I try to 2-Class Categolization. I retreive Image descriptors SURF and BOW, and SVM is used for training. My question is what I specify to clusterCount of BOWKMeansTrainer. training code is like below,
void createTrainDataUsingBow(std::vector<char*> files, cv::Mat& train, cv::Mat& response, int label)
{
cv::Ptr<cv::DescriptorMatcher> matcher = cv::DescriptorMatcher::create("FlannBased");
cv::Ptr<cv::DescriptorExtractor> extractor = new cv::SurfDescriptorExtractor();
cv::BOWImgDescriptorExtractor dextract( extractor, matcher );
cv::SurfFeatureDetector detector(500);
// cluster count
int cluster = 100;
// create the object for the vocabulary.
cv::BOWKMeansTrainer bow( cluster, cv::TermCriteria(CV_TERMCRIT_EPS+CV_TERMCRIT_ITER, 10, FLT_EPSILON), 1, cv::KMEANS_PP_CENTERS );
// get SURF descriptors and add to BOW each input files
std::vector<char*>::const_iterator file;
for( file = files.begin(); file != files.end(); file++)
{
cv::Mat img = cv::imread( *file, CV_LOAD_IMAGE_GRAYSCALE );
std::vector<cv::KeyPoint> keypoints = detector.detect( img, keypoints);
cv::Mat descriptors;
extractor->compute( img, keypoints, descriptors);
if ( !descriptors.empty() ) bow.add( descriptors );
}
// Create the vocabulary with KMeans.
cv::Mat vocabulary;
vocabulary = bow.cluster();
for( file = files.begin(); file != files.end(); file++)
{
// set training data using BOWImgDescriptorExtractor
dextract.setVocabulary( vocabulary );
std::vector<cv::KeyPoint> keypoints = detector.detect( img, keypoints);
cv::Mat img = cv::imread( *file, CV_LOAD_IMAGE_GRAYSCALE );
cv::Mat desc;
dextract.compute( img, keypoints, desc );
if ( !desc.empty() )
{
train.push_back( desc ); // update training data
response.push_back( label ); // update response data
}
}
}
int trainSVM((std::vector<char*> positive, std::vector<char*> negative)
{
// create training data
cv::Mat train;
cv::Mat response;
createTrainDataUsingBow(positive, train, response, 1.0);
createTrainDataUsingBow(negative, train, response, -1.0);
// svm parameters
CvTermCriteria criteria = cvTermCriteria(CV_TERMCRIT_EPS, 1000, FLT_EPSILON);
CvSVMParams svm_param = CvSVMParams( CvSVM::C_SVC, CvSVM::RBF, 10.0, 8.0, 1.0, 10.0, 0.5, 0.1, NULL, criteria);
// train svm
cv::SVM svm;
svm.train(train, response, cv::Mat(), cv::Mat(), svm_param);
svm.save("svm-classifier.xml");
return 0;
}
classifier xml file is successfully created, but exception occerred when I use SVM predict method. I doubt clusterCount is illegal ?
exception is below,
OpenCV Error: Sizes of input arguments do not match (The sample size is different from what has been used for training) in cvPreparePredictData, file ......\src\opencv\modules\ml\src\inner_functions.cpp, line 1114.