I was following this answer, which explains step by step the coding for svm. But I am having a runtime error in the predict function, here is the code I came up with
#include <opencv2/core/core.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>
#include<opencv2/ml.hpp>
#include <iostream>
#include <vector>
using namespace std;
using namespace cv;
using namespace cv::ml;
int main ( int argc, char** argv )
{
cout << "Manas\n";
char* filename;
Mat input_image;
VideoCapture capture(0);
FileStorage fs;
fs.open("SVM.xml", FileStorage::READ);
Mat SVM_TrainingData;
Mat SVM_Classes;
fs["TrainingData"] >> SVM_TrainingData;
fs["classes"] >> SVM_Classes;
Ptr<SVM> SVM_params = SVM::create();
SVM_params->setType(SVM::C_SVC);
SVM_params->setKernel(SVM::LINEAR);
SVM_params->setTermCriteria(TermCriteria(TermCriteria::MAX_ITER, 100, 0.01));
Ptr<TrainData> td = TrainData::create(SVM_TrainingData, ROW_SAMPLE, SVM_Classes);
SVM_params->train(td);
while (true)
{
capture.read(input_image);
resize(input_image, input_image, Size(200, 200));
Mat img_gray;
cvtColor(input_image, img_gray, CV_BGR2GRAY);
blur(img_gray, img_gray, Size(5,5));
Mat p= img_gray.reshape(1, img_gray.channels()*img_gray.size().area());
p.convertTo(p, CV_32F);
int response = (int)SVM_params->predict( p );
if(response==1) cout<<"Detected";
imshow("Plate Detected", input_image);
int c = waitKey(10);
if (c == 27)
break;
}
return 0;
}
I am sure I am missing something, but i can't figure out what.Please suggest what else shall i include.
Update
Here is the code that I am using for training my images
#include <opencv2/core/core.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <cv.h>
#include <highgui.h>
#include <cvaux.h>
#include <iostream>
#include <vector>
#include<string.h>
using namespace std;
using namespace cv;
int main ( int argc, char** argv )
{
cout << "OpenCV Training SVM Automatic Number Plate Recognition\n";
cout << "\n";
char* path_Plates;
char* path_NoPlates;
int numPlates;
int numNoPlates;
int imageWidth=150;
int imageHeight=150;
//Check if user specify image to process
if(1)
{
numPlates= 12;
numNoPlates= 90 ;
path_Plates= "/home/kaushik/opencv_work/Manas6/Pics/Positive_Images/";
path_NoPlates= "/home/kaushik/opencv_work/Manas6/Pics/Negative_Images/i";
}else{
cout << "Usage:\n" << argv[0] << " <num Plate Files> <num Non Plate Files> <path to plate folder files> <path to non plate files> \n";
return 0;
}
Mat classes;//(numPlates+numNoPlates, 1, CV_32FC1);
Mat trainingData;//(numPlates+numNoPlates, imageWidth*imageHeight, CV_32FC1 );
Mat trainingImages;
vector<int> trainingLabels;
for(int i=1; i<= numPlates; i++)
{
stringstream ss(stringstream::in | stringstream::out);
ss<<path_Plates<<i<<".jpg";
try{
const char* a = ss.str().c_str();
printf("\n%s\n",a);
Mat img = imread(ss.str(), CV_LOAD_IMAGE_UNCHANGED);
img= img.clone().reshape(1, 1);
//imshow("Window",img);
//cout<<ss.str();
trainingImages.push_back(img);
trainingLabels.push_back(1);
}
catch(Exception e){;}
}
for(int i=0; i< numNoPlates; i++)
{
stringstream ss(stringstream::in | stringstream::out);
ss << path_NoPlates<<i << ".jpg";
try
{
const char* a = ss.str().c_str();
printf("\n%s\n",a);
Mat img=imread(ss.str(),CV_LOAD_IMAGE_UNCHANGED);
//imshow("Win",img);
img= img.clone().reshape(1, 1);
trainingImages.push_back(img);
trainingLabels.push_back(0);
//cout<<ss.str();
}
catch(Exception e){;}
}
Mat(trainingImages).copyTo(trainingData);
//trainingData = trainingData.reshape(1,trainingData.rows);
trainingData.convertTo(trainingData, CV_32FC1);
Mat(trainingLabels).copyTo(classes);
FileStorage fs("SVM.xml", FileStorage::WRITE);
fs << "TrainingData" << trainingData;
fs << "classes" << classes;
fs.release();
return 0;
}
