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Author SHA1 Message Date
Thomas PÉRIN 0f0fc3f502 Final version 2023-03-01 23:35:58 +01:00
Thomas PÉRIN d90d3ae2b4 Lab1 Progress, begining of calculations 2023-02-24 12:06:11 +01:00
Thomas PÉRIN f76e338c9f Average Green Value Found in the ROI 2023-02-24 11:18:10 +01:00
Thomas PÉRIN e9ae38eae7 ROI corrected 2023-02-24 11:10:13 +01:00
1 changed files with 88 additions and 15 deletions

101
ppg.cpp
View File

@ -2,22 +2,38 @@
#include "opencv2/videoio.hpp"
#include "opencv2/highgui.hpp"
#include <iostream>
const int FPS = 30;
const int FPS = 15;
bool isDiscardData = true;
int countDiscard = 0;
const int DISCARD_DURATION = 5;
const int BUFFER_DURATION = 30 ;
const int I = 1;
bool isBufferFull = false;
int sampleIdBuffer = 0;
std::vector<double> greenFFTModule;
template <typename T>
cv::Mat plotGraph(std::vector<T>& vals, int YRange[2])
{
auto it = minmax_element(vals.begin(), vals.end());
float scale = 1./ceil(*it.second - *it.first);
float bias = *it.first;
int rows = YRange[1] - YRange[0] + 1;
cv::Mat image = 255*cv::Mat::ones( rows, vals.size(), CV_8UC3 );
image.setTo(255);
for (int i = 0; i < (int)vals.size()-1; i++)
{
cv::line(image, cv::Point(i, rows - 1 - (vals[i] - bias)*scale*YRange[1]), cv::Point(i+1, rows - 1 - (vals[i+1] - bias)*scale*YRange[1]), cv::Scalar(255, 0, 0), 1);
}
return image;
}
int main()
{
cv::VideoCapture cap;
cap.open(0);
if (!cap.isOpened())
{
std::cerr << "[ERROR] Unable to open camera!" << std::endl;
return -2;
}
//If Haard Cascade not found: error
cv::CascadeClassifier faceDetector;
if( !faceDetector.load("./haarcascade_frontalface_alt.xml"))
@ -25,6 +41,12 @@ int main()
std::cerr << "[ERROR] Unable to load face cascade" << std::endl;
return -1;
};
cv::Rect foreheadROI;
if (!cap.isOpened())
{
std::cerr << "[ERROR] Unable to open camera!" << std::endl;
return -2;
}
while (true)
{
@ -49,18 +71,69 @@ int main()
//Draw Rectangle around the face
std::vector<cv::Rect> faceRectangles;
faceDetector.detectMultiScale(frame, faceRectangles, 1.1, 3, 0,
cv::Size(20, 20));
cv::rectangle(frame, faceRectangles[0], cv::Scalar(0, 0, 255), 1, 1, 0);
//Reduce to ROI
cv::Rect foreheadROI;
faceDetector.detectMultiScale(frame, faceRectangles, 1.1, 3, 0,cv::Size(20, 20));
if (faceRectangles.size() > 0)
{
foreheadROI = faceRectangles[0];
foreheadROI.height *= 0.5;
foreheadROI.height *= 0.3;
cv::rectangle(frame, faceRectangles[0], cv::Scalar(0, 0, 255), 1, 1, 0);
cv::rectangle(frame, foreheadROI, cv::Scalar(255, 0, 0), 1, 1, 0);
cv::Mat frame_forehead = frame(foreheadROI);
cv::Scalar avg_forehead = mean(frame_forehead);
//
cv::Mat greenSignal(1, FPS*BUFFER_DURATION, CV_64F);
if (!isBufferFull)
{
greenSignal.at<double>(0, sampleIdBuffer) = avg_forehead[1] ;
sampleIdBuffer++;
if (sampleIdBuffer == FPS*BUFFER_DURATION)
{
isBufferFull = true;
}
}
else
{
std::vector<double> greenSignalNormalized;
cv::Scalar mean, stddev;
cv::meanStdDev(greenSignal, mean, stddev);
for (int l_sample=0; l_sample < FPS*BUFFER_DURATION; l_sample++)
{
greenSignalNormalized.push_back((greenSignal.at<double>(0, l_sample) - mean[0])/stddev[0]);
}
int range[2] = {0, (int)(FPS*BUFFER_DURATION)};
cv::Mat greenFFT;
///
cv::dft(greenSignalNormalized,greenFFT,cv::DFT_ROWS|cv::DFT_COMPLEX_OUTPUT);
cv::Mat planes[] = {cv::Mat::zeros(greenSignalNormalized.size(),1, CV_64F),
cv::Mat::zeros(greenSignalNormalized.size(),1, CV_64F)};
cv::split(greenFFT, planes); //planes[0] = Re(DFT(I),
//planes[1] = Im(DFT(I))
greenFFTModule.clear();
for (int l=0; l < planes[1].cols; l++)
{
double moduleFFT = pow(planes[1].at<double>(0,l),2) + pow(planes[0].at<double>(0,l),2);
greenFFTModule.push_back(sqrt(moduleFFT));
}
// display green FFT
cv::imshow("FFT module green", plotGraph(greenFFTModule, range));
}
}
cv::imshow("Your Face PLS", frame);
if (cv::waitKey(1000.0/FPS) >= 0)
break;
}
}
return 0;
}