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flann: fix Index::radiusSearch output size mismatch #28990 ## Problem `Index::radiusSearch` returns `nn` — the number of neighbors found within the radius — but the output arrays `_indices` and `_dists` are always allocated with `maxResults` columns regardless of how many neighbors were actually found. This creates two inconsistencies: 1. When `nn < maxResults`, the output arrays contain stale entries beyond position `nn`, so `nn != indices.cols` and callers cannot rely on the output size to know how many results are valid. 2. When `nn > maxResults`, the return value exceeds the capacity of the output arrays, which have only `maxResults` columns. The extra neighbors were never stored, so the return value is misleading. The following snippet reproduces both cases: ```cpp int testFLANN(){ std::vector<cv::Point2f> corners={{3679.83,1857.22},{3324.43,1850.67},{3278.83,1502.32},{3621.32,1508.69},{3662.26,1837.97},{3336.06,1839.28},{3291.74,1516.03},{3608.94,1518.72},{2980.66,1843.22},{2628.11,1837.14},{2607.73,1491.57},{2948.22,1496.76},{2289.31,1830.19},{1943.99,1824.17},{1945.51,1482.34},{2280.68,1487.39},{1607.47,1819.11},{1260.04,1813.26},{1283.94,1470.34},{1620.03,1475.85},{923.063,1808.08},{576.193,1802.4},{624.713,1459.78},{959.715,1464.93},{3270.25,1494.98},{2952.95,1492.19},{2922.75,1190.02},{3231.05,1194.81},{3284.82,1507.62},{2942.74,1502.59},{2912.32,1178.33},{3242.98,1183.19},{2612.82,1496.37},{2276.44,1491.63},{2267.61,1170.13},{2593.64,1174.43},{1949.73,1486.61},{1614.92,1480.64},{1626.77,1160.34},{1952,1165.51},{1289.38,1476.21},{953.709,1470.21},{986.779,1148.92},{1311.98,1154.89},{3567.28,1195.1},{3237.51,1189.03},{3197.63,884.15},{3518.61,888.76},{2918.31,1183.62},{2588.69,1179.37},{2570.64,875.672},{2889.87,878.902},{2271.97,1174.25},{1947.62,1169.61},{1948.56,868.197},{2263.8,872.533},{1630.99,1164.6},{1306.74,1159.52},{1327.81,858.358},{1642.69,862.765},{992.896,1155.52},{666.107,1149.96},{705.246,845.776},{1023.25,851.582},{3204.48,889.981},{2883.49,885.252},{2859.31,593.752},{3175.43,594.736},{2575.86,880.331},{2259.44,876.647},{2252.33,589.235},{2560.47,592.332},{1954.36,873.708},{1636.7,868.068},{1646.93,580.76},{1956.14,584.797},{1332.02,862.624},{1017.11,856.71},{1045.32,572.178},{1350.95,577.635},{3481.36,605.324},{3169.05,601.083},{3138.84,324.116},{3446.12,325.545},{2866.14,599.61},{2555.38,597.142},{2541.51,320.931},{2845.5,322.419},{2256.79,593.253},{1950.17,590.12},{1951.8,317.445},{2250.88,319.418},{1654.16,587.663},{1344.83,582.787},{1362.8,309.253},{1663.89,313.056},{1050.94,577.867},{741.476,571.648},{776.433,300.444},{1076.97,304.56},{3327.05,1847.65},{2977.74,1840.48},{2945.48,1499.68},{3281.82,1504.97},{2630.85,1834.22},{2287.2,1828.06},{2278.56,1489.51},{2610.64,1494.31},{1946.11,1822.05},{1604.75,1816.18},{1617.11,1478.59},{1947.62,1484.48},{1262.96,1810.53},{920.46,1805.05},{956.712,1467.57},{1286.66,1473.27},{3618.7,1511.71},{3281.82,1504.97},{3240.24,1186.11},{3564.22,1192.53},{2945.48,1499.68},{2610.64,1494.31},{2591.52,1176.55},{2915.32,1180.97},{2278.56,1489.51},{1947.62,1484.48},{1949.81,1167.56},{2269.79,1172.18},{1617.11,1478.59},{1286.66,1473.27},{1308.98,1157.53},{1628.88,1162.47},{956.712,1467.57},{627.315,1462.81},{669.943,1146.75},{989.494,1151.86},{3240.25,1186.11},{2915.32,1180.98},{2887.03,881.727},{3200.69,886.725},{2591.52,1176.55},{2269.79,1172.19},{2261.62,874.587},{2573.63,878.324},{1949.81,1167.55},{1628.88,1162.47},{1640.44,864.751},{1950.74,870.259},{1308.98,1157.53},{989.494,1151.86},{1019.41,854.787},{1329.92,860.49},{3515.88,891.68},{3200.69,886.725},{3171.89,598.263},{3478.26,602.785},{2887.04,881.725},{2573.63,878.324},{2558.28,594.392},{2863.1,597.005},{2261.62,874.587},{1950.74,870.259},{1952.4,588.114},{2254.56,591.241},{1640.44,864.751},{1329.92,860.49},{1348.65,579.559},{1650.55,584.209},{1019.41,854.787},{708.649,849.44},{745.388,568.534},{1047.42,574.313},{3171.89,598.263},{2863.1,597.005},{2842.6,325.169},{3141.93,326.654},{2558.28,594.392},{2254.56,591.241},{2248.65,321.425},{2544.55,323.537},{1952.4,588.113},{1650.55,584.209},{1660.07,316.284},{1954.02,319.457},{1348.65,579.559},{1047.43,574.312},{1073.06,307.674},{1366.42,312.707}}; cv::flann::KDTreeIndexParams indexParams(1); cv::Mat data = cv::Mat(corners).reshape(1, static_cast<int>(corners.size())); auto index = std::make_shared<cv::flann::Index>(data, indexParams); int maxResults = 4; int nTimesError1 = 0; // nn != indices.size() int nTimesError2 = 0; // nn > maxResults for (size_t i = 0; i < corners.size(); i++) { std::vector<int> indices(4); std::vector<float> dists(4); int nn = index->radiusSearch(data.row(static_cast<int>(i)), indices, dists, 100, maxResults); if (nn != (int)indices.size()) { nTimesError1++; } if (nn > maxResults) { nTimesError2++; } } std::cout << "nTimesError1: " << nTimesError1 << std::endl; // > 0 before fix std::cout << "nTimesError2: " << nTimesError2 << std::endl; // > 0 before fix return 1; } ``` ## Fix - Capture the search result in `rsearch_ret` instead of returning early from each `switch` case (this also required adding the missing `break` statements that would otherwise have caused fall-through between type-incompatible distance specialisations). - Cap `rsearch_ret` at `maxResults` so the return value never exceeds the capacity of the output arrays. - When `rsearch_ret < maxResults`, trim `_indices` and `_dists` to `query.rows × rsearch_ret` via `colRange(0, rsearch_ret).copyTo(...)` so the output dimensions always match the returned count.