HOGDescriptor OpenCV dsize.area() assertion failed - c++

Question

I'm trying to train SVM and use it inside HOGDescrpitor from OpenCV.
The xml file was succesfully generated and loaded by HOGDescriptor but when I try to detect some object, then assertion is occurred:
OpenCV Error: Assertion failed (dsize.area() || (inv_scale_x > 0 &&
inv_scale_y > 0)) in resize, file
/build/buildd/opencv-2.4.8+dfsg1/modules/imgproc/src/imgwarp.cpp, line
1825 terminate called after throwing an instance of
'tbb::captured_exception' what():
/build/buildd/opencv-2.4.8+dfsg1/modules/imgproc/src/imgwarp.cpp:1825:
error: (-215) dsize.area() || (inv_scale_x > 0 && inv_scale_y > 0) in
function resize
To implement SVM trainer I used hints from using OpenCV and SVM with images
Generated XML file has about 144Kbytes. For positive and negative samples I used images of size 64x128 (2000 for positive and 2000 for negative)
Parameter for SVM trainer:
CvSVMParams svmParams;
svmParams.svm_type = CvSVM::C_SVC;
svmParams.kernel_type = CvSVM::LINEAR;
svmParams.term_crit = cvTermCriteria( CV_TERMCRIT_ITER, 10000, 1e-6 );
Code for detection:
int main()
{
HOGDescriptor hog();
if(!hog.load("/home/bin/hogdescriptor.xml"))
{
std::cout << "Failed to load file!" << std::endl;
return -1;
}
VideoCapture cap(0);
if(!cap.isOpened())
{
std::cout << "Error opening camera!" << std::endl;
return 1;
}
Mat testImage;
while ((cvWaitKey(30) & 255) != 27)
{
cap >> testImage;
detectTest(hog, testImage);
imshow("HOG custom detection", testImage);
}
return EXIT_SUCCESS;
}
void showDetections(const vector<Rect>& found, Mat& imageData) {
for (const Rect& rect : found)
{
Point rectPoint1;
rectPoint1.x = rect.x;
rectPoint1.y = rect.y;
Point rectPoint2;
rectPoint2.x = rect.x + rect.width;
rectPoint2.y = rect.y + rect.height;
std::cout << "detection x: " << rect.x << ", y: " << rect.y << std::endl;
rectangle(imageData, rectPoint1, rectPoint2, Scalar(0, 255, 0));
}
}
void detectTest(const HOGDescriptor& hog, Mat& imageData)
{
std::cout << "Trying to detect" << std::endl;
vector<Rect> found;
int groupThreshold = 2;
Size padding(Size(32, 32));
Size winStride(Size(8, 8));
double hitThreshold = 0.; // tolerance
hog.detectMultiScale(imageData, found, hitThreshold, winStride, padding, 1.05, groupThreshold);
// hog.detectMultiScale(imageData, found);
std::cout << "Trying to show detections" << std::endl;
showDetections(found, imageData);
}
XML:
<?xml version="1.0"?>
<opencv_storage>
<my_svm type_id="opencv-ml-svm">
<svm_type>C_SVC</svm_type>
<kernel><type>LINEAR</type></kernel>
<C>1.</C>
<term_criteria><epsilon>2.2204460492503131e-16</epsilon>
<iterations>10000</iterations></term_criteria>
<var_all>8192</var_all>
<var_count>8192</var_count>
<class_count>2</class_count>
<class_labels type_id="opencv-matrix">
<rows>1</rows>
<cols>2</cols>
<dt>i</dt>
<data>
-1 1</data></class_labels>
<sv_total>1</sv_total>
<support_vectors>
<_>
-9.25376153e-05 -9.25376153e-05 -9.25376153e-05 -9.25376153e-05 ...and many, many...</_></support_vectors>
<decision_functions>
<_>
<sv_count>1</sv_count>
<rho>-1.</rho>
<alpha>
1.</alpha>
<index>
0</index></_></decision_functions></my_svm>
</opencv_storage>
Can someone explain me this assertion or maybe can provide some solution for this problem? I spent almost 3 days to fix this but without any success... Thanks in advance!

Answer 1

this is the closer what i got... still trying to use this xml
private static void buscar_hog_svm() {
if (clasificador == null) {
clasificador = new CvSVM();
clasificador.load(path_vectores);
}
Mat img_gray = new Mat();
//gray
Imgproc.cvtColor(imag, img_gray, Imgproc.COLOR_BGR2GRAY);
//Extract HogFeature
hog = new HOGDescriptor(
_winSize //new Size(32, 16)
, _blockSize, _blockStride, _cellSize, _nbins);
MatOfFloat descriptorsValues = new MatOfFloat();
MatOfPoint locations = new MatOfPoint();
hog.compute(img_gray,
descriptorsValues,
_winSize,
_padding, locations);
Mat fm = descriptorsValues;
System.out.println("tamano fm: " + fm.size());
//Classification whether data is positive or negative
float result = clasificador.predict(fm);
System.out.println("resultado= " + result);
}
if you have more clues, please share