generic-library/opencv
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remove dead code

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This commit is contained in:
marina.kolpakova 2012-12-24 09:33:25 +04:00
parent d4d47b1e58
commit 19236b6e43
1 changed files with 1 additions and 35 deletions
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36
apps/sft/octave.cpp
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@ -85,13 +85,6 @@ sft::Octave::~Octave(){}
bool sft::Octave::train( const cv::Mat& _trainData, const cv::Mat& _responses, const cv::Mat& varIdx, bool sft::Octave::train( const cv::Mat& _trainData, const cv::Mat& _responses, const cv::Mat& varIdx,
const cv::Mat& sampleIdx, const cv::Mat& varType, const cv::Mat& missingDataMask) const cv::Mat& sampleIdx, const cv::Mat& varType, const cv::Mat& missingDataMask)
{ {
// std::cout << "WARNING: sampleIdx " << sampleIdx << std::endl;
// std::cout << "WARNING: trainData " << _trainData << std::endl;
// std::cout << "WARNING: _responses " << _responses << std::endl;
// std::cout << "WARNING: varIdx" << varIdx << std::endl;
// std::cout << "WARNING: varType" << varType << std::endl;
bool update = false; bool update = false;
return cv::Boost::train(_trainData, CV_COL_SAMPLE, _responses, varIdx, sampleIdx, varType, missingDataMask, params, return cv::Boost::train(_trainData, CV_COL_SAMPLE, _responses, varIdx, sampleIdx, varType, missingDataMask, params,
update); update);
@ -119,10 +112,6 @@ void sft::Octave::setRejectThresholds(cv::Mat& thresholds)
mptr[si] = cv::saturate_cast<uchar>((uint)( (responses.ptr<float>(si)[0] == 1.f) && (decision == 1.f))); mptr[si] = cv::saturate_cast<uchar>((uint)( (responses.ptr<float>(si)[0] == 1.f) && (decision == 1.f)));
} }
// std::cout << "WARNING: responses " << responses << std::endl;
// std::cout << "WARNING: desisions " << desisions << std::endl;
// std::cout << "WARNING: ppmask " << ppmask << std::endl;
int weaks = weak->total; int weaks = weak->total;
thresholds.create(1, weaks, CV_64FC1); thresholds.create(1, weaks, CV_64FC1);
double* thptr = thresholds.ptr<double>(0); double* thptr = thresholds.ptr<double>(0);
@ -144,10 +133,7 @@ void sft::Octave::setRejectThresholds(cv::Mat& thresholds)
double mintrace = 0.; double mintrace = 0.;
cv::minMaxLoc(traces.row(w), &mintrace); cv::minMaxLoc(traces.row(w), &mintrace);
thptr[w] = mintrace; thptr[w] = mintrace;
// std::cout << "mintrace " << mintrace << std::endl << traces.colRange(0, npositives).rowRange(w, w + 1) << std::endl << std::endl << std::endl << std::endl;
} }
std::cout << "WARNING: thresholds " << thresholds << std::endl;
} }
namespace { namespace {
@ -211,8 +197,6 @@ public:
}; };
} }
// ToDo: parallelize it, fix curring
// ToDo: sunch model size and shrinced model size usage/ Now model size mean already shrinked model
void sft::Octave::processPositives(const Dataset& dataset, const FeaturePool& pool) void sft::Octave::processPositives(const Dataset& dataset, const FeaturePool& pool)
{ {
Preprocessor prepocessor(shrinkage); Preprocessor prepocessor(shrinkage);
@ -227,8 +211,6 @@ void sft::Octave::processPositives(const Dataset& dataset, const FeaturePool& po
{ {
const string& curr = *it; const string& curr = *it;
// dprintf("Process candidate positive image %s\n", curr.c_str());
cv::Mat sample = cv::imread(curr); cv::Mat sample = cv::imread(curr);
cv::Mat channels = integrals.row(total).reshape(0, h / shrinkage * 10 + 1); cv::Mat channels = integrals.row(total).reshape(0, h / shrinkage * 10 + 1);
@ -266,9 +248,6 @@ void sft::Octave::generateNegatives(const Dataset& dataset)
{ {
int curr = iRand(idxEng); int curr = iRand(idxEng);
// dprintf("View %d-th sample\n", curr);
// dprintf("Process %s\n", dataset.neg[curr].c_str());
Mat frame = cv::imread(dataset.neg[curr]); Mat frame = cv::imread(dataset.neg[curr]);
int maxW = frame.cols - 2 * boundingBox.x - boundingBox.width; int maxW = frame.cols - 2 * boundingBox.x - boundingBox.width;
@ -352,7 +331,7 @@ void sft::Octave::traverse(const CvBoostTree* tree, cv::FileStorage& fs, int& nf
fs << "leafValues" << "["; fs << "leafValues" << "[";
for (int ni = 0; ni < -leafValIdx; ni++) for (int ni = 0; ni < -leafValIdx; ni++)
fs << leafs[ni];//( (!th) ? leafs[ni] : (sgn(leafs[ni]) * *th)); fs << leafs[ni];
fs << "]"; fs << "]";
@ -447,19 +426,6 @@ bool sft::Octave::train(const Dataset& dataset, const FeaturePool& pool, int wea
bool ok = train(trainData, responses, varIdx, sampleIdx, varType, missingMask); bool ok = train(trainData, responses, varIdx, sampleIdx, varType, missingMask);
if (!ok) if (!ok)
std::cout << "ERROR: tree can not be trained " << std::endl; std::cout << "ERROR: tree can not be trained " << std::endl;
#if defined SELF_TEST
cv::Mat a(1, nfeatures, CV_32FC1);
cv::Mat votes(1, cvSliceLength( CV_WHOLE_SEQ, weak ), CV_32FC1, cv::Scalar::all(0));
// std::cout << a.cols << " " << a.rows << " !!!!!!!!!!! " << data->var_all << std::endl;
for (int si = 0; si < nsamples; ++si)
{
// trainData.col(si).copyTo(a.reshape(0,trainData.rows));
float desision = predict(trainData.col(si), votes, false, true);
// std::cout << "desision " << desision << " class " << responses.at<float>(si, 0) << votes <<std::endl;
}
#endif
return ok; return ok;
} }