opencv/samples/cpp/bgfg_segm.cpp

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// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html
#include "opencv2/core.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/video.hpp"
#include "opencv2/videoio.hpp"
#include "opencv2/highgui.hpp"
#include <iostream>
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using namespace std;
using namespace cv;
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int main(int argc, const char** argv)
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{
const String keys = "{c camera | 0 | use video stream from camera (device index starting from 0) }"
"{fn file_name | | use video file as input }"
"{m method | mog2 | method: background subtraction algorithm ('knn', 'mog2')}"
"{h help | | show help message}";
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CommandLineParser parser(argc, argv, keys);
parser.about("This sample demonstrates background segmentation.");
if (parser.has("help"))
{
parser.printMessage();
return 0;
}
int camera = parser.get<int>("camera");
String file = parser.get<String>("file_name");
String method = parser.get<String>("method");
if (!parser.check())
{
parser.printErrors();
return 1;
}
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VideoCapture cap;
if (file.empty())
cap.open(camera);
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else
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{
file = samples::findFileOrKeep(file); // ignore gstreamer pipelines
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cap.open(file.c_str());
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}
if (!cap.isOpened())
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{
cout << "Can not open video stream: '" << (file.empty() ? "<camera>" : file) << "'" << endl;
return 2;
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}
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Ptr<BackgroundSubtractor> model;
if (method == "knn")
model = createBackgroundSubtractorKNN();
else if (method == "mog2")
model = createBackgroundSubtractorMOG2();
if (!model)
{
cout << "Can not create background model using provided method: '" << method << "'" << endl;
return 3;
}
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cout << "Press <space> to toggle background model update" << endl;
cout << "Press 's' to toggle foreground mask smoothing" << endl;
cout << "Press ESC or 'q' to exit" << endl;
bool doUpdateModel = true;
bool doSmoothMask = false;
Mat inputFrame, frame, foregroundMask, foreground, background;
for (;;)
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{
// prepare input frame
cap >> inputFrame;
if (inputFrame.empty())
{
cout << "Finished reading: empty frame" << endl;
break;
}
const Size scaledSize(640, 640 * inputFrame.rows / inputFrame.cols);
resize(inputFrame, frame, scaledSize, 0, 0, INTER_LINEAR);
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// pass the frame to background model
model->apply(frame, foregroundMask, doUpdateModel ? -1 : 0);
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// show processed frame
imshow("image", frame);
// show foreground image and mask (with optional smoothing)
if (doSmoothMask)
{
GaussianBlur(foregroundMask, foregroundMask, Size(11, 11), 3.5, 3.5);
threshold(foregroundMask, foregroundMask, 10, 255, THRESH_BINARY);
}
if (foreground.empty())
foreground.create(scaledSize, frame.type());
foreground = Scalar::all(0);
frame.copyTo(foreground, foregroundMask);
imshow("foreground mask", foregroundMask);
imshow("foreground image", foreground);
// show background image
model->getBackgroundImage(background);
if (!background.empty())
imshow("mean background image", background );
// interact with user
const char key = (char)waitKey(30);
if (key == 27 || key == 'q') // ESC
{
cout << "Exit requested" << endl;
break;
}
else if (key == ' ')
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{
doUpdateModel = !doUpdateModel;
cout << "Toggle background update: " << (doUpdateModel ? "ON" : "OFF") << endl;
}
else if (key == 's')
{
doSmoothMask = !doSmoothMask;
cout << "Toggle foreground mask smoothing: " << (doSmoothMask ? "ON" : "OFF") << endl;
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}
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}
return 0;
}