OpenCV_4.2.0/opencv_contrib-4.2.0/modules/ximgproc/samples/live_demo.cpp

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C++

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#include <opencv2/core.hpp>
#include <opencv2/core/utility.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/ximgproc.hpp>
using namespace cv;
using namespace cv::ximgproc;
#include <iostream>
using namespace std;
typedef void(*FilteringOperation)(const Mat& src, Mat& dst);
//current mode (filtering operation example)
FilteringOperation g_filterOp = NULL;
//list of filtering operations
void filterDoNothing(const Mat& frame, Mat& dst);
void filterBlurring(const Mat& frame, Mat& dst);
void filterStylize(const Mat& frame, Mat& dst);
void filterDetailEnhancement(const Mat& frame8u, Mat& dst);
//common sliders for every mode
int g_sigmaColor = 25;
int g_sigmaSpatial = 10;
//for Stylizing mode
int g_edgesGamma = 100;
//for Details Enhancement mode
int g_contrastBase = 100;
int g_detailsLevel = 100;
int g_numberOfCPUs = cv::getNumberOfCPUs();
//We will use two callbacks to change parameters
void changeModeCallback(int state, void *filter);
void changeNumberOfCpuCallback(int count, void*);
void splitScreen(const Mat& rawFrame, Mat& outputFrame, Mat& srcFrame, Mat& processedFrame);
//trivial filter
void filterDoNothing(const Mat& frame, Mat& dst)
{
frame.copyTo(dst);
}
//simple edge-aware blurring
void filterBlurring(const Mat& frame, Mat& dst)
{
dtFilter(frame, frame, dst, g_sigmaSpatial, g_sigmaColor, DTF_RF);
}
//stylizing filter
void filterStylize(const Mat& frame, Mat& dst)
{
//blur frame
Mat filtered;
dtFilter(frame, frame, filtered, g_sigmaSpatial, g_sigmaColor, DTF_NC);
//compute grayscale blurred frame
Mat filteredGray;
cvtColor(filtered, filteredGray, COLOR_BGR2GRAY);
//find gradients of blurred image
Mat gradX, gradY;
Sobel(filteredGray, gradX, CV_32F, 1, 0, 3, 1.0/255);
Sobel(filteredGray, gradY, CV_32F, 0, 1, 3, 1.0/255);
//compute magnitude of gradient and fit it accordingly the gamma parameter
Mat gradMagnitude;
magnitude(gradX, gradY, gradMagnitude);
cv::pow(gradMagnitude, g_edgesGamma/100.0, gradMagnitude);
//multiply a blurred frame to the value inversely proportional to the magnitude
Mat multiplier = 1.0/(1.0 + gradMagnitude);
cvtColor(multiplier, multiplier, COLOR_GRAY2BGR);
multiply(filtered, multiplier, dst, 1, dst.type());
}
void filterDetailEnhancement(const Mat& frame8u, Mat& dst)
{
Mat frame;
frame8u.convertTo(frame, CV_32F, 1.0/255);
//Decompose image to 3 Lab channels
Mat frameLab, frameLabCn[3];
cvtColor(frame, frameLab, COLOR_BGR2Lab);
split(frameLab, frameLabCn);
//Generate progressively smoother versions of the lightness channel
Mat layer0 = frameLabCn[0]; //first channel is original lightness
Mat layer1, layer2;
dtFilter(layer0, layer0, layer1, g_sigmaSpatial, g_sigmaColor, DTF_IC);
dtFilter(layer1, layer1, layer2, 2*g_sigmaSpatial, g_sigmaColor, DTF_IC);
//Compute detail layers
Mat detailLayer1 = layer0 - layer1;
Mat detailLayer2 = layer1 - layer2;
double cBase = g_contrastBase / 100.0;
double cDetails1 = g_detailsLevel / 100.0;
double cDetails2 = 2.0 - g_detailsLevel / 100.0;
//Generate lightness
double meanLigtness = mean(frameLabCn[0])[0];
frameLabCn[0] = cBase*(layer2 - meanLigtness) + meanLigtness; //fit contrast of base (most blurred) layer
frameLabCn[0] += cDetails1*detailLayer1; //add weighted sum of detail layers to new lightness
frameLabCn[0] += cDetails2*detailLayer2; //
//Update new lightness
merge(frameLabCn, 3, frameLab);
cvtColor(frameLab, frame, COLOR_Lab2BGR);
frame.convertTo(dst, CV_8U, 255);
}
void changeModeCallback(int state, void *filter)
{
if (state == 1)
g_filterOp = (FilteringOperation) filter;
}
void changeNumberOfCpuCallback(int count, void*)
{
count = std::max(1, count);
g_numberOfCPUs = count;
}
//divide screen on two parts: srcFrame and processed Frame
void splitScreen(const Mat& rawFrame, Mat& outputFrame, Mat& srcFrame, Mat& processedFrame)
{
int h = rawFrame.rows;
int w = rawFrame.cols;
int cn = rawFrame.channels();
outputFrame.create(h, 2 * w, CV_MAKE_TYPE(CV_8U, cn));
srcFrame = outputFrame(Range::all(), Range(0, w));
processedFrame = outputFrame(Range::all(), Range(w, 2 * w));
rawFrame.convertTo(srcFrame, srcFrame.type());
}
int main()
{
VideoCapture cap(0);
if (!cap.isOpened())
{
cerr << "Capture device was not found" << endl;
return -1;
}
namedWindow("Demo");
displayOverlay("Demo", "Press Ctrl+P to show property window", 5000);
//Thread trackbar
createTrackbar("Threads", String(), &g_numberOfCPUs, cv::getNumberOfCPUs(), changeNumberOfCpuCallback);
//Buttons to choose different modes
createButton("Mode Details Enhancement", changeModeCallback, (void*)filterDetailEnhancement, QT_RADIOBOX, true);
createButton("Mode Stylizing", changeModeCallback, (void*)filterStylize, QT_RADIOBOX, false);
createButton("Mode Blurring", changeModeCallback, (void*)filterBlurring, QT_RADIOBOX, false);
createButton("Mode DoNothing", changeModeCallback, (void*)filterDoNothing, QT_RADIOBOX, false);
//sliders for Details Enhancement mode
g_filterOp = filterDetailEnhancement; //set Details Enhancement as default filter
createTrackbar("Detail contrast", String(), &g_contrastBase, 200);
createTrackbar("Detail level" , String(), &g_detailsLevel, 200);
//sliders for Stylizing mode
createTrackbar("Style gamma", String(), &g_edgesGamma, 300);
//sliders for every mode
createTrackbar("Sigma Spatial", String(), &g_sigmaSpatial, 200);
createTrackbar("Sigma Color" , String(), &g_sigmaColor, 200);
Mat rawFrame, outputFrame;
Mat srcFrame, processedFrame;
for (;;)
{
do
{
cap >> rawFrame;
} while (rawFrame.empty());
cv::setNumThreads(g_numberOfCPUs); //speedup filtering
splitScreen(rawFrame, outputFrame, srcFrame, processedFrame);
g_filterOp(srcFrame, processedFrame);
imshow("Demo", outputFrame);
if (waitKey(1) == 27) break;
}
return 0;
}