commented debug out
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@@ -84,11 +84,11 @@ bool sft::Octave::train( const cv::Mat& _trainData, const cv::Mat& _responses, c
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const cv::Mat& sampleIdx, const cv::Mat& varType, const cv::Mat& missingDataMask)
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{
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std::cout << "WARNING: sampleIdx " << sampleIdx << std::endl;
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std::cout << "WARNING: trainData " << _trainData << std::endl;
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std::cout << "WARNING: _responses " << _responses << std::endl;
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std::cout << "WARNING: varIdx" << varIdx << std::endl;
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std::cout << "WARNING: varType" << varType << std::endl;
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// std::cout << "WARNING: sampleIdx " << sampleIdx << std::endl;
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// std::cout << "WARNING: trainData " << _trainData << std::endl;
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// std::cout << "WARNING: _responses " << _responses << std::endl;
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// std::cout << "WARNING: varIdx" << varIdx << std::endl;
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// std::cout << "WARNING: varType" << 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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@@ -117,9 +117,9 @@ void sft::Octave::setRejectThresholds(cv::Mat& thresholds)
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mptr[si] = cv::saturate_cast<uchar>((uint)(responses.ptr<float>(si)[0] == 1.f && decision == 1.f));
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}
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std::cout << "WARNING: responses " << responses << std::endl;
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std::cout << "WARNING: desisions " << desisions << std::endl;
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std::cout << "WARNING: ppmask " << ppmask << std::endl;
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// std::cout << "WARNING: responses " << responses << std::endl;
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// std::cout << "WARNING: desisions " << desisions << std::endl;
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// std::cout << "WARNING: ppmask " << ppmask << std::endl;
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int weaks = weak->total;
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thresholds.create(1, weaks, CV_64FC1);
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@@ -142,7 +142,7 @@ void sft::Octave::setRejectThresholds(cv::Mat& thresholds)
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double mintrace = 0.;
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cv::minMaxLoc(traces.row(w), &mintrace);
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thptr[w] = mintrace;
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std::cout << "mintrace " << mintrace << std::endl << traces.colRange(0, npositives) << std::endl;
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// std::cout << "mintrace " << mintrace << std::endl << traces.colRange(0, npositives) << std::endl;
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}
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}
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@@ -223,7 +223,7 @@ void sft::Octave::processPositives(const Dataset& dataset, const FeaturePool& po
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{
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const string& curr = *it;
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dprintf("Process candidate positive image %s\n", curr.c_str());
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// dprintf("Process candidate positive image %s\n", curr.c_str());
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cv::Mat sample = cv::imread(curr);
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@@ -262,8 +262,8 @@ void sft::Octave::generateNegatives(const Dataset& dataset)
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{
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int curr = iRand(idxEng);
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dprintf("View %d-th sample\n", curr);
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dprintf("Process %s\n", dataset.neg[curr].c_str());
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// dprintf("View %d-th sample\n", curr);
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// dprintf("Process %s\n", dataset.neg[curr].c_str());
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Mat frame = cv::imread(dataset.neg[curr]);
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@@ -349,12 +349,12 @@ bool sft::Octave::train(const Dataset& dataset, const FeaturePool& pool, int wea
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cv::Mat a(1, nfeatures, CV_32FC1);
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cv::Mat votes(1, cvSliceLength( CV_WHOLE_SEQ, weak ), CV_32FC1, cv::Scalar::all(0));
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std::cout << a.cols << " " << a.rows << " !!!!!!!!!!! " << data->var_all << std::endl;
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// std::cout << a.cols << " " << a.rows << " !!!!!!!!!!! " << data->var_all << std::endl;
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for (int si = 0; si < nsamples; ++si)
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{
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// trainData.col(si).copyTo(a.reshape(0,trainData.rows));
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float desision = predict(trainData.col(si), votes, false, true);
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std::cout << "desision " << desision << " class " << responses.at<float>(si, 0) << votes <<std::endl;
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// std::cout << "desision " << desision << " class " << responses.at<float>(si, 0) << votes <<std::endl;
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}
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#endif
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return ok;
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@@ -129,16 +129,20 @@ int main(int argc, char** argv)
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if (boost.train(dataset, pool, cfg.weaks, cfg.treeDepth))
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{
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std::cout << "Octave " << *it << " was successfully trained..." << std::endl;
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CvFileStorage* fout = cvOpenFileStorage(cfg.resPath(it).c_str(), 0, CV_STORAGE_WRITE);
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boost.write(fout, cfg.cascadeName);
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// strong.push_back(octave);
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cvReleaseFileStorage( &fout);
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cv::Mat thresholds;
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boost.setRejectThresholds(thresholds);
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std::cout << "thresholds " << thresholds << std::endl;
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// std::cout << "thresholds " << thresholds << std::endl;
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cv::FileStorage tfs(("thresholds." + cfg.resPath(it)).c_str(), cv::FileStorage::WRITE);
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tfs << "thresholds" << thresholds;
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std::cout << "Octave " << *it << " was successfully trained..." << std::endl;
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}
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}
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