cv::Octave boost(boundingBox, npositives, nnegatives, *it, shrinkage);
std::string path = cfg.trainPath;
- sft::ScaledDataset dataset(path, boost.logScale);
+ sft::ScaledDataset dataset(path, *it);
if (boost.train(&dataset, &pool, cfg.weaks, cfg.treeDepth))
{
virtual void setRejectThresholds(OutputArray thresholds);
virtual void write( CvFileStorage* fs, string name) const;
virtual void write( cv::FileStorage &fs, const FeaturePool* pool, InputArray thresholds) const;
- virtual ~Octave();
-
-
virtual float predict( InputArray _sample, InputArray _votes, bool raw_mode, bool return_sum ) const;
-
-
-
-
- int logScale;
-
+ virtual ~Octave();
protected:
virtual bool train( const cv::Mat& trainData, const cv::Mat& responses, const cv::Mat& varIdx=cv::Mat(),
const cv::Mat& sampleIdx=cv::Mat(), const cv::Mat& varType=cv::Mat(), const cv::Mat& missingDataMask=cv::Mat());
void traverse(const CvBoostTree* tree, cv::FileStorage& fs, int& nfeatures, int* used, const double* th) const;
virtual void initial_weights(double (&p)[2]);
+ int logScale;
cv::Rect boundingBox;
int npositives;