337 lines
12 KiB
C++
337 lines
12 KiB
C++
#include <iostream>
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#include <memory>
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#include <chrono>
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#include <fstream>
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#include <boost/filesystem.hpp>
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#include <boost/timer/timer.hpp>
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#include <boost/program_options.hpp>
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#include <boost/algorithm/string.hpp>
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#include "Frame.h"
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#include "Face.h"
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#include "FrameDetector.h"
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#include "AffdexException.h"
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#include "AFaceListener.hpp"
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#include "PlottingImageListener.hpp"
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#include "LoggingImageListener.hpp"
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#include "StatusListener.hpp"
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using namespace std;
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using namespace affdex;
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using namespace cv;
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FeaturePoint minPoint(VecFeaturePoint points)
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{
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VecFeaturePoint::iterator it = points.begin();
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FeaturePoint ret = *it;
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for (; it != points.end(); it++)
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{
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if (it->x < ret.x) ret.x = it->x;
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if (it->y < ret.y) ret.y = it->y;
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}
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return ret;
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};
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FeaturePoint maxPoint(VecFeaturePoint points)
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{
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VecFeaturePoint::iterator it = points.begin();
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FeaturePoint ret = *it;
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for (; it != points.end(); it++)
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{
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if (it->x > ret.x) ret.x = it->x;
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if (it->y > ret.y) ret.y = it->y;
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}
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return ret;
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};
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std::string getAsJson(int framenr, const std::map<FaceId, Face> faces, const double timeStamp)
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{
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std::stringstream ss;
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ss << "{" << "\"t\":" << timeStamp << ",";
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ss << "\"nr\":" << framenr << ",";
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ss << "\"faces\":[";
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int i(0);
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for (auto & face_id_pair : faces)
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{
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Face f = face_id_pair.second;
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if(i > 0) { ss << ","; }
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i++;
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ss << "{";
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// fStream << timeStamp << ","
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// << f.id << ","
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// << f.measurements.interocularDistance << ","
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// << glassesMap[f.appearance.glasses] << ","
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// << ageMap[f.appearance.age] << ","
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// << ethnicityMap[f.appearance.ethnicity] << ","
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// << genderMap[f.appearance.gender] << ","
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// << affdex::EmojiToString(f.emojis.dominantEmoji) << ",";
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float *values = (float *)&f.measurements.orientation;
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for (std::string angle : { "pitch", "yaw", "roll" })
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{
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ss << "\"" << angle << "\":" << (*values) << ",";
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values++;
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}
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values = (float *)&f.emotions;
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for (std::string emotion : {
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"joy", "fear", "disgust", "sadness", "anger",
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"surprise", "contempt", "valence", "engagement"
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})
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{
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ss << "\"" << emotion << "\":" << (*values) << ",";
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values++;
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}
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values = (float *)&f.expressions;
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for (std::string expression : {
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"smile", "innerBrowRaise", "browRaise", "browFurrow", "noseWrinkle",
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"upperLipRaise", "lipCornerDepressor", "chinRaise", "lipPucker", "lipPress",
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"lipSuck", "mouthOpen", "smirk", "eyeClosure", "attention", "eyeWiden", "cheekRaise",
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"lidTighten", "dimpler", "lipStretch", "jawDrop"
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})
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{
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ss << "\"" << expression << "\":" << (*values) << ",";
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values++;
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}
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FeaturePoint tl = minPoint(f.featurePoints);
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FeaturePoint br = maxPoint(f.featurePoints);
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ss << "\"rect\":{\"x\":" << tl.x << ",\"y\":" << tl.y
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<< ",\"w\":" << (br.x - tl.x) << ",\"h\":" << (br.y - tl.y) << "},";
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ss << "\"ioDistance\":"<< f.measurements.interocularDistance << ",";
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ss << "\"id\":"<< f.id;
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ss << "}";
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}
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ss << "]"; // faces
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ss << "}";
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return ss.str();
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}
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/// <summary>
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/// Project for demoing the Windows SDK CameraDetector class (grabbing and processing frames from the camera).
