
for match in matches_nocc:
    if match:
        print('%d -> %d: %f' % (match[0].queryIdx, match[0].trainIdx, match[0].distance))

[alalek]

Proposed code works without this patch.
Looks like there is mess with sources/targets values above.

Added the simple test to this patch.

[alalek]

Looks good to me! Thank you 👍