How to create inputs and targets for Neural Network?
3 visualizzazioni (ultimi 30 giorni)
Mostra commenti meno recenti
Lauren Pitts
il 2 Ago 2019
Commentato: Lauren Pitts
il 7 Ago 2019
I need to know how to set my SURF code as my input (x) and ind out what my target (t) needs to be.
This is my neural network code:
close all;
clear;
%%GOAL%%
% get 300 images
% x = 640 x 300
% t = 3 x 300
[x,t] = ?????
net = patternnet(10);
view(net);
[net,tr] = train(net,x,t);
nntraintool;
plotperform(tr)
testX = x(:,tr.testInd);
testT = t(:,tr.testInd);
testY = net(testX);
testIndices = vec2ind(testY);
plotconfusion(testT,testY)
I need to add my SURF extraction code as my input (I think) but I have no idea what the t-target is.
SURF extraction code:
images_dir ='C:\Users\pittsl\Desktop\Matlab\train\cup';
pngfiles=dir(fullfile(images_dir,'\*.png*'));
n=numel(pngfiles);
for i=1:n
figure;
image = pngfiles(i).name;
im1 = imread(fullfile(images_dir,image));
I = rgb2gray(im1);
imshow(I);
points = detectSURFFeatures(I);
imshow(I);
hold on;
plot(points.selectStrongest(10));
[features, valid_points] = extractFeatures(I, points);
plot(valid_points.selectStrongest(5),'showOrientation',true);
end
0 Commenti
Risposta accettata
Shashank Gupta
il 5 Ago 2019
Hi,Lauren
“detectSURFFeatures” function is just a feature extraction tool, it will help you to extract important information about the image in a robust way. I am assuming you want your input not to be multidimensional data whereas descriptor gives multidimensional data. One way to tackle this is to use “bag of features”. It discretizes the space of descriptor and gives you a single vector.
You can check out furthermore on “bag of features” in
On the other hand, Target (t) vector you can construct it depending on whether you want to classify or detect something in Image.
For example, “an Iris dataset” has 3 classes and you want to classify the image in one of the three class, so target vector should look something like [0,0,1] (a categorical data) where “1” represent the image belong to that class.
Hope it helps!
Più risposte (0)
Vedere anche
Categorie
Scopri di più su Image Data Workflows in Help Center e File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!