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/// </summary>
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int main(int argsc, char ** argsv)
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{
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namespace po = boost::program_options; // abbreviate namespace
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std::cerr << "Hit ESCAPE key to exit app.." << endl;
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shared_ptr<FrameDetector> frameDetector;
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try{
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const std::vector<int> DEFAULT_RESOLUTION{ 640, 480 };
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affdex::path DATA_FOLDER;
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std::vector<int> resolution;
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int process_framerate = 30;
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int buffer_length = 2;
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unsigned int nFaces = 1;
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bool draw_display = true;
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int faceDetectorMode = (int)FaceDetectorMode::SMALL_FACES;
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boost::filesystem::path imgPath("~/emo_in_file.jpg");
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boost::filesystem::path outPath("~/output/");
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float last_timestamp = -1.0f;
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float capture_fps = -1.0f;
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const int precision = 2;
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std::cerr.precision(precision);
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std::cout.precision(precision);
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po::options_description description("Project for demoing the Affdex SDK CameraDetector class (grabbing and processing frames from the camera).");
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description.add_options()
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("help,h", po::bool_switch()->default_value(false), "Display this help message.")
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#ifdef _WIN32
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("data,d", po::wvalue< affdex::path >(&DATA_FOLDER)->default_value(affdex::path(L"data"), std::string("data")), "Path to the data folder")
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#else // _WIN32
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("data,d", po::value< affdex::path >(&DATA_FOLDER)->default_value(affdex::path("data"), std::string("data")), "Path to the data folder")
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#endif // _WIN32
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("pfps", po::value< int >(&process_framerate)->default_value(30), "Processing framerate.")
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("bufferLen", po::value< int >(&buffer_length)->default_value(30), "process buffer size.")
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("faceMode", po::value< int >(&faceDetectorMode)->default_value((int)FaceDetectorMode::SMALL_FACES), "Face detector mode (large faces vs small faces).")
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("numFaces", po::value< unsigned int >(&nFaces)->default_value(1), "Number of faces to be tracked.")
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("draw", po::value< bool >(&draw_display)->default_value(true), "Draw metrics on screen.")
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//~ ("file,f", po::value< boost::filesystem::path >(&imgPath)->default_value(imgPath), "Filename of image that is watched/tracked for changes.")
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("frameOutput,o", po::value< boost::filesystem::path >(&outPath)->default_value(outPath), "Directory to store the frame in (and json)")
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;
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po::variables_map args;
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try
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{
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po::store(po::command_line_parser(argsc, argsv).options(description).run(), args);
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if (args["help"].as<bool>())
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{
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std::cout << description << std::endl;
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return 0;
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}
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po::notify(args);
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}
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catch (po::error& e)
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{
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std::cerr << "ERROR: " << e.what() << std::endl << std::endl;
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std::cerr << "For help, use the -h option." << std::endl << std::endl;
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return 1;
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}
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if (!boost::filesystem::exists(DATA_FOLDER))
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{
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std::cerr << "Folder doesn't exist: " << std::string(DATA_FOLDER.begin(), DATA_FOLDER.end()) << std::endl << std::endl;;
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std::cerr << "Try specifying the folder through the command line" << std::endl;
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std::cerr << description << std::endl;
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return 1;
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}
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if (!boost::filesystem::exists(outPath))
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{
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std::cerr << "Folder doesn't exist: " << outPath.native() << std::endl << std::endl;;
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std::cerr << "Try specifying the output folder through the command line" << std::endl;
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std::cerr << description << std::endl;
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return 1;
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}
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std::ofstream csvFileStream;
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std::cerr << "Initializing Affdex FrameDetector" << endl;
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shared_ptr<FaceListener> faceListenPtr(new AFaceListener());
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shared_ptr<PlottingImageListener> listenPtr(new PlottingImageListener(csvFileStream, draw_display)); // Instanciate the ImageListener class
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shared_ptr<StatusListener> videoListenPtr(new StatusListener());
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frameDetector = make_shared<FrameDetector>(buffer_length, process_framerate, nFaces, (affdex::FaceDetectorMode) faceDetectorMode); // Init the FrameDetector Class
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//Initialize detectors
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frameDetector->setDetectAllEmotions(true);
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frameDetector->setDetectAllExpressions(true);
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frameDetector->setDetectAllEmojis(false);
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frameDetector->setDetectAllAppearances(false);
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frameDetector->setClassifierPath(DATA_FOLDER);
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frameDetector->setImageListener(listenPtr.get());
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frameDetector->setFaceListener(faceListenPtr.get());
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frameDetector->setProcessStatusListener(videoListenPtr.get());
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auto start_time = std::chrono::system_clock::now();
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std::cout << "Max num of faces set to: " << frameDetector->getMaxNumberFaces() << std::endl;
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std::string mode;
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switch (frameDetector->getFaceDetectorMode())
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{
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case FaceDetectorMode::LARGE_FACES:
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mode = "LARGE_FACES";
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break;
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case FaceDetectorMode::SMALL_FACES:
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mode = "SMALL_FACES";
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break;
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default:
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break;
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}
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std::cout << "Face detector mode set to: " << mode << std::endl;
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//Start the frame detector thread.
