mirror of https://github.com/CGAL/cgal
Fix conversion warnings
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parent
a1df51aafb
commit
566e84f154
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@ -158,14 +158,14 @@ public:
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std::size_t nb_samples = 0;
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for (std::size_t i = 0; i < ground_truth.size(); ++ i)
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if (ground_truth[i] != -1)
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if (int(ground_truth[i]) != -1)
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++ nb_samples;
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cv::Mat training_features (int(nb_samples), int(m_features.size()), CV_32FC1);
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cv::Mat training_labels (int(nb_samples), 1, CV_32FC1);
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for (std::size_t i = 0, index = 0; i < ground_truth.size(); ++ i)
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if (ground_truth[i] != -1)
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if (int(ground_truth[i]) != -1)
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{
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for (std::size_t f = 0; f < m_features.size(); ++ f)
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training_features.at<float>(int(index), int(f)) = m_features[f]->value(i);
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@ -311,7 +311,7 @@ public:
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std::vector<std::vector<std::size_t> > training_sets (m_labels.size());
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std::size_t nb_tot = 0;
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for (std::size_t i = 0; i < ground_truth.size(); ++ i)
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if (ground_truth[i] != -1)
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if (int(ground_truth[i]) != -1)
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{
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training_sets[std::size_t(ground_truth[i])].push_back (i);
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++ nb_tot;
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@ -202,9 +202,9 @@ void Surface_mesh_item_classification::train
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BOOST_FOREACH(face_descriptor fd, faces(*(m_mesh->polyhedron())))
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{
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training[fd] = m_training[fd];
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if (training[fd] != -1)
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if (training[fd] != std::size_t(-1))
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{
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nb_label[std::size_t(training[fd])] ++;
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nb_label[training[fd]] ++;
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++ nb_total;
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}
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}
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