void LatentSvmDetector::detect( const Mat& image,
std::vector<ObjectDetection>& objectDetections,
float overlapThreshold,
int numThreads )
{
objectDetections.clear();
if( numThreads <= 0 )
numThreads = 1;
for( size_t classID = 0; classID < detectors.size(); classID++ )
{
IplImage image_ipl = image;
CvMemStorage* storage = cvCreateMemStorage(0);
CvSeq* detections = cvLatentSvmDetectObjects( &image_ipl, detectors[classID], storage, overlapThreshold, numThreads );
// convert results
objectDetections.reserve( objectDetections.size() + detections->total );
for( int detectionIdx = 0; detectionIdx < detections->total; detectionIdx++ )
{
CvObjectDetection detection = *(CvObjectDetection*)cvGetSeqElem( detections, detectionIdx );
objectDetections.push_back( ObjectDetection(Rect(detection.rect), detection.score, (int)classID) );
}
cvReleaseMemStorage( &storage );
}
}
int64 start = 0, finish = 0;
#ifdef HAVE_TBB
tbb::task_scheduler_init init(tbb::task_scheduler_init::deferred);
if (numThreads > 0)
{
init.initialize(numThreads);
printf("Number of threads %i\n", numThreads);
}
else
{
printf("Number of threads is not correct for TBB version");<<std::endl;
return;
}
#endif
start = cvGetTickCount();
detections = cvLatentSvmDetectObjects(image, this->detector, storage, 0.3f, numThreads);
finish = cvGetTickCount();
printf("++++++++++\ndetection time = %.3f\n", (float)(finish - start) / (float)(cvGetTickFrequency() * 1000000.0));
#ifdef HAVE_TBB
init.terminate();
#endif
preHists=currHists;
currHists.clear();
for(int i = 0; i<tracked.size(); i++)
{
tracked[i].fresh = false;
}
if(depth_ptr!=NULL)
{
