moodmeter/opencv-webcam-demo/opencv-webcam-demo.cpp

#include <iostream>
#include <memory>
#include <chrono>
#include <fstream>
#include <boost/filesystem.hpp>
#include <boost/timer/timer.hpp>
#include <boost/program_options.hpp>
#include <boost/algorithm/string.hpp>

#include "Frame.h"
#include "Face.h"
#include "FrameDetector.h"
#include "AffdexException.h"

#include "AFaceListener.hpp"
#include "PlottingImageListener.hpp"
#include "LoggingImageListener.hpp"
#include "StatusListener.hpp"


using namespace std;
using namespace affdex;
using namespace cv;


FeaturePoint minPoint(VecFeaturePoint points)
{
	VecFeaturePoint::iterator it = points.begin();
	FeaturePoint ret = *it;
	for (; it != points.end(); it++)
	{
		if (it->x < ret.x) ret.x = it->x;
		if (it->y < ret.y) ret.y = it->y;
	}
	return ret;
};

FeaturePoint maxPoint(VecFeaturePoint points)
{
	VecFeaturePoint::iterator it = points.begin();
	FeaturePoint ret = *it;
	for (; it != points.end(); it++)
	{
		if (it->x > ret.x) ret.x = it->x;
		if (it->y > ret.y) ret.y = it->y;
	}
	return ret;
};

std::string getAsJson(int framenr, const std::map<FaceId, Face> faces, const double timeStamp)
{
    std::stringstream ss;
    ss << "{" << "\"t\":" << timeStamp << ",";
    ss << "\"nr\":" << framenr << ",";
    ss << "\"faces\":[";

    int i(0);
    

    for (auto & face_id_pair : faces)
    {
        Face f = face_id_pair.second;
        
        if(i > 0) { ss << ","; }
        i++;
        

        ss << "{";

        // fStream << timeStamp << ","
        //     << f.id << ","
        //     << f.measurements.interocularDistance << ","
        //     << glassesMap[f.appearance.glasses] << ","
        //     << ageMap[f.appearance.age] << ","
        //     << ethnicityMap[f.appearance.ethnicity] << ","
        //     << genderMap[f.appearance.gender] << ","
        //     << affdex::EmojiToString(f.emojis.dominantEmoji) << ",";

        float *values = (float *)&f.measurements.orientation;
        for (std::string angle : { "pitch", "yaw", "roll" })
        {
            ss << "\"" << angle << "\":" << (*values) << ",";
            values++;
        }

        values = (float *)&f.emotions;
        for (std::string emotion : {
            "joy", "fear", "disgust", "sadness", "anger",
            "surprise", "contempt", "valence", "engagement"
        })
        {
            ss << "\"" << emotion << "\":" << (*values) << ",";
            values++;
        }

        values = (float *)&f.expressions;
        for (std::string expression : {
            "smile", "innerBrowRaise", "browRaise", "browFurrow", "noseWrinkle",
            "upperLipRaise", "lipCornerDepressor", "chinRaise", "lipPucker", "lipPress",
            "lipSuck", "mouthOpen", "smirk", "eyeClosure", "attention", "eyeWiden", "cheekRaise",
            "lidTighten", "dimpler", "lipStretch", "jawDrop"
        })
        {
            ss << "\"" << expression << "\":" <<  (*values) << ",";
            values++;
        }
        
		FeaturePoint tl = minPoint(f.featurePoints);
		FeaturePoint br = maxPoint(f.featurePoints);
		
		ss << "\"rect\":{\"x\":" << tl.x << ",\"y\":" << tl.y
		   << ",\"w\":" << (br.x - tl.x) << ",\"h\":" << (br.y - tl.y) << "},";
		
        ss << "\"ioDistance\":"<< f.measurements.interocularDistance << ",";
        ss << "\"id\":"<< f.id;
        ss << "}";
    }

    ss << "]"; // faces
    ss << "}";
    return ss.str();
}

/// <summary>
/// Project for demoing the Windows SDK CameraDetector class (grabbing and processing frames from the camera).
/// </summary>
int main(int argsc, char ** argsv)
{
    namespace po = boost::program_options; // abbreviate namespace

