X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=blobdiff_plain;f=materials.cc;fp=materials.cc;h=bbb6cbf437eb9b542e983c83e467a6080c9e3813;hb=d922ad61d35e9a6996730bec24b16f8bf7bc426c;hp=0000000000000000000000000000000000000000;hpb=3bb118f5a9462d02ff7d99ef28ecc0d7e23529f9;p=folded-ctf.git
diff --git a/materials.cc b/materials.cc
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--- /dev/null
+++ b/materials.cc
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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 . //
+// //
+// Written by Francois Fleuret, (C) IDIAP //
+// Contact for comments & bug reports //
+///////////////////////////////////////////////////////////////////////////
+
+#include "materials.h"
+#include "boosted_classifier.h"
+#include "parsing_pool.h"
+#include "rgb_image_subpixel.h"
+
+void write_referential_png(char *filename,
+ int level,
+ RichImage *image,
+ PiReferential *referential,
+ PiFeature *pf) {
+
+ scalar_t s = global.discrete_log_scale_to_scale(referential->common_scale());
+
+ RGBImage result(int(image->width() * s), int(image->height() * s));
+
+ for(int y = 0; y < result.height(); y++) {
+ for(int x = 0; x < result.width(); x++) {
+ int c = 0;
+
+ // GRAYSCALES
+
+ for(int b = 0; b < RichImage::nb_gray_tags; b++) {
+ c += (b * 256)/RichImage::nb_gray_tags *
+ image->nb_tags_in_window(referential->common_scale(),
+ RichImage::first_gray_tag + b,
+ x, y,
+ x + 1, y + 1);
+ }
+
+ // EDGES
+
+ // for(int b = 0; b < RichImage::nb_edge_tags; b++) {
+ // c += image->nb_tags_in_window(referential->common_scale(),
+ // RichImage::first_edge_tag + b,
+ // x, y,
+ // x + 1, y + 1);
+ // }
+ // c = 255 - (c * 255)/RichImage::nb_edge_tags;
+
+ // THRESHOLDED VARIANCE
+
+ // c = image->nb_tags_in_window(referential->common_scale(),
+ // RichImage::variance_tag,
+ // x, y,
+ // x + 1, y + 1);
+ // c = (1 - c) * 255;
+
+ result.set_pixel(x, y, c, c, c);
+ }
+ }
+
+ RGBImageSubpixel result_sp(&result);
+
+ if(pf) {
+ pf->draw(&result_sp, 255, 255, 0, referential);
+ } else {
+ referential->draw(&result_sp, level);
+ }
+
+ (*global.log_stream) << "Writing " << filename << endl;
+ result_sp.write_png(filename);
+}
+
+void write_one_pi_feature_png(char *filename,
+ LabelledImage *image,
+ PoseCellHierarchy *hierarchy,
+ int nb_target,
+ int level,
+ PiFeature *pf) {
+
+ PoseCell target_cell;
+ hierarchy->get_containing_cell(image, level,
+ image->get_target_pose(nb_target), &target_cell);
+ PiReferential referential(&target_cell);
+ RGBImage result(image->width(), image->height());
+ image->to_rgb(&result);
+ RGBImageSubpixel result_sp(&result);
+ referential.draw(&result_sp, level);
+ // pf->draw(&result_sp, 255, 255, 0, &referential);
+ result_sp.write_png(filename);
+}
+
+void write_pool_images_with_poses_and_referentials(LabelledImagePool *pool,
+ Detector *detector) {
+ LabelledImage *image;
+ char buffer[buffer_size];
+
+ PoseCell target_cell;
+ Pose p;
+ PiFeature *pf;
+
+ PoseCellHierarchy *hierarchy = new PoseCellHierarchy(pool);
+
+ for(int i = 0; i < min(global.nb_images, pool->nb_images()); i++) {
+ image = pool->grab_image(i);
+ RGBImage result(image->width(), image->height());
+ image->to_rgb(&result);
+ RGBImageSubpixel result_sp(&result);
+
+ if(global.pictures_for_article) {
+ for(int t = 0; t < image->nb_targets(); t++) {
+ image->get_target_pose(t)->draw(8, 255, 255, 255,
