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Select random regions + interpret LAS classification property in plugin

This commit is contained in:
Simon Giraudot 2017-10-05 08:49:53 +02:00
parent c52b32b744
commit f9384c3453
4 changed files with 131 additions and 22 deletions
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16
Polyhedron/demo/Polyhedron/Plugins/Classification/Classification_plugin.cpp
View File

@ -157,7 +157,7 @@ public:
action_train = ui_widget.menu->menu()->addAction ("Train classifier");
connect(action_train, SIGNAL(triggered()), this,
SLOT(on_train_clicked()));
action_reset = ui_widget.menu->menu()->addAction ("Reset all training sets");
connect(action_reset, SIGNAL(triggered()), this,
SLOT(on_reset_training_sets_clicked()));
@ -742,6 +742,20 @@ public Q_SLOTS:
classif->validate_selection();
}
void on_select_random_region_clicked()
{
Item_classification_base* classif
= get_classification();
if(!classif)
{
print_message("Error: there is no point set classification item!");
return;
}
classif->select_random_region();
item_changed(classif->item());
}
void on_train_clicked()
{
Item_classification_base* classif

1
Polyhedron/demo/Polyhedron/Plugins/Classification/Item_classification_base.h
View File

@ -40,6 +40,7 @@ public:
virtual void reset_training_set (const char* name) = 0;
virtual void reset_training_sets() = 0;
virtual void select_random_region() = 0;
virtual void validate_selection () = 0;
virtual void train(int classifier, unsigned int nb_trials) = 0;
virtual bool run (int method, int classifier, std::size_t subdivisions, double smoothing) = 0;

