shailesh's profile - activity

This is my code.... It works well but, the classifier is not predicting right.. it shows the same result each time for any kind of evaluation data. I am not able to figure out where the problem lies. Its very urgent. I'll be grateful

#include "stdafx.h"
#include <vector>
#include <boost/filesystem.hpp>
#include <opencv2/opencv.hpp>
#include<stdio.h>
#include<conio.h>
using namespace std;
using namespace boost::filesystem;
using namespace cv;

//location of the training data
#define TRAINING_DATA_DIR "data/train/"
//location of the evaluation data
#define EVAL_DATA_DIR "data/eval/"

//See article on BoW model for details

Ptr<FeatureDetector> detector = FeatureDetector::create("SURF");
Ptr<DescriptorExtractor> extractor = DescriptorExtractor::create("SURF");
Ptr<DescriptorMatcher> matcher = DescriptorMatcher::create("FlannBased");
//See article on BoW model for details
int dictionarySize = 1000;
TermCriteria tc(CV_TERMCRIT_ITER+CV_TERMCRIT_EPS, 10, 0.001);
int retries = 1;
int flags = KMEANS_PP_CENTERS;

//See article on BoW model for details
BOWKMeansTrainer bowTrainer(dictionarySize, tc, retries, flags);
//See article on BoW model for details
BOWImgDescriptorExtractor bowDE(extractor, matcher);
/*
CvSVMParams params;
params.svm_type    = CvSVM::C_SVC;
params.kernel_type = CvSVM::LINEAR;
params.term_crit   = cvTermCriteria(CV_TERMCRIT_ITER, 100, 1e-6);
*/
/**
 * \brief Recursively traverses a folder hierarchy. Extracts features from the training images and adds them to the bowTrainer.
 */

bool readVocabulary( const string& filename, Mat& vocabulary )
{
    cout << "Reading vocabulary...";
    FileStorage fs( filename, FileStorage::READ );
    if( fs.isOpened() )
    {
        fs["vocabulary"] >> vocabulary;
        cout << "done" << endl;
        return true;
    }
    return false;
}

bool writeVocabulary( const string& filename, const Mat& vocabulary )
{
    cout << "Saving vocabulary..." << endl;
    FileStorage fs( filename, FileStorage::WRITE );
    if( fs.isOpened() )
    {
        fs << "vocabulary" << vocabulary;
        return true;
    }
    return false;
}

void extractTrainingVocabulary(const path& basepath) {
    for (directory_iterator iter = directory_iterator(basepath); iter
            != directory_iterator(); iter++) {
        directory_entry entry = *iter;

        if (is_directory(entry.path())) {

            cout << "Processing directory " << entry.path().string() << endl;
            extractTrainingVocabulary(entry.path());

        } else {

            path entryPath = entry.path();
            if (entryPath.extension() == ".jpg") {

                cout << "Processing file " << entryPath.string() << endl;
                Mat img = imread(entryPath.string(),0);
                if (!img.empty()) {
                    vector<KeyPoint> keypoints;
                    detector->detect(img, keypoints);
                    if (keypoints.empty()) {
                        cerr << "Warning: Could not find key points in image: "
                                << entryPath.string() << endl;
                    } else {
                        Mat features;
                        extractor->compute(img, keypoints, features);
                        bowTrainer.add(features);
                    }
                } else {
                    cerr << "Warning: Could not read image: "
                            << entryPath.string() << endl;
                }

            }
        }
    }

}

/**
 * \brief Recursively traverses a folder hierarchy. Creates a BoW descriptor for each image encountered.
 */
void extractBOWDescriptor(const path& basepath, Mat& descriptors, Mat& labels) {
    for (directory_iterator iter = directory_iterator(basepath); iter
            != directory_iterator(); iter++) {
        directory_entry entry = *iter;
        if (is_directory(entry.path())) {
            cout << "Processing directory " << entry.path().string() << endl;
            extractBOWDescriptor(entry.path(), descriptors, labels);
        } else {
            path entryPath = entry.path();
            if (entryPath.extension() == ".jpg") {
                cout << "Processing file " << entryPath.string() << endl;
                Mat img = imread(entryPath.string(),0);
                if (!img.empty()) {
                    vector<KeyPoint> keypoints;
                    detector->detect(img, keypoints);
                    if (keypoints.empty()) {
                        cerr << "Warning: Could not find key points in image: "
                                << entryPath.string() << endl;
                    } else {
                        Mat histogram;
                        bowDE.compute(img, keypoints, histogram);
                        descriptors.push_back(histogram);
                        float label=atof(entryPath.filename().string().c_str());
                        labels.push_back(label);
                    }
                } else {
                    cerr << "Warning: Could not read image: "
                            << entryPath.string() << endl;
                }
            }
        }
    }

}

int main(int argc, char ** argv) {

    cout<<"Creating dictionary..."<<endl;
    Mat dictionary;
    if( !readVocabulary( "k.txt", dictionary) )
    {
    extractTrainingVocabulary(path(TRAINING_DATA_DIR));
    vector<Mat> descriptors ...