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opencv
Commit f01c5d90 authored by marina.kolpakova's avatar marina.kolpakova
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compute scales pyramid

parent a54d456a
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Showing with 110 additions and 140 deletions
modules/objdetect/src/softcascade.cpp
View file @ f01c5d90
......@@ -75,27 +75,93 @@ namespace {
{printf(" stage: %f %f\n",threshold, weight);}
};
// according to R. Benenson, M. Mathias, R. Timofte and L. Van Gool paper
struct CascadeIntrinsics
{
static const float lambda = 1.099f, a = 0.89f;
static const float intrinsics[10][4];
static float getFor(int channel, float scaling)
{
CV_Assert(channel < 10);
if ((scaling - 1.f) < FLT_EPSILON)
return 1.f;
int ud = (int)(scaling < 1.f);
return intrinsics[channel][(ud << 1)] * pow(scaling, intrinsics[channel][(ud << 1) + 1]);
}
};
const float CascadeIntrinsics::intrinsics[10][4] =
{ //da, db, ua, ub
// hog-like orientation bins
{a, lambda / log(2), 1, 2},
{a, lambda / log(2), 1, 2},
{a, lambda / log(2), 1, 2},
{a, lambda / log(2), 1, 2},
{a, lambda / log(2), 1, 2},
{a, lambda / log(2), 1, 2},
// gradient magnitude
{a, lambda / log(2), 1, 2},
// luv color channels
{1, 2, 1, 2},
{1, 2, 1, 2},
{1, 2, 1, 2}
};
static const char *SC_F_THRESHOLD = "threshold";
static const char *SC_F_DIRECTION = "direction";
static const char *SC_F_CHANNEL = "chennel";
static const char *SC_F_CHANNEL = "channel";
static const char *SC_F_RECT = "rect";
struct Feature
{
float threshold;
int direction;
int chennel;
int channel;
cv::Rect rect;
Feature() {}
Feature(const cv::FileNode& fn)
: threshold((float)fn[SC_F_THRESHOLD]), direction((int)fn[SC_F_DIRECTION]),
chennel((int)fn[SC_F_CHANNEL])
channel((int)fn[SC_F_CHANNEL])
{
cv::FileNode rn = fn[SC_F_RECT];
cv::FileNodeIterator r_it = rn.begin();
rect = cv::Rect(*(r_it++), *(r_it++), *(r_it++), *(r_it++));
printf(" feature: %f %d %d [%d %d %d %d]\n",threshold, direction, chennel, rect.x, rect.y, rect.width, rect.height);}
printf(" feature: %f %d %d [%d %d %d %d]\n",threshold, direction, channel, rect.x, rect.y, rect.width, rect.height);}
Feature rescale(float relScale)
{
Feature res(*this);
res.rect = cv::Rect (cvRound(rect.x * relScale), cvRound(rect.y * relScale),
cvRound(rect.width * relScale), cvRound(rect.height * relScale));
res.threshold = threshold * CascadeIntrinsics::getFor(channel, relScale);
return res;
}
};
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); }
};
}
......@@ -112,6 +178,43 @@ struct cv::SoftCascade::Filds
std::vector<Octave> octaves;
std::vector<Stage> stages;
std::vector<Feature> features;
std::vector<Level> levels;
// compute levels of full pyramid
void calcLevels(int frameW, int frameH, int scales)
{
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 - (origObjWidth * scale)), std::max(0.0f, frameH - (origObjHeight * 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));
}
for (std::vector<Level>::iterator level = levels.begin(); level < levels.end(); ++level)
{
float minAbsLog = FLT_MAX;
for (std::vector<Octave>::iterator oct = octaves.begin(); oct < octaves.end(); ++oct)
{
const Octave& octave =*oct;
float logOctave = log(octave.scale);
float logAbsScale = fabs((*level).logFactor - logOctave);
if(logAbsScale < minAbsLog)
(*level).assign(octave.scale, ORIG_OBJECT_WIDTH, ORIG_OBJECT_HEIGHT);
}
}
}
bool fill(const FileNode &root, const float mins, const float maxs)
{
......@@ -193,110 +296,6 @@ struct cv::SoftCascade::Filds
}
};
// 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, a = 0.89f;
// static const float intrinsics[10][4];
// static float getFor(int chennel, float scaling)
// {
// CV_Assert(chennel < 10);
// if ((scaling - 1.f) < FLT_EPSILON)
// return 1.f;
// int ud = (int)(scaling < 1.f);
// return intrinsics[chennel][(ud << 1)] * pow(scaling, intrinsics[chennel][(ud << 1) + 1]);
// }
// };
// const float CascadeIntrinsics::intrinsics[10][4] =
// { //da, db, ua, ub
// // hog-like orientation bins
// {a, lambda / log(2), 1, 2},
// {a, lambda / log(2), 1, 2},
// {a, lambda / log(2), 1, 2},
// {a, lambda / log(2), 1, 2},
// {a, lambda / log(2), 1, 2},
// {a, lambda / log(2), 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}
// };
// struct Feature
// {
// cv::Rect rect;
// int channel;
// float threshold;
// Feature(int x, int y, int w, int h, int c, float t) : rect(cv::Rect(x, y, w, h)), channel(c), threshold(t) {}
// Feature(cv::Rect r, int c, float t) : rect(r), channel(c), threshold(t) {}
// Feature rescale(float relScale)
// {
// cv::Rect r(cvRound(rect.x * relScale), cvRound(rect.y * relScale), cvRound(rect.width * relScale), cvRound(rect.height * relScale));
// return Feature( r, channel, threshold * CascadeIntrinsics::getFor(channel, relScale));
// }
// };
// }
cv::SoftCascade::SoftCascade() : filds(0) {}
cv::SoftCascade::SoftCascade( const string& filename, const float minScale, const float maxScale)
......@@ -318,38 +317,9 @@ bool cv::SoftCascade::load( const string& filename, const float minScale, const
if (!fs.isOpened()) return false;
filds = new Filds;
if (!(*filds).fill(fs.getFirstTopLevelNode(), minScale, maxScale)) return false;
// ////////////////
// // 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
// std::vector<Level> levels;
// pyrLevels(FRAME_WIDTH, FRAME_HEIGHT, ORIG_OBJECT_WIDTH, ORIG_OBJECT_HEIGHT, 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, ORIG_OBJECT_WIDTH, ORIG_OBJECT_HEIGHT);
// }
// }
// load cascade from xml
// read(const FileNode &root)
Filds& flds = *filds;
if (!flds.fill(fs.getFirstTopLevelNode(), minScale, maxScale)) return false;
// flds.calcLevels(FRAME_WIDTH, FRAME_HEIGHT, TOTAL_SCALES);
return true;
}
......
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