mirror of https://github.com/CGAL/cgal
add missing std::ios::binary to input file stream
and fix conversion warnings
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parent
87c9ffd0fa
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5e4f3e72c6
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@ -40,7 +40,7 @@ typedef Classification::Point_set_feature_generator<Kernel, Point_set, Pmap>
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int main (int argc, char** argv)
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int main (int argc, char** argv)
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{
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{
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std::string filename (argc > 1 ? argv[1] : "data/b9_training.ply");
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std::string filename (argc > 1 ? argv[1] : "data/b9_training.ply");
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std::ifstream in (filename.c_str());
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std::ifstream in (filename.c_str(), std::ios::binary);
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Point_set pts;
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Point_set pts;
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std::cerr << "Reading input" << std::endl;
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std::cerr << "Reading input" << std::endl;
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@ -91,7 +91,7 @@ int main (int argc, char** argv)
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Classification::classify_with_graphcut<CGAL::Sequential_tag>
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Classification::classify_with_graphcut<CGAL::Sequential_tag>
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(pts, pts.point_map(), labels, classifier,
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(pts, pts.point_map(), labels, classifier,
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generator.neighborhood().k_neighbor_query(12),
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generator.neighborhood().k_neighbor_query(12),
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0.2, 1, label_indices);
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0.2f, 1, label_indices);
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t.stop();
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t.stop();
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std::cerr << "Classification with graphcut done in " << t.time() << " second(s)" << std::endl;
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std::cerr << "Classification with graphcut done in " << t.time() << " second(s)" << std::endl;
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@ -135,7 +135,7 @@ public:
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{
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{
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for (std::size_t f = 0; f < m_features.size(); ++ f)
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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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training_features.at<float>(int(index), int(f)) = m_features[f]->value(i);
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training_labels.at<float>(int(index), 0) = ground_truth[i];
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training_labels.at<float>(int(index), 0) = static_cast<float>(ground_truth[i]);
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++ index;
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++ index;
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}
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}
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