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1ae02c0cc4
- bgfg_segm - peopledetect - opencv_version - dnn/colorization - tapi/opencl_custom_kernel - tapi/dense_optical_flow (renamed tvl1_optical_flow)
122 lines
3.9 KiB
C++
122 lines
3.9 KiB
C++
// 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/core.hpp"
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#include "opencv2/imgproc.hpp"
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#include "opencv2/video.hpp"
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#include "opencv2/videoio.hpp"
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#include "opencv2/highgui.hpp"
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#include <iostream>
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using namespace std;
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using namespace cv;
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int main(int argc, const char** argv)
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{
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const String keys = "{c camera | 0 | use video stream from camera (device index starting from 0) }"
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"{fn file_name | | use video file as input }"
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"{m method | mog2 | method: background subtraction algorithm ('knn', 'mog2')}"
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"{h help | | show help message}";
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CommandLineParser parser(argc, argv, keys);
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parser.about("This sample demonstrates background segmentation.");
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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 file = parser.get<String>("file_name");
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String method = parser.get<String>("method");
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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 (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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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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Ptr<BackgroundSubtractor> model;
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if (method == "knn")
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model = createBackgroundSubtractorKNN();
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else if (method == "mog2")
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model = createBackgroundSubtractorMOG2();
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if (!model)
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{
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cout << "Can not create background model using provided method: '" << method << "'" << endl;
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return 3;
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}
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cout << "Press <space> to toggle background model update" << endl;
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cout << "Press 's' to toggle foreground mask smoothing" << endl;
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cout << "Press ESC or 'q' to exit" << endl;
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bool doUpdateModel = true;
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bool doSmoothMask = false;
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Mat inputFrame, frame, foregroundMask, foreground, background;
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for (;;)
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{
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// prepare input frame
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cap >> inputFrame;
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if (inputFrame.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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const Size scaledSize(640, 640 * inputFrame.rows / inputFrame.cols);
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resize(inputFrame, frame, scaledSize, 0, 0, INTER_LINEAR);
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// pass the frame to background model
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model->apply(frame, foregroundMask, doUpdateModel ? -1 : 0);
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// show processed frame
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imshow("image", frame);
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// show foreground image and mask (with optional smoothing)
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if (doSmoothMask)
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{
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GaussianBlur(foregroundMask, foregroundMask, Size(11, 11), 3.5, 3.5);
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threshold(foregroundMask, foregroundMask, 10, 255, THRESH_BINARY);
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}
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if (foreground.empty())
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foreground.create(scaledSize, frame.type());
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foreground = Scalar::all(0);
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frame.copyTo(foreground, foregroundMask);
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imshow("foreground mask", foregroundMask);
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imshow("foreground image", foreground);
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// show background image
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model->getBackgroundImage(background);
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if (!background.empty())
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imshow("mean background image", background );
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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 == ' ')
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{
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doUpdateModel = !doUpdateModel;
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cout << "Toggle background update: " << (doUpdateModel ? "ON" : "OFF") << endl;
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}
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else if (key == 's')
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{
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doSmoothMask = !doSmoothMask;
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cout << "Toggle foreground mask smoothing: " << (doSmoothMask ? "ON" : "OFF") << endl;
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}
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}
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return 0;
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}
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