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fix floating point precision

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This commit is contained in:
marina.kolpakova 2012-12-17 15:13:03 +04:00
parent ef4b18f341
commit 23d0e36167
3 changed files with 12 additions and 49 deletions
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4
apps/sft/include/sft/octave.hpp
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@ -147,7 +147,7 @@ public:
virtual void setRejectThresholds(cv::Mat& thresholds);
virtual void write( CvFileStorage* fs, string name) const;
virtual void write( cv::FileStorage &fs, const FeaturePool& pool, const Mat& thresholds = Mat()) const;
virtual void write( cv::FileStorage &fs, const FeaturePool& pool, const Mat& thresholds) const;
int logScale;
@ -160,7 +160,7 @@ protected:
float predict( const Mat& _sample, const cv::Range range) const;
private:
void traverse(const CvBoostTree* tree, cv::FileStorage& fs, int& nfeatures, int* used, const float* th = 0) const;
void traverse(const CvBoostTree* tree, cv::FileStorage& fs, int& nfeatures, int* used, const double* th) const;
virtual void initial_weights(double (&p)[2]);
cv::Rect boundingBox;

23
apps/sft/octave.cpp
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@ -116,7 +116,7 @@ void sft::Octave::setRejectThresholds(cv::Mat& thresholds)
for (int si = 0; si < nsamples; ++si)
{
float decision = dptr[si] = predict(trainData.col(si), stab, false, false);
mptr[si] = cv::saturate_cast<uchar>((uint)(responses.ptr<float>(si)[0] == 1.f && decision == 1.f));
mptr[si] = cv::saturate_cast<uchar>((uint)( (responses.ptr<float>(si)[0] == 1.f) && (decision == 1.f)));
}
// std::cout << "WARNING: responses " << responses << std::endl;
@ -144,8 +144,10 @@ void sft::Octave::setRejectThresholds(cv::Mat& thresholds)
double mintrace = 0.;
cv::minMaxLoc(traces.row(w), &mintrace);
thptr[w] = mintrace;
// std::cout << "mintrace " << mintrace << std::endl << traces.colRange(0, npositives) << std::endl;
// std::cout << "mintrace " << mintrace << std::endl << traces.colRange(0, npositives).rowRange(w, w + 1) << std::endl << std::endl << std::endl << std::endl;
}
std::cout << "WARNING: thresholds " << thresholds << std::endl;
}
namespace {
@ -300,7 +302,7 @@ template <typename T> int sgn(T val) {
return (T(0) < val) - (val < T(0));
}
void sft::Octave::traverse(const CvBoostTree* tree, cv::FileStorage& fs, int& nfeatures, int* used, const float* th) const
void sft::Octave::traverse(const CvBoostTree* tree, cv::FileStorage& fs, int& nfeatures, int* used, const double* th) const
{
std::queue<const CvDTreeNode*> nodes;
nodes.push( tree->get_root());
@ -310,6 +312,7 @@ void sft::Octave::traverse(const CvBoostTree* tree, cv::FileStorage& fs, int& nf
float* leafs = new float[(int)pow(2.f, get_params().max_depth)];
fs << "{";
fs << "treeThreshold" << *th;
fs << "internalNodes" << "[";
while (!nodes.empty())
{
@ -349,14 +352,16 @@ void sft::Octave::traverse(const CvBoostTree* tree, cv::FileStorage& fs, int& nf
fs << "leafValues" << "[";
for (int ni = 0; ni < -leafValIdx; ni++)
fs << ( (!th) ? leafs[ni] : (sgn(leafs[ni]) * *th));
fs << leafs[ni];//( (!th) ? leafs[ni] : (sgn(leafs[ni]) * *th));
fs << "]";
fs << "}";
}
void sft::Octave::write( cv::FileStorage &fso, const FeaturePool& pool, const Mat& thresholds) const
{
CV_Assert(!thresholds.empty());
cv::Mat used( 1, weak->total * (pow(2, params.max_depth) - 1), CV_32SC1);
int* usedPtr = used.ptr<int>(0);
int nfeatures = 0;
@ -373,19 +378,13 @@ void sft::Octave::write( cv::FileStorage &fso, const FeaturePool& pool, const Ma
CvBoostTree* tree;
CV_READ_SEQ_ELEM( tree, reader );
if (!thresholds.empty())
traverse(tree, fso, nfeatures, usedPtr, thresholds.ptr<float>(0)+ i);
else
traverse(tree, fso, nfeatures, usedPtr);
traverse(tree, fso, nfeatures, usedPtr, thresholds.ptr<double>(0) + i);
}
//
fso << "]";
// features
fso << "features" << "[";
for (int i = 0; i < nfeatures; ++i)
// fso << usedPtr[i];
pool.write(fso, usedPtr[i]);
fso << "]"
<< "}";
@ -409,7 +408,6 @@ bool sft::Octave::train(const Dataset& dataset, const FeaturePool& pool, int wea
// 1. fill integrals and classes
processPositives(dataset, pool);
generateNegatives(dataset);
// exit(0);
// 2. only sumple case (all features used)
int nfeatures = pool.size();
@ -550,7 +548,6 @@ void sft::FeaturePool::fill(int desired)
if (std::find(pool.begin(), pool.end(),f) == pool.end())
{
// std::cout << f << std::endl;
pool.push_back(f);
}
}

34
apps/sft/sft.cpp
View File

@ -100,16 +100,6 @@ int main(int argc, char** argv)
return 1;
}
cv::FileStorage fsr(cfg.outXmlPath + ".raw.xml" , cv::FileStorage::WRITE);
if(!fsr.isOpened())
{
std::cout << "Training stopped. Output classifier Xml file " <<cfg.outXmlPath + ".raw.xml" << " can't be opened." << std::endl << std::flush;
return 1;
}
// ovector strong;
// strong.reserve(cfg.octaves.size());
fso << cfg.cascadeName
<< "{"
<< "stageType" << "BOOST"
@ -120,16 +110,6 @@ int main(int argc, char** argv)
<< "shrinkage" << cfg.shrinkage
<< "octaves" << "[";
fsr << cfg.cascadeName
<< "{"
<< "stageType" << "BOOST"
<< "featureType" << "ICF"
<< "octavesNum" << (int)cfg.octaves.size()
<< "width" << cfg.modelWinSize.width
<< "height" << cfg.modelWinSize.height
<< "shrinkage" << cfg.shrinkage
<< "octaves" << "[";
// 3. Train all octaves
for (ivector::const_iterator it = cfg.octaves.begin(); it != cfg.octaves.end(); ++it)
{
@ -163,8 +143,6 @@ int main(int argc, char** argv)
boost.setRejectThresholds(thresholds);
boost.write(fso, pool, thresholds);
boost.write(fsr, pool);
// std::cout << "thresholds " << thresholds << std::endl;
cv::FileStorage tfs(("thresholds." + cfg.resPath(it)).c_str(), cv::FileStorage::WRITE);
tfs << "thresholds" << thresholds;
@ -174,18 +152,6 @@ int main(int argc, char** argv)
}
fso << "]" << "}";
fsr << "]" << "}";
// // // 6. Set thresolds
// // cascade.prune();
// // // 7. Postprocess
// // cascade.normolize();
// // // 8. Write result xml
// // cv::FileStorage ofs(cfg.outXmlPath, cv::FileStorage::WRITE);
// // ofs << cfg.cascadeName << cascade;
std::cout << "Training complete..." << std::endl;
return 0;
}