125 lines
3.7 KiB
C++
125 lines
3.7 KiB
C++
//C++
|
|
|
|
#include <iostream>
|
|
//include those opencv2 files in our program
|
|
#include "opencv2/opencv.hpp"
|
|
#include "opencv2/videoio.hpp"
|
|
#include "opencv2/highgui.hpp"
|
|
|
|
int FPS=30; //FPS variable. FPS is the framerate of your video, aka your recording device's
|
|
int DISCARD_DURATION=5;
|
|
bool isDiscardData=true;
|
|
int countDiscard=0;
|
|
|
|
bool isBufferFull = false; //buffer variables to initialise before main();
|
|
int sampleIdBuffer = 0;
|
|
int BUFFER_DURATION= 5;
|
|
|
|
int main(){
|
|
//Print "PPG algorithm" to terminal
|
|
//Note to self: std::endl; returns to line in terminal; use it everytime when done printing something.
|
|
std::cout << "PPG algorithm"<< std::endl;
|
|
|
|
cv::VideoCapture cap;
|
|
cap.open(0);
|
|
if (!cap.isOpened())
|
|
{
|
|
//Check if we can access the camera
|
|
std::cerr<<"[ERROR] unable to open camera!"<<std::endl;
|
|
return -2;
|
|
}
|
|
|
|
cv::CascadeClassifier faceDetector;
|
|
if(!faceDetector.load("./haarcascade_frontalface_alt.xml"))//Testing to see if cascade_frontalface.xml is available (necessary for the program to work)
|
|
{
|
|
std::cerr<<"[ERROR] Unable to load face cascade"<<std::endl;
|
|
return -1;
|
|
};
|
|
|
|
while (true)
|
|
{
|
|
if(isDiscardData) //This function delays the beginning of the analysis of the data to avoid processing frames taken during white balancing.
|
|
{
|
|
countDiscard++;
|
|
if (countDiscard == DISCARD_DURATION*FPS)
|
|
{
|
|
isDiscardData=false;
|
|
}
|
|
}
|
|
else
|
|
{
|
|
//Create a matrix to store the image from the cam
|
|
cv::Mat frame;
|
|
//Wait for a new frame from camera and store it into "frame"
|
|
cap.read(frame);
|
|
|
|
//Check if we succeeded
|
|
if (frame.empty()) //If the camera records a blank frame, returns an error.
|
|
{
|
|
std::cerr<<"[ERROR] Blank frame grabbed"<<std::endl;
|
|
break;
|
|
}
|
|
cv::imshow("Color", frame); //shows the colored frame
|
|
if (cv::waitKey(1000.0/FPS)>=0) //Stops after 1000/FPS frames
|
|
{
|
|
break;
|
|
}
|
|
|
|
cv::Mat frame_gray;
|
|
cv::cvtColor(frame, frame_gray, cv::COLOR_BGR2GRAY);
|
|
cv::imshow("Gray", frame_gray); //Shows frame in greyscale
|
|
std::vector<cv::Rect> faceRectangles;
|
|
faceDetector.detectMultiScale(frame_gray, faceRectangles, 1.1, 3, 0, cv::Size(20,20)); //Detects face
|
|
|
|
cv::Rect foreheadROI; //create a forehead ROI equal to the face ROI slightly moved upward.
|
|
foreheadROI = faceRectangles[0];
|
|
foreheadROI.height *= 0.3;
|
|
|
|
cv::Mat frame_forehead = frame(foreheadROI);
|
|
cv::Scalar avg_forehead = mean(frame_forehead); //calculates mean of object frame_forehead
|
|
|
|
//Buffer of average value for the green channel over the forehead ROI
|
|
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;
|
|
}
|
|
}
|
|
|
|
//Normalisation of our signal
|
|
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])
|
|
}
|
|
|
|
//Display normalised signal
|
|
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;
|
|
}
|
|
|
|
}
|
|
}
|
|
}
|
|
|