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shrinking before integral calculation

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pull/137/head
marina.kolpakova 12 years ago
parent dc74ce20ab
commit 6f53be4102
2 changed files with 106 additions and 76 deletions
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  1. 180
      modules/objdetect/src/softcascade.cpp
  2. 2
      modules/objdetect/test/test_softcascade.cpp

180
modules/objdetect/src/softcascade.cpp
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@ -161,8 +161,8 @@ namespace {
// {1, 2, 1, 2}
// };
// struct Level
// {
struct Level
{
// int index;
// float factor;
@ -189,7 +189,7 @@ namespace {
// float relScale() {return (factor / octave.scale); }
// float srScale() {return (factor / octave.scale * shrinkage); }
// };
};
// struct Integral
// {
@ -209,6 +209,8 @@ struct cv::SoftCascade::Filds
int origObjWidth;
int origObjHeight;
int shrinkage;
std::vector<Octave> octaves;
std::vector<Stage> stages;
std::vector<Node> nodes;
@ -216,6 +218,8 @@ struct cv::SoftCascade::Filds
std::vector<Feature> features;
std::vector<Level> levels;
// typedef std::vector<Stage>::iterator stIter_t;
// // carrently roi must be save for out of ranges.
@ -236,11 +240,11 @@ struct cv::SoftCascade::Filds
// }
// }
// // compute levels of full pyramid
// void calcLevels(int frameW, int frameH, int scales)
// {
// CV_Assert(scales > 1);
// levels.clear();
// 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;
@ -274,7 +278,7 @@ struct cv::SoftCascade::Filds
// }
// }
// }
// }
}
bool fill(const FileNode &root, const float mins, const float maxs)
{
@ -360,15 +364,16 @@ struct cv::SoftCascade::Filds
for (; st != st_end; ++st )
features.push_back(Feature(*st));
}
shrinkage = octaves[0].shrinkage;
return true;
}
};
cv::SoftCascade::SoftCascade() : filds(0) {}
cv::SoftCascade::SoftCascade( const string& filename, const float minScale, const float maxScale)
cv::SoftCascade::SoftCascade( const string& filename, const float minScale, const float maxScale) : filds(0)
{
filds = new Filds;
load(filename, minScale, maxScale);
}
cv::SoftCascade::~SoftCascade()
@ -378,7 +383,8 @@ cv::SoftCascade::~SoftCascade()
bool cv::SoftCascade::load( const string& filename, const float minScale, const float maxScale)
{
delete filds;
if (filds)
delete filds;
filds = 0;
cv::FileStorage fs(filename, FileStorage::READ);
@ -387,56 +393,92 @@ bool cv::SoftCascade::load( const string& filename, const float minScale, const
filds = new Filds;
Filds& flds = *filds;
if (!flds.fill(fs.getFirstTopLevelNode(), minScale, maxScale)) return false;
// // flds.calcLevels(FRAME_WIDTH, FRAME_HEIGHT, TOTAL_SCALES);
flds.calcLevels(FRAME_WIDTH, FRAME_HEIGHT, TOTAL_SCALES);
return true;
}
namespace {
void calcHistBins(const cv::Mat& grey, cv::Mat magIntegral, std::vector<cv::Mat>& histInts, const int bins)
void calcHistBins(const cv::Mat& grey, cv::Mat& magIntegral, std::vector<cv::Mat>& histInts, const int bins, int shrinkage)
{
// CV_Assert( grey.type() == CV_8U);
// const int rows = grey.rows + 1;
// const int cols = grey.cols + 1;
// cv::Size intSumSize(cols, rows);
// histInts.clear();
// std::vector<cv::Mat> hist;
// for (int bin = 0; bin < bins; ++bin)
// {
// hist.push_back(cv::Mat(rows, cols, CV_32FC1));
// }
// cv::Mat df_dx, df_dy, mag, angle;
// cv::Sobel(grey, df_dx, CV_32F, 1, 0);
// cv::Sobel(grey, df_dy, CV_32F, 0, 1);
// cv::cartToPolar(df_dx, df_dy, mag, angle, true);
// const float magnitudeScaling = 1.0 / sqrt(2);
// mag *= magnitudeScaling;
// angle /= 60;
// for (int h = 0; h < mag.rows; ++h)
// {
