Hi, I have already download the latest opencv from github and successed compile it. I notice that the latest version realize the soft cascade algorithm and I want to test it. But I don't know how to detect a pedestrian use this method. Is there anybody know it? My platform is vs2010+win64+opencv3.00 ，
you can use it in a very similar way to the HogDetector or the CascadeClassifier:
cv::softcascade::Detector soft;
// load data ( no idea why the other one did not work..)
cv::FileStorage fs("E:/code/opencv/data/softcascade/soft-cascade-17.12.2012.xml", cv::FileStorage::READ);
bool ok = soft.load(fs.getFirstTopLevelNode());
if ( ! ok ) {
std::cerr << "cascade load error!" << std::endl;
return -1;
}
std::vector<cv::Rect> rois; // where in the image to look for people
// pretty nifty, if you got a bg-separator in front of it, so you only
// need to look at small (moving) parts of the image...
rois.push_back(Rect(0,0,img.cols,img.rows)); //for now, the whole img
std::vector<cv::softcascade::Detection> softobj; // results
soft.detect(img,rois,softobj);
for ( size_t j=0; j<softobj.size(); ++j ) // lame visualization ..
{
cv::Rect R(softobj[j].x, softobj[j].y, softobj[j].w, softobj[j].h);
cv::rectangle(img,R,cv::Scalar(softobj[j].confidence*3-128 ,0,0),2);
}
Nice, didn't know the interface was that similar :)
According with the exp result I review your code，if add a "grouprectangles" function for the output location may be better. I found that the training of soft cascade is independent with adaboost. Can I train a detector by myself use haar or hog feature by the latest opencv?
Asked: 2014-01-20 21:12:46 -0600
Seen: 1,250 times
Last updated: Jan 21 '14
The softcascade is indeed implemented but it is not documented. The only way to get a hang from it is to browse through the sourcecode and try to decipher the different functions the algorithm supplies. It is one of the downsides of an open-source library where people could add functionality as they pleased in the past. If you however, figure it out, create a sample, add it to the repository so that future users can get a hang of it also.