Follow your step，but only get 73% verification correct rate

First, thank you for your contribution.

I follow your step, used CASIA data and 'mnist_siamese_solver.prototxt', 'CASIA_train_test.prototxt' in 'caffe_proto' folder training CNN without mean file by caffe. After 500,000 iterations, validation set accuracy rate is about 72%. Cnn seems already fitting.

Then, I write matlab code to extracting features and L2 Classification for LFW dataset. But only get 73% verification correct rate.

The matlab code is:

``` matlab
dr_lfw_features = [];
for i= 1:length(fileLines)
im = imread( fileLines{i} );
im = rgb2gray(im);
im = imresize(im, [100 100]);
im = single(im);
im = im /128.0;
im = im';
drop5_data = net.forward({im});
drop5_data = reshape(drop5_data{1}, 1, 320);
fprintf('iamge is %s, i = %d\n', fileLines{i}, i);
dr_lfw_features = [dr_lfw_features; drop5_data];
end

load('pairlist_lfw.mat');
test_Intra = pairlist_lfw.IntraPersonPair;
test_Extra = pairlist_lfw.ExtraPersonPair;
test_pair = [test_Intra; test_Extra];

F1_index = test_pair(:,1);
F2_index = test_pair(:,2);

AllFeature1 = dr_lfw_features(F1_index, :);
AllFeature2 = dr_lfw_features(F2_index, :);

num = length(AllFeature1);
F1 = AllFeature1;
F1 = bsxfun(@rdivide, F1, sqrt(sum(F1.^2,2)));
F2 = AllFeature2;
F2 = bsxfun(@rdivide, F2, sqrt(sum(F2.^2,2)));
thresh2 = zeros(num,1);
for i = 1:num
thresh2(i) = pdist2( F1(i,:),F2(i,:) );
end;
figure;
hist(thresh2(1:3000), 500);
figure;
hist(thresh2(3001:end), 500);

accuracies = zeros(10,1);
for i=1:10
test_idx = [(i-1) * 300 + 1 : i*300, (i-1) * 300 + 3001 : i*300 + 3000];
train_idx = 1:6000;
train_idx(test_idx) = [];
bestc=256;
same_label = ones(6000,1);
same_label(3001:6000) = 0;
cmd = [' -t 0 -h 0'];
model = svmtrain(same_label(train_idx),thresh2(train_idx),cmd);
[class, accuracy, deci] = svmpredict(same_label(test_idx),thresh2(test_idx),model);
accuracies(i) = accuracy(1);
end;
mean(accuracies)
cmd = [' -t 0 -h 0'];
model = svmtrain(same_label,thresh2,cmd);
[class, accuracy, deci] = svmpredict(same_label,thresh2,model);
```

By hist histogram, you can see the same data threshold and different data threshold obviously inseparable.

I think there are errors in this matlab code, do you have any good suggestions?