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clean code

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This commit is contained in:
marina.kolpakova 2012-11-07 03:14:15 +04:00
parent 4656872161
commit f1e36043e6
2 changed files with 43 additions and 120 deletions
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2
modules/objdetect/src/icf.cpp
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@ -41,8 +41,6 @@
//M*/ //M*/
#include <precomp.hpp> #include <precomp.hpp>
#include <opencv2/objdetect/objdetect.hpp>
#include <opencv2/core/core.hpp>
cv::SCascade::Channels::Channels(int shr) : shrinkage(shr) {} cv::SCascade::Channels::Channels(int shr) : shrinkage(shr) {}

155
modules/objdetect/src/softcascade.cpp
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@ -41,29 +41,16 @@
//M*/ //M*/
#include <precomp.hpp> #include <precomp.hpp>
#include <opencv2/objdetect/objdetect.hpp>
#include <opencv2/core/core.hpp>
#include <vector>
#include <string>
#include <iostream>
#include <cstdio>
#include <stdarg.h>
// used for noisy printfs
// #define WITH_DEBUG_OUT
#if defined WITH_DEBUG_OUT
# define dprintf(format, ...) \
do { printf(format, ##__VA_ARGS__); } while (0)
#else
# define dprintf(format, ...)
#endif
namespace { namespace {
struct Octave struct Octave
{ {
Octave(const int i, cv::Size origObjSize, const cv::FileNode& fn)
: index(i), scale((float)fn[SC_OCT_SCALE]), stages((int)fn[SC_OCT_STAGES]),
size(cvRound(origObjSize.width * scale), cvRound(origObjSize.height * scale)),
shrinkage((int)fn[SC_OCT_SHRINKAGE]) {}
int index; int index;
float scale; float scale;
int stages; int stages;
@ -73,49 +60,32 @@ struct Octave
static const char *const SC_OCT_SCALE; static const char *const SC_OCT_SCALE;
static const char *const SC_OCT_STAGES; static const char *const SC_OCT_STAGES;
static const char *const SC_OCT_SHRINKAGE; static const char *const SC_OCT_SHRINKAGE;
Octave(const int i, cv::Size origObjSize, const cv::FileNode& fn)
: index(i), scale((float)fn[SC_OCT_SCALE]), stages((int)fn[SC_OCT_STAGES]),
size(cvRound(origObjSize.width * scale), cvRound(origObjSize.height * scale)),
shrinkage((int)fn[SC_OCT_SHRINKAGE])
{}
}; };
const char *const Octave::SC_OCT_SCALE = "scale";
const char *const Octave::SC_OCT_STAGES = "stageNum";
const char *const Octave::SC_OCT_SHRINKAGE = "shrinkingFactor";
struct Weak struct Weak
{ {
Weak(){}
Weak(const cv::FileNode& fn) : threshold((float)fn[SC_STAGE_THRESHOLD]){}
float threshold; float threshold;
static const char *const SC_STAGE_THRESHOLD; static const char *const SC_STAGE_THRESHOLD;
Weak(){}
Weak(const cv::FileNode& fn) : threshold((float)fn[SC_STAGE_THRESHOLD]){}
}; };
const char *const Weak::SC_STAGE_THRESHOLD = "stageThreshold";
struct Node struct Node
{ {
int feature;
float threshold;
Node(){} Node(){}
Node(const int offset, cv::FileNodeIterator& fIt) Node(const int offset, cv::FileNodeIterator& fIt)
: feature((int)(*(fIt +=2)++) + offset), threshold((float)(*(fIt++))){} : feature((int)(*(fIt +=2)++) + offset), threshold((float)(*(fIt++))){}
int feature;
float threshold;
}; };
struct Feature struct Feature
{ {
int channel;
cv::Rect rect;
float rarea;
static const char * const SC_F_CHANNEL;
static const char * const SC_F_RECT;
Feature() {} Feature() {}
Feature(const cv::FileNode& fn) : channel((int)fn[SC_F_CHANNEL]) Feature(const cv::FileNode& fn) : channel((int)fn[SC_F_CHANNEL])
{ {
@ -126,41 +96,23 @@ struct Feature
// 1 / area // 1 / area
rarea = 1.f / ((rect.width - rect.x) * (rect.height - rect.y)); rarea = 1.f / ((rect.width - rect.x) * (rect.height - rect.y));
} }
int channel;
cv::Rect rect;
float rarea;
static const char *const SC_F_CHANNEL;
static const char *const SC_F_RECT;
}; };
const char *const Octave::SC_OCT_SCALE = "scale";
const char *const Octave::SC_OCT_STAGES = "stageNum";
const char *const Octave::SC_OCT_SHRINKAGE = "shrinkingFactor";
const char *const Weak::SC_STAGE_THRESHOLD = "stageThreshold";
