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fix the function name

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pull/1077/head
yao 12 years ago
parent c23510785b
commit 88ed74a7ec
3 changed files with 27 additions and 26 deletions
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  1. 2
      modules/ocl/include/opencv2/ocl/ocl.hpp
  2. 36
      modules/ocl/src/kmeans.cpp
  3. 15
      modules/ocl/src/opencl/kmeans_kernel.cl

2
modules/ocl/include/opencv2/ocl/ocl.hpp
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@ -838,7 +838,7 @@ namespace cv
//! Compute closest centers for each lines in source and lable it after center's index
// supports CV_32FC1/CV_32FC2/CV_32FC4 data type
void DistanceComputer(oclMat &dists, oclMat &labels, const oclMat &src, const oclMat &centers);
CV_EXPORTS void distanceToCenters(oclMat &dists, oclMat &labels, const oclMat &src, const oclMat &centers);
//!Does k-means procedure on GPU
// supports CV_32FC1/CV_32FC2/CV_32FC4 data type

36
modules/ocl/src/kmeans.cpp
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@ -51,11 +51,11 @@ using namespace ocl;
namespace cv
{
namespace ocl
{
////////////////////////////////////OpenCL kernel strings//////////////////////////
extern const char *kmeans_kernel;
}
namespace ocl
{
////////////////////////////////////OpenCL kernel strings//////////////////////////
extern const char *kmeans_kernel;
}
}
static void generateRandomCenter(const vector<Vec2f>& box, float* center, RNG& rng)
@ -142,7 +142,7 @@ static void generateCentersPP(const Mat& _data, Mat& _out_centers,
int ci = i;
parallel_for_(Range(0, N),
KMeansPPDistanceComputer(tdist2, data, dist, dims, step, step*ci));
KMeansPPDistanceComputer(tdist2, data, dist, dims, step, step*ci));
for( i = 0; i < N; i++ )
{
s += tdist2[i];
@ -169,7 +169,7 @@ static void generateCentersPP(const Mat& _data, Mat& _out_centers,
}
}
void cv::ocl::DistanceComputer(oclMat &dists, oclMat &labels, const oclMat &src, const oclMat &centers)
void cv::ocl::distanceToCenters(oclMat &dists, oclMat &labels, const oclMat &src, const oclMat &centers)
{
//if(src.clCxt -> impl -> double_support == 0 && src.type() == CV_64F)
//{
@ -179,7 +179,7 @@ void cv::ocl::DistanceComputer(oclMat &dists, oclMat &labels, const oclMat &src,
Context *clCxt = src.clCxt;
int labels_step = (int)(labels.step/labels.elemSize());
string kernelname = "kmeansComputeDistance";
string kernelname = "distanceToCenters";
int threadNum = src.rows > 256 ? 256 : src.rows;
size_t localThreads[3] = {1, threadNum, 1};
size_t globalThreads[3] = {1, src.rows, 1};
@ -198,7 +198,7 @@ void cv::ocl::DistanceComputer(oclMat &dists, oclMat &labels, const oclMat &src,
}
///////////////////////////////////k - means /////////////////////////////////////////////////////////
double cv::ocl::kmeans(const oclMat &_src, int K, oclMat &_bestLabels,
TermCriteria criteria, int attempts, int flags, oclMat &_centers)
TermCriteria criteria, int attempts, int flags, oclMat &_centers)
{
const int SPP_TRIALS = 3;
bool isrow = _src.rows == 1 && _src.oclchannels() > 1;
@ -214,16 +214,16 @@ double cv::ocl::kmeans(const oclMat &_src, int K, oclMat &_bestLabels,
if( flags & CV_KMEANS_USE_INITIAL_LABELS )
{
CV_Assert( (_bestLabels.cols == 1 || _bestLabels.rows == 1) &&
_bestLabels.cols * _bestLabels.rows == N &&
_bestLabels.type() == CV_32S );
_bestLabels.cols * _bestLabels.rows == N &&
_bestLabels.type() == CV_32S );
_bestLabels.download(_labels);
}
else
{
if( !((_bestLabels.cols == 1 || _bestLabels.rows == 1) &&
_bestLabels.cols * _bestLabels.rows == N &&
_bestLabels.type() == CV_32S &&
_bestLabels.isContinuous()))
_bestLabels.cols * _bestLabels.rows == N &&
_bestLabels.type() == CV_32S &&
_bestLabels.isContinuous()))
_bestLabels.create(N, 1, CV_32S);
_labels.create(_bestLabels.size(), _bestLabels.type());
}
@ -307,7 +307,7 @@ double cv::ocl::kmeans(const oclMat &_src, int K, oclMat &_bestLabels,
k = labels[i];
float* center = centers.ptr<float>(k);
j=0;
#if CV_ENABLE_UNROLLED
#if CV_ENABLE_UNROLLED
for(; j <= dims - 4; j += 4 )
{
float t0 = center[j] + sample[j];
@ -322,7 +322,7 @@ double cv::ocl::kmeans(const oclMat &_src, int K, oclMat &_bestLabels,
center[j+2] = t0;
center[j+3] = t1;
}
#endif
#endif
for( ; j < dims; j++ )
center[j] += sample[j];
counters[k]++;
@ -410,10 +410,10 @@ double cv::ocl::kmeans(const oclMat &_src, int K, oclMat &_bestLabels,
// assign labels
oclMat _dists(1, N, CV_64F);
_bestLabels.upload(_labels);
_centers.upload(centers);
DistanceComputer(_dists, _bestLabels, _src, _centers);
distanceToCenters(_dists, _bestLabels, _src, _centers);
Mat dists;
_dists.download(dists);

15
modules/ocl/src/opencl/kmeans_kernel.cl
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@ -43,7 +43,7 @@
//
//M*/
__kernel void kmeansComputeDistance(
__kernel void distanceToCenters(
int label_step, int K,
__global float *src,
__global int *labels, int dims, int rows,
@ -51,20 +51,20 @@ __kernel void kmeansComputeDistance(
__global float *dists)
{
int gid = get_global_id(1);
float dist, euDist, min;
int minCentroid;
if(gid >= rows)
return;
for(int i = 0 ;i < K; i++)
for(int i = 0 ; i < K; i++)
{
euDist = 0;
for(int j = 0; j < dims; j++)
{
dist = (src[j + gid * dims]
- centers[j + i * dims]);
dist = (src[j + gid * dims]
- centers[j + i * dims]);
euDist += dist * dist;
}
@ -72,7 +72,8 @@ __kernel void kmeansComputeDistance(
{
min = euDist;
minCentroid = 0;
} else if(euDist < min)
}
else if(euDist < min)
{
min = euDist;
minCentroid = i;

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