opengaze/src/opengaze.cpp
2019-01-10 13:26:03 +01:00

502 lines
23 KiB
C++

#include "opengaze.hpp"
#include <iostream>
#include <time.h>
using namespace std;
using namespace cv;
namespace opengaze {
double clockToMilliseconds(clock_t ticks){
// units/(units/time) => time (seconds) * 1000 = milliseconds
return (ticks/(double)CLOCKS_PER_SEC)*1000.0;
}
OpenGaze::OpenGaze(int argc, char** argv){
namespace fs = boost::filesystem;
namespace po = boost::program_options;
// default value of parameters
camera_id_ = 0;
input_type_ = InputHandler::InputType::Camera;
is_face_model_ = true;
string gaze_method;
string gpu_id;
string temp;
int number_user;
fs::path calib_camera, calib_screen, cnn_param_path, cnn_model_path;
// parse command line options for input/output paths
po::options_description command_line("Command line options");
command_line.add_options()
("root_dir,r", po::value<string>(), "configuration file")
("input_type,t", po::value<string>(), "input type (camera, video file, directory)")
("gaze_method,g", po::value<string>(), "gaze estimation method, could be MPIIGaze or OpenFace")
("input,i", po::value<string>(), "parameter for input")
("output,o", po::value<string>(), "output directory")
("calib_camera", po::value<string>(), "camera calibration file")
("calib_screen", po::value<string>(), "camera-screen calibration file")
("gpu_id,p", po::value<string>(), "gpu id number, default is 0")
("debug,d", "show debug output")
("face_model,f", "to use face model or not")
("save_video,s", "save output visualization or not")
("number_user,n", "the maximum number of users in the input image")
;
cout << "Parsing command line options..." << endl;
po::variables_map vm_command;
po::store(po::parse_command_line(argc, argv, command_line), vm_command);
po::notify(vm_command);
// parse config file for data paths
po::options_description config_file("Config file options");
config_file.add_options()
("root_dir,r", po::value<string>(), "configuration file")
("input_type, t", po::value<string>(), "input type (camera, video file, directory)")
("input, i", po::value<string>(), "parameter for input")
("output,o", po::value<string>(), "output directory")
("cnn_param_path", po::value<string>(), "Caffe prototxt path")
("cnn_model_path", po::value<string>(), "Caffe model path")
("calib_camera", po::value<string>(), "camera calibration file")
("calib_screen", po::value<string>(), "camera-screen calibration file")
("gaze_method", po::value<string>(), "gaze estimation method, could be cnn or openface")
("gpu_id,p", po::value<string>(), "gpu id number, default is 0")
("face_model", po::value<bool>(), "face model or not")
("save_video", po::value<bool>(), "save output visualization or not")
("number_user", po::value<string>(), "the maximum number of users in the input image")
;
fs::path root_dir, config_path;
if(vm_command.count("root_dir")) root_dir = vm_command["root_dir"].as<string>();
else {
root_dir = OPENGAZE_CON_DIR;
cout << "No root directory is found, default value " << root_dir << " will be use" << endl;
}
config_path = root_dir / "default.cfg";
cout << "Reading config from \"" << config_path.string