mirror of https://github.com/opencv/opencv.git
- bgfg_segm - peopledetect - opencv_version - dnn/colorization - tapi/opencl_custom_kernel - tapi/dense_optical_flow (renamed tvl1_optical_flow)pull/11411/head^2
Maksim Shabunin
7 years ago
parent
ed96279920
commit
e283a75a19
7 changed files with 301 additions and 423 deletions
@ -1,177 +1,126 @@ |
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#include <iostream> |
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#include <stdexcept> |
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// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html
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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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#include <iostream> |
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#include <iomanip> |
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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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class Detector |
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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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enum Mode { Default, Daimler } m; |
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HOGDescriptor hog, hog_d; |
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public: |
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Detector() : m(Default), hog(), hog_d(Size(48, 96), Size(16, 16), Size(8, 8), Size(8, 8), 9) |
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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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hog.setSVMDetector(HOGDescriptor::getDefaultPeopleDetector()); |
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hog_d.setSVMDetector(HOGDescriptor::getDaimlerPeopleDetector()); |
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} |
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for (size_t i = 0; i < found_filtered.size(); i++) |
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void toggleMode() { m = (m == Default ? Daimler : Default); } |
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string modeName() const { return (m == Default ? "Default" : "Daimler"); } |
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vector<Rect> detect(InputArray img) |
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{ |
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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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vector<Rect> found; |
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if (m == Default) |
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hog.detectMultiScale(img, found, 0, Size(8,8), Size(32,32), 1.05, 2, false); |
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else if (m == Daimler) |
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hog_d.detectMultiScale(img, found, 0.5, Size(8,8), Size(32,32), 1.05, 2, true); |
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return found; |
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} |
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void adjustRect(Rect & r) const |
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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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}; |
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static const string keys = "{ help h | | print help message }" |
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"{ camera c | 0 | capture video from camera (device index starting from 0) }" |
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"{ video v | | use video as input }"; |
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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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parser.about("This sample demonstrates the use ot the HoG descriptor."); |
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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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int camera = parser.get<int>("camera"); |
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string file = parser.get<string>("video"); |
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if (!parser.check()) |
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{ |
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pattern_glob = parser.get<string>("directory"); |
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parser.printErrors(); |
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return 1; |
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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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VideoCapture cap; |
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if (file.empty()) |
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cap.open(camera); |
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else |
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cap.open(file.c_str()); |
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if (!cap.isOpened()) |
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{ |
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video_filename = parser.get<string>("video"); |
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cout << "Can not open video stream: '" << (file.empty() ? "<camera>" : file) << "'" << endl; |
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return 2; |
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} |
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if (!pattern_glob.empty() || camera_id != -1 || !video_filename.empty()) |
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cout << "Press 'q' or <ESC> to quit." << endl; |
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cout << "Press <space> to toggle between Default and Daimler detector" << endl; |
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Detector detector; |
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Mat frame; |
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for (;;) |
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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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cap >> frame; |
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if (frame.empty()) |
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{ |
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String folder(pattern_glob); |
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glob(folder, filenames); |
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cout << "Finished reading: empty frame" << endl; |
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break; |
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} |
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else if (camera_id != -1) |
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int64 t = getTickCount(); |
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vector<Rect> found = detector.detect(frame); |
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t = getTickCount() - t; |
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// show the window
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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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ostringstream buf; |
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buf << "Mode: " << detector.modeName() << " ||| " |
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<< "FPS: " << fixed << setprecision(1) << (getTickFrequency() / (double)t); |
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putText(frame, buf.str(), Point(10, 30), FONT_HERSHEY_PLAIN, 2.0, Scalar(0, 0, 255), 2, LINE_AA); |
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} |
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else |
