ppg.cpp

makefile

@@ -1 +1,7 @@
-The makeFile
+all: ppg
+	g++ ppg.o -o ppg.exe -L/usr/lib/x86_64-linux-gnu/ -lopencv_stitching -lopencv_aruco -lopencv_bgsegm -lopencv_bioinspired -lopencv_ccalib -lopencv_dnn_objdetect -lopencv_dnn_superres -lopencv_dpm -lopencv_highgui -lopencv_face -lopencv_freetype -lopencv_fuzzy -lopencv_hdf -lopencv_hfs -lopencv_img_hash -lopencv_line_descriptor -lopencv_quality -lopencv_reg -lopencv_rgbd -lopencv_saliency -lopencv_shape -lopencv_stereo -lopencv_structured_light -lopencv_phase_unwrapping -lopencv_superres -lopencv_optflow -lopencv_surface_matching -lopencv_tracking -lopencv_datasets -lopencv_text -lopencv_dnn -lopencv_plot -lopencv_ml -lopencv_videostab -lopencv_videoio -lopencv_viz -lopencv_ximgproc -lopencv_video -lopencv_xobjdetect -lopencv_objdetect -lopencv_calib3d -lopencv_imgcodecs -lopencv_features2d -lopencv_flann -lopencv_xphoto -lopencv_photo -lopencv_imgproc -lopencv_core
+ppg: ppg.cpp
+	g++ -c ppg.cpp -I/usr/include/opencv4
+clean:
+	rm *.o
+	rm *.exe

ppg.cpp

@@ -1 +1,156 @@
 //PPG Algorithm
+//Author: Adrien COMBE
+//Date: 24/02/2023
+
+#include <iostream>
+#include "opencv2/opencv.hpp"
+#include "opencv2/core.hpp"
+#include "opencv2/videoio.hpp"
+#include "opencv2/highgui.hpp"
+#include "opencv2/objdetect.hpp"
+
+
+bool isDiscardData = true;
+int DISCARD_DURATION = 5;
+int BUFFER_DURATION = 15;
+int countDiscard = 0;
+int FPS=20;
+
+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()
+{
+	std::cout <<"PPG algorithm"<<std::endl;
+	cv::VideoCapture cap;
+	cap.open(0);
+	if (!cap.isOpened())
+	{
+		std::cerr << "[ERROR] Unable to open camera!" << std::endl;
+		return -2;
+	}
+	
+	cv::CascadeClassifier faceDetector;
+	if( !faceDetector.load("./haarcascade_frontalface_alt.xml"))
+	{
+		std::cerr << "[ERROR] Unable to load face cascade" << std::endl;
+		return -1;
+	}
+	
+	std::vector<cv::Rect> faceRectangles;
+	bool isBufferFull = false;
+	int sampleIdBuffer = 0;
+	cv::Mat greenSignal(1, FPS*BUFFER_DURATION, CV_64F);
+	
+	while (true)
+	{
+		// create a matrix to store the image from the cam
+		cv::Mat frame;
+		cv::Mat frame_grey;
+		//cv::Mat frame;
+		// wait for a new frame from camera and store it into 'frame'
+		cap.read(frame);
+		if (frame.empty())
+		{
+			std::cerr << "[ERROR] blank frame grabbed" << std::endl;
+			break;
+		}
+		if (isDiscardData)
+		{
+			countDiscard++;
+			if (countDiscard == DISCARD_DURATION*FPS)
+				isDiscardData = false;
+		}
+		else
+		{
+			if (faceRectangles.size()==0)
+			{
+				// convert to grayscale
+				cv::cvtColor(frame, frame_grey, cv::COLOR_BGR2GRAY);
+				faceDetector.detectMultiScale(frame_grey, faceRectangles, 1.1, 3, 0,
+				cv::Size(20, 20));
+			}
+			else
+			{
+				cv::rectangle(frame, faceRectangles[0], cv::Scalar(0, 0, 255), 1, 1, 0);
+				cv::Rect foreheadROI;
+				foreheadROI = faceRectangles[0];
+				foreheadROI.height *= 0.3;
+				cv::Mat frame_forehead = frame(foreheadROI);
+				cv::Scalar avg_forehead = mean(frame_forehead);
+				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::imshow("green", plotGraph(greenSignalNormalized,
+					range));
+					cv::Mat greenFFT;
+					std::vector<double> greenFFTModule;
+					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
+					
+					std::vector<int> peak_indices;
+					
+					int i;
+					
+					for (i = 0; i < greenSignalNormalized.size(); i++) {
+    for (int j = 0; j < greenFFTModule.size(); j++) {
+        if (greenSignalNormalized[i] == greenFFTModule[j]) {
+            peak_indices.push_back(i);
+        }
+    }
+}
+	std::cout<<"index = " << peak_indices[i] << '\n';
+	}
+			}
+		}
+		cv::imshow("Color", frame);
+		if (cv::waitKey(1000.0/FPS) >= 0)
+		break;
+	}
+	cv::putText(image, "Text in Images", text_position, FONT_HERSHEY_COMPLEX, 12,(255,255,255), 10);
+}