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+
+///////////////////////////////////////////////////////////////////////////
+// This program is free software: you can redistribute it and/or modify  //
+// it under the terms of the version 3 of the GNU General Public License //
+// as published by the Free Software Foundation.                         //
+//                                                                       //
+// This program is distributed in the hope that it will be useful, but   //
+// WITHOUT ANY WARRANTY; without even the implied warranty of            //
+// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU      //
+// General Public License for more details.                              //
+//                                                                       //
+// You should have received a copy of the GNU General Public License     //
+// along with this program. If not, see <http://www.gnu.org/licenses/>.  //
+//                                                                       //
+// Written by Francois Fleuret, (C) IDIAP                                //
+// Contact <francois.fleuret@idiap.ch> for comments & bug reports        //
+///////////////////////////////////////////////////////////////////////////
+
+#ifndef GLOBAL_H
+#define GLOBAL_H
+
+#include <iostream>
+
+using namespace std;
+
+#include "misc.h"
+#include "param_parser.h"
+#include "progress_bar.h"
+
+enum { LOSS_EXPONENTIAL,
+       LOSS_EV_REGULARIZED,
+       LOSS_HINGE,
+       LOSS_LOGISTIC };
+
+class Global {
+public:
+  int niceness;
+  int random_seed;
+  int pictures_for_article;
+
+  char pool_name[buffer_size];
+  char test_pool_name[buffer_size];
+  char detector_name[buffer_size];
+  char result_path[buffer_size];
+
+  char materials_image_numbers[buffer_size];
+  char materials_pf_numbers[buffer_size];
+
+  int loss_type;
+
+  int nb_images;
+
+  int tree_depth_max;
+
+  int nb_weak_learners_per_classifier;
+  int nb_classifiers_per_level;
+  int nb_levels;
+
+  scalar_t proportion_negative_cells_for_training;
+  int nb_negative_samples_per_positive;
+  int nb_features_for_boosting_optimization;
+  int force_head_belly_independence;
+
+  scalar_t proportion_for_train;
+  scalar_t proportion_for_validation;
+  scalar_t proportion_for_test;
+  bool write_validation_rocs;
+  bool write_parse_images;
+  bool write_tag_images;
+  scalar_t wanted_true_positive_rate;
+  int nb_wanted_true_positive_rates;
+
+  int nb_scales_per_power_of_two;
+  scalar_t min_head_radius;
+  scalar_t max_head_radius;
+  int root_cell_nb_xy_per_scale;
+
+  scalar_t pi_feature_window_min_size;
+
+  ProgressBar bar;
+
+  Global();
+  ~Global();
+
+  void init_parser(ParamParser *parser);
+  void read_parser(ParamParser *parser);
+
+  ostream *log_stream;
+
+  inline int scale_to_discrete_log_scale(scalar_t scale_ratio) {
+    return int(floor(log(scale_ratio) / log(2.0) * nb_scales_per_power_of_two));
+  }
+
+  inline scalar_t discrete_log_scale_to_scale(int discrete_scale) {
+    return exp( - scalar_t(discrete_scale) * log(2.0) / scalar_t(nb_scales_per_power_of_two));
+  }
+};
+
+extern Global global;
+
+#endif