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for (vector<Rect>::iterator i = found.begin(); i != found.end(); ++i) |
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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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Rect &r = *i; |
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detector.adjustRect(r); |
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rectangle(frame, r.tl(), r.br(), cv::Scalar(0, 255, 0), 2); |
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} |
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imshow("People detector", frame); |
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vector<String>::const_iterator it_image = filenames.begin(); |
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for (;;) |
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// interact with user
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const char key = (char)waitKey(30); |
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if (key == 27 || key == 'q') // ESC
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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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cout << "Exit requested" << endl; |
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break; |
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} |
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else if (key == ' ') |
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{ |
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detector.toggleMode(); |
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} |
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} |
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return 0; |
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} |
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@ -0,0 +1,151 @@ |
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// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html
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#include <iostream> |
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#include <iomanip> |
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#include <vector> |
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#include "opencv2/core/ocl.hpp" |
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#include "opencv2/core/utility.hpp" |
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#include "opencv2/imgcodecs.hpp" |
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#include "opencv2/videoio.hpp" |
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#include "opencv2/highgui.hpp" |
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#include "opencv2/video.hpp" |
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using namespace std; |
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using namespace cv; |
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static Mat getVisibleFlow(InputArray flow) |
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{ |
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vector<UMat> flow_vec; |
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split(flow, flow_vec); |
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UMat magnitude, angle; |
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cartToPolar(flow_vec[0], flow_vec[1], magnitude, angle, true); |
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magnitude.convertTo(magnitude, CV_32F, 0.2); |
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vector<UMat> hsv_vec; |
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hsv_vec.push_back(angle); |
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hsv_vec.push_back(UMat::ones(angle.size(), angle.type())); |
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hsv_vec.push_back(magnitude); |
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UMat hsv; |
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merge(hsv_vec, hsv); |
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Mat img; |
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cvtColor(hsv, img, COLOR_HSV2BGR); |
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return img; |
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} |
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static Size fitSize(const Size & sz, const Size & bounds) |
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{ |
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CV_Assert(sz.area() > 0); |
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if (sz.width > bounds.width || sz.height > bounds.height) |
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{ |
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double scale = std::min((double)bounds.width / sz.width, (double)bounds.height / sz.height); |
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return Size(cvRound(sz.width * scale), cvRound(sz.height * scale)); |
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} |
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return sz; |
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} |
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int main(int argc, const char* argv[]) |
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{ |
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const char* keys = |
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"{ h help | | print help message }" |
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"{ c camera | 0 | capture video from camera (device index starting from 0) }" |
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"{ a algorithm | fb | algorithm (supported: 'fb', 'tvl')}" |
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"{ m cpu | | run without OpenCL }" |
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"{ v video | | use video as input }" |
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"{ o original | | use original frame size (do not resize to 640x480)}" |
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; |
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CommandLineParser parser(argc, argv, keys); |
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parser.about("This sample demonstrates using of dense optical flow algorithms."); |
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if (parser.has("help")) |
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{ |
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parser.printMessage(); |
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return 0; |
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} |
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int camera = parser.get<int>("camera"); |
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string algorithm = parser.get<string>("algorithm"); |
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bool useCPU = parser.has("cpu"); |
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string filename = parser.get<string>("video"); |
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bool useOriginalSize = parser.has("original"); |
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if (!parser.check()) |
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{ |
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parser.printErrors(); |
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return 1; |
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} |
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VideoCapture cap; |
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if(filename.empty()) |
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cap.open(camera); |
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else |
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cap.open(filename); |
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if (!cap.isOpened()) |
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{ |