    std::cerr << "Hit ESCAPE key to exit app.." << endl;
    shared_ptr<FrameDetector> frameDetector;

    try{

        const std::vector<int> DEFAULT_RESOLUTION{ 640, 480 };

        affdex::path DATA_FOLDER;

        std::vector<int> resolution;
        int process_framerate = 30;
        int buffer_length = 2;
        unsigned int nFaces = 1;
        bool draw_display = true;
        int faceDetectorMode = (int)FaceDetectorMode::SMALL_FACES;
        boost::filesystem::path imgPath("~/emo_in_file.jpg");
        boost::filesystem::path outPath("~/output/");

        float last_timestamp = -1.0f;
        float capture_fps = -1.0f;

        const int precision = 2;
        std::cerr.precision(precision);
        std::cout.precision(precision);

        po::options_description description("Project for demoing the Affdex SDK CameraDetector class (grabbing and processing frames from the camera).");
        description.add_options()
            ("help,h", po::bool_switch()->default_value(false), "Display this help message.")
#ifdef _WIN32
            ("data,d", po::wvalue< affdex::path >(&DATA_FOLDER)->default_value(affdex::path(L"data"), std::string("data")), "Path to the data folder")
#else //  _WIN32
            ("data,d", po::value< affdex::path >(&DATA_FOLDER)->default_value(affdex::path("data"), std::string("data")), "Path to the data folder")
#endif // _WIN32
            ("pfps", po::value< int >(&process_framerate)->default_value(30), "Processing framerate.")
            ("bufferLen", po::value< int >(&buffer_length)->default_value(30), "process buffer size.")
            ("faceMode", po::value< int >(&faceDetectorMode)->default_value((int)FaceDetectorMode::SMALL_FACES), "Face detector mode (large faces vs small faces).")
            ("numFaces", po::value< unsigned int >(&nFaces)->default_value(1), "Number of faces to be tracked.")
            ("draw", po::value< bool >(&draw_display)->default_value(true), "Draw metrics on screen.")
            //~ ("file,f", po::value< boost::filesystem::path >(&imgPath)->default_value(imgPath), "Filename of image that is watched/tracked for changes.")
            ("frameOutput,o", po::value< boost::filesystem::path >(&outPath)->default_value(outPath), "Directory to store the frame in (and json)")
            ;
        po::variables_map args;
        try
        {
            po::store(po::command_line_parser(argsc, argsv).options(description).run(), args);
            if (args["help"].as<bool>())
            {
                std::cout << description << std::endl;
                return 0;
            }
            po::notify(args);
        }
        catch (po::error& e)
        {
            std::cerr << "ERROR: " << e.what() << std::endl << std::endl;
            std::cerr << "For help, use the -h option." << std::endl << std::endl;
            return 1;
        }

        if (!boost::filesystem::exists(DATA_FOLDER))
        {
            std::cerr << "Folder doesn't exist: " << std::string(DATA_FOLDER.begin(), DATA_FOLDER.end()) << std::endl << std::endl;;
            std::cerr << "Try specifying the folder through the command line" << std::endl;
            std::cerr << description << std::endl;
            return 1;
        }
        if (!boost::filesystem::exists(outPath))
        {
            std::cerr << "Folder doesn't exist: " << outPath.native() << std::endl << std::endl;;
            std::cerr << "Try specifying the output folder through the command line" << std::endl;
            std::cerr << description << std::endl;
            return 1;
        }

        std::ofstream csvFileStream;

        std::cerr << "Initializing Affdex FrameDetector" << endl;
        shared_ptr<FaceListener> faceListenPtr(new AFaceListener());
        shared_ptr<PlottingImageListener> listenPtr(new PlottingImageListener(csvFileStream, draw_display));    // Instanciate the ImageListener class
        shared_ptr<StatusListener> videoListenPtr(new StatusListener());
        frameDetector = make_shared<FrameDetector>(buffer_length, process_framerate, nFaces, (affdex::FaceDetectorMode) faceDetectorMode);        // Init the FrameDetector Class

