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test_lfw.m
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test_lfw.m
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load('D:\wf\face\dataset\WDRef\id_lfw.mat');
load('D:\wf\face\dataset\WDRef\imagelist_lfw.mat');
load('D:\wf\face\dataset\WDRef\lbp_lfw.mat');
load('D:\wf\face\dataset\WDRef\pairlist_lfw.mat');
load('D:\wf\face\dataset\lbp_lfw_baseline_cvpr13.mat')
% labels = double(train_y) * (0:9)';
labels = id_lfw;
X = double(lbp_lfw_baseline_cvpr12);
% X = sqrt(X);
% X = bsxfun(@rdivide,X,sum(X.^2,2));
idx = [];
testing = 10;
tmp = pairlist_lfw.IntraPersonPair;
tmp((testing-1)*300+1:testing*300,:) = [];
train_Intra = tmp;
idx = [idx;tmp(:)];
tmp = pairlist_lfw.ExtraPersonPair;
tmp((testing-1)*300+1:testing*300,:) = [];
train_Extra = tmp;
idx = [idx;tmp(:)];
idx = unique(idx);
train_x = X(idx,:);
train_y = id_lfw(idx);
train_mean = mean(train_x, 1);
[COEFF,SCORE] = princomp(train_x,'econ');
train_x = SCORE(:,1:1000);
normX = bsxfun(@minus,X,train_mean);
normX = normX * COEFF;
normX = normX(:,1:1000);
[mappedX, mapping] = JointBayesian(train_x, train_y);
Dis_train_Intra = zeros(2700,1);
Dis_train_Extra = zeros(2700,1);
for i=1:2700
Dis_train_Intra(i) = normX(train_Intra(i,1),:) * mapping.A * normX(train_Intra(i,1),:)' + normX(train_Intra(i,2),:) * mapping.A * normX(train_Intra(i,2),:)' - 2 * normX(train_Intra(i,1),:) * mapping.G * normX(train_Intra(i,2),:)';
Dis_train_Extra(i) = normX(train_Extra(i,1),:) * mapping.A * normX(train_Extra(i,1),:)' + normX(train_Extra(i,2),:) * mapping.A * normX(train_Extra(i,2),:)' - 2 * normX(train_Extra(i,1),:) * mapping.G * normX(train_Extra(i,2),:)';
end;
group_train = [ones(2700,1);zeros(2700,1)];
training = [Dis_train_Intra;Dis_train_Extra];
% thresh1 = min(min(Dis_train_Intra),max(Dis_validate_Extra));
% thresh2 = max(min(Dis_train_Intra),max(Dis_validate_Extra));
%
% CrossData = [Dis_validate_Intra(Dis_validate_Intra>=thresh1&Dis_validate_Intra<=thresh2);Dis_validate_Extra(Dis_validate_Extra>=thresh1&Dis_validate_Extra<=thresh2)];
% thresh = mean(CrossData);
% testing = 8;
test_Intra = pairlist_lfw.IntraPersonPair((testing-1)*300+1:testing*300,:);
test_Extra = pairlist_lfw.ExtraPersonPair((testing-1)*300+1:testing*300,:);
result_Intra = zeros(300,1);
result_Extra = zeros(300,1);
for i=1:300
result_Intra(i) = normX(test_Intra(i,1),:) * mapping.A * normX(test_Intra(i,1),:)' + normX(test_Intra(i,2),:) * mapping.A * normX(test_Intra(i,2),:)' - 2 * normX(test_Intra(i,1),:) * mapping.G * normX(test_Intra(i,2),:)';
result_Extra(i) = normX(test_Extra(i,1),:) * mapping.A * normX(test_Extra(i,1),:)' + normX(test_Extra(i,2),:) * mapping.A * normX(test_Extra(i,2),:)' - 2 * normX(test_Extra(i,1),:) * mapping.G * normX(test_Extra(i,2),:)';
end;
group_sample = [ones(300,1);zeros(300,1)];
sample = [result_Intra;result_Extra];
bestc=256;
% bestg=128;
% cmd = ['-c ', num2str(bestc), ' -g ', num2str(bestg)];
cmd = [' -t 0 -h 0'];
model = svmtrain(group_train,training,cmd);
[class,accTotal] = svmpredict(group_sample,sample,model);
% (sum(result_Intra>thresh)+sum(result_Extra<thresh))/600
% sum(result_Intra>0)
% sum(result_Extra<0)
% thresh1 = min(min(result_Intra),max(result_Extra));
% thresh2 = max(min(result_Intra),max(result_Extra));
%
% CrossData = [result_Intra(result_Intra>=thresh1&result_Intra<=thresh2);result_Extra(result_Extra>=thresh1&result_Extra<=thresh2)];
% thresh = mean(CrossData);
% for i=1:300
% result_Intra(i) = -thresh - 2 * normX(test_Intra(i,1),:) * mapping.G * normX(test_Intra(i,2),:)';
% result_Extra(i) = -thresh - 2 * normX(test_Extra(i,1),:) * mapping.G * normX(test_Extra(i,2),:)';
% end;
% (sum(result_Intra>0)+sum(result_Extra<0))/600
%
%
%
% % % mapping.Sw = mapping.Sw * 4479 / 6916;
% % mapping.G = -1 .* (2 * mapping.Su + mapping.Sw) \ mapping.Su / mapping.Sw;
% % mapping.A = inv(mapping.Su + mapping.Sw) - (inv(mapping.Sw) + mapping.G);
% % HI = [mapping.Su + mapping.Sw mapping.Su;mapping.Su mapping.Su + mapping.Sw];
% % HE = [mapping.Su + mapping.Sw zeros(size(mapping.Sw));zeros(size(mapping.Sw)) mapping.Su + mapping.Sw];
% % IHI = inv(HI);
% % IHE = inv(HE);
% %
% % for i=1:300
% % result_Intra(i) = [normX(test_Intra(i,1),:) normX(test_Intra(i,2),:)] * IHE *[normX(test_Intra(i,1),:) normX(test_Intra(i,2),:)]' - [normX(test_Intra(i,1),:) normX(test_Intra(i,2),:)] * IHI *[normX(test_Intra(i,1),:) normX(test_Intra(i,2),:)]';
% % result_Extra(i) = [normX(test_Extra(i,1),:) normX(test_Extra(i,2),:)] * IHE *[normX(test_Extra(i,1),:) normX(test_Extra(i,2),:)]' - [normX(test_Extra(i,1),:) normX(test_Extra(i,2),:)] * IHI *[normX(test_Extra(i,1),:) normX(test_Extra(i,2),:)]';
% % end;
% % sum(result_Intra>0)
% % sum(result_Extra<0)
%
% % tmp = [pairlist_lfw.IntraPersonPair((validate-1)*300+1:validate*300,:);pairlist_lfw.ExtraPersonPair((validate-1)*300+1:validate*300,:)];
% % idx = unique(tmp(:));
%
% m = size(train_x,1);
% n = size(train_x,2);
%
% % Make sure labels are nice
% [classes, bar, train_y] = unique(train_y);
% nc = length(classes);
%
% % Intialize Sw
% Sw = zeros(size(train_x, 2), size(train_x, 2));
%
% cur = {};
% withinCount = 0;
% for i=1:nc
% % Get all instances with class i
% cur{i} = train_x(train_y == i,:);
% if size(cur{i},1)>1
% withinCount = withinCount + size(cur{i},1);
% end;
% end;
%
% u = zeros(n,nc);
% % Sum over classes
% for i=1:nc
% % Update within-class scatter
% u(:,i) = mean(cur{i},1)';
% if size(cur{i},1)>1
% C = cov(cur{i});
% p = size(cur{i}, 1) / (withinCount - 1);
% Sw = Sw + (p * C);
% end;
% end;
% Su = cov(u');
% F = inv(Sw);
% G = -1 .* (2 .* Su + Sw) \ Su / Sw;
% A = inv(Su + Sw) - (F + G);
% c = zeros(m,1);
% for i = 1:m
% c(i) = train_x(i,:) * A * train_x(i,:)';
% end;
% result_Intra = zeros(300,1);
% result_Extra = zeros(300,1);
% for i=1:300
% result_Intra(i) = normX(test_Intra(i,1),:) * A * normX(test_Intra(i,1),:)' + normX(test_Intra(i,2),:) * A * normX(test_Intra(i,2),:)' - 2 * normX(test_Intra(i,1),:) * G * normX(test_Intra(i,2),:)';
% result_Extra(i) = normX(test_Extra(i,1),:) * A * normX(test_Extra(i,1),:)' + normX(test_Extra(i,2),:) * A * normX(test_Extra(i,2),:)' - 2 * normX(test_Extra(i,1),:) * G * normX(test_Extra(i,2),:)';
% end;
% % MM = X * G *X';
% % DIS = repmat(c,1,length(c))+repmat(c,1,length(c))' - 2*MM;
% % GT = zeros(m,m);
% % for i = 1:m
% % for j=1:m
% % GT(i,j) = id_lfw(i)==id_lfw(j);
% % end;
% % end;
% % ER = (GT ~= (DIS>=0));
% % totalER = sum(sum(abs(ER*DIS)));
% % sumER = sum(sum(ER));