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Replace naive normL2Sqr with hal::normL2Sqr_ for better performance

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This commit is contained in:
woody.chow
2018-09-06 17:43:07 +09:00
parent 8e8315abfd
commit 07c6b0a8df
2 changed files with 43 additions and 5 deletions
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modules/core/src/kmeans.cpp
+6 -5
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@@ -43,6 +43,7 @@
#include "precomp.hpp"
#include <opencv2/core/utils/configuration.private.hpp>
#include <opencv2/core/hal/hal.hpp>
////////////////////////////////////////// kmeans ////////////////////////////////////////////
@@ -74,7 +75,7 @@ public:
for (int i = begin; i<end; i++)
{
tdist2[i] = std::min(normL2Sqr(data.ptr<float>(i), data.ptr<float>(ci), dims), dist[i]);
tdist2[i] = std::min(hal::normL2Sqr_(data.ptr<float>(i), data.ptr<float>(ci), dims), dist[i]);
}
}
@@ -106,7 +107,7 @@ static void generateCentersPP(const Mat& data, Mat& _out_centers,
for (int i = 0; i < N; i++)
{
dist[i] = normL2Sqr(data.ptr<float>(i), data.ptr<float>(centers[0]), dims);
dist[i] = hal::normL2Sqr_(data.ptr<float>(i), data.ptr<float>(centers[0]), dims);
sum0 += dist[i];
}
@@ -185,7 +186,7 @@ public:
if (onlyDistance)
{
const float* center = centers.ptr<float>(labels[i]);
distances[i] = normL2Sqr(sample, center, dims);
distances[i] = hal::normL2Sqr_(sample, center, dims);
continue;
}
else
@@ -196,7 +197,7 @@ public:
for (int k = 0; k < K; k++)
{
const float* center = centers.ptr<float>(k);
const double dist = normL2Sqr(sample, center, dims);
const double dist = hal::normL2Sqr_(sample, center, dims);
if (min_dist > dist)
{
@@ -379,7 +380,7 @@ double cv::kmeans( InputArray _data, int K,
if (labels[i] != max_k)
continue;
const float* sample = data.ptr<float>(i);
double dist = normL2Sqr(sample, _base_center, dims);
double dist = hal::normL2Sqr_(sample, _base_center, dims);
if (max_dist <= dist)
{