const char *const Feature::SC_F_CHANNEL = "channel"; const char *const Feature::SC_F_CHANNEL = "channel";
const char *const Feature::SC_F_RECT = "rect"; const char *const Feature::SC_F_RECT = "rect";
struct CascadeIntrinsics
{
static const float lambda = 1.099f, a = 0.89f;
static float getFor(bool isUp, float scaling)
{
if (fabs(scaling - 1.f) < FLT_EPSILON)
return 1.f;
// according to R. Benenson, M. Mathias, R. Timofte and L. Van Gool's and Dallal's papers
static const float A[2][2] =
{ //channel <= 6, otherwise
{ 0.89f, 1.f}, // down
{ 1.00f, 1.f} // up
};
static const float B[2][2] =
{ //channel <= 6, otherwise
{ 1.099f / log(2), 2.f}, // down
{ 0.f, 2.f} // up
};
float a = A[(int)(scaling >= 1)][(int)(isUp)];
float b = B[(int)(scaling >= 1)][(int)(isUp)];
dprintf("scaling: %f %f %f %f\n", scaling, a, b, a * pow(scaling, b));
return a * pow(scaling, b);
}
};
struct Level struct Level
{ {
const Octave* octave; const Octave* octave;
@ -172,37 +124,36 @@ struct Level
cv::Size workRect; cv::Size workRect;
cv::Size objSize; cv::Size objSize;
enum { R_SHIFT = 1 << 15 }; float scaling[2]; // 0-th for channels <= 6, 1-st otherwise
typedef cv::SCascade::Detection Detection;
float scaling[2];
typedef cv::SCascade::Detection detection_t;
Level(const Octave& oct, const float scale, const int shrinkage, const int w, const int h) Level(const Octave& oct, const float scale, const int shrinkage, const int w, const int h)
: octave(&oct), origScale(scale), relScale(scale / oct.scale), : octave(&oct), origScale(scale), relScale(scale / oct.scale),
workRect(cv::Size(cvRound(w / (float)shrinkage),cvRound(h / (float)shrinkage))), workRect(cv::Size(cvRound(w / (float)shrinkage),cvRound(h / (float)shrinkage))),
objSize(cv::Size(cvRound(oct.size.width * relScale), cvRound(oct.size.height * relScale))) objSize(cv::Size(cvRound(oct.size.width * relScale), cvRound(oct.size.height * relScale)))
{ {
scaling[0] = CascadeIntrinsics::getFor(false, relScale) / (relScale * relScale); scaling[0] = ((relScale >= 1.f)? 1.f : (0.89f * pow(relScale, 1.099f / log(2)))) / (relScale * relScale);
scaling[1] = CascadeIntrinsics::getFor(true, relScale) / (relScale * relScale); scaling[1] = 1.f;
scaleshift = relScale * (1 << 16); scaleshift = relScale * (1 << 16);
} }
void addDetection(const int x, const int y, float confidence, std::vector<detection_t>& detections) const void addDetection(const int x, const int y, float confidence, std::vector<Detection>& detections) const
{ {
int shrinkage = (*octave).shrinkage; int shrinkage = (*octave).shrinkage;
cv::Rect rect(cvRound(x * shrinkage), cvRound(y * shrinkage), objSize.width, objSize.height); cv::Rect rect(cvRound(x * shrinkage), cvRound(y * shrinkage), objSize.width, objSize.height);
detections.push_back(detection_t(rect, confidence)); detections.push_back(Detection(rect, confidence));
} }
float rescale(cv::Rect& scaledRect, const float threshold, int idx) const float rescale(cv::Rect& scaledRect, const float threshold, int idx) const
{ {
#define SSHIFT(a) ((a) + (1 << 15)) >> 16
// rescale // rescale
scaledRect.x = (scaleshift * scaledRect.x + R_SHIFT) >> 16; scaledRect.x = SSHIFT(scaleshift * scaledRect.x);
scaledRect.y = (scaleshift * scaledRect.y + R_SHIFT) >> 16; scaledRect.y = SSHIFT(scaleshift * scaledRect.y);
scaledRect.width = (scaleshift * scaledRect.width + R_SHIFT) >> 16; scaledRect.width = SSHIFT(scaleshift * scaledRect.width);
scaledRect.height = (scaleshift * scaledRect.height + R_SHIFT) >> 16; scaledRect.height = SSHIFT(scaleshift * scaledRect.height);
#undef SSHIFT
float sarea = (scaledRect.width - scaledRect.x) * (scaledRect.height - scaledRect.y); float sarea = (scaledRect.width - scaledRect.x) * (scaledRect.height - scaledRect.y);
// compensation areas rounding // compensation areas rounding
@ -219,7 +170,6 @@ struct ChannelStorage
enum {HOG_BINS = 6, HOG_LUV_BINS = 10}; enum {HOG_BINS = 6, HOG_LUV_BINS = 10};
ChannelStorage() {}
ChannelStorage(const cv::Mat& colored, int shr) : shrinkage(shr) ChannelStorage(const cv::Mat& colored, int shr) : shrinkage(shr)
