scale pyramid calculations

pull/137/head
marina.kolpakova 13 years ago
parent cd301e530f
commit fb113e5ce4
  1. 3
      modules/objdetect/include/opencv2/objdetect/objdetect.hpp
  2. 137
      modules/objdetect/src/softcascade.cpp

@ -506,6 +506,7 @@ protected:
// int stripSize, int yStep, double factor, vector<Rect>& candidates,
// vector<int>& rejectLevels, vector<double>& levelWeights, bool outputRejectLevels=false);
enum { BOOST = 0 };
enum { FRAME_WIDTH = 640, FRAME_HEIGHT = 480, TOTAL_SCALES = 55, CLASSIFIERS = 5};
private:
struct Feature
@ -514,7 +515,7 @@ private:
int channel;
};
stuct Stamp
struct Stamp
{
};

@ -39,8 +39,15 @@
// the use of this software, even if advised of the possibility of such damage.
//M*/
struct Filds
#include <precomp.hpp>
#include <opencv2/objdetect/objdetect.hpp>
#include <vector>
struct cv::SoftCascade::Filds
{
std::vector<float> octaves;
// cv::Mat luv;
// std::vector<cv::Mat> bins;
// cv::Mat magnitude;
@ -48,27 +55,139 @@ struct Filds
// int windowStep;
};
namespace {
struct Cascade {
int logOctave;
float octave;
cv::Size objSize;
};
struct Level {
int index;
float factor;
float logFactor;
int width;
int height;
float octave;
cv::Size objSize;
Level(int i,float f, float lf, int w, int h) : index(i), factor(f), logFactor(lf), width(w), height(h), octave(0.f) {}
void assign(float o, int detW, int detH)
{
octave = o;
objSize = cv::Size(cv::saturate_cast<int>(detW * o), cv::saturate_cast<int>(detH * o));
}
float relScale() {return (factor / octave); }
};
// compute levels of full pyramid
void pyrLevels(int frameW, int frameH, int detW, int detH, int scales, float minScale, float maxScale, std::vector<Level> levels)
{
CV_Assert(scales > 1);
levels.clear();
float logFactor = (log(maxScale) - log(minScale)) / (scales -1);
float scale = minScale;
for (int sc = 0; sc < scales; ++sc)
{
Level level(sc, scale, log(scale) + logFactor, std::max(0.0f, frameW - (detW * scale)), std::max(0.0f, frameH - (detH * scale)));
if (!level.width || !level.height)
break;
else
levels.push_back(level);
if (fabs(scale - maxScale) < FLT_EPSILON) break;
scale = std::min(maxScale, expf(log(scale) + logFactor));
}
}
// according to R. Benenson, M. Mathias, R. Timofte and L. Van Gool paper
struct CascadeIntrinsics {
static const float lambda = 1.099f/ 0.301029996f, a = 0.89f;
static const float intrinsics[10][4];
SoftCascade::SoftCascade() : filds(0) {}
static float getFor(int chennel, int scaling, int ab)
{
CV_Assert(chennel < 10 && scaling < 2 && ab < 2);
return intrinsics[chennel][(scaling << 1) + ab];
}
SoftCascade::SoftCascade( const string& filename )
};
const float CascadeIntrinsics::intrinsics[10][4] =
{ //da, db, ua, ub
// hog-like orientation bins
{a, lambda, 1, 2},
{a, lambda, 1, 2},
{a, lambda, 1, 2},
{a, lambda, 1, 2},
{a, lambda, 1, 2},
{a, lambda, 1, 2},
// gradient magnitude
{a, lambda / log(2), 1, 2},
// luv -color chennels
{1, 2, 1, 2},
{1, 2, 1, 2},
{1, 2, 1, 2}
};
}
cv::SoftCascade::SoftCascade() : filds(0) {}
cv::SoftCascade::SoftCascade( const string& filename )
{
filds = new filds;
filds = new Filds;
load(filename);
}
virtual SoftCascade::~SoftCascade()
cv::SoftCascade::~SoftCascade()
{
delete filds;
}
bool SoftCascade::load( const string& filename )
bool cv::SoftCascade::load( const string& filename )
{
// temp fixture
Filds& flds = *filds;
flds.octaves.push_back(0.5f);
flds.octaves.push_back(1.0f);
flds.octaves.push_back(2.0f);
flds.octaves.push_back(4.0f);
flds.octaves.push_back(8.0f);
// scales calculations
int origObjectW = 64;
int origObjectH = 128;
float maxScale = 5.f, minScale = 0.4f;
std::vector<Level> levels;
pyrLevels(FRAME_WIDTH, FRAME_HEIGHT, origObjectW, origObjectH, TOTAL_SCALES, minScale, maxScale,levels);
for (std::vector<Level>::iterator level = levels.begin(); level < levels.end(); ++level)
{
float minAbsLog = FLT_MAX;
for (std::vector<float>::iterator oct = flds.octaves.begin(); oct < flds.octaves.end(); ++oct)
{
float logOctave = log(*oct);
float logAbsScale = fabs((*level).logFactor - logOctave);
if(logAbsScale < minAbsLog)
(*level).assign(*oct, origObjectW, origObjectH);
}
}
return true;
}
virtual void SoftCascade::detectMultiScale(const Mat& image, const std::vector<cv::Rect>& rois, std::vector<cv::Rect>& objects,
const double factor = 1.05, const int step = 4, const int rejectfactor = 1)
void cv::SoftCascade::detectMultiScale(const Mat& image, const std::vector<cv::Rect>& rois, std::vector<cv::Rect>& objects,
const double factor, const int step, const int rejectfactor)
{}
virtual void SoftCascade::detectForOctave(const int octave)
void cv::SoftCascade::detectForOctave(const int octave)
{}
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