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cout << "Can not open video stream: '" << (filename.empty() ? "<camera>" : filename) << "'" << endl; |
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return 2; |
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} |
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cv::Ptr<cv::DenseOpticalFlow> alg; |
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if (algorithm == "fb") |
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alg = cv::FarnebackOpticalFlow::create(); |
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else if (algorithm == "tvl") |
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alg = cv::DualTVL1OpticalFlow::create(); |
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else |
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{ |
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cout << "Invalid algorithm: " << algorithm << endl; |
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return 3; |
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} |
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ocl::setUseOpenCL(!useCPU); |
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cout << "Press 'm' to toggle CPU/GPU processing mode" << endl; |
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cout << "Press ESC or 'q' to exit" << endl; |
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UMat prevFrame, frame, input_frame, flow; |
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for(;;) |
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{ |
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if (!cap.read(input_frame) || input_frame.empty()) |
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{ |
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cout << "Finished reading: empty frame" << endl; |
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break; |
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} |
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Size small_size = fitSize(input_frame.size(), Size(640, 480)); |
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if (!useOriginalSize && small_size != input_frame.size()) |
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resize(input_frame, frame, small_size); |
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else |
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frame = input_frame; |
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cvtColor(frame, frame, COLOR_BGR2GRAY); |
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imshow("frame", frame); |
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if (!prevFrame.empty()) |
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{ |
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int64 t = getTickCount(); |
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alg->calc(prevFrame, frame, flow); |
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t = getTickCount() - t; |
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{ |
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Mat img = getVisibleFlow(flow); |
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ostringstream buf; |
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buf << "Algo: " << algorithm << " | " |
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<< "Mode: " << (useCPU ? "CPU" : "GPU") << " | " |
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<< "FPS: " << fixed << setprecision(1) << (getTickFrequency() / (double)t); |
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putText(img, buf.str(), Point(10, 30), FONT_HERSHEY_PLAIN, 2.0, Scalar(0, 0, 255), 2, LINE_AA); |
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imshow("Dense optical flow field", img); |
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} |
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} |
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frame.copyTo(prevFrame); |
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// interact with user
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const char key = (char)waitKey(30); |
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if (key == 27 || key == 'q') // ESC
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{ |
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cout << "Exit requested" << endl; |
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break; |
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} |
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else if (key == 'm') |
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{ |
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useCPU = !useCPU; |
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ocl::setUseOpenCL(!useCPU); |
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cout << "Set processing mode to: " << (useCPU ? "CPU" : "GPU") << endl; |
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} |
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} |
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return 0; |
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} |
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@ -1,233 +0,0 @@ |
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#include <iostream> |
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#include <vector> |
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#include <iomanip> |
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#include "opencv2/core/ocl.hpp" |
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#include "opencv2/core/utility.hpp" |
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#include "opencv2/imgcodecs.hpp" |
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#include "opencv2/videoio.hpp" |
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#include "opencv2/highgui.hpp" |
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#include "opencv2/video.hpp" |
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using namespace std; |
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using namespace cv; |
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typedef unsigned char uchar; |
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#define LOOP_NUM 10 |
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int64 work_begin = 0; |
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int64 work_end = 0; |
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static void workBegin() |
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{ |
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work_begin = getTickCount(); |
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} |
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static void workEnd() |
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{ |
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work_end += (getTickCount() - work_begin); |
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} |
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static double getTime() |
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{ |
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return work_end * 1000. / getTickFrequency(); |
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} |
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template <typename T> inline T clamp (T x, T a, T b) |
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{ |
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return ((x) > (a) ? ((x) < (b) ? (x) : (b)) : (a)); |
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} |
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template <typename T> inline T mapValue(T x, T a, T b, T c, T d) |
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{ |
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x = ::clamp(x, a, b); |
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return c + (d - c) * (x - a) / (b - a); |
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} |
