nms: part 1

pull/158/head
marina.kolpakova 12 years ago
parent a9f10e5cad
commit d2e88e1d4d
  1. 6
      modules/gpu/include/opencv2/gpu/gpu.hpp
  2. 67
      modules/gpu/src/cuda/icf-sc.cu
  3. 2
      modules/gpu/src/gpu_init.cpp
  4. 22
      modules/gpu/src/softcascade.cpp

@ -1552,12 +1552,14 @@ public:
enum {PEDESTRIAN = 0}; enum {PEDESTRIAN = 0};
}; };
enum { NO_REJECT = 1, DOLLAR = 2, /*PASCAL = 4,*/ DEFAULT = NO_REJECT};
// An empty cascade will be created. // An empty cascade will be created.
// Param minScale is a minimum scale relative to the original size of the image on which cascade will be applyed. // Param minScale is a minimum scale relative to the original size of the image on which cascade will be applyed.
// Param minScale is a maximum scale relative to the original size of the image on which cascade will be applyed. // Param minScale is a maximum scale relative to the original size of the image on which cascade will be applyed.
// Param scales is a number of scales from minScale to maxScale. // Param scales is a number of scales from minScale to maxScale.
// Param rejfactor is used for NMS. // Param rejfactor is used for NMS.
SCascade(const double minScale = 0.4, const double maxScale = 5., const int scales = 55, const int rejfactor = 1); SCascade(const double minScale = 0.4, const double maxScale = 5., const int scales = 55, const int rejCriteria = 1);
virtual ~SCascade(); virtual ~SCascade();
@ -1595,7 +1597,7 @@ private:
double maxScale; double maxScale;
int scales; int scales;
int rejfactor; int rejCriteria;
}; };
////////////////////////////////// SURF ////////////////////////////////////////// ////////////////////////////////// SURF //////////////////////////////////////////

@ -41,9 +41,10 @@
//M*/ //M*/
#include <opencv2/gpu/device/common.hpp> #include <opencv2/gpu/device/common.hpp>
#include <icf.hpp> #include <icf.hpp>
#include <stdio.h>
#include <float.h> #include <float.h>
#include <stdio.h>
namespace cv { namespace gpu { namespace device { namespace cv { namespace gpu { namespace device {
namespace icf { namespace icf {
@ -79,6 +80,70 @@ namespace icf {
} }
} }
__device__ __forceinline__ float overlapArea(const Detection &a, const Detection &b)
{
int w = ::min(a.x + a.w, b.x + b.w) - ::max(a.x, b.x);
int h = ::min(a.y + a.h, b.y + b.h) - ::max(a.y, b.y);
return (w < 0 || h < 0)? 0.f : (float)(w * h);
}
__global__ void overlap(const uint* n, const Detection* detections, uchar* overlaps)
{
const int idx = threadIdx.x;
const int total = *n;
for (int i = idx; i < total; i += 192)
{
const Detection& a = detections[i];
bool excluded = false;
for (int j = i + 1; j < total; ++j)
{
const Detection& b = detections[j];
float ovl = overlapArea(a, b) / ::min(a.w * a.h, b.w * b.h);
if (ovl > 0.65f)
{
int suppessed = (a.confidence > b.confidence)? j : i;
overlaps[suppessed] = 1;
excluded = excluded || (suppessed == i);
}
if (__all(excluded)) break;
}
}
}
__global__ void collect(const uint* n, const Detection* detections, uchar* overlaps)
{
const int idx = threadIdx.x;
const int total = *n;
for (int i = idx; i < total; i += 192)
{
if (!overlaps[i])
{
const Detection& det = detections[i];
// printf("%d: %d %d %d %d %f\n", i, det.x, det.y, det.w, det.h, det.confidence );
}
}
}
void suppress(const PtrStepSzb& objects, PtrStepSzb overlaps, PtrStepSzi ndetections)
{
int block = 192;
int grid = 1;
overlap<<<grid, block>>>((uint*)ndetections.ptr(0), (Detection*)objects.ptr(0), (uchar*)overlaps.ptr(0));
collect<<<grid, block>>>((uint*)ndetections.ptr(0), (Detection*)objects.ptr(0), (uchar*)overlaps.ptr(0));
// if (!stream)
{
cudaSafeCall( cudaGetLastError());
cudaSafeCall( cudaDeviceSynchronize());
}
}
template<typename Policy> template<typename Policy>
struct PrefixSum struct PrefixSum
{ {

