void GazeTracker::load() {
CvFileStorage *in = cvOpenFileStorage("calibration.xml", NULL, CV_STORAGE_READ);
CvFileNode *root = cvGetRootFileNode(in);
load(in, cvGetFileNodeByName(in, root, "GazeTracker"));
cvReleaseFileStorage(&in);
updateGaussianProcesses();
}
CvMat * icvReadSVHNLabels(char * filename, const int max_samples)
{
CvFileStorage * fs = cvOpenFileStorage(filename,0,CV_STORAGE_READ);
if (!fs){fprintf(stderr,"file loading error: %s\n",filename);return 0;}
CvFileNode * fnode = cvGetRootFileNode(fs);
char tagname[20]; int ii;
const int nparams = 4;
CvMat * data = cvCreateMat(max_samples,1+nparams*10,CV_32S); cvZero(data);
for (ii=0;;ii++){
sprintf(tagname,"img%d",ii+1);
CvMat * sample = (CvMat*)cvReadByName(fs,fnode,tagname);
if (!sample || ii==max_samples){break;}
int nnumbers = sample->rows;
CV_MAT_ELEM(*data,int,ii,0)=nnumbers;
for (int jj=0;jj<nnumbers;jj++){
float xx = CV_MAT_ELEM(*sample,float,jj,0);
float yy = CV_MAT_ELEM(*sample,float,jj,1);
float ww = CV_MAT_ELEM(*sample,float,jj,2);
float hh = CV_MAT_ELEM(*sample,float,jj,3);
float ll = CV_MAT_ELEM(*sample,float,jj,4);
CV_MAT_ELEM(*data,int,ii,1+nparams*jj+0)=cvRound(xx+ww*.5f); // x
CV_MAT_ELEM(*data,int,ii,1+nparams*jj+1)=cvRound(yy+hh*.5f); // y
CV_MAT_ELEM(*data,int,ii,1+nparams*jj+2)=cvRound(MAX(ww,hh)); // scale
CV_MAT_ELEM(*data,int,ii,1+nparams*jj+3)=cvRound(ll); // label
}
cvReleaseMat(&sample);
}
data->rows = ii;
cvReleaseFileStorage(&fs);
return data;
}
/*!
\fn CvBinGabAdaFeatureSelect::loadweaks(const char* filename)
*/
void CvBinGabAdaFeatureSelect::loadweaks(const char* filename)
{
//clear();
{
delete new_pool;
weaks.clear();
}
CvMemStorage* fstorage = cvCreateMemStorage( 0 );
CvFileStorage *fs;
fs = cvOpenFileStorage( filename, fstorage, CV_STORAGE_READ );
CvFileNode *root = cvGetRootFileNode( fs, 0);
char *weakname = new char[20];
int i = 0;
CvMemStorage* storage = cvCreateMemStorage(0);
CvSeq* seq = cvCreateSeq(0, sizeof(CvSeq), sizeof(CvGaborTree), storage );
while(1)
{
sprintf( weakname, "weak_%d", i);
CvFileNode *weaknode = cvGetFileNodeByName( fs, root, weakname);
if (!weaknode) break;
CvGaborTree tree;
weaknode2tree(weaknode, fs, &tree);
cvSeqPush( seq, &tree );
i++;
}
/* from squence to vector weaks*/
new_pool = new CvGaborFeaturePool;
for (int i = 0; i <seq->total; i++)
{
CvGaborTree *atree = (CvGaborTree*)cvGetSeqElem(seq, i);
CvWeakLearner *weak = new CvWeakLearner;
weak->setType( weaklearner_type );
weak->setthreshold(atree->threshold);
weak->setparity(atree->parity);
weaks.push_back(*weak);
CvGaborFeature *feature = new CvGaborFeature(atree->x, atree->y, atree->Mu, atree->Nu);
new_pool->add(feature);
alphas.push_back(atree->alpha);
delete weak;
delete feature;
}
cvReleaseMemStorage( &storage );
cvReleaseFileStorage(&fs);
cvReleaseMemStorage( &fstorage );
delete [] weakname;
/* set member variables */
current = new_pool->getSize();
falsepositive = 0.0;
nexpfeatures = new_pool->getSize();
nselecfeatures = new_pool->getSize();
printf(" %d weak classifiers have been loaded!\n", nselecfeatures);
}
bool CvMatrix::read( CvFileStorage* fs, const char* seqname, int idx )
{
void* obj = 0;
CvMat* m = 0;
CvFileNode* seqnode = seqname ?
cvGetFileNodeByName( fs, 0, seqname ) : cvGetRootFileNode(fs,0);
if( seqnode && CV_NODE_IS_SEQ(seqnode->tag) )
obj = cvRead( fs, (CvFileNode*)cvGetSeqElem( seqnode->data.seq, idx ));
m = icvRetrieveMatrix(obj);
set( m, false );
return m != 0;
}
bool CvImage::read( CvFileStorage* fs, const char* seqname, int idx )
{
void* obj = 0;
IplImage* img = 0;
CvFileNode* seqnode = seqname ?
cvGetFileNodeByName( fs, 0, seqname ) : cvGetRootFileNode(fs,0);
if( seqnode && CV_NODE_IS_SEQ(seqnode->tag) )
obj = cvRead( fs, (CvFileNode*)cvGetSeqElem( seqnode->data.seq, idx ));
img = icvRetrieveImage(obj);
attach( img );
return img != 0;
}
int CV_MLBaseTest::read_params( CvFileStorage* _fs )
{
if( !_fs )
test_case_count = -1;
else
{
CvFileNode* fn = cvGetRootFileNode( _fs, 0 );
fn = (CvFileNode*)cvGetSeqElem( fn->data.seq, 0 );
fn = cvGetFileNodeByName( _fs, fn, "run_params" );
CvSeq* dataSetNamesSeq = cvGetFileNodeByName( _fs, fn, modelName.c_str() )->data.seq;
test_case_count = dataSetNamesSeq ? dataSetNamesSeq->total : -1;
if( test_case_count > 0 )
{
dataSetNames.resize( test_case_count );
vector<string>::iterator it = dataSetNames.begin();
for( int i = 0; i < test_case_count; i++, it++ )
*it = ((CvFileNode*)cvGetSeqElem( dataSetNamesSeq, i ))->data.str.ptr;
}
}
return CvTS::OK;;
}