From: Francois Fleuret Date: Sat, 11 Oct 2008 22:11:23 +0000 (+0200) Subject: automatic commit X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=commitdiff_plain;h=4953a336630d0ee905c949bf1fe846b85cabb744;p=folded-ctf.git automatic commit --- diff --git a/README.txt b/README.txt index 9f2d329..3bca7f0 100644 --- a/README.txt +++ b/README.txt @@ -1,5 +1,6 @@ -INTRODUCTION +###################################################################### +## INTRODUCTION This is the C++ implementation of the folded hierarchy of classifiers for cat detection described in @@ -9,7 +10,8 @@ INTRODUCTION Please cite this paper when referring to this software. -INSTALLATION +###################################################################### +## INSTALLATION This program was developed on Debian GNU/Linux computers with the following main tool versions @@ -36,12 +38,12 @@ INSTALLATION You can also run the full thing with the following commands if you have wget installed - wget http://www.idiap.ch/folded-ctf/not-public-yet/data/folding-gpl.tgz - tar zxvf folding-gpl.tgz - cd folding - wget http://www.idiap.ch/folded-ctf/not-public-yet/data/rmk.tgz - tar zxvf rmk.tgz - ./run.sh + > wget http://www.idiap.ch/folded-ctf/not-public-yet/data/folding-gpl.tgz + > tar zxvf folding-gpl.tgz + > cd folding + > wget http://www.idiap.ch/folded-ctf/not-public-yet/data/rmk.tgz + > tar zxvf rmk.tgz + > ./run.sh Note that every one of the twenty rounds of training/testing takes more than three days on a powerful PC. However, the script detects @@ -54,7 +56,8 @@ INSTALLATION You are welcome to send bug reports and comments to fleuret@idiap.ch -PARAMETERS +###################################################################### +## PARAMETERS To set the value of a parameter during an experiment, just add an argument of the form --parameter-name=value before the commands that @@ -73,7 +76,7 @@ PARAMETERS * pictures-for-article ("no") - Should the pictures be generated to be clear in b&w + Should the pictures be generated for printing in black and white. * pool-name (no default) @@ -90,14 +93,14 @@ PARAMETERS * result-path ("/tmp/") - In what directory should we save all the produced file during the + In what directory should we save all the produced files during the computation. * loss-type ("exponential") - What kind of loss to use for the boosting. While different loss are - implementer in the code, only the exponential has been thoroughly - tested. + What kind of loss to use for the boosting. While different losses + are implemented in the code, only the exponential has been + thoroughly tested. * nb-images (-1) @@ -107,7 +110,7 @@ PARAMETERS * tree-depth-max (1) Maximum depth of the decision trees used as weak learners in the - classifier. + classifier. The default value corresponds to stumps. * proportion-negative-cells-for-training (0.025) @@ -116,14 +119,14 @@ PARAMETERS * nb-negative-samples-per-positive (10) - How many negative cell to sample for every positive cell during + How many negative cells to sample for every positive cell during training. * nb-features-for-boosting-optimization (10000) How many pose-indexed features to use at every step of boosting. - * force-head-belly-independence (no) + * force-head-belly-independence ("no") Should we force the independence between the two levels of the detector (i.e. make an H+B detector) @@ -139,8 +142,8 @@ PARAMETERS * nb-levels (1) - How many levels in the hierarchy, this is 2 for the JMLR paper - experiments. + How many levels in the hierarchy. This should be 2 for the JMLR + paper experiments. * proportion-for-train (0.5) @@ -207,7 +210,8 @@ PARAMETERS Should we display a progress bar. -COMMANDS +###################################################################### +## COMMANDS * open-pool @@ -245,6 +249,6 @@ COMMANDS Write PNG images of the scenes in the pool. - -- - Francois Fleuret - October 2008 +-- +Francois Fleuret +October 2008 diff --git a/detector.cc b/detector.cc index 1c3ef23..358c66b 100644 --- a/detector.cc +++ b/detector.cc @@ -446,7 +446,6 @@ void Detector::read(istream *is) { _thresholds = new scalar_t[_nb_classifiers]; for(int q = 0; q < _nb_classifiers; q++) { - cout << "Read classifier " << q << endl; _pi_feature_families[q] = new PiFeatureFamily(); _pi_feature_families[q]->read(is); _classifiers[q] = read_classifier(is); diff --git a/materials.cc b/materials.cc index 21f6790..64729db 100644 --- a/materials.cc +++ b/materials.cc @@ -171,7 +171,7 @@ void write_pool_images_with_poses_and_referentials(LabelledImagePool *pool, if(detector) { int nb_features = 100; for(int f = 0; f < nb_features; f++) - if(f == 0 || f ==50 || f == 53) { + if(f == 0 || f == 50 || f == 53) { int n_family, n_feature; if(f < nb_features/2) { n_family = 0; @@ -192,17 +192,6 @@ void write_pool_images_with_poses_and_referentials(LabelledImagePool *pool, 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); }