        //Initialize detectors
        frameDetector->setDetectAllEmotions(true);
        frameDetector->setDetectAllExpressions(true);
        frameDetector->setDetectAllEmojis(false);
        frameDetector->setDetectAllAppearances(false);
        frameDetector->setClassifierPath(DATA_FOLDER);
        frameDetector->setImageListener(listenPtr.get());
        frameDetector->setFaceListener(faceListenPtr.get());
        frameDetector->setProcessStatusListener(videoListenPtr.get());
        
        auto start_time = std::chrono::system_clock::now();
        
        std::cout << "Max num of faces set to: " << frameDetector->getMaxNumberFaces() << std::endl;
        std::string mode;
        switch (frameDetector->getFaceDetectorMode())
        {
        case FaceDetectorMode::LARGE_FACES:
            mode = "LARGE_FACES";
            break;
        case FaceDetectorMode::SMALL_FACES:
            mode = "SMALL_FACES";
            break;
        default:
            break;
        }
        std::cout << "Face detector mode set to: " << mode << std::endl;

        //Start the frame detector thread.
        frameDetector->start();
        
		int frameNrIn = 1;
		int frameNrOut = 1;
		std::time_t lastImgUpdate(0);
        while(true){ //(cv::waitKey(20) != -1);
			char buff[100];
			snprintf(buff, sizeof(buff), "frame%06d.jpg", frameNrIn);
			boost::filesystem::path imgPath = outPath / buff;
			if ( !boost::filesystem::exists( imgPath.native() )|| frameNrIn > frameNrOut ) {
				// wait for file to appear
				// and for the in file to be parsed (frame out)
				usleep(5000); // wait 1/20 sec to avoid useless fast loop
			} else {
				std::cerr << "Read " << imgPath.native() << std::endl;
				
				char buff[100];
				snprintf(buff, sizeof(buff), "frame%06d.json", frameNrIn);
				boost::filesystem::path jsonPath = outPath / buff;
				
				// don't redo existing jsons
				if( !boost::filesystem::exists( jsonPath.native() )) {
					cv::Mat img = imread(imgPath.native(), 1);

					//Calculate the Image timestamp and the capture frame rate;
					const auto milliseconds = std::chrono::duration_cast<std::chrono::milliseconds>(std::chrono::system_clock::now() - start_time);
					const double seconds = milliseconds.count() / 1000.f;

					// Create a frame
					Frame f(img.size().width, img.size().height, img.data, Frame::COLOR_FORMAT::BGR, seconds);
					capture_fps = 1.0f / (seconds - last_timestamp);
					last_timestamp = seconds;
					frameDetector->process(f);  //Pass the frame to detector
				} else {
					frameNrOut ++; // this won't happen later, but nr. should stay equal if skipping items.
				}
			
				frameNrIn++;
			}
			
            // For each frame processed (returns async)
            if (listenPtr->getDataSize() > 0)
            {
				
                std::pair<Frame, std::map<FaceId, Face> > dataPoint = listenPtr->getData();
                Frame frame = dataPoint.first;
                std::map<FaceId, Face> faces = dataPoint.second;

                // Draw metrics to the GUI
                if (draw_display)
                {
                    listenPtr->draw(faces, frame);
                }

                std::string json = getAsJson(frameNrOut, faces, frame.getTimestamp());
                std::cout << json << std::endl;
                
                // store json
				char buff[100];
				snprintf(buff, sizeof(buff), "frame%06d.json", frameNrOut);
				boost::filesystem::path targetFilename = outPath / buff;
				std::ofstream out(targetFilename.native());
				std::cerr << "write "<< targetFilename.native() << std::endl;
				out << json << "\n";
				out.close();

				frameNrOut++;
            }

        }

        std::cerr << "Stopping FrameDetector Thread" << endl;
        frameDetector->stop();    //Stop frame detector thread
    }
    catch (AffdexException ex)
    {
        std::cerr << "Encountered an AffdexException " << ex.what();
        return 1;
    }
    catch (std::runtime_error err)
    {
        std::cerr << "Encountered a runtime error " << err.what();
        return 1;
    }
    catch (std::exception ex)
    {
        std::cerr << "Encountered an exception " << ex.what();
        return 1;
    }
    catch (...)
    {
        std::cerr << "Encountered an unhandled exception ";
        return 1;
    }

    return 0;
}