Extracting features with CNN VGG16 and KNN classification

Hi, I'm new to machine learning and classification. I read a lot of documentation in matlab in order to create a function that calculates the features of a given dataset. This is what I wrote:

    tic;

    net = vgg16;
    layer = 'fc7';
    net_size = net.Layers(1).InputSize;

    [images, labels] = readlists();
    n = numel(images);

    f = [];

    for i = 1 : n
        im = imread(['simplicity/' images{i}]);
        im = imresize(im, net_size(1:2));
        f = [f; activations(net, im, layer, 'ExecutionEnvironment', 'gpu')];
    end

    toc;

    save('f', 'f');

Is this correct or did I calculated something useless? However I've tested it and the accuracy of training is: 95% and test: 94% using a dataset of 1000 images.

Now I want to know if I'm doing it right. How can I get the corresponding label to an image? I mean, if I want to know the corresponding label, given an image (for example food) of the dataset, how can I do that?

By the way, readList() returns a cell array filled with the name of each image (images) and the corresponding labels (labels).

It takes about ~30 secs to calculate 'f' using gpu.