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raplase error output on CV_Error

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This commit is contained in:
marina.kolpakova 2013-01-09 16:10:05 +04:00
parent dd8de0c41f
commit a0f2203f22
1 changed files with 1 additions and 4 deletions

5
modules/ml/src/octave.cpp

@ -221,7 +221,6 @@ void cv::Octave::processPositives(const Dataset* dataset, const FeaturePool* poo
integrals.create(pool->size(), (w / shrinkage + 1) * (h / shrinkage * 10 + 1), CV_32SC1); integrals.create(pool->size(), (w / shrinkage + 1) * (h / shrinkage * 10 + 1), CV_32SC1);
int total = 0; int total = 0;
// for (svector::const_iterator it = dataset.pos.begin(); it != dataset.pos.end(); ++it)
for (int curr = 0; curr < dataset->available( Dataset::POSITIVE); ++curr) for (int curr = 0; curr < dataset->available( Dataset::POSITIVE); ++curr)
{ {
cv::Mat sample = dataset->get( Dataset::POSITIVE, curr); cv::Mat sample = dataset->get( Dataset::POSITIVE, curr);
@ -247,7 +246,6 @@ void cv::Octave::generateNegatives(const Dataset* dataset, const FeaturePool* po
sft::Random::engine eng(65633343L); sft::Random::engine eng(65633343L);
sft::Random::engine idxEng(764224349868L); sft::Random::engine idxEng(764224349868L);
// int w = boundingBox.width;
int h = boundingBox.height; int h = boundingBox.height;
int nimages = dataset->available(Dataset::NEGATIVE); int nimages = dataset->available(Dataset::NEGATIVE);
@ -276,7 +274,6 @@ void cv::Octave::generateNegatives(const Dataset* dataset, const FeaturePool* po
pool->preprocess(frame, channels); pool->preprocess(frame, channels);
dprintf("generated %d %d\n", dx, dy); dprintf("generated %d %d\n", dx, dy);
// // if (predict(sum)) // // if (predict(sum))
{ {
responses.ptr<float>(i)[0] = 0.f; responses.ptr<float>(i)[0] = 0.f;
@ -436,7 +433,7 @@ bool cv::Octave::train(const Dataset* dataset, const FeaturePool* pool, int weak
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; CV_Error(CV_StsInternal, "ERROR: tree can not be trained");
return ok; return ok;
} }