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% This script tests functionality of SVM solvers implemneted in the LIBOCAS.
%
% The script runs SVM solvers on example data (in ./data/) and compares
% the obtained results with the solutions stored in reference files.
%
% This script is useful to check potential bugs e.g. introduced when
% changing the library code.
%
% jump to root dir of libocas
cd(fileparts(which('svmocas')));
% two-class problem
TWO_CLASS_PROBLEM = './data/riply_trn.mat';
% two-class problem in SVM^light format
TWO_CLASS_PROBLEM_SVMLIGHT = './data/riply_trn.light';
% multi-class problem
MULTI_CLASS_PROBLEM = './data/example4_train.mat';
% multi-class problem in SVM^light format
MULTI_CLASS_PROBLEM_SVMLIGHT = './data/example4_train.light';
% gender classification (male vs. female) from face images
GENDER_IMAGE_DATABASE = './data/gender_images.mat';
% file to store/load reference solution
ReferenceFile = './data/reference_solution';
% if 1 save results to reference files else compares the results to the
% reference solutions;
CREATE_REFERNCE_FILES = 0;
%% Solver settings
opt.C = 1;
opt.Method = 1;
opt.TolRel = 0.01;
opt.TolAbs = 0;
opt.QPBound = 0;
opt.BufSize = 500;
opt.MaxTime = inf;
opt.X0 = 1;
opt.verb = 0;
%% run all solvers for different inputs
% SVMOCAS for dense double features
fprintf('SVMOCAS: training two-class SVM classifier from dense features in double precision ...');
data = load( TWO_CLASS_PROBLEM );
[svmocasResults.W,svmocasResults.W0,svmocasResults.stat] = ...
svmocas(data.X,opt.X0,data.y, opt.C,opt.Method,opt.TolRel,...
opt.TolAbs,opt.QPBound,opt.BufSize,inf,opt.MaxTime,opt.verb);
fprintf('done.\n');
% SVMOCAS for dense single prec. features
fprintf('SVMOCAS: training two-class SVM classifier from dense features in single precision ...');
data = load( TWO_CLASS_PROBLEM );
data.X = single(data.X);
[svmocasSingleResults.W,svmocasSingleResults.W0,svmocasSingleResults.stat] = ...
svmocas(data.X,opt.X0,data.y, opt.C,opt.Method,opt.TolRel,...
opt.TolAbs,opt.QPBound,opt.BufSize,inf,opt.MaxTime,opt.verb);
fprintf('done.\n');
% SVMOCAS for sparse double features
fprintf('SVMOCAS: training two-class SVM classifier from sparse features in double precision ...');
data = load( TWO_CLASS_PROBLEM );
data.X = sparse(data.X);
[svmocasSparseResults.W,svmocasSparseResults.W0,svmocasSparseResults.stat] = ...
svmocas(data.X,opt.X0,data.y, opt.C,opt.Method,opt.TolRel,...
opt.TolAbs,opt.QPBound,opt.BufSize,inf,opt.MaxTime,opt.verb);
fprintf('done.\n');
% SVMOCAS for INT8 features
fprintf('SVMOCAS: training two-class SVM classifier from dense int8 features ...');
data = load( TWO_CLASS_PROBLEM );
data.X = int8(100*data.X);
[svmocasInt8Results.W,svmocasInt8Results.W0,svmocasInt8Results.stat] = ...
svmocas(data.X,opt.X0,data.y, opt.C,opt.Method,opt.TolRel,...
opt.TolAbs,opt.QPBound,opt.BufSize,inf,opt.MaxTime,opt.verb);
fprintf('done.\n');
% SVMOCAS_LIGHT
fprintf('SVMOCAS_LIGHT: training two-class SVM classifier from examples stored in SVM^light file ...');
[svmocasLightResults.W,svmocasLightResults.W0,svmocasLightResults.stat] = ...
svmocas_light(TWO_CLASS_PROBLEM_SVMLIGHT,opt.X0, opt.C,opt.Method,opt.TolRel,...
opt.TolAbs,opt.QPBound,opt.BufSize,inf,opt.MaxTime,opt.verb);
fprintf('done.\n');
% SVMOCAS_LBP
fprintf('SVMOCAS_LBP: training two-class SVM classifier from LBP features computed on images ...');
data = load( GENDER_IMAGE_DATABASE );
HEIGHT_OF_LBP_PYRAMID = 4;
BASE_WINDOW_SIZE = [60 40];
numMaleImages = size(data.trn_male_images,2);
numFemaleImages = size(data.trn_male_images,2);
wins = [ [1:numMaleImages numMaleImages+[1:numFemaleImages]]; ...
repmat([20;15;0],1,numFemaleImages+numMaleImages)];
labels = [ones(1,numMaleImages) -ones(1,numFemaleImages)];
[svmocasLBPResults.W,svmocasLBPResults.W0,svmocasLBPResults.stat] = ...