// float* magnitude = mag.ptr<float>(h);
// float* ang = angle.ptr<float>(h);
// for (int w = 0; w < mag.cols; ++w)
// {
// hist[(int)ang[w]].ptr<float>(h)[w] = magnitude[w];
// }
// }
// for (int bin = 0; bin < bins; ++bin)
// {
// cv::Mat sum;
// cv::integral(hist[bin], sum);
// histInts.push_back(sum);
// }
// cv::integral(mag, magIntegral, mag.depth());
CV_Assert( grey.type() == CV_8U);
float scale = 1.f / shrinkage;
const int rows = grey.rows + 1;
const int cols = grey.cols + 1;
cv::Size intSumSize(cols, rows);
histInts.clear();
std::vector<cv::Mat> hist;
for (int bin = 0; bin < bins; ++bin)
{
hist.push_back(cv::Mat(rows, cols, CV_32FC1));
}
cv::Mat df_dx, df_dy, mag, angle;
cv::Sobel(grey, df_dx, CV_32F, 1, 0);
cv::Sobel(grey, df_dy, CV_32F, 0, 1);
cv::cartToPolar(df_dx, df_dy, mag, angle, true);
const float magnitudeScaling = 1.0 / sqrt(2);
mag *= magnitudeScaling;
angle /= 60;
for (int h = 0; h < mag.rows; ++h)
{
float* magnitude = mag.ptr<float>(h);
float* ang = angle.ptr<float>(h);
for (int w = 0; w < mag.cols; ++w)
{
hist[(int)ang[w]].ptr<float>(h)[w] = magnitude[w];
}
}
for (int bin = 0; bin < bins; ++bin)
{
cv::Mat shrunk, sum;
cv::resize(hist[bin], shrunk, cv::Size(), scale, scale, cv::INTER_AREA);
cv::integral(shrunk, sum);
histInts.push_back(sum);
}
cv::Mat shrMag;
cv::resize(mag, shrMag, cv::Size(), scale, scale, cv::INTER_AREA);
cv::integral(shrMag, magIntegral, mag.depth());
}
struct ChannelStorage
{
std::vector<cv::Mat> hog;
cv::Mat luv;
cv::Mat magnitude;
int shrinkage;
enum {HOG_BINS = 6};
ChannelStorage() {}
ChannelStorage(const cv::Mat& colored, int shr) : shrinkage(shr)
{
cv::Mat _luv;
cv::cvtColor(colored, _luv, CV_BGR2Luv);
cv::integral(luv, luv);
cv::Mat grey;
cv::cvtColor(colored, grey, CV_RGB2GRAY);
calcHistBins(grey, magnitude, hog, HOG_BINS, shrinkage);
std::cout << magnitude.cols << " " << magnitude.rows << std::endl;
cv::imshow("1", magnitude);
cv::waitKey(0);
}
};
}
@ -444,31 +486,19 @@ namespace {
void cv::SoftCascade::detectMultiScale(const Mat& image, const std::vector<cv::Rect>& rois, std::vector<cv::Rect>& objects,
const int step, const int rejectfactor)// add step scaling
{
// typedef std::vector<cv::Rect>::const_iterator RIter_t;
// // only color images are supperted
// CV_Assert(image.type() == CV_8UC3);
// // only this window size allowed
// CV_Assert(image.cols == 640 && image.rows == 480);
// objects.clear();
// // create integrals
// cv::Mat luv;
// cv::cvtColor(image, luv, CV_BGR2Luv);
typedef std::vector<cv::Rect>::const_iterator RIter_t;
// only color images are supperted
CV_Assert(image.type() == CV_8UC3);
// cv::Mat luvIntegral;
// cv::integral(luv, luvIntegral);
// only this window size allowed
CV_Assert(image.cols == 640 && image.rows == 480);
// cv::Mat grey;
// cv::cvtColor(image, grey, CV_RGB2GRAY);
objects.clear();
// std::vector<cv::Mat> hist;
// cv::Mat magnitude;
// const int bins = 6;
// calcHistBins(grey, magnitude, hist, bins);
const Filds& fld = *filds;
// Integral integrals(magnitude, hist, luv);
// create integrals
ChannelStorage storage(image, fld.shrinkage);
// for (RIter_t it = rois.begin(); it != rois.end(); ++it)
// {

2
modules/objdetect/test/test_softcascade.cpp
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@ -51,7 +51,7 @@ TEST(SoftCascade, readCascade)
TEST(SoftCascade, detect)
{
std::string xml = cvtest::TS::ptr()->get_data_path() + "cascadeandhog/softcascade.xml";
std::string xml = cvtest::TS::ptr()->get_data_path() + "cascadeandhog/sc_cvpr_2012_to_opencv.xml";
cv::SoftCascade cascade;
ASSERT_TRUE(cascade.load(xml));

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