1 | initial version |
there is a similar code i have posted before you can also take a look at http://answers.opencv.org/question/80580
here is your code adopted to run with OpenCV 3.1
#include <opencv2/opencv.hpp>
#include <iostream>
#include <vector>
int main(int argc, char *argv[])
{
if (argc < 3)
{
std::cerr << "Usage: " << argv[0] << " in.file out.file" << std::endl;
return -1;
}
cv::Mat frame;
cv::Mat back;
cv::Mat fore;
std::cerr << "opening " << argv[1] << std::endl;
cv::VideoCapture cap(argv[1]);
cv::Ptr<cv::BackgroundSubtractor> bg = cv::createBackgroundSubtractorMOG2();
//bg.nmixtures = 3;
//bg.bShadowDetection = false;
cv::VideoWriter output;
//int ex = static_cast<int>(cap.get(CV_CAP_PROP_FOURCC));
int ex = CV_FOURCC('P', 'I', 'M', '1');
cv::Size size = cv::Size((int)cap.get(CV_CAP_PROP_FRAME_WIDTH),
(int)cap.get(CV_CAP_PROP_FRAME_HEIGHT));
std::cerr << "saving to " << argv[2] << std::endl;
output.open(argv[2], ex, cap.get(CV_CAP_PROP_FPS), size, true);
std::vector<std::vector<cv::Point> > contours;
cv::namedWindow("Frame");
cv::namedWindow("Fore");
cv::namedWindow("Background");
cv::SimpleBlobDetector::Params params;
params.minThreshold = 40;
params.maxThreshold = 60;
params.thresholdStep = 5;
params.minArea = 100;
params.minConvexity = 0.3;
params.minInertiaRatio = 0.01;
params.maxArea = 8000;
params.maxConvexity = 10;
params.filterByColor = false;
params.filterByCircularity = false;
cv::Ptr<cv::SimpleBlobDetector> blobDtor = cv::SimpleBlobDetector::create(params);
std::vector<std::vector<cv::Point> > blobContours;
std::vector<cv::KeyPoint> keyPoints;
cv::Mat out;
cv::HOGDescriptor hog;
hog.setSVMDetector(cv::HOGDescriptor::getDefaultPeopleDetector());
for (;;)
{
cap >> frame;
bg->apply(frame, fore);
bg->getBackgroundImage(back);
cv::erode(fore, fore, cv::Mat());
cv::dilate(fore, fore, cv::Mat());
blobDtor->detect(fore, keyPoints, cv::Mat());
//cv::imshow("Fore", fore);
cv::findContours(fore, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);
cv::drawContours(frame, contours, -1, cv::Scalar(0, 0, 255), 2);
std::vector<std::vector<cv::Point> >::const_iterator it = contours.begin();
std::vector<std::vector<cv::Point> >::const_iterator end = contours.end();
while (it != end)
{
cv::Rect bounds = cv::boundingRect(*it);
cv::rectangle(frame, bounds, cv::Scalar(0, 255, 0), 2);
++it;
}
cv::drawKeypoints(fore, keyPoints, out, CV_RGB(0, 255, 0), cv::DrawMatchesFlags::DEFAULT);
cv::imshow("Fore", out);
std::vector<cv::Rect> found, found_filtered;
hog.detectMultiScale(frame, found, 0, cv::Size(8, 8), cv::Size(32, 32), 1.05, 2);
for (int i = 0; i < found.size(); ++i)
{
cv::Rect r = found[i];
int j = 0;
for (; j < found.size(); ++j)
{
if (j != i && (r & found[j]) == r)
{
break;
}
}
if (j == found.size())
{
found_filtered.push_back(r);
}
}
for (int i = 0; i < found_filtered.size(); ++i)
{
cv::Rect r = found_filtered[i];
cv::rectangle(frame, r.tl(), r.br(), cv::Scalar(255, 0, 0), 3);
}
output << frame;
cv::resize(frame, frame, cv::Size(1280, 720));
cv::imshow("Frame", frame);
cv::resize(back, back, cv::Size(1280, 720));
cv::imshow("Background", back);
if (cv::waitKey(30) >= 0) break;
}
return 0;
}