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Commit 8fb1f409 authored by marina.kolpakova's avatar marina.kolpakova
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removed unused code

parent e63ab8de
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Showing with 2 additions and 204 deletions
modules/gpu/src/cascadeclassifier.cpp
View file @ 8fb1f409
...@@ -266,24 +266,6 @@ namespace cv { namespace gpu { namespace device ...@@ -266,24 +266,6 @@ namespace cv { namespace gpu { namespace device
{ {
namespace lbp namespace lbp
{ {
void classifyStumpFixed(const DevMem2Di& integral,
const int integralPitch,
const DevMem2Db& mstages,
const int nstages,
const DevMem2Di& mnodes,
const DevMem2Df& mleaves,
const DevMem2Di& msubsets,
const DevMem2Db& mfeatures,
const int workWidth,
const int workHeight,
const int clWidth,
const int clHeight,
float scale,
int step,
int subsetSize,
DevMem2D_<int4> objects,
unsigned int* classified);
void classifyPyramid(int frameW, void classifyPyramid(int frameW,
int frameH, int frameH,
int windowW, int windowW,
...@@ -303,8 +285,6 @@ namespace cv { namespace gpu { namespace device ...@@ -303,8 +285,6 @@ namespace cv { namespace gpu { namespace device
DevMem2Di integral); DevMem2Di integral);
void connectedConmonents(DevMem2D_<int4> candidates, int ncandidates, DevMem2D_<int4> objects,int groupThreshold, float grouping_eps, unsigned int* nclasses); void connectedConmonents(DevMem2D_<int4> candidates, int ncandidates, DevMem2D_<int4> objects,int groupThreshold, float grouping_eps, unsigned int* nclasses);
void bindIntegral(DevMem2Di integral);
void unbindIntegral();
} }
}}} }}}
......
modules/gpu/src/cuda/lbp.cu
View file @ 8fb1f409
...@@ -48,14 +48,10 @@ namespace cv { namespace gpu { namespace device ...@@ -48,14 +48,10 @@ namespace cv { namespace gpu { namespace device
{ {
namespace lbp namespace lbp
{ {
texture<int, cudaTextureType2D, cudaReadModeElementType> tintegral(false, cudaFilterModePoint, cudaAddressModeClamp);
struct LBP struct LBP
{ {
__host__ __device__ __forceinline__ LBP() {} __host__ __device__ __forceinline__ LBP() {}
// for integral matrix stored in the global memory
__device__ __forceinline__ int operator() (const int* integral, int ty, int fh, int fw, int& shift) const __device__ __forceinline__ int operator() (const int* integral, int ty, int fh, int fw, int& shift) const
{ {
int anchors[9]; int anchors[9];
...@@ -123,79 +119,6 @@ namespace cv { namespace gpu { namespace device ...@@ -123,79 +119,6 @@ namespace cv { namespace gpu { namespace device
anchors[7] -= anchors[4]; anchors[7] -= anchors[4];
anchors[8] -= anchors[4]; anchors[8] -= anchors[4];
shift |= (~(anchors[6] >> 31)) & 2;
shift |= (~(anchors[7] >> 31)) & 4;
shift |= (~(anchors[8] >> 31)) & 8;
return response;
}
// for texture fetchrd integral matrix
__device__ __forceinline__ int operator() (int ty, int tx, int fh, int fw, int& shift) const
{
int anchors[9];
anchors[0] = tex2D(tintegral, tx, ty);
anchors[1] = tex2D(tintegral, tx + fw, ty);
anchors[0] -= anchors[1];
anchors[2] = tex2D(tintegral, tx + fw * 2, ty);
anchors[1] -= anchors[2];
anchors[2] -= tex2D(tintegral, tx + fw * 3, ty);
ty += fh;
anchors[3] = tex2D(tintegral, tx, ty);
anchors[4] = tex2D(tintegral, tx + fw, ty);
anchors[3] -= anchors[4];
anchors[5] = tex2D(tintegral, tx + fw * 2, ty);
anchors[4] -= anchors[5];
anchors[5] -= tex2D(tintegral, tx + fw * 3, ty);
anchors[0] -= anchors[3];
anchors[1] -= anchors[4];
anchors[2] -= anchors[5];
// 0 - 2 contains s0 - s2
ty += fh;
anchors[6] = tex2D(tintegral, tx, ty);
anchors[7] = tex2D(tintegral, tx + fw, ty);
anchors[6] -= anchors[7];
anchors[8] = tex2D(tintegral, tx + fw * 2, ty);
anchors[7] -= anchors[8];
anchors[8] -= tex2D(tintegral, tx + fw * 3, ty);
anchors[3] -= anchors[6];
anchors[4] -= anchors[7];
anchors[5] -= anchors[8];
