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Apply to KMeansIndex KMeanspp the same modification as in HierarchicalClusteringIndex

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Pierre-Emmanuel Viel 2013-12-17 13:04:49 +01:00
parent 45e0e5f8e9
commit 5aeeaa6fce
1 changed files with 9 additions and 2 deletions
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11
modules/flann/include/opencv2/flann/kmeans_index.h
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@ -211,6 +211,7 @@ public:
for (int i = 0; i < n; i++) { for (int i = 0; i < n; i++) {
closestDistSq[i] = distance_(dataset_[indices[i]], dataset_[indices[index]], dataset_.cols); closestDistSq[i] = distance_(dataset_[indices[i]], dataset_[indices[index]], dataset_.cols);
closestDistSq[i] *= closestDistSq[i];
currentPot += closestDistSq[i]; currentPot += closestDistSq[i];
} }
@ -236,7 +237,10 @@ public:
// Compute the new potential // Compute the new potential
double newPot = 0; double newPot = 0;
for (int i = 0; i < n; i++) newPot += std::min( distance_(dataset_[indices[i]], dataset_[indices[index]], dataset_.cols), closestDistSq[i] ); for (int i = 0; i < n; i++) {
DistanceType dist = distance_(dataset_[indices[i]], dataset_[indices[index]], dataset_.cols);
newPot += std::min( dist*dist, closestDistSq[i] );
}
// Store the best result // Store the best result
if ((bestNewPot < 0)||(newPot < bestNewPot)) { if ((bestNewPot < 0)||(newPot < bestNewPot)) {
@ -248,7 +252,10 @@ public:
// Add the appropriate center // Add the appropriate center
centers[centerCount] = indices[bestNewIndex]; centers[centerCount] = indices[bestNewIndex];
currentPot = bestNewPot; currentPot = bestNewPot;
for (int i = 0; i < n; i++) closestDistSq[i] = std::min( distance_(dataset_[indices[i]], dataset_[indices[bestNewIndex]], dataset_.cols), closestDistSq[i] ); for (int i = 0; i < n; i++) {
DistanceType dist = distance_(dataset_[indices[i]], dataset_[indices[bestNewIndex]], dataset_.cols);
closestDistSq[i] = std::min( dist*dist, closestDistSq[i] );
}
} }
centers_length = centerCount; centers_length = centerCount;