134
Polyhedron/demo/Polyhedron/Plugins/Classification/Point_set_item_classification.cpp
View File

@ -29,10 +29,32 @@ Point_set_item_classification::Point_set_item_classification(Scene_points_with_n
boost::tie (m_training, training_found) = m_points->point_set()->add_property_map<int>("training", -1);
bool classif_found = false;
boost::tie (m_classif, classif_found) = m_points->point_set()->add_property_map<int>("label", -1);
training_found = !training_found; // add_property_map returns false if
classif_found = !classif_found; // property was already there
bool las_found = false;
if (!classif_found)
{
Point_set::Property_map<unsigned char> las_classif;
boost::tie (las_classif, las_found) = m_points->point_set()->property_map<unsigned char>("classification");
if (las_found)
{
for (Point_set::const_iterator it = m_points->point_set()->begin();
it != m_points->point_set()->first_selected(); ++ it)
{
unsigned char uc = las_classif[*it];
m_classif[*it] = int(uc);
if (!training_found)
m_training[*it] = int(uc);
}
m_points->point_set()->remove_property_map (las_classif);
classif_found = true;
training_found = true;
}
}
if (training_found || classif_found)
{
int lmax = 0;
@ -51,22 +73,47 @@ Point_set_item_classification::Point_set_item_classification(Scene_points_with_n
lmax = (std::max)(l, lmax);
}
}
// Try to recover label names from PLY comments
std::map<int, std::string> label_names;
const std::string& comments = m_points->comments();
std::istringstream stream (comments);
std::string line;
while (getline(stream, line))
if (las_found) // Use LAS standard
{
std::stringstream iss (line);
std::string tag;
if (iss >> tag && tag == "label")
label_names.insert (std::make_pair (0, std::string("never_clfied")));
label_names.insert (std::make_pair (1, std::string("unclassified")));
label_names.insert (std::make_pair (2, std::string("ground")));
label_names.insert (std::make_pair (3, std::string("low_veget")));
label_names.insert (std::make_pair (4, std::string("med_veget")));
label_names.insert (std::make_pair (5, std::string("high_veget")));
label_names.insert (std::make_pair (6, std::string("building")));
label_names.insert (std::make_pair (7, std::string("noise")));
label_names.insert (std::make_pair (8, std::string("reserved")));
label_names.insert (std::make_pair (9, std::string("water")));
label_names.insert (std::make_pair (10, std::string("rail")));
label_names.insert (std::make_pair (11, std::string("road surface")));
label_names.insert (std::make_pair (12, std::string("reserved_2")));
label_names.insert (std::make_pair (13, std::string("wire_guard")));
label_names.insert (std::make_pair (14, std::string("wire_conduct")));
label_names.insert (std::make_pair (15, std::string("trans_tower")));
label_names.insert (std::make_pair (16, std::string("wire_connect")));
label_names.insert (std::make_pair (17, std::string("bridge_deck")));
label_names.insert (std::make_pair (18, std::string("high_noise")));
}
else // Try to recover label names from PLY comments
{
const std::string& comments = m_points->comments();
std::istringstream stream (comments);
std::string line;
while (getline(stream, line))
{
int idx;
std::string name;
if (iss >> idx >> name)
label_names.insert (std::make_pair (idx, name));
std::stringstream iss (line);
std::string tag;
if (iss >> tag && tag == "label")
{
int idx;
std::string name;
if (iss >> idx >> name)
label_names.insert (std::make_pair (idx, name));
}
}
}
@ -83,12 +130,9 @@ Point_set_item_classification::Point_set_item_classification(Scene_points_with_n
m_labels.add(oss.str().c_str());
}
CGAL::Classification::HSV_Color hsv;
hsv[0] = 360. * (i / double(lmax + 1));
hsv[1] = 76.;
hsv[2] = 85.;
Color rgb = CGAL::Classification::hsv_to_rgb(hsv);
m_label_colors.push_back (QColor(rgb[0], rgb[1], rgb[2]));
m_label_colors.push_back (QColor (64 + rand() % 192,
64 + rand() % 192,
64 + rand() % 192));
}
}
else
@ -369,7 +413,55 @@ void Point_set_item_classification::compute_features (std::size_t nb_scales)
std::cerr << "Features = " << m_features.size() << std::endl;
}
void Point_set_item_classification::select_random_region()
{
m_points->point_set()->reset_indices();
std::size_t scale = (rand() % m_generator->number_of_scales());
bool use_grid = (rand() % 2);
std::vector<std::size_t> selected;
if (use_grid)
{
std::size_t x = (rand() % m_generator->grid(scale).width());
std::size_t y = (rand() % m_generator->grid(scale).height());
std::copy (m_generator->grid(scale).indices_begin(x,y),
m_generator->grid(scale).indices_end(x,y),
std::back_inserter (selected));
}
else
{
m_generator->neighborhood(0).sphere_neighbor_query (m_generator->radius_neighbors(scale))
(*(m_points->point_set()->points().begin() + (rand() % m_points->point_set()->size())),
std::back_inserter (selected));
}
if (selected.empty())
return;
std::sort (selected.begin(), selected.end());
std::size_t current_idx = 0;
std::vector<std::size_t> unselected;
for (Point_set::const_iterator it = m_points->point_set()->begin();
it != m_points->point_set()->end(); ++ it)
if (std::size_t(*it) == selected[current_idx])
current_idx ++;
else
unselected.push_back (*it);
for (std::size_t i = 0; i < unselected.size(); ++ i)
*(m_points->point_set()->begin() + i) = unselected[i];
for (std::size_t i = 0; i < selected.size(); ++ i)
*(m_points->point_set()->begin() + (unselected.size() + i)) = selected[i];
m_points->point_set()->set_first_selected
(m_points->point_set()->begin() + unselected.size());
}
void Point_set_item_classification::train(int classifier, unsigned int nb_trials)
{

2
Polyhedron/demo/Polyhedron/Plugins/Classification/Point_set_item_classification.h
View File

@ -46,6 +46,8 @@ class Point_set_item_classification : public Item_classification_base
void erase_item() { m_points = NULL; }
void compute_features (std::size_t nb_scales);
void select_random_region();
void add_selection_to_training_set (const char* name)
{