comite.cpp

#include <highgui.h>
#include <cv.h>
#include <ml.h>
#include <stdlib.h>
#include <stdio.h>
#include <iostream>
#include <string.h>

using namespace std;
using namespace cv;

//Comite: red33.xml red35.xml red356dos.xml
int main(int argc, char *argv[]){
    
    if(argc<3){
        cout << "Usage: ./" << argv[0] << " < Infile Net1 > <Infile Net 2> <Infile Net3> < Test Case 1 >...< Test Case N >" << endl;
        exit(-1);
    }

    CvANN_MLP red1,red2,red3;
    red1.load(argv[1]);
    red2.load(argv[2]);
    red3.load(argv[3]);

    //Matrices
    Mat input, src;

    for(int i =4; i<argc; i++){

        //Se leen las imagenes por argumentos
        src = imread(argv[i],CV_LOAD_IMAGE_GRAYSCALE);

        //cout << argv[i][6] << argv[i][6]-'A' <<  endl;

        /*Mat out;
        out = Mat::zeros(1,26,CV_32FC1);
        out.at<float>(argv[i][6]-'A')=1;
        output.push_back(out);

        cout << out<<endl;*/

        if(!src.data){
            cout << "Error al leer la imagen" << endl;
            continue;
        }

        //Turns matrix to vector
        src = src.reshape(0,1);

        //Push it to the input matrix
        input.push_back(src);

        //cout << src<<endl;
    }

    //The number of training samples. 
    int train_sample_count = input.rows;

    //Get the number of samples.
    printf("Found training file with %d samples...\n", train_sample_count);

    //Create the matrices

    //Input data samples. Matrix of order (train_sample_count x 2)
    Mat trainData;
    input.convertTo(trainData,CV_32FC1);

    Mat closeenough1;
    Mat closeenough2;
    Mat closeenough3;

    red1.predict(trainData, closeenough1);
    red2.predict(trainData, closeenough2);
    red3.predict(trainData, closeenough3);

    float sum[26];
    int k=0;
    int corr =0;

    for(int i=0;i<train_sample_count;i++){
        memset(sum,0,sizeof(float)*26);
		float max=-2;
		int m=0;
        for(int j=0; j<26; j++){
            sum[j]=closeenough1.at<float>(i,j)+closeenough2.at<float>(i,j)+closeenough3.at<float>(i,j); 
            if(sum[j]>max){
                m=j;
				max=sum[j];
            }
        }

        printf("%c",m+'A');
		if(k+'A'==m+'A')corr++;
        if((i+1)%100==0){
            printf(" %d\n",corr);
            k++;
			corr=0;
        }
    }

}