vendor: OpenCV 5.0.0 snapshot at 755e50675d97db9b7d449d8bd6b09888646f6c6e
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/*
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* By downloading, copying, installing or using the software you agree to this license.
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* If you do not agree to this license, do not download, install,
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* copy or use the software.
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*
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*
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* License Agreement
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* For Open Source Computer Vision Library
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* (3 - clause BSD License)
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*
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* Redistribution and use in source and binary forms, with or without modification,
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* are permitted provided that the following conditions are met :
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*
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* * Redistributions of source code must retain the above copyright notice,
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* this list of conditions and the following disclaimer.
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*
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* * Redistributions in binary form must reproduce the above copyright notice,
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* this list of conditions and the following disclaimer in the documentation
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* and / or other materials provided with the distribution.
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*
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* * Neither the names of the copyright holders nor the names of the contributors
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* may be used to endorse or promote products derived from this software
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* without specific prior written permission.
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*
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* This software is provided by the copyright holders and contributors "as is" and
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* any express or implied warranties, including, but not limited to, the implied
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* warranties of merchantability and fitness for a particular purpose are disclaimed.
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* In no event shall copyright holders or contributors be liable for any direct,
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* indirect, incidental, special, exemplary, or consequential damages
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* (including, but not limited to, procurement of substitute goods or services;
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* loss of use, data, or profits; or business interruption) however caused
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* and on any theory of liability, whether in contract, strict liability,
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* or tort(including negligence or otherwise) arising in any way out of
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* the use of this software, even if advised of the possibility of such damage.
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*/
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#include <opencv2/core.hpp>
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#include <opencv2/core/utility.hpp>
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#include <opencv2/highgui.hpp>
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#include <opencv2/imgproc.hpp>
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#include <opencv2/ximgproc.hpp>
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using namespace cv;
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using namespace cv::ximgproc;
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#include <iostream>
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using namespace std;
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typedef void(*FilteringOperation)(const Mat& src, Mat& dst);
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//current mode (filtering operation example)
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FilteringOperation g_filterOp = NULL;
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//list of filtering operations
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void filterDoNothing(const Mat& frame, Mat& dst);
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void filterBlurring(const Mat& frame, Mat& dst);
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void filterStylize(const Mat& frame, Mat& dst);
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void filterDetailEnhancement(const Mat& frame8u, Mat& dst);
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//common sliders for every mode
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int g_sigmaColor = 25;
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int g_sigmaSpatial = 10;
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//for Stylizing mode
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int g_edgesGamma = 100;
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//for Details Enhancement mode
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int g_contrastBase = 100;
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int g_detailsLevel = 100;
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int g_numberOfCPUs = cv::getNumberOfCPUs();
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//We will use two callbacks to change parameters
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void changeModeCallback(int state, void *filter);
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void changeNumberOfCpuCallback(int count, void*);
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void splitScreen(const Mat& rawFrame, Mat& outputFrame, Mat& srcFrame, Mat& processedFrame);
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//trivial filter
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void filterDoNothing(const Mat& frame, Mat& dst)
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{
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frame.copyTo(dst);
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}
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//simple edge-aware blurring
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void filterBlurring(const Mat& frame, Mat& dst)
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{
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dtFilter(frame, frame, dst, g_sigmaSpatial, g_sigmaColor, DTF_RF);
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}
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//stylizing filter
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void filterStylize(const Mat& frame, Mat& dst)
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{
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//blur frame
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Mat filtered;
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dtFilter(frame, frame, filtered, g_sigmaSpatial, g_sigmaColor, DTF_NC);
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//compute grayscale blurred frame
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Mat filteredGray;
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cvtColor(filtered, filteredGray, COLOR_BGR2GRAY);
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//find gradients of blurred image
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Mat gradX, gradY;
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Sobel(filteredGray, gradX, CV_32F, 1, 0, 3, 1.0/255);
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Sobel(filteredGray, gradY, CV_32F, 0, 1, 3, 1.0/255);
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//compute magnitude of gradient and fit it accordingly the gamma parameter
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Mat gradMagnitude;
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magnitude(gradX, gradY, gradMagnitude);
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cv::pow(gradMagnitude, g_edgesGamma/100.0, gradMagnitude);
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//multiply a blurred frame to the value inversely proportional to the magnitude