svmocas_lbp([data.trn_male_images data.trn_female_images], data.IMAGE_SIZE,...
uint32(wins), BASE_WINDOW_SIZE, HEIGHT_OF_LBP_PYRAMID, opt.X0, labels, 0.001*opt.C, ...
opt.Method, opt.TolRel,opt.TolAbs,opt.QPBound,opt.BufSize,inf,opt.MaxTime,opt.verb);
fprintf('done.\n');
% MSVMOCAS
fprintf('MSVMOCAS: training multi-class SVM classifier from dense features in double precision ...');
data = load( MULTI_CLASS_PROBLEM );
[msvmocasResults.W,msvmocasResults.stat] = ...
msvmocas(data.X,data.y,opt.C,opt.Method,opt.TolRel,...
opt.TolAbs,opt.QPBound,opt.BufSize,inf,opt.MaxTime,opt.verb);
fprintf('done.\n');
% MSVMOCAS_LIGHT
fprintf('MSVMOCAS_LIGHT: training multi-class SVM classifier from examples stored in SVM^light file ...');
[msvmocasLightResults.W,msvmocasLightResults.stat] = ...
msvmocas_light(MULTI_CLASS_PROBLEM_SVMLIGHT,opt.C,opt.Method,opt.TolRel,...
opt.TolAbs,opt.QPBound,opt.BufSize,inf,opt.MaxTime,opt.verb);
fprintf('done.\n');
if CREATE_REFERNCE_FILES == 1,
%% save reference solutions to file
fprintf('Saving reference solutions to %s\n', ReferenceFile);
save(ReferenceFile,'svmocasResults','svmocasSparseResults','msvmocasResults',...
'svmocasInt8Results','svmocasLBPResults','svmocasSingleResults', ...
'svmocasLightResults','msvmocasLightResults');
else
%% compare obtained solutions to those stored in the reference file
ref = load(ReferenceFile);
test = [];
% SVMOCAS for dense double features
test(1).dif = sum(abs(svmocasResults.W - ref.svmocasResults.W) + ...
abs(svmocasResults.W0-ref.svmocasResults.W0));
test(1).name = 'sum(|W-ref.W| + |W0-ref.W0])';
test(2).dif = abs(svmocasResults.stat.Q_P - ref.svmocasResults.stat.Q_P);
test(2).name = 'PrimalVal - ref.PrimalVal ';
test(3).dif = abs(svmocasResults.stat.Q_D - ref.svmocasResults.stat.Q_D);
test(3).name = 'DualVal - ref.DualVal ';
fprintf('\nSVMOCAS for dense features in double precision:\n');
for i=1:length(test)
fprintf(' %s = %.20f ... ',test(i).name,test(i).dif);
if test(i).dif == 0
fprintf('SOLUTIONS EQUAL - OK\n');
else
fprintf('SOLUTION IS DIFFERENT!!!\n');
end
end
% SVMOCAS for dense single precision features
test(1).dif = sum(abs(svmocasSingleResults.W - ref.svmocasSingleResults.W) + ...
abs(svmocasSingleResults.W0-ref.svmocasSingleResults.W0));
test(1).name = 'sum(|W-ref.W| + |W0-ref.W0])';
test(2).dif = abs(svmocasSingleResults.stat.Q_P - ref.svmocasSingleResults.stat.Q_P);
test(2).name = 'PrimalVal - ref.PrimalVal ';
test(3).dif = abs(svmocasSingleResults.stat.Q_D - ref.svmocasSingleResults.stat.Q_D);
test(3).name = 'DualVal - ref.DualVal ';
fprintf('\nSVMOCAS for dense features in single precision:\n');
for i=1:length(test)
fprintf(' %s = %.20f ... ',test(i).name,test(i).dif);
if test(i).dif == 0
fprintf('SOLUTIONS EQUAL - OK\n');
else
fprintf('SOLUTION IS DIFFERENT!!!\n');
end
end
% SVMOCAS for sparse double features
test(1).dif = sum(abs(svmocasSparseResults.W - ref.svmocasSparseResults.W) + ...
abs(svmocasSparseResults.W0-ref.svmocasSparseResults.W0));
test(1).name = 'sum(|W-ref.W| + |W0-ref.W0])';
test(2).dif = abs(svmocasSparseResults.stat.Q_P - ref.svmocasSparseResults.stat.Q_P);
test(2).name = 'PrimalVal - ref.PrimalVal ';
test(3).dif = abs(svmocasSparseResults.stat.Q_D - ref.svmocasSparseResults.stat.Q_D);
test(3).name = 'DualVal - ref.DualVal ';
fprintf('\nSVMOCAS for sparse features in double precision:\n');
for i=1:length(test)
fprintf(' %s = %.20f ... ',test(i).name,test(i).dif);
if test(i).dif == 0
fprintf('SOLUTIONS EQUAL - OK\n');
else
fprintf('SOLUTION IS DIFFERENT!!!\n');
end
end
% SVMOCAS for dense INT8 features
test(1).dif = sum(abs(svmocasInt8Results.W - ref.svmocasInt8Results.W) + ...
