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