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Merge pull request #12440 from woodychow:fix_normL2Sqr_speed_regression_3.4

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This commit is contained in:
Alexander Alekhin 2018-09-06 10:33:33 +00:00
commit 66d15e89df
2 changed files with 43 additions and 5 deletions
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37
modules/core/src/batch_distance.cpp
View File

@ -5,6 +5,7 @@
#include "precomp.hpp"
#include "stat.hpp"
#include <opencv2/core/hal/hal.hpp>
namespace cv
{
@ -45,6 +46,24 @@ void batchDistL2Sqr_(const _Tp* src1, const _Tp* src2, size_t step2,
}
}
template<>
void batchDistL2Sqr_(const float* src1, const float* src2, size_t step2,
int nvecs, int len, float* dist, const uchar* mask)
{
step2 /= sizeof(src2[0]);
if( !mask )
{
for( int i = 0; i < nvecs; i++ )
dist[i] = hal::normL2Sqr_(src1, src2 + step2*i, len);
}
else
{
float val0 = std::numeric_limits<float>::max();
for( int i = 0; i < nvecs; i++ )
dist[i] = mask[i] ? hal::normL2Sqr_(src1, src2 + step2*i, len) : val0;
}
}
template<typename _Tp, typename _Rt>
void batchDistL2_(const _Tp* src1, const _Tp* src2, size_t step2,
int nvecs, int len, _Rt* dist, const uchar* mask)
@ -63,6 +82,24 @@ void batchDistL2_(const _Tp* src1, const _Tp* src2, size_t step2,
}
}
template<>
void batchDistL2_(const float* src1, const float* src2, size_t step2,
int nvecs, int len, float* dist, const uchar* mask)
{
step2 /= sizeof(src2[0]);
if( !mask )
{
for( int i = 0; i < nvecs; i++ )
dist[i] = std::sqrt(hal::normL2Sqr_(src1, src2 + step2*i, len));
}
else
{
float val0 = std::numeric_limits<float>::max();
for( int i = 0; i < nvecs; i++ )
dist[i] = mask[i] ? std::sqrt(hal::normL2Sqr_(src1, src2 + step2*i, len)) : val0;
}
}
static void batchDistHamming(const uchar* src1, const uchar* src2, size_t step2,
int nvecs, int len, int* dist, const uchar* mask)
{

11
modules/core/src/kmeans.cpp
View File

@ -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)
{