abs(svmocasInt8Results.W0-ref.svmocasInt8Results.W0));
test(1).name = 'sum(|W-ref.W| + |W0-ref.W0])';
test(2).dif = abs(svmocasInt8Results.stat.Q_P - ref.svmocasInt8Results.stat.Q_P);
test(2).name = 'PrimalVal - ref.PrimalVal ';
test(3).dif = abs(svmocasInt8Results.stat.Q_D - ref.svmocasInt8Results.stat.Q_D);
test(3).name = 'DualVal - ref.DualVal ';
fprintf('\nSVMOCAS for dense int8 features:\n');
for i=1:length(test)
fprintf(' %s = %.20f ... ',test(i).name,test(i).dif);
if test(i).dif == 0
fprintf('SOLUTIONS EQUAL - OK\n');
else
fprintf('SOLUTION IS DIFFERENT!!!\n');
end
end
% SVMOCAS_LIGHT
test(1).dif = sum(abs(svmocasLightResults.W - ref.svmocasLightResults.W) + ...
abs(svmocasLightResults.W0-ref.svmocasLightResults.W0));
test(1).name = 'sum(|W-ref.W| + |W0-ref.W0])';
test(2).dif = abs(svmocasLightResults.stat.Q_P - ref.svmocasLightResults.stat.Q_P);
test(2).name = 'PrimalVal - ref.PrimalVal ';
test(3).dif = abs(svmocasLightResults.stat.Q_D - ref.svmocasLightResults.stat.Q_D);
test(3).name = 'DualVal - ref.DualVal ';
fprintf('\nSVMOCAS_LIGHT:\n');
for i=1:length(test)
fprintf(' %s = %.20f ... ',test(i).name,test(i).dif);
if test(i).dif == 0
fprintf('SOLUTIONS EQUAL - OK\n');
else
fprintf('SOLUTION IS DIFFERENT!!!\n');
end
end
% SVMOCAS_LBP
test(1).dif = sum(abs(svmocasLBPResults.W - ref.svmocasLBPResults.W) + ...
abs(svmocasLBPResults.W0-ref.svmocasLBPResults.W0));
test(1).name = 'sum(|W-ref.W| + |W0-ref.W0])';
test(2).dif = abs(svmocasLBPResults.stat.Q_P - ref.svmocasLBPResults.stat.Q_P);
test(2).name = 'PrimalVal - ref.PrimalVal ';
test(3).dif = abs(svmocasLBPResults.stat.Q_D - ref.svmocasLBPResults.stat.Q_D);
test(3).name = 'DualVal - ref.DualVal ';
fprintf('\nSVMOCAS_LBP:\n');
for i=1:length(test)
fprintf(' %s = %.20f ... ',test(i).name,test(i).dif);
if test(i).dif == 0
fprintf('SOLUTIONS EQUAL - OK\n');
else
fprintf('SOLUTION IS DIFFERENT!!!\n');
end
end
% MSVMOCAS
test(1).dif = sum(sum(abs(msvmocasResults.W - ref.msvmocasResults.W)));
test(1).name = 'sum(|W-ref.W|) ';
test(2).dif = abs(msvmocasResults.stat.Q_P - ref.msvmocasResults.stat.Q_P);
test(2).name = 'PrimalVal - ref.PrimalVal';
test(3).dif = abs(msvmocasResults.stat.Q_D - ref.msvmocasResults.stat.Q_D);
test(3).name = 'DualVal - ref.DualVal ';
fprintf('\nMSVMOCAS:\n');
for i=1:length(test)
fprintf(' %s = %.20f ... ',test(i).name, test(i).dif);
if test(i).dif == 0
fprintf('SOLUTIONS EQUAL - OK\n');
else
fprintf('SOLUTION IS DIFFERENT!!!\n');
end
end
% MSVMOCAS_LIGHT
test(1).dif = sum(sum(abs(msvmocasLightResults.W - ref.msvmocasLightResults.W)));
test(1).name = 'sum(|W-ref.W|) ';
test(2).dif = abs(msvmocasLightResults.stat.Q_P - ref.msvmocasLightResults.stat.Q_P);
test(2).name = 'PrimalVal - ref.PrimalVal';
test(3).dif = abs(msvmocasLightResults.stat.Q_D - ref.msvmocasLightResults.stat.Q_D);
test(3).name = 'DualVal - ref.DualVal ';
fprintf('\nMSVMOCAS_LIGHT:\n');
for i=1:length(test)
fprintf(' %s = %.20f ... ',test(i).name, test(i).dif);
if test(i).dif == 0
fprintf('SOLUTIONS EQUAL - OK\n');
else
fprintf('SOLUTION IS DIFFERENT!!!\n');
end
end
end
% EOF
|
