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SetDefaultSuperParsingParams.m
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SetDefaultSuperParsingParams.m
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function [SPparam] = SetDefaultSuperParsingParams(HOME,DATASET,testName,testSetName)
SPparam.SPCODE = fullfile(pwd,'im_parser');
SPparam.HOME = HOME;
SPparam.DATASET = DATASET;
SPparam.HOMEDATA = fullfile(HOME,DATASET);
SPparam.HOMEIMAGES = fullfile(SPparam.HOMEDATA,'Images');
SPparam.HOMEANNOTATIONS = fullfile(SPparam.HOMEDATA,'Annotations');
SPparam.HOMELABELSETS = {fullfile(SPparam.HOMEDATA,'SemanticLabels')};
SPparam.testName = testName;
SPparam.testSetName = testSetName;
SPparam.HOMETESTDATA = fullfile(SPparam.HOMEDATA,testName);
SPparam.UseLabelSet = [1];
SPparam.UseClassifier = [0];
SPparam.globalDescriptors = {'spatialPryScaled','colorGist','coHist'};
% superpixel parameter
SPparam.K = 200;
SPparam.segSuffix = [];
SPparam.segmentDescriptors = {
'centered_mask_sp', 'bb_extent', 'pixel_area', ... % Shape
'absolute_mask', 'top_height',... % Location
'int_text_hist_mr','dial_text_hist_mr',... % Texture
'sift_hist_int_','sift_hist_dial','sift_hist_bottom','sift_hist_top','sift_hist_right','sift_hist_left'... % SIFT
'mean_color','color_std','color_hist','dial_color_hist',... % Color
'color_thumb','color_thumb_mask','gist_int'}; % Appearance
% Naive bayesian classifier parameters (Tighe and Lazebnik, ECCV'10)
SPparam.retSetSize = 200; % # of retrieved image
SPparam.minSPinRetSet = 1500; % minimum number of superpixel
SPparam.targetNN = 20;
% MRF parameters
SPparam.LabelSmoothing = [0, 8];
SPparam.LabelPenality = {'conditional'};
SPparam.InterLabelSmoothing = [0, 8];
SPparam.InterLabelPenality = {'pots','conditional'};
SPparam.claParams.stopval = .001;
SPparam.claParams.num_iterations = 100;
SPparam.claParams.subSample = 0;
SPparam.claParams.balancedsubSample = 1;
SPparam.claParams.testsetnum = 1;
SPparam.claParams.init_weight = 'cFreq';
SPparam.claParams.num_nodes = 8;
SPparam.claParams.K = SPparam.K;
SPparam.claParams.segSuffix = SPparam.segSuffix;
SPparam.claParams.segmentDescriptors = SPparam.segmentDescriptors;
disp(SPparam);
return;