{ {
hog.clear(); hog.clear();
@ -273,29 +223,19 @@ struct cv::SCascade::Fields
cv::Size frameSize; cv::Size frameSize;
enum { BOOST = 0 };
typedef std::vector<Octave>::iterator octIt_t; typedef std::vector<Octave>::iterator octIt_t;
void detectAt(const int dx, const int dy, const Level& level, const ChannelStorage& storage, void detectAt(const int dx, const int dy, const Level& level, const ChannelStorage& storage,
std::vector<Detection>& detections) const std::vector<Detection>& detections) const
{ {
dprintf("detect at: %d %d\n", dx, dy);
float detectionScore = 0.f; float detectionScore = 0.f;
const Octave& octave = *(level.octave); const Octave& octave = *(level.octave);
int stBegin = octave.index * octave.stages, stEnd = stBegin + 1024;//octave.stages; int stBegin = octave.index * octave.stages, stEnd = stBegin + 1024;//octave.stages;
dprintf(" octave stages: %d to %d index %d %f level %f\n",
stBegin, stEnd, octave.index, octave.scale, level.origScale);
int st = stBegin; int st = stBegin;
for(; st < stEnd; ++st) for(; st < stEnd; ++st)
{ {
dprintf("index: %d\n", st);
const Weak& stage = stages[st]; const Weak& stage = stages[st];
{ {
int nId = st * 3; int nId = st * 3;
@ -309,12 +249,8 @@ struct cv::SCascade::Fields
float sum = storage.get(feature.channel, scaledRect); float sum = storage.get(feature.channel, scaledRect);
dprintf("root feature %d %f\n",feature.channel, sum);
int next = (sum >= threshold)? 2 : 1; int next = (sum >= threshold)? 2 : 1;
dprintf("go: %d (%f >= %f)\n\n" ,next, sum, threshold);
// leaves // leaves
const Node& leaf = nodes[nId + next]; const Node& leaf = nodes[nId + next];
const Feature& fLeaf = features[leaf.feature]; const Feature& fLeaf = features[leaf.feature];
@ -327,25 +263,12 @@ struct cv::SCascade::Fields
int lShift = (next - 1) * 2 + ((sum >= threshold) ? 1 : 0); int lShift = (next - 1) * 2 + ((sum >= threshold) ? 1 : 0);
float impact = leaves[(st * 4) + lShift]; float impact = leaves[(st * 4) + lShift];
dprintf("decided: %d (%f >= %f) %d %f\n\n" ,next, sum, threshold, lShift, impact);
detectionScore += impact; detectionScore += impact;
} }
dprintf("extracted stage:\n");
dprintf("ct %f\n", stage.threshold);
dprintf("computed score %f\n\n", detectionScore);
#if defined WITH_DEBUG_OUT
if (st - stBegin > 50 ) break;
#endif
if (detectionScore <= stage.threshold) return; if (detectionScore <= stage.threshold) return;
} }
dprintf("x %d y %d: %d\n", dx, dy, st - stBegin);
dprintf(" got %d\n", st);
level.addDetection(dx, dy, detectionScore, detections); level.addDetection(dx, dy, detectionScore, detections);
} }
@ -546,16 +469,18 @@ void cv::SCascade::detect(cv::InputArray _image, cv::InputArray _rois, std::vect
if (_rois.kind() == cv::_InputArray::NONE) if (_rois.kind() == cv::_InputArray::NONE)
return detectNoRoi(image, objects); return detectNoRoi(image, objects);
int shr = fld.shrinkage;
cv::Mat roi = _rois.getMat(); cv::Mat roi = _rois.getMat();
cv::Mat mask(image.rows / fld.shrinkage, image.cols / fld.shrinkage, CV_8UC1); cv::Mat mask(image.rows / shr, image.cols / shr, CV_8UC1);
mask.setTo(cv::Scalar::all(0)); mask.setTo(cv::Scalar::all(0));
cv::Rect* r = roi.ptr<cv::Rect>(0); cv::Rect* r = roi.ptr<cv::Rect>(0);
for (int i = 0; i < (int)roi.cols; ++i) for (int i = 0; i < (int)roi.cols; ++i)
cv::Mat(mask, cv::Rect(r[i].x / fld.shrinkage, r[i].y / fld.shrinkage, r[i].width / fld.shrinkage , r[i].height / fld.shrinkage)).setTo(cv::Scalar::all(1)); cv::Mat(mask, cv::Rect(r[i].x / shr, r[i].y / shr, r[i].width / shr , r[i].height / shr)).setTo(cv::Scalar::all(1));
// create integrals // create integrals
ChannelStorage storage(image, fld.shrinkage); ChannelStorage storage(image, shr);
typedef std::vector<Level>::const_iterator lIt; typedef std::vector<Level>::const_iterator lIt;
for (lIt it = fld.levels.begin(); it != fld.levels.end(); ++it) for (lIt it = fld.levels.begin(); it != fld.levels.end(); ++it)