📄 segoutputsv.m
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function [valsOutline,valsMarkup]=segoutputSV(edges,vals,solution)%Function [valsOutline,valsMarkup]=segoutputSV(edges,vals,solution) %generates output for a graph-based segmentation%%Inputs: edges - Mx2 edge list for the graph% vals - Original vals for the graph% solution - A 1xN vector assigning an integer to each node% indicating its membership in a segment%%Outputs: valsMarkup - The same vals as the inputs with the red channel % (first column) set to 1 along the borders of segments% valsOutline - A white background with black lines indicating the % segments borders%%%5/23/03 - Leo Grady% Copyright (C) 2002, 2003 Leo Grady <lgrady@cns.bu.edu>% Computer Vision and Computational Neuroscience Lab% Department of Cognitive and Neural Systems% Boston University% Boston, MA 02215%% This program is free software; you can redistribute it and/or% modify it under the terms of the GNU General Public License% as published by the Free Software Foundation; either version 2% of the License, or (at your option) any later version.%% 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, write to the Free Software% Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.%% Date - $Id: segoutputSV.m,v 1.3 2003/08/21 17:29:29 lgrady Exp $%========================================================================%%InitializationN=max(max(edges));%Build incidence matrixA=incidence(edges);%Find segment borderssegBorders=find(A*solution);segBorders=[edges(segBorders,1);edges(segBorders,2)];%Build valsOutlinevalsOutline=ones(N,1);valsOutline(segBorders)=0;%Build valsMarkupvalsMarkup=vals;if size(vals,2) == 1 valsMarkup(:,2:3)=[vals,vals];endvalsMarkup(segBorders,:)=0;valsMarkup(segBorders,1)=1;
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