fix feature computing

apps/CMakeLists.txt

 add_subdirectory(haartraining)
 add_subdirectory(traincascade)
+add_subdirectory(sft)
+

apps/sft/include/sft/octave.hpp

@@ -73,6 +73,22 @@ struct ICF
         return bb != b.bb || channel != b.channel;
     }
 
+
+    float operator() (const Mat& integrals, const cv::Size& model) const
+    {
+        const int* ptr = integrals.ptr<int>(0) + (model.height * channel + bb.y) * model.width + bb.x;
+
+        int a = ptr[0];
+        int b = ptr[bb.width];
+
+        ptr += bb.height * model.width;
+
+        int c = ptr[bb.width];
+        int d = ptr[0];
+
+        return (float)(a - b + c - d);
+    }
+
 private:
     cv::Rect bb;
     int channel;

apps/sft/octave.cpp

@@ -93,6 +93,10 @@ bool sft::Octave::train( const cv::Mat& trainData, const cv::Mat& _responses, co
     }
 
     std::cout << "WARNING: " << sampleIdx << std::endl;
+    std::cout << "WARNING: " << trainData << std::endl;
+    std::cout << "WARNING: " << _responses << std::endl;
+    std::cout << "WARNING: " << varIdx << std::endl;
+    std::cout << "WARNING: " << varType << std::endl;
 
     bool update = false;
     return cv::Boost::train(trainData, CV_COL_SAMPLE, _responses, varIdx, sampleIdx, varType, missingDataMask, _params,
@@ -313,7 +317,7 @@ sft::FeaturePool::~FeaturePool(){}
 
 float sft::FeaturePool::apply(int fi, int si, const Mat& integrals) const
 {
-    return 0.f;
+    return pool[fi](integrals.row(si), model);
 }
 
 

apps/sft/sft.cpp

@@ -113,7 +113,7 @@ int main(int argc, char** argv)
         int shrinkage  = cfg.shrinkage;
         int octave = *it;
 
-        cv::Size model = cfg.modelWinSize;
+        cv::Size model = cv::Size(cfg.modelWinSize.width / cfg.shrinkage, cfg.modelWinSize.height / cfg.shrinkage );
         std::string path = cfg.trainPath;
 
         cv::Rect boundingBox(cfg.offset.x / cfg.shrinkage, cfg.offset.y / cfg.shrinkage,