So I have followed this guide to train my own pedestrian HOG detector. https://github.com/DaHoC/trainHOG/wiki/trainHOG-Tutorial
And it was successful with 4 files generated.
- cvHOGClassifier.yaml
- descriptorvector.dat
- features.dat
- svmlightmodel.dat
Does anyone know how to load the descriptorvector.dat file as a vector?
I've tried this but failed.
vector<float> detector;
std::ifstream file;
file.open("descriptorvector.dat");
file >> detector;
file.close();
This is something I would like to use eventually.
gpu::HOGDescriptor hog(Size(64, 128), Size(16, 16), Size(8, 8), Size(8, 8),9);
hog.setSVMDetector(detector);
Thank you in advance!
If you have already trained your SVM, you could just save the weights and the intercept in a TXT file and then load it in an array/vector. You would then use it as follows:
std::vector<float> descriptorsValues; //A vector to store the computed HoG values
std::vector<cv::Point> locations;
hog.compute(image, descriptorsValues, cv::Size(0, 0), cv::Size(0, 0), locations);
double res = 0;
for (int i = 0; i < svmDimension - 1; i++)
{
res += w[i] * descriptorsValues.at(i);
}
res = res + w[svmDimension - 1];
return res;
where svmDimension is the array/vector which contains the SVM weights followed by the SVM intercept, and res is the SVM response
You can read the file and push every value back to an array of float, so first declare it:
vector<float> myDescriptorVector;
Then push every value:
ifstream infile ("yourFile.dat".c_str());
float number;
while (infile >> number)
myDescriptorVector.push_back(number);
return myDescriptorVector;
Finally use the standard initialization for the HOG and pass the vector to the SVM detector as you already guessed:
hog.setSVMDetector(myDescriptorVector);
