% GO_CONFIG   GO_* scripts configuration%%  See GO_TREE(), GO_SIGN(), GO_STAT(), GO_CLASSIFY().% AUTORIGHTS% Copyright (C) 2006 Regents of the University of California% All rights reserved% % Written by Andrea Vedaldi (UCLA VisionLab).% % Redistribution and use in source and binary forms, with or without% modification, are permitted provided that the following conditions are met% %     * Redistributions of source code must retain the above copyright%       notice, this list of conditions and the following disclaimer.%     * Redistributions in binary form must reproduce the above copyright%       notice, this list of conditions and the following disclaimer in the%       documentation and/or other materials provided with the distribution.%     * Neither the name of the University of California, Berkeley nor the%       names of its contributors may be used to endorse or promote products%       derived from this software without specific prior written permission.% % THIS SOFTWARE IS PROVIDED BY THE REGENTS AND CONTRIBUTORS ``AS IS'' AND ANY% EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED% WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE% DISCLAIMED. IN NO EVENT SHALL THE REGENTS AND CONTRIBUTORS BE LIABLE FOR ANY% DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES% (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;% LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND% ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT% (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS% SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.% data_min_sigma          Build database: drop features smaller than this% data_shuffle            Build database: shuffle images in categories%                         after loading them.% tree_fair_data          Build k-tree: uses same amount of features from%                         each category.% tree_limit_data         Build k-tree: sample this many features (%) from%                         all possible features.% tree_K                  K-tree K.% tree_nleaves            K-tree approximate number of leaves.% tree_restrict_to_train  Learn K-tree only on training set.% class_ntrain            NN classifier: number of training images% class_nvotes            NN classifier: number of votes to take% select a set of configuration parameterswhich_exp = 3 ;switch which_exp case 1	pfx_images     = '~/data/caltech-4/' ;	pfx_sift       = '~/extra/caltech-4/std-sift/' ;	pfx_ktree      = '~/extra/caltech-4/std-tree' ;	pfx_classifier = '~/extra/caltech-4/std-class' ;	data_min_sigma          = 1 ;	data_shuffle            = 1 ;		tree_fair_data          = 1 ;   	tree_limit_data         = 0.1 ; 	tree_K                  = 10 ;	tree_nleaves            = 10000 ;	tree_restrict_to_train  = 0 ;	stat_downsample         = 10 ;			class_ntrain            = 100 ;	class_nvotes            = 10 ;	 case 2	pfx_images     = '~/data/caltech-4/' ;	pfx_sift       = '~/extra/caltech-4/rand-sift/' ;	pfx_key        = '~/extra/caltech-4/rand-key/' ;	pfx_tree       = '~/extra/caltech-4/rand-tree' ;	pfx_classifier = '~/extra/caltech-4/rand-class' ;		data_min_sigma          = 1 ;	data_shuffle            = 1 ;		tree_fair_data          = 1 ;   	tree_limit_data         = 0.1 ; 	tree_K                  = 10 ;	tree_nleaves            = 10000 ;	tree_restrict_to_train  = 0 ;	stat_downsample         = 10 ;			class_ntrain            = 100 ;	class_nvotes            = 10 ;	 case 3	pfx_images     = '~/data/caltech-4/' ;	pfx_sift       = '~/extra/caltech-4/rand-sift/' ;	pfx_key        = '~/extra/caltech-4/rand-key/' ;	pfx_tree       = '~/extra/caltech-4/rand-tree-s' ;	pfx_classifier = '~/extra/caltech-4/rand-class-s' ;		data_min_sigma          = 1 ;	data_shuffle            = 1 ;		tree_fair_data          = 1 ;   	tree_limit_data         = 1 ; 	tree_K                  = 10 ;	tree_nleaves            = 10000 ;	tree_restrict_to_train  = 1 ;	stat_downsample         = 10 ;			class_ntrain            = 100 ;	class_nvotes            = 10 ; case 4	pfx_images     = '~/data/caltech-101/' ;	pfx_sift       = '~/extra/caltech-101/rand-sift/' ;	pfx_key        = '~/extra/caltech-101/rand-key/' ;	pfx_tree       = '~/extra/caltech-101/rand-tree' ;	pfx_classifier = '~/extra/caltech-101/rand-class' ;		data_min_sigma          = 1 ;	data_shuffle            = 1 ;		tree_fair_data          = 1 ;   	tree_limit_data         = 0.1 ; 	tree_K                  = 10 ;	tree_nleaves            = 10000 ;	tree_restrict_to_train  = 1 ;	stat_downsample         = 10 ;			class_ntrain            = 30 ;	class_nvotes            = 5 ;end