// 3 - 5 contains s3 - s5
anchors[0] -= anchors[4];
anchors[1] -= anchors[4];
anchors[2] -= anchors[4];
anchors[3] -= anchors[4];
anchors[5] -= anchors[4];
int response = (~(anchors[0] >> 31)) & 4;
response |= (~(anchors[1] >> 31)) & 2;;
response |= (~(anchors[2] >> 31)) & 1;
shift = (~(anchors[5] >> 31)) & 16;
shift |= (~(anchors[3] >> 31)) & 1;
ty += fh;
anchors[0] = tex2D(tintegral, tx, ty);
anchors[1] = tex2D(tintegral, tx + fw, ty);
anchors[0] -= anchors[1];
anchors[2] = tex2D(tintegral, tx + fw * 2, ty);
anchors[1] -= anchors[2];
anchors[2] -= tex2D(tintegral, tx + fw * 3, ty);
anchors[6] -= anchors[0];
anchors[7] -= anchors[1];
anchors[8] -= anchors[2];
// 0 -2 contains s6 - s8
anchors[6] -= anchors[4];
anchors[7] -= anchors[4];
anchors[8] -= anchors[4];
shift |= (~(anchors[6] >> 31)) & 2; shift |= (~(anchors[6] >> 31)) & 2;
shift |= (~(anchors[7] >> 31)) & 4; shift |= (~(anchors[7] >> 31)) & 4;
shift |= (~(anchors[8] >> 31)) & 8; shift |= (~(anchors[8] >> 31)) & 8;
...@@ -203,97 +126,6 @@ namespace cv { namespace gpu { namespace device ...@@ -203,97 +126,6 @@ namespace cv { namespace gpu { namespace device
} }
}; };
void bindIntegral(DevMem2Di integral)
{
cudaChannelFormatDesc desc = cudaCreateChannelDesc<int>();
cudaSafeCall( cudaBindTexture2D(0, &tintegral, integral.ptr(), &desc, (size_t)integral.cols, (size_t)integral.rows, (size_t)integral.step));
}
void unbindIntegral()
{
cudaSafeCall( cudaUnbindTexture(&tintegral));
}
struct Classifier
{
__host__ __device__ __forceinline__ Classifier(const int* _integral, int _pitch, const Stage* _stages, const ClNode* _nodes, const float* _leaves,
const int* _subsets, const uchar4* _features, int _nstages, int _clWidth, int _clHeight, float _scale, int _step, int _subsetSize)
: integral(_integral), pitch(_pitch), stages(_stages), nodes(_nodes), leaves(_leaves), subsets(_subsets), features(_features), nstages(_nstages),
clWidth(_clWidth), clHeight(_clHeight), scale(_scale), step(_step), subsetSize(_subsetSize){}
__device__ __forceinline__ void operator() (int y, int x, DevMem2D_<int4> objects, const unsigned int maxN, unsigned int* n) const
{
int current_node = 0;
int current_leave = 0;
for (int s = 0; s < nstages; ++s)
{
float sum = 0;
Stage stage = stages[s];
for (int t = 0; t < stage.ntrees; t++)
{
ClNode node = nodes[current_node];
uchar4 feature = features[node.featureIdx];
int shift;
// int c = evaluator(y + feature.y, x + feature.x, feature.w, feature.z, shift);
int c = evaluator(integral, (y + feature.y) * pitch + x + feature.x, feature.w * pitch, feature.z, shift);
int idx = (subsets[ current_node * subsetSize + c] & ( 1 << shift)) ? current_leave : current_leave + 1;
sum += leaves[idx];
current_node += 1;
current_leave += 2;
}
if (sum < stage.threshold)
return;
}
int4 rect;
rect.x = roundf(x * scale);
rect.y = roundf(y * scale);
rect.z = clWidth;
rect.w = clHeight;
int res = Emulation::smem::atomicInc(n, maxN);
objects(0, res) = rect;
}
const int* integral;
const int pitch;
const Stage* stages;
const ClNode* nodes;
const float* leaves;
const int* subsets;
const uchar4* features;
const int nstages;
const int clWidth;
const int clHeight;
const float scale;
const int step;
const int subsetSize;
const LBP evaluator;
};
__global__ void lbp_classify_stump(const Classifier classifier, DevMem2D_<int4> objects, const unsigned int maxN, unsigned int* n)
{
int x = threadIdx.x * classifier.step;
int y = blockIdx.x * classifier.step;
classifier(y, x, objects, maxN, n);
}
__global__ void lbp_classify_stump(const Classifier classifier, DevMem2D_<int4> objects, const unsigned int maxN, unsigned int* n, int maxX)
{
int ftid = blockIdx.x * blockDim.x + threadIdx.x;
int y = ftid / maxX;
int x = ftid - y * maxX;
classifier(y * classifier.step, x * classifier.step, objects, maxN, n);
}
template<typename Pr> template<typename Pr>