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frameDetector->start();
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int frameNrIn = 1;
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int frameNrOut = 1;
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std::time_t lastImgUpdate(0);
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while(true){ //(cv::waitKey(20) != -1);
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char buff[100];
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snprintf(buff, sizeof(buff), "frame%06d.jpg", frameNrIn);
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boost::filesystem::path imgPath = outPath / buff;
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if ( !boost::filesystem::exists( imgPath.native() )|| frameNrIn > frameNrOut ) {
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// wait for file to appear
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// and for the in file to be parsed (frame out)
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usleep(5000); // wait 1/20 sec to avoid useless fast loop
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} else {
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std::cerr << "Read " << imgPath.native() << std::endl;
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char buff[100];
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snprintf(buff, sizeof(buff), "frame%06d.json", frameNrIn);
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boost::filesystem::path jsonPath = outPath / buff;
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// don't redo existing jsons
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if( !boost::filesystem::exists( jsonPath.native() )) {
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cv::Mat img = imread(imgPath.native(), 1);
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//Calculate the Image timestamp and the capture frame rate;
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const auto milliseconds = std::chrono::duration_cast<std::chrono::milliseconds>(std::chrono::system_clock::now() - start_time);
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const double seconds = milliseconds.count() / 1000.f;
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// Create a frame
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Frame f(img.size().width, img.size().height, img.data, Frame::COLOR_FORMAT::BGR, seconds);
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capture_fps = 1.0f / (seconds - last_timestamp);
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last_timestamp = seconds;
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frameDetector->process(f); //Pass the frame to detector
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} else {
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frameNrOut ++; // this won't happen later, but nr. should stay equal if skipping items.
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}
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frameNrIn++;
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}
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// For each frame processed (returns async)
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if (listenPtr->getDataSize() > 0)
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{
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std::pair<Frame, std::map<FaceId, Face> > dataPoint = listenPtr->getData();
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Frame frame = dataPoint.first;
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std::map<FaceId, Face> faces = dataPoint.second;
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// Draw metrics to the GUI
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if (draw_display)
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{
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listenPtr->draw(faces, frame);
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}
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std::string json = getAsJson(frameNrOut, faces, frame.getTimestamp());
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std::cout << json << std::endl;
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// store json
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char buff[100];
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snprintf(buff, sizeof(buff), "frame%06d.json", frameNrOut);
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boost::filesystem::path targetFilename = outPath / buff;
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std::ofstream out(targetFilename.native());
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std::cerr << "write "<< targetFilename.native() << std::endl;
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out << json << "\n";
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out.close();
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frameNrOut++;
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}
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}
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std::cerr << "Stopping FrameDetector Thread" << endl;
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frameDetector->stop(); //Stop frame detector thread
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}
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catch (AffdexException ex)
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{
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std::cerr << "Encountered an AffdexException " << ex.what();
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return 1;
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}
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catch (std::runtime_error err)
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{
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std::cerr << "Encountered a runtime error " << err.what();
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return 1;
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}
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catch (std::exception ex)
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{
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std::cerr << "Encountered an exception " << ex.what();
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return 1;
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}
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catch (...)
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{
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std::cerr << "Encountered an unhandled exception ";
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return 1;
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}
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return 0;
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}
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