--- /dev/null
+
+///////////////////////////////////////////////////////////////////////////
+// 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