From a0f2203f222c5a8e7ecfab37a73324e40395d491 Mon Sep 17 00:00:00 2001 From: "marina.kolpakova" Date: Wed, 9 Jan 2013 16:10:05 +0400 Subject: [PATCH] raplase error output on CV_Error --- modules/ml/src/octave.cpp | 5 +---- 1 file changed, 1 insertion(+), 4 deletions(-) diff --git a/modules/ml/src/octave.cpp b/modules/ml/src/octave.cpp index e8fc600..fa34ad1 100644 --- a/modules/ml/src/octave.cpp +++ b/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); 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) { 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 idxEng(764224349868L); - // int w = boundingBox.width; int h = boundingBox.height; int nimages = dataset->available(Dataset::NEGATIVE); @@ -276,7 +274,6 @@ void cv::Octave::generateNegatives(const Dataset* dataset, const FeaturePool* po pool->preprocess(frame, channels); dprintf("generated %d %d\n", dx, dy); - // // if (predict(sum)) { responses.ptr(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); if (!ok) - std::cout << "ERROR: tree can not be trained " << std::endl; + CV_Error(CV_StsInternal, "ERROR: tree can not be trained"); return ok; } -- 2.7.4