Video very long time to load. Opencv - c++

Question

I'm a novice programmer. My experience is very small. Now I have a code to detected people. I use SVM classifier and a HOG descriptor. Video is very long to be loaded and processed. Please help me with this problem.
#include <assert.h>
#include "opencv2/core/core.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/objdetect/objdetect.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
#include <conio.h>
#include "opencv2/opencv.hpp"
using namespace cv;
using namespace std;
int main()
{
string filename = "Street.MP4";
VideoCapture capture(filename);
Mat frame;
//namedWindow("w", 1);
while (true)
{
capture >> frame;
if (frame.empty())
break;
Mat img, res;
Mat framecopy = frame.clone();
resize(framecopy, img, Size(2 * framecopy.cols, 2 * framecopy.rows));
int nbins = 9;
Size cellSize(8, 8);
Size blockSize(16, 16);
Size blockStride(8, 8);
Size winSize(64, 128);
Size winStride(4, 4);
HOGDescriptor hog(winSize, blockSize, blockStride, cellSize, nbins);
hog.setSVMDetector(HOGDescriptor::getDefaultPeopleDetector());
assert(hog.checkDetectorSize());
vector<Rect> locations;
vector<double> weights;
hog.detectMultiScale(img, locations, weights, 0.0, winStride, Size(), 1.05, 2., true);
resize(img, res, Size(framecopy.cols / 2, framecopy.rows / 2));
for (size_t i = 0; i < locations.size(); ++i)
{
Rect detection = locations[i];
detection.x /= 2;
detection.y /= 2;
detection.width /= 2;
detection.height /= 2;
rectangle(res, detection, Scalar(0, 0, 255), 2);
}
imshow("w", res);
waitKey(20); // waits to display frame
}
waitKey();
return 0;
}

Answer 1

Don't create the hog detector in each iteration.
try:
#include <assert.h>
#include "opencv2/core/core.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/objdetect/objdetect.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
#include <conio.h>
#include "opencv2/opencv.hpp"
using namespace cv;
using namespace std;
int main()
{
string filename = "Street.MP4";
VideoCapture capture(filename);
Mat frame;
//namedWindow("w", 1);
int nbins = 9;
Size cellSize(8, 8);
Size blockSize(16, 16);
Size blockStride(8, 8);
Size winSize(64, 128);
Size winStride(4, 4);
HOGDescriptor hog(winSize, blockSize, blockStride, cellSize, nbins);
hog.setSVMDetector(HOGDescriptor::getDefaultPeopleDetector());
assert(hog.checkDetectorSize());
while (true)
{
capture >> frame;
if (frame.empty())
break;
Mat img, res;
Mat framecopy = frame.clone();
resize(framecopy, img, Size(2 * framecopy.cols, 2 * framecopy.rows));
vector<Rect> locations;
vector<double> weights;
hog.detectMultiScale(img, locations, weights, 0.0, winStride, Size(), 1.05, 2., true);
resize(img, res, Size(framecopy.cols / 2, framecopy.rows / 2));
for (size_t i = 0; i < locations.size(); ++i)
{
Rect detection = locations[i];
detection.x /= 2;
detection.y /= 2;
detection.width /= 2;
detection.height /= 2;
rectangle(res, detection, Scalar(0, 0, 255), 2);
}
imshow("w", res);
waitKey(1); // waits to display frame
}
waitKey();
return 0;
}
But keep in mind that HoG detection is a quite expensive operation. What's the resolution of your images?