+ hierarchy->nb_levels() - 1, &result_sp);
+
+ }
+ for(int t = 0; t < image->nb_targets(); t++) {
+ image->get_target_pose(t)->draw(4, 0, 0, 0,
+ hierarchy->nb_levels() - 1, &result_sp);
+ }
+ } else {
+ for(int t = 0; t < image->nb_targets(); t++) {
+ image->get_target_pose(t)->draw(4, 255, 128, 0,
+ hierarchy->nb_levels() - 1, &result_sp);
+ }
+ }
+
+ sprintf(buffer, "/tmp/truth-%05d.png", i);
+ cout << "Writing " << buffer << endl;
+ result_sp.write_png(buffer);
+ pool->release_image(i);
+ }
+
+ for(int i = 0; i < min(global.nb_images, pool->nb_images()); i++) {
+ image = pool->grab_image(i);
+
+ RGBImage result(image->width(), image->height());
+ image->to_rgb(&result);
+ RGBImageSubpixel result_sp(&result);
+
+ int u = 0;
+
+ // image->compute_rich_structure();
+
+ for(int t = 0; t < image->nb_targets(); t++) {
+
+ image->get_target_pose(t)->draw(4, 255, 0, 0,
+ hierarchy->nb_levels() - 1, &result_sp);
+
+ hierarchy->get_containing_cell(image,
+ hierarchy->nb_levels() - 1,
+ image->get_target_pose(t), &target_cell);
+
+ target_cell.get_centroid(&p);
+
+ p.draw(4, 0, 255, 0, hierarchy->nb_levels() - 1, &result_sp);
+
+ PiReferential referential(&target_cell);
+
+ sprintf(buffer, "/tmp/referential-%05d-%02d.png", i, u);
+ image->compute_rich_structure();
+ write_referential_png(buffer, hierarchy->nb_levels() - 1, image, &referential, 0);
+
+ if(detector) {
+ int nb_features = 100;
+ for(int f = 0; f < nb_features; f++)
+ if(f == 0 || f ==50 || f == 53) {
+ int n_family, n_feature;
+ if(f < nb_features/2) {
+ n_family = 0;
+ n_feature = f;
+ } else {
+ n_family = detector->_nb_classifiers_per_level;
+ n_feature = f - nb_features/2;
+ }
+ pf = detector->_pi_feature_families[n_family]->get_feature(n_feature);
+ sprintf(buffer, "/tmp/pf-%05d-%02d-%03d.png", i, u, f);
+ write_referential_png(buffer,
+ hierarchy->nb_levels() - 1,
+ image,
+ &referential,
+ pf);
+ }
+ }
+ u++;
+ }
+
+ // sprintf(buffer, "/tmp/image-%05d.png", i);
+ // cout << "Writing " << buffer << endl;
+ // result_sp.write_png(buffer);
+
+ // if(global.write_tag_images) {
+ // sprintf(buffer, "/tmp/image-%05d_tags.png", i);
+ // cout << "Writing " << buffer << endl;
+ // image->compute_rich_structure();
+ // image->write_tag_png(buffer);
+ // }
+
+ pool->release_image(i);
+ }
+
+ delete hierarchy;
+}
+
+void write_image_with_detections(const char *filename,
+ LabelledImage *image,
+ PoseCellSet *detections,
+ int level) {
+
+ RGBImage result(image->width(), image->height());
+
+ for(int y = 0; y < result.height(); y++) {
+ for(int x = 0; x < result.width(); x++) {
+ int c = image->value(x, y);
+ result.set_pixel(x, y, c, c, c);
+ }
+ }
+
+ RGBImageSubpixel result_sp(&result);
+
+ if(global.pictures_for_article) {
+ for(int a = 0; a < detections->nb_cells(); a++) {
+ Pose pose;
+ detections->get_cell(a)->get_centroid(&pose);
+ pose.draw(8, 255, 255, 255, level, &result_sp);
+ }
+ for(int a = 0; a < detections->nb_cells(); a++) {
+ Pose pose;
+ detections->get_cell(a)->get_centroid(&pose);
+ pose.draw(4, 0, 0, 0, level, &result_sp);
+ }
+ } else {
+ for(int a = 0; a < detections->nb_cells(); a++) {
+ Pose pose;
+ detections->get_cell(a)->get_centroid(&pose);
+ pose.draw(4, 255, 128, 0, level, &result_sp);
+ }
+ }
+
+ (*global.log_stream) << "Writing " << filename << endl;
+
+ result_sp.write_png(filename);
+}