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static void getFlowField(const Mat& u, const Mat& v, Mat& flowField) |
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{ |
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float maxDisplacement = 1.0f; |
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for (int i = 0; i < u.rows; ++i) |
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{ |
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const float* ptr_u = u.ptr<float>(i); |
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const float* ptr_v = v.ptr<float>(i); |
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for (int j = 0; j < u.cols; ++j) |
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{ |
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float d = max(fabsf(ptr_u[j]), fabsf(ptr_v[j])); |
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if (d > maxDisplacement) |
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maxDisplacement = d; |
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} |
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} |
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flowField.create(u.size(), CV_8UC4); |
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for (int i = 0; i < flowField.rows; ++i) |
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{ |
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const float* ptr_u = u.ptr<float>(i); |
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const float* ptr_v = v.ptr<float>(i); |
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Vec4b* row = flowField.ptr<Vec4b>(i); |
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for (int j = 0; j < flowField.cols; ++j) |
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{ |
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row[j][0] = 0; |
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row[j][1] = static_cast<unsigned char> (mapValue (-ptr_v[j], -maxDisplacement, maxDisplacement, 0.0f, 255.0f)); |
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row[j][2] = static_cast<unsigned char> (mapValue ( ptr_u[j], -maxDisplacement, maxDisplacement, 0.0f, 255.0f)); |
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row[j][3] = 255; |
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} |
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} |
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} |
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int main(int argc, const char* argv[]) |
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{ |
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const char* keys = |
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"{ h help | | print help message }" |
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"{ l left | | specify left image }" |
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"{ r right | | specify right image }" |
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"{ o output | tvl1_output.jpg | specify output save path }" |
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"{ c camera | 0 | enable camera capturing }" |
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"{ m cpu_mode | | run without OpenCL }" |
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"{ v video | | use video as input }"; |
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CommandLineParser cmd(argc, argv, keys); |
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if (cmd.has("help")) |
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{ |
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cout << "Usage: pyrlk_optical_flow [options]" << endl; |
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cout << "Available options:" << endl; |
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cmd.printMessage(); |
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return EXIT_SUCCESS; |
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} |
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string fname0 = cmd.get<string>("l"); |
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string fname1 = cmd.get<string>("r"); |
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string vdofile = cmd.get<string>("v"); |
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string outpath = cmd.get<string>("o"); |
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bool useCPU = cmd.get<bool>("m"); |
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bool useCamera = cmd.get<bool>("c"); |
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int inputName = cmd.get<int>("c"); |
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UMat frame0, frame1; |
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imread(fname0, cv::IMREAD_GRAYSCALE).copyTo(frame0); |
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imread(fname1, cv::IMREAD_GRAYSCALE).copyTo(frame1); |
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cv::Ptr<cv::DenseOpticalFlow> alg = cv::createOptFlow_DualTVL1(); |
||||
|
||||
UMat flow; |
||||
Mat show_flow; |
||||
vector<UMat> flow_vec; |
||||
if (frame0.empty() || frame1.empty()) |
||||
useCamera = true; |
||||
|
||||
if (useCamera) |
||||
{ |
||||
VideoCapture capture; |
||||
UMat frame, frameCopy; |
||||
UMat frame0Gray, frame1Gray; |
||||
UMat ptr0, ptr1; |
||||
|
||||
if(vdofile.empty()) |
||||
capture.open( inputName ); |
||||
else |
||||
capture.open(vdofile.c_str()); |
||||
|
||||
if(!capture.isOpened()) |
||||
{ |
||||
if(vdofile.empty()) |
||||
cout << "Capture from CAM " << inputName << " didn't work" << endl; |
||||
else |
||||
cout << "Capture from file " << vdofile << " failed" <<endl; |
||||
goto nocamera; |
||||
} |
||||
|
||||
cout << "In capture ..." << endl; |
||||
for(int i = 0;; i++) |
||||
{ |
||||
if( !capture.read(frame) ) |
||||
break; |
||||
|
||||
if (i == 0) |
||||
{ |
||||
frame.copyTo( frame0 ); |
||||
cvtColor(frame0, frame0Gray, COLOR_BGR2GRAY); |
||||
} |
||||
else |
||||
{ |
||||
if (i%2 == 1) |
||||
{ |
||||
frame.copyTo(frame1); |
||||
cvtColor(frame1, frame1Gray, COLOR_BGR2GRAY); |
||||
ptr0 = frame0Gray; |
||||
ptr1 = frame1Gray; |
||||
} |
||||
else |
||||
{ |
||||
frame.copyTo(frame0); |
||||
cvtColor(frame0, frame0Gray, COLOR_BGR2GRAY); |
||||
ptr0 = frame1Gray; |
||||
ptr1 = frame0Gray; |
||||
} |
||||
|
||||
alg->calc(ptr0, ptr1, flow); |
||||
split(flow, flow_vec); |
||||
|
||||
if (i%2 == 1) |
||||
frame1.copyTo(frameCopy); |
||||
else |
||||
frame0.copyTo(frameCopy); |
||||
getFlowField(flow_vec[0].getMat(ACCESS_READ), flow_vec[1].getMat(ACCESS_READ), show_flow); |
||||
imshow("tvl1 optical flow field", show_flow); |
||||
} |
||||
|
||||
char key = (char)waitKey(10); |
||||
if (key == 27) |
||||
break; |
||||
else if (key == 'm' || key == 'M') |
||||
{ |
||||
ocl::setUseOpenCL(!cv::ocl::useOpenCL()); |
||||
cout << "Switched to " << (ocl::useOpenCL() ? "OpenCL" : "CPU") << " mode\n"; |
||||
} |
||||
} |
||||
|
||||
capture.release(); |
||||
} |
||||
else |
||||
{ |
||||
nocamera: |
||||
if (cmd.has("cpu_mode")) |
||||
{ |
||||
ocl::setUseOpenCL(false); |
||||
std::cout << "OpenCL was disabled" << std::endl; |
||||
} |
||||
for(int i = 0; i <= LOOP_NUM; i ++) |
||||
{ |
||||
cout << "loop" << i << endl; |
||||
|
||||
if (i > 0) workBegin(); |
||||
|
||||
alg->calc(frame0, frame1, flow); |
||||
split(flow, flow_vec); |
||||
|
||||
if (i > 0 && i <= LOOP_NUM) |
||||
workEnd(); |
||||
|
||||
if (i == LOOP_NUM) |
||||
{ |
||||
if (useCPU) |
||||
cout << "average CPU time (noCamera) : "; |
||||
else |
||||
cout << "average GPU time (noCamera) : "; |
||||
cout << getTime() / LOOP_NUM << " ms" << endl; |
||||
|
||||
getFlowField(flow_vec[0].getMat(ACCESS_READ), flow_vec[1].getMat(ACCESS_READ), show_flow); |
||||
imshow("PyrLK [Sparse]", show_flow); |
||||
imwrite(outpath, show_flow); |
||||
} |
||||
} |
||||
} |
||||
|
||||
waitKey(); |
||||
|
||||
return EXIT_SUCCESS; |
||||
} |
||||
Loading…
Reference in new issue