74 lines
2.0 KiB
C++
74 lines
2.0 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;
|
|
|
|
|
|
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
|
|
}
|
|
}
|
|
}
|
|
|