Hi all,
I trying to implement a simple sample, the purpose is tranning and detect a number. Source as following:
Step 1: Initial data for tranning: I used a collect of images number for traning data,
Mat vectorMatToMat(vector<Mat> list) {
if (list.empty()) {
return Mat();
}
int row = list.size();
int col = list.at(0).rows * list.at(0).cols;
Mat data(row, col, CV_32FC1);
int i = 0;
for (i = 0; i < row; i++) {
Mat rowMat = list.at(i).reshape(1, 1);
rowMat.copyTo(data.row(i));
}
return data;
}
Mat vectorIntToMat(vector<int> list) {
int row = list.size();
Mat data(row, 1, CV_32SC1, &list[0]);
return data;
}
Mat dataMat = vectorMatToMat(listImageForTraining);
Mat dataLabel = vectorIntToMat(listLabel);
Step 2: Init SVM:
Ptr<TrainData> trainData = TrainData::create(dataMat, ROW_SAMPLE, dataLabel);
Ptr<SVM> model = SVM::create();
model->setType(SVM::C_SVC);
model->setKernel(SVM::LINEAR);
model->setC(7);
model->setNu(SVM::NU_SVC);
model->setP(0);
model->setDegree(0);
model->setGamma(20);
model->setCoef0(0);
TermCriteria term(CV_TERMCRIT_ITER +CV_TERMCRIT_EPS, 1000, 1e-6);
model->setTermCriteria(term);
model->train(trainData);
Step 3: trying using SVM for predict:
int i = 0;
for (i = 0; i < 15; i++) {
Mat check = dataMat.row(i);
ostringstream oss;
oss << i;
imshow(oss.str(), check.reshape(1, 128));
check = check.reshape(1, 1);
int lable = svm.predict(check);
cout << "Result: " << lable << endl;
}
Step 4: Result:
Result: -1237234688
Result: 159407376
Result: 159407376
Result: 167908848
Result: 1065353216
Result: 1065353216
Result: 1065353216
Result: 1065353216
Result: 1065353216
Result: 1065353216
Result: 1065353216
Result: 1065353216
Result: 1065353216
Result: 1065353216
Result: 1065353216
As we can see, my result are very large number, although my labels are numbers in 0 to 10. I can not understand why, i think i have a mistake when I init SVM model.
But i dont know how to fix this issue, If there is any idea, please help me.
Thanks & Best Regards,
Thiep