__global__ void disjoin(int4* candidates, int4* objects, unsigned int n, int groupThreshold, float grouping_eps, unsigned int* nclasses) __global__ void disjoin(int4* candidates, int4* objects, unsigned int n, int groupThreshold, float grouping_eps, unsigned int* nclasses)
{ {
...@@ -349,20 +181,6 @@ namespace cv { namespace gpu { namespace device ...@@ -349,20 +181,6 @@ namespace cv { namespace gpu { namespace device
} }
} }
void classifyStumpFixed(const DevMem2Di& integral, const int pitch, const DevMem2Db& mstages, const int nstages, const DevMem2Di& mnodes, const DevMem2Df& mleaves, const DevMem2Di& msubsets, const DevMem2Db& mfeatures,
const int workWidth, const int workHeight, const int clWidth, const int clHeight, float scale, int step, int subsetSize, DevMem2D_<int4> objects, unsigned int* classified)
{
Classifier clr(integral, pitch, (Stage*)mstages.ptr(), (ClNode*)mnodes.ptr(), mleaves.ptr(), msubsets,
(uchar4*)mfeatures.ptr(), nstages, clWidth, clHeight, scale, step, subsetSize);
int total = ceilf(workHeight / (float)step) * ceilf(workWidth / (float)step);
int block = 256;
int grid = divUp(total, block);
lbp_classify_stump<<<grid, block>>>(clr, objects, objects.cols, classified, workWidth >> 1);
cudaSafeCall( cudaGetLastError() );
}
void connectedConmonents(DevMem2D_<int4> candidates, int ncandidates, DevMem2D_<int4> objects, int groupThreshold, float grouping_eps, unsigned int* nclasses) void connectedConmonents(DevMem2D_<int4> candidates, int ncandidates, DevMem2D_<int4> objects, int groupThreshold, float grouping_eps, unsigned int* nclasses)
{ {
int block = ncandidates; int block = ncandidates;
...@@ -378,7 +196,7 @@ namespace cv { namespace gpu { namespace device ...@@ -378,7 +196,7 @@ namespace cv { namespace gpu { namespace device
: stages(_stages), nstages(_nstages), nodes(_nodes), leaves(_leaves), subsets(_subsets), features(_features), subsetSize(_subsetSize){} : stages(_stages), nstages(_nstages), nodes(_nodes), leaves(_leaves), subsets(_subsets), features(_features), subsetSize(_subsetSize){}
__device__ __forceinline__ bool operator() (int y, int x, int* integral, const int pitch/*, DevMem2D_<int4> objects, const unsigned int maxN, unsigned int* n*/) const __device__ __forceinline__ bool operator() (int y, int x, int* integral, const int pitch) const
{ {
int current_node = 0; int current_node = 0;
int current_leave = 0; int current_leave = 0;
...@@ -482,7 +300,7 @@ namespace cv { namespace gpu { namespace device ...@@ -482,7 +300,7 @@ namespace cv { namespace gpu { namespace device
const DevMem2Db& mstages, const int nstages, const DevMem2Di& mnodes, const DevMem2Df& mleaves, const DevMem2Di& msubsets, const DevMem2Db& mfeatures, const DevMem2Db& mstages, const int nstages, const DevMem2Di& mnodes, const DevMem2Df& mleaves, const DevMem2Di& msubsets, const DevMem2Db& mfeatures,
const int subsetSize, DevMem2D_<int4> objects, unsigned int* classified, DevMem2Di integral) const int subsetSize, DevMem2D_<int4> objects, unsigned int* classified, DevMem2Di integral)
{ {
const int block = 256; const int block = 128;
int grid = divUp(workAmount, block); int grid = divUp(workAmount, block);
Cascade cascade((Stage*)mstages.ptr(), nstages, (ClNode*)mnodes.ptr(), mleaves.ptr(), msubsets.ptr(), (uchar4*)mfeatures.ptr(), subsetSize); Cascade cascade((Stage*)mstages.ptr(), nstages, (ClNode*)mnodes.ptr(), mleaves.ptr(), msubsets.ptr(), (uchar4*)mfeatures.ptr(), subsetSize);
lbp_cascade<<<grid, block>>>(cascade, frameW, frameH, windowW, windowH, initialScale, factor, workAmount, integral.ptr(), integral.step / sizeof(int), objects, classified); lbp_cascade<<<grid, block>>>(cascade, frameW, frameH, windowW, windowH, initialScale, factor, workAmount, integral.ptr(), integral.step / sizeof(int), objects, classified);
......
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