@ -49,7 +49,7 @@ CV_INIT_ALGORITHM(SCascade, "CascadeDetector.SCascade",
obj.info()->addParam(obj, "minScale", obj.minScale); obj.info()->addParam(obj, "minScale", obj.minScale);
obj.info()->addParam(obj, "maxScale", obj.maxScale); obj.info()->addParam(obj, "maxScale", obj.maxScale);
obj.info()->addParam(obj, "scales", obj.scales); obj.info()->addParam(obj, "scales", obj.scales);
obj.info()->addParam(obj, "rejfactor", obj.rejfactor)); obj.info()->addParam(obj, "rejCriteria", obj.rejCriteria));
bool initModule_gpu(void) bool initModule_gpu(void)
{ {

@ -85,6 +85,8 @@ namespace cv { namespace gpu { namespace device {
namespace icf { namespace icf {
void fillBins(cv::gpu::PtrStepSzb hogluv, const cv::gpu::PtrStepSzf& nangle, void fillBins(cv::gpu::PtrStepSzb hogluv, const cv::gpu::PtrStepSzf& nangle,
const int fw, const int fh, const int bins, cudaStream_t stream); const int fw, const int fh, const int bins, cudaStream_t stream);
void suppress(const PtrStepSzb& objects, PtrStepSzb overlaps, PtrStepSzi ndetections);
} }
namespace imgproc { namespace imgproc {
@ -309,6 +311,8 @@ struct cv::gpu::SCascade::Fields
hogluv.create((fh / shr) * HOG_LUV_BINS + 1, fw / shr + 1, CV_32SC1); hogluv.create((fh / shr) * HOG_LUV_BINS + 1, fw / shr + 1, CV_32SC1);
hogluv.setTo(cv::Scalar::all(0)); hogluv.setTo(cv::Scalar::all(0));
overlaps.create(1, 5000, CV_8UC1);
return true; return true;
} }
@ -437,7 +441,15 @@ private:
} }
} }
#include <iostream>
public: public:
void suppress(GpuMat& ndetections, GpuMat& objects)
{
ensureSizeIsEnough(objects.rows, objects.cols, CV_8UC1, overlaps);
overlaps.setTo(0);
device::icf::suppress(objects, overlaps, ndetections);
// std::cout << cv::Mat(overlaps) << std::endl;
}
// scales range // scales range
float minScale; float minScale;
@ -469,6 +481,9 @@ public:
// 161x121x10 // 161x121x10
GpuMat hogluv; GpuMat hogluv;
// used for area overlap computing during
GpuMat overlaps;
// Cascade from xml // Cascade from xml
GpuMat octaves; GpuMat octaves;
GpuMat stages; GpuMat stages;
@ -478,6 +493,8 @@ public:
GpuMat sobelBuf; GpuMat sobelBuf;
GpuMat collected;
std::vector<device::icf::Octave> voctaves; std::vector<device::icf::Octave> voctaves;
DeviceInfo info; DeviceInfo info;
@ -494,7 +511,7 @@ public:
}; };
cv::gpu::SCascade::SCascade(const double mins, const double maxs, const int sc, const int rjf) cv::gpu::SCascade::SCascade(const double mins, const double maxs, const int sc, const int rjf)
: fields(0), minScale(mins), maxScale(maxs), scales(sc), rejfactor(rjf) {} : fields(0), minScale(mins), maxScale(maxs), scales(sc), rejCriteria(rjf) {}
cv::gpu::SCascade::~SCascade() { delete fields; } cv::gpu::SCascade::~SCascade() { delete fields; }
@ -534,6 +551,9 @@ void cv::gpu::SCascade::detect(InputArray image, InputArray _rois, OutputArray _
cudaStream_t stream = StreamAccessor::getStream(s); cudaStream_t stream = StreamAccessor::getStream(s);
flds.detect(rois, tmp, objects, stream); flds.detect(rois, tmp, objects, stream);
// if (rejCriteria != NO_REJECT)
flds.suppress(tmp, objects);
} }
void cv::gpu::SCascade::genRoi(InputArray _roi, OutputArray _mask, Stream& stream) const void cv::gpu::SCascade::genRoi(InputArray _roi, OutputArray _mask, Stream& stream) const

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