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Mat multiplier = 1.0/(1.0 + gradMagnitude);
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cvtColor(multiplier, multiplier, COLOR_GRAY2BGR);
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multiply(filtered, multiplier, dst, 1, dst.type());
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}
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void filterDetailEnhancement(const Mat& frame8u, Mat& dst)
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{
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Mat frame;
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frame8u.convertTo(frame, CV_32F, 1.0/255);
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//Decompose image to 3 Lab channels
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Mat frameLab, frameLabCn[3];
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cvtColor(frame, frameLab, COLOR_BGR2Lab);
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split(frameLab, frameLabCn);
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//Generate progressively smoother versions of the lightness channel
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Mat layer0 = frameLabCn[0]; //first channel is original lightness
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Mat layer1, layer2;
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dtFilter(layer0, layer0, layer1, g_sigmaSpatial, g_sigmaColor, DTF_IC);
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dtFilter(layer1, layer1, layer2, 2*g_sigmaSpatial, g_sigmaColor, DTF_IC);
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//Compute detail layers
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Mat detailLayer1 = layer0 - layer1;
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Mat detailLayer2 = layer1 - layer2;
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double cBase = g_contrastBase / 100.0;
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double cDetails1 = g_detailsLevel / 100.0;
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double cDetails2 = 2.0 - g_detailsLevel / 100.0;
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//Generate lightness
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double meanLigtness = mean(frameLabCn[0])[0];
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frameLabCn[0] = cBase*(layer2 - meanLigtness) + meanLigtness; //fit contrast of base (most blurred) layer
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frameLabCn[0] += cDetails1*detailLayer1; //add weighted sum of detail layers to new lightness
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frameLabCn[0] += cDetails2*detailLayer2; //
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//Update new lightness
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merge(frameLabCn, 3, frameLab);
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cvtColor(frameLab, frame, COLOR_Lab2BGR);
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frame.convertTo(dst, CV_8U, 255);
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}
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void changeModeCallback(int state, void *filter)
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{
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if (state == 1)
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g_filterOp = (FilteringOperation) filter;
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}
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void changeNumberOfCpuCallback(int count, void*)
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{
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count = std::max(1, count);
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g_numberOfCPUs = count;
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}
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//divide screen on two parts: srcFrame and processed Frame
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void splitScreen(const Mat& rawFrame, Mat& outputFrame, Mat& srcFrame, Mat& processedFrame)
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{
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int h = rawFrame.rows;
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int w = rawFrame.cols;
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int cn = rawFrame.channels();
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outputFrame.create(h, 2 * w, CV_MAKE_TYPE(CV_8U, cn));
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srcFrame = outputFrame(Range::all(), Range(0, w));
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processedFrame = outputFrame(Range::all(), Range(w, 2 * w));
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rawFrame.convertTo(srcFrame, srcFrame.type());
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}
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int main()
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{
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VideoCapture cap(0);
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if (!cap.isOpened())
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{
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cerr << "Capture device was not found" << endl;
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return -1;
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}
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namedWindow("Demo");
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displayOverlay("Demo", "Press Ctrl+P to show property window", 5000);
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//Thread trackbar
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createTrackbar("Threads", String(), &g_numberOfCPUs, cv::getNumberOfCPUs(), changeNumberOfCpuCallback);
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//Buttons to choose different modes
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createButton("Mode Details Enhancement", changeModeCallback, (void*)filterDetailEnhancement, QT_RADIOBOX, true);
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createButton("Mode Stylizing", changeModeCallback, (void*)filterStylize, QT_RADIOBOX, false);
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createButton("Mode Blurring", changeModeCallback, (void*)filterBlurring, QT_RADIOBOX, false);
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createButton("Mode DoNothing", changeModeCallback, (void*)filterDoNothing, QT_RADIOBOX, false);
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//sliders for Details Enhancement mode
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g_filterOp = filterDetailEnhancement; //set Details Enhancement as default filter
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createTrackbar("Detail contrast", String(), &g_contrastBase, 200);
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createTrackbar("Detail level" , String(), &g_detailsLevel, 200);
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//sliders for Stylizing mode
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createTrackbar("Style gamma", String(), &g_edgesGamma, 300);
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//sliders for every mode
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createTrackbar("Sigma Spatial", String(), &g_sigmaSpatial, 200);
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createTrackbar("Sigma Color" , String(), &g_sigmaColor, 200);
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Mat rawFrame, outputFrame;
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Mat srcFrame, processedFrame;
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for (;;)
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{
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do
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{
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cap >> rawFrame;
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} while (rawFrame.empty());
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cv::setNumThreads(g_numberOfCPUs); //speedup filtering
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splitScreen(rawFrame, outputFrame, srcFrame, processedFrame);
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g_filterOp(srcFrame, processedFrame);
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imshow("Demo", outputFrame);
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if (waitKey(1) == 27) break;
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}
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return 0;
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}
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