fix feature computing
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30b2a94582
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@ -1,2 +1,4 @@
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add_subdirectory(haartraining)
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add_subdirectory(traincascade)
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add_subdirectory(sft)
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@ -73,6 +73,22 @@ struct ICF
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return bb != b.bb || channel != b.channel;
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}
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float operator() (const Mat& integrals, const cv::Size& model) const
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{
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const int* ptr = integrals.ptr<int>(0) + (model.height * channel + bb.y) * model.width + bb.x;
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int a = ptr[0];
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int b = ptr[bb.width];
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ptr += bb.height * model.width;
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int c = ptr[bb.width];
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int d = ptr[0];
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return (float)(a - b + c - d);
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}
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private:
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cv::Rect bb;
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int channel;
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@ -93,6 +93,10 @@ bool sft::Octave::train( const cv::Mat& trainData, const cv::Mat& _responses, co
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}
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std::cout << "WARNING: " << sampleIdx << std::endl;
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std::cout << "WARNING: " << trainData << std::endl;
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std::cout << "WARNING: " << _responses << std::endl;
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std::cout << "WARNING: " << varIdx << std::endl;
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std::cout << "WARNING: " << varType << std::endl;
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bool update = false;
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return cv::Boost::train(trainData, CV_COL_SAMPLE, _responses, varIdx, sampleIdx, varType, missingDataMask, _params,
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@ -313,7 +317,7 @@ sft::FeaturePool::~FeaturePool(){}
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float sft::FeaturePool::apply(int fi, int si, const Mat& integrals) const
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{
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return 0.f;
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return pool[fi](integrals.row(si), model);
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}
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@ -113,7 +113,7 @@ int main(int argc, char** argv)
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int shrinkage = cfg.shrinkage;
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int octave = *it;
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cv::Size model = cfg.modelWinSize;
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cv::Size model = cv::Size(cfg.modelWinSize.width / cfg.shrinkage, cfg.modelWinSize.height / cfg.shrinkage );
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std::string path = cfg.trainPath;
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cv::Rect boundingBox(cfg.offset.x / cfg.shrinkage, cfg.offset.y / cfg.shrinkage,
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