2 ///////////////////////////////////////////////////////////////////////////
3 // This program is free software: you can redistribute it and/or modify //
4 // it under the terms of the version 3 of the GNU General Public License //
5 // as published by the Free Software Foundation. //
7 // This program is distributed in the hope that it will be useful, but //
8 // WITHOUT ANY WARRANTY; without even the implied warranty of //
9 // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU //
10 // General Public License for more details. //
12 // You should have received a copy of the GNU General Public License //
13 // along with this program. If not, see <http://www.gnu.org/licenses/>. //
15 // Written by Francois Fleuret, (C) IDIAP //
16 // Contact <francois.fleuret@idiap.ch> for comments & bug reports //
17 ///////////////////////////////////////////////////////////////////////////
19 #include "parsing_pool.h"
22 ParsingPool::ParsingPool(LabelledImagePool *image_pool, PoseCellHierarchy *hierarchy, scalar_t proportion_negative_cells) {
23 _nb_images = image_pool->nb_images();
24 _parsings = new Parsing *[_nb_images];
27 _nb_positive_cells = 0;
28 _nb_negative_cells = 0;
29 for(int i = 0; i < _nb_images; i++) {
30 _parsings[i] = new Parsing(image_pool, hierarchy, proportion_negative_cells, i);
31 _nb_cells += _parsings[i]->nb_cells();
32 _nb_positive_cells += _parsings[i]->nb_positive_cells();
33 _nb_negative_cells += _parsings[i]->nb_negative_cells();
35 (*global.log_stream) << "ParsingPool initialized" << endl;
36 (*global.log_stream) << " _nb_cells = " << _nb_cells << endl;
37 (*global.log_stream) << " _nb_positive_cells = " << _nb_positive_cells << endl;
38 (*global.log_stream) << " _nb_negative_cells = " << _nb_negative_cells << endl;
41 ParsingPool::~ParsingPool() {
42 for(int i = 0; i < _nb_images; i++)
47 void ParsingPool::down_one_level(LossMachine *loss_machine, PoseCellHierarchy *hierarchy, int level) {
48 scalar_t *labels = new scalar_t[_nb_cells];
49 scalar_t *tmp_responses = new scalar_t[_nb_cells];
53 { ////////////////////////////////////////////////////////////////////
56 for(int i = 0; i < _nb_images; i++) {
57 for(int d = 0; d < _parsings[i]->nb_cells(); d++) {
58 if(_parsings[i]->label(d) != 0) {
59 l += exp( - _parsings[i]->label(d) * _parsings[i]->response(d));
63 (*global.log_stream) << "* INITIAL LOSS IS " << l << endl;
64 } ////////////////////////////////////////////////////////////////////
66 // Put the negative samples with their current responses, and all
70 for(int i = 0; i < _nb_images; i++) {
71 for(int d = 0; d < _parsings[i]->nb_cells(); d++) {
72 if(_parsings[i]->label(d) < 0) {
74 tmp_responses[c] = _parsings[i]->response(d);
83 // Sub-sample among the negative ones
85 int *sample_nb_occurences = new int[_nb_cells];
86 scalar_t *sample_responses = new scalar_t[_nb_cells];
88 loss_machine->subsample(_nb_cells, labels, tmp_responses,
89 _nb_negative_cells, sample_nb_occurences, sample_responses,
93 for(int i = 0; i < _nb_images; i++) {
94 for(int d = 0; d < _parsings[i]->nb_cells(); d++) {
95 if(_parsings[i]->label(d) > 0) {
96 sample_nb_occurences[c + d] = 1;
97 sample_responses[c + d] = _parsings[i]->response(d);
101 int d = c + _parsings[i]->nb_cells();
103 _parsings[i]->down_one_level(hierarchy, level, sample_nb_occurences + c, sample_responses + c);
108 { ////////////////////////////////////////////////////////////////////
111 for(int i = 0; i < _nb_images; i++) {
112 for(int d = 0; d < _parsings[i]->nb_cells(); d++) {
113 if(_parsings[i]->label(d) != 0) {
114 l += exp( - _parsings[i]->label(d) * _parsings[i]->response(d));
118 (*global.log_stream) << "* FINAL LOSS IS " << l << endl;
119 } ////////////////////////////////////////////////////////////////////
121 delete[] sample_responses;
122 delete[] sample_nb_occurences;
125 delete[] tmp_responses;
128 void ParsingPool::update_cell_responses(PiFeatureFamily *pi_feature_family,
129 Classifier *classifier) {
130 for(int i = 0; i < _nb_images; i++) {
131 _parsings[i]->update_cell_responses(pi_feature_family, classifier);
135 void ParsingPool::weighted_sampling(LossMachine *loss_machine,
136 PiFeatureFamily *pi_feature_family,
137 SampleSet *sample_set,
138 scalar_t *responses) {
140 int nb_negatives_to_sample = sample_set->nb_samples() - _nb_positive_cells;
142 ASSERT(nb_negatives_to_sample > 0);
144 scalar_t *labels = new scalar_t[_nb_cells];
145 scalar_t *tmp_responses = new scalar_t[_nb_cells];
149 // Put the negative samples with their current responses, and all
153 for(int i = 0; i < _nb_images; i++) {
154 for(int d = 0; d < _parsings[i]->nb_cells(); d++) {
155 if(_parsings[i]->label(d) < 0) {
157 tmp_responses[c] = _parsings[i]->response(d);
160 tmp_responses[c] = 0;
166 // Sub-sample among the negative ones
168 int *sample_nb_occurences = new int[_nb_cells];
169 scalar_t *sample_responses = new scalar_t[_nb_cells];
171 loss_machine->subsample(_nb_cells, labels, tmp_responses,
172 nb_negatives_to_sample, sample_nb_occurences, sample_responses,
175 for(int k = 0; k < _nb_cells; k++) {
176 if(sample_nb_occurences[k] > 0) {
177 ASSERT(sample_nb_occurences[k] == 1);
179 tmp_responses[k] = sample_responses[k];
185 delete[] sample_responses;
186 delete[] sample_nb_occurences;
188 // Put the positive ones
191 for(int i = 0; i < _nb_images; i++) {
192 for(int d = 0; d < _parsings[i]->nb_cells(); d++) {
193 if(_parsings[i]->label(d) > 0) {
195 tmp_responses[c] = _parsings[i]->response(d);
201 // Here we have the responses for the sub-sampled in tmp_responses,
202 // and we have labels[n] set to zero for non-sampled samples
207 for(int i = 0; i < _nb_images; i++) {
209 int *to_collect = new int[_parsings[i]->nb_cells()];
211 for(int d = 0; d < _parsings[i]->nb_cells(); d++) {
212 to_collect[d] = (labels[c + d] != 0);
215 _parsings[i]->collect_samples(sample_set, pi_feature_family, s, to_collect);
217 for(int d = 0; d < _parsings[i]->nb_cells(); d++) {
219 responses[s++] = tmp_responses[c + d];
225 c += _parsings[i]->nb_cells();
228 delete[] tmp_responses;
232 void ParsingPool::write_roc(ofstream *out) {
233 int nb_negatives = nb_negative_cells();
234 int nb_positives = nb_positive_cells();
236 scalar_t *pos_responses = new scalar_t[nb_positives];
237 scalar_t *neg_responses = new scalar_t[nb_negatives];
239 for(int i = 0; i < _nb_images; i++) {
240 for(int c = 0; c < _parsings[i]->nb_cells(); c++) {
241 if(_parsings[i]->label(c) > 0)
242 pos_responses[np++] = _parsings[i]->response(c);
243 else if(_parsings[i]->label(c) < 0)
244 neg_responses[nn++] = _parsings[i]->response(c);
248 ASSERT(nn == nb_negatives && np == nb_positives);
250 print_roc_small_pos(out,
251 nb_positives, pos_responses,
252 nb_negatives, neg_responses,
255 delete[] pos_responses;
256 delete[] neg_responses;