2 * folded-ctf is an implementation of the folded hierarchy of
3 * classifiers for object detection, developed by Francois Fleuret
6 * Copyright (c) 2008 Idiap Research Institute, http://www.idiap.ch/
7 * Written by Francois Fleuret <francois.fleuret@idiap.ch>
9 * This file is part of folded-ctf.
11 * folded-ctf is free software: you can redistribute it and/or modify
12 * it under the terms of the GNU General Public License version 3 as
13 * published by the Free Software Foundation.
15 * folded-ctf is distributed in the hope that it will be useful, but
16 * WITHOUT ANY WARRANTY; without even the implied warranty of
17 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
18 * General Public License for more details.
20 * You should have received a copy of the GNU General Public License
21 * along with folded-ctf. If not, see <http://www.gnu.org/licenses/>.
27 A SampleSet stands for a set of samples from R^d with their
28 labels. It abstracts the notion features and is what the machine
29 learning techniques of this software see.
36 #include "pose_cell.h"
37 #include "pi_feature_family.h"
38 #include "shared_responses.h"
43 SharedResponses *_shared_feature_values;
44 scalar_t **_feature_values;
49 inline int nb_samples() { return _nb_samples; }
50 inline int nb_features() { return _nb_features; }
52 inline int label(int n_sample) {
53 ASSERT(n_sample >= 0 && n_sample < _nb_samples);
54 return _labels[n_sample];
57 inline scalar_t feature_value(int n_sample, int n_feature) {
58 ASSERT(n_sample >= 0 && n_sample < _nb_samples &&
59 n_feature >= 0 && n_feature < _nb_features);
60 ASSERT(!isnan(_feature_values[n_sample][n_feature]));
61 return _feature_values[n_sample][n_feature];
64 SampleSet(int nb_features, int nb_samples);
65 SampleSet(SampleSet *father, int nb, int *indexes);
69 void set_sample(int n,
70 PiFeatureFamily *pi_feature_family,