How do I write a function that contain a for loop to go through my filesname to find a match?

I currently collected a set of "name_list" together with a set of "numoflikes_list". Each name has certain num of likes attached to it. (i.e 123456789.jpg, 345 likes; 1432546435.jpg, 23 likes)

And I would like to write a function that go through all my image_name in a folder to find a match with the "name_list" that I have collected and eventually obtaining the num of likes that is associated with my image name.

This is what I have so far, was stuck and not sure how to write the for loop for this function:

    function numofLikes=get_num_of_likes(image_name,name_list,numoflikes_list)

    for i=1:size(name_list, 1)
    name_list{i}

Answer 1

[Thorsten]

It a one-liner; your probably do not want to write a function for it

nol = numoflike_list(strcmp(image_name, name_list));

[Josephine Ng]

i'm thinking a function is needed because they are of different .m files.

I have attached the two different .m files for your reference. testcellv2.m is the file that i collected the name_list and numoflike_list from. whereas cnn_classify.m file is the main file that i will like to load the function to find a match.

can the above solution be used if they are of different .m files?

[Thorsten]

If you run testcellv2, you should have the corresponding variables in your work space, and you can use them if you run cnn_classify.

[Josephine Ng]

so meaning to say i just have to run testcellv2 first, then run cnn_classify next?

is it possible to use the function mtd so that I can just run cnn_classify by loading the testcellv2.mat then afterwhich use the function to find a match to obtain the num of likes?

[Thorsten]

Yes. Why not? As far as I can see, if this is what you want to compute, then go ahead.

[Josephine Ng]

yes. but i am stuck with the for loop and need help with the function.

[Josephine Ng]

another can help me with the for loop??

[Thorsten]

You don't Need a for loop, just use the line I've posted above.

[Josephine Ng]

i tried the line u posted but still I still an error message of: Subscripted assignment dimension mismatch.

Error in cnn_classify (line 38) mat(nol,:)=E;

   % install and compile MatConvNet (run once)
%untar(['http://www.vlfeat.org/matconvnet/download/' ...
%'matconvnet-1.0-beta12.tar.gz']) ;
cd('C:\Users\karmun cheah\Documents\MATLAB\matconvnet-1.0-beta12');
% run matlab/vl_compilenn

 %download a pre?trained CNN from the web (run once)
%urlwrite(...
 %   'http://www.vlfeat.org/matconvnet/models/imagenet-vgg-f.mat', ...
  %  'imagenet-vgg-f.mat');

    % setup MatConvNet
    run matlab/vl_setupnn

   % load the pre?trained CNN
 net = load('imagenet-vgg-f.mat') ;

   %load till 7th layer
 net.layers=net.layers(1:18); 

% load and preprocess an image
for j=1:2
foldername=['Test/fashion' num2str(j) '/'];
 file_names=dir(foldername);

   % file_names(1:542).name;
for i=1:size(file_names,1)-2
im = imread([foldername file_names(i+2).name]);
im_ = imresize(single(im), net.normalization.imageSize(1:2));

   load ('testcellv2.mat');
nol = numoflike_list(strcmp(file_names(i+2), C));
%numofLikes=get_num_of_likes(file_names(i+2).name,C,D);
mat(nol,:)=E;

    if (size(im_,3)==1)
for k=1:3
new_img(:,:,k)=im_;
end
im_=new_img;
end

   im_ = im_ - net.normalization.averageImage;

   % run the CNN
   res = vl_simplenn(net, im_);
   A=res(19).x;
   B=squeeze(A);size(B);
   mat(i,:)=B;

   end
end
% show the classification result
scores = squeeze(gather(res(end).x)) ;
[bestScore, best] = max(scores) ;
figure(1) ; clf ; imagesc(im) ;
title(sprintf('%s (%d), score %.3f',...
net.classes.description{best}, best, bestScore)) ;

   rank = ranksvm(B,E);

[Thorsten]

E must be 1 x N or N x 1.