trying to make face recognition with ANN

edit

opencv comes with a MLP readymade that you could use.

here is a nice post on how to prepare the data (for an svm, but that step is the same for ANN, too)

apart from that: if you're really into ann's allow some time for this

that post is realy good:) i already made data loading, now just reading the "MLP readymade" to get a grip how its made :)

found an mlp example

can someone explain me why i get memory allocation problem?

int sks[4]={10,10,5,1};
  CvMat skuoksniai= cvMat(1,4,CV_8UC1,sks); // not sure about CV_8UC1 part as well :/
  CvANN_MLP tinklas;
  tinklas.create( &skuoksniai,CvANN_MLP::SIGMOID_SYM,1,1); //problem line.

int sks[4]={10,10,5,1};
cv::Mat skuoksniai= cv::Mat(1,4,CV_32SC1,sks); // just use CV_32S
CvANN_MLP tinklas;
tinklas.create(skuoksniai,CvANN_MLP::SIGMOID_SYM,1,1); //problem no more i hope ;)

(yea, i know, that cv::Mat, cvMat is annoying ...)

is that lithuanian above ;) ?

thank you for quick response. k, ill leave CV_32SC1 part for later. but when i remove & i get "no instance of overloaded function "CvANN_MLP::create"" :( yes :)

damn, works fine here ...

dude, sry my bad.. didn't sow the "cv::Mat" part. now its seams to run :) thank you so much :)

and one again i get memory allocation problem. cv::Mat trainData(17,38416,CV_8UC1)// its 17 rows and 38416 columns of grey images 1 row = image
cv::Mat label= cv::Mat(1,17,CV_32S,temp);// temp is int temp[17]; witch contains {0,0,0,0,0,0,0,1,1,1,1,1,2,2,2,2,2} cv::Mat weights= cv::Mat::ones(1,17,CV_32S); tinklas.train(trainData,label,weights);

i tried cv::Mat new; cvtColor(trainData,new,CV_32S);

http://docs.opencv.org/modules/ml/doc/neural_networks.html#cvann-mlp-train

• your trainData Mat has the correct shape, but the wrong type. you need float data here, so it needs a simple conversion, before you apply it: trainData.convertTo(trainData, CV_32F); (cvtColor is more for translating from bgr to hsv or such, it does not change the datatype)
• your labels have the wrong shape. for 17 feature vecs(rows), you need 17 labels(rows) as well, so: cv::Mat label= cv::Mat(17,1,CV_32S,temp); // only rows/cols swapped to what you got before

again, don't worry too much. you're doing fine. all that confusion is pretty normal ;)