fixes for soft cascade training app

apps/sft/config.cpp

@@ -69,6 +69,7 @@ void sft::Config::write(cv::FileStorage& fs) const
        << "outXmlPath"   << outXmlPath
 
        << "seed"         << seed
+       << "featureType"  << featureType
        << "}";
 }
 
@@ -99,6 +100,7 @@ void sft::Config::read(const cv::FileNode& node)
     outXmlPath =  (std::string)node["outXmlPath"];
 
     seed = (int)node["seed"];
+    featureType = (std::string)node["featureType"];
 }
 
 void sft::write(cv::FileStorage& fs, const string&, const Config& x)
@@ -153,7 +155,8 @@ std::ostream& sft::operator<<(std::ostream& out, const Config& m)
 
         << std::setw(14) << std::left  << "cascadeName"  << m.cascadeName  << std::endl
         << std::setw(14) << std::left  << "outXmlPath"   << m.outXmlPath   << std::endl
-        << std::setw(14) << std::left  << "seed"         << m.seed         << std::endl;
+        << std::setw(14) << std::left  << "seed"         << m.seed         << std::endl
+        << std::setw(14) << std::left  << "featureType"  << m.featureType  << std::endl;
 
     return out;
 }

apps/sft/include/sft/config.hpp

@@ -121,6 +121,9 @@ struct Config
     // seed for random generation
     int seed;
 
+    // channel feature type
+    string featureType;
+
     // // bounding rectangle for actual example into example window
     // cv::Rect exampleWindow;
 };

apps/sft/sft.cpp

@@ -104,7 +104,7 @@ int main(int argc, char** argv)
     fso << cfg.cascadeName
         << "{"
         << "stageType"   << "BOOST"
-        << "featureType" << "ICF"
+        << "featureType" << cfg.featureType
         << "octavesNum"  << (int)cfg.octaves.size()
         << "width"       << cfg.modelWinSize.width
         << "height"      << cfg.modelWinSize.height
@@ -118,7 +118,12 @@ int main(int argc, char** argv)
         int nfeatures  = cfg.poolSize;
         cv::Size model = cfg.model(it);
         std::cout << "Model " << model << std::endl;
-        cv::Ptr<cv::FeaturePool> pool = cv::FeaturePool::create(model, nfeatures);
+
+        int nchannels = (cfg.featureType == "HOG6MagLuv") ? 10: 8;
+
+        std::cout << "number of feature channels is " << nchannels << std::endl;
+
+        cv::Ptr<cv::FeaturePool> pool = cv::FeaturePool::create(model, nfeatures, nchannels);
         nfeatures = pool->size();
 
 
@@ -130,7 +135,9 @@ int main(int argc, char** argv)
 
         typedef cv::Octave Octave;
 
-        cv::Ptr<Octave> boost = Octave::create(boundingBox, npositives, nnegatives, *it, shrinkage, nfeatures);
+        cv::Ptr<cv::ChannelFeatureBuilder> builder = cv::ChannelFeatureBuilder::create(cfg.featureType);
+        std::cout << "Channel builder " << builder->info()->name() << std::endl;
+        cv::Ptr<Octave> boost = Octave::create(boundingBox, npositives, nnegatives, *it, shrinkage, nfeatures, builder);
 
         std::string path = cfg.trainPath;
         sft::ScaledDataset dataset(path, *it);

modules/softcascade/src/soft_cascade_octave.cpp

@@ -137,7 +137,7 @@ BoostedSoftCascadeOctave::BoostedSoftCascadeOctave(cv::Rect bb, int np, int nn,
     int w = boundingBox.width;
     int h = boundingBox.height;
 
-    integrals.create(poolSize, (w / shrinkage + 1) * (h / shrinkage * 10 + 1), CV_32SC1);
+    integrals.create(poolSize, (w / shrinkage + 1) * (h / shrinkage * builder->totalChannels() + 1), CV_32SC1);
 }
 
 BoostedSoftCascadeOctave::~BoostedSoftCascadeOctave(){}