Error in training neural network: Inputs and targets have different numbers of samples

Question

I am trying to code neural network for face detection.
I have input as (1372*4096) and target as (1372*1). The inputs are images, each image is represented in a row. Therefore, I have 1372 images.
For each image I would like to output one value: output 1 if the image is a face and -1 if it is not a face.

I wrote this code:

[input target]=LoadImage();

net=newff(input,target,[10 5 1],{'tansig','tansig','purelin'}, 'trainrp');

net.trainParam.goal=1e-5;
net.trainParam.epochs=1000;
net.trainParam.lr=0.5;
net.trainParam.show=10;

% start training
net=train(net,input,target);

But I get this error:

Error using trainrp (line 107)
Inputs and targets have different numbers of samples.

Error in network/train (line 106)
[net,tr] = feval(net.trainFcn,net,X,T,Xi,Ai,EW,net.trainParam);

Error in train1 (line 12)
net=train(net,d,out_d);

What should I do to fix this error?

Answer 1

For the Neural Network Toolbox, each input must be a vector, so you will have a matrix with as many columns Q as there are different images. Then the target should be a 1xQ. So it looks like you need to reshape the inputs.

I would recommend using new function FEEDFORWARDNET over the obsolete (but still working) NEWFF.