| OpenCV 3.4.1 Open Source Computer Vision

peopledetect.cpp
#include <iostream>
#include <stdexcept>
#include <opencv2/objdetect.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/imgcodecs.hpp>
#include <opencv2/video.hpp>
#include <opencv2/videoio.hpp>
using namespace cv;
using namespace std;
const char* keys =
{
"{ help h | | print help message }"
"{ image i | | specify input image}"
"{ camera c | | enable camera capturing }"
"{ video v | ../data/vtest.avi | use video as input }"
"{ directory d | | images directory}"
};
static void detectAndDraw(const HOGDescriptor &hog, Mat &img)
{
vector<Rect> found, found_filtered;
double t = (double) getTickCount();
// Run the detector with default parameters. to get a higher hit-rate
// (and more false alarms, respectively), decrease the hitThreshold and
// groupThreshold (set groupThreshold to 0 to turn off the grouping completely).
hog.detectMultiScale(img, found, 0, Size(8,8), Size(32,32), 1.05, 2);
t = (double) getTickCount() - t;
cout << "detection time = " << (t*1000./cv::getTickFrequency()) << " ms" << endl;
for(size_t i = 0; i < found.size(); i++ )
{
Rect r = found[i];
size_t j;
// Do not add small detections inside a bigger detection.
for ( j = 0; j < found.size(); j++ )
if ( j != i && (r & found[j]) == r )
break;
if ( j == found.size() )
found_filtered.push_back(r);
}
for (size_t i = 0; i < found_filtered.size(); i++)
{
Rect r = found_filtered[i];
// The HOG detector returns slightly larger rectangles than the real objects,
// so we slightly shrink the rectangles to get a nicer output.
r.x += cvRound(r.width*0.1);
r.width = cvRound(r.width*0.8);
r.y += cvRound(r.height*0.07);
r.height = cvRound(r.height*0.8);
rectangle(img, r.tl(), r.br(), cv::Scalar(0,255,0), 3);
}
}
int main(int argc, char** argv)
{
CommandLineParser parser(argc, argv, keys);
if (parser.has("help"))
{
cout << "\nThis program demonstrates the use of the HoG descriptor using\n"
" HOGDescriptor::hog.setSVMDetector(HOGDescriptor::getDefaultPeopleDetector());\n";
parser.printMessage();
cout << "During execution:\n\tHit q or ESC key to quit.\n"
"\tUsing OpenCV version " << CV_VERSION << "\n"
"Note: camera device number must be different from -1.\n" << endl;
return 0;
}
HOGDescriptor hog;
hog.setSVMDetector(HOGDescriptor::getDefaultPeopleDetector());
namedWindow("people detector", 1);
string pattern_glob = "";
string video_filename = "../data/vtest.avi";
int camera_id = -1;
if (parser.has("directory"))
{
pattern_glob = parser.get<string>("directory");
}
else if (parser.has("image"))
{
pattern_glob = parser.get<string>("image");
}
else if (parser.has("camera"))
{
camera_id = parser.get<int>("camera");
}
else if (parser.has("video"))
{
video_filename = parser.get<string>("video");
}
if (!pattern_glob.empty() || camera_id != -1 || !video_filename.empty())
{
//Read from input image files
vector<String> filenames;
//Read from video file
VideoCapture vc;
Mat frame;
if (!pattern_glob.empty())
{
String folder(pattern_glob);
glob(folder, filenames);
}
else if (camera_id != -1)
{
vc.open(camera_id);
if (!vc.isOpened())
{
stringstream msg;
msg << "can't open camera: " << camera_id;
throw runtime_error(msg.str());
}
}
else
{
vc.open(video_filename.c_str());
if (!vc.isOpened())
throw runtime_error(string("can't open video file: " + video_filename));
}
vector<String>::const_iterator it_image = filenames.begin();
for (;;)
{
if (!pattern_glob.empty())
{
bool read_image_ok = false;
for (; it_image != filenames.end(); ++it_image)
{
cout << "\nRead: " << *it_image << endl;
// Read current image
frame = imread(*it_image);
if (!frame.empty())
{
++it_image;
read_image_ok = true;
break;
}
}
//No more valid images
if (!read_image_ok)
{
//Release the image in order to exit the while loop
frame.release();
}
}
else
{
vc >> frame;
}
if (frame.empty())
break;
detectAndDraw(hog, frame);
imshow("people detector", frame);
int c = waitKey( vc.isOpened() ? 30 : 0 ) & 255;
if ( c == 'q' || c == 'Q' || c == 27)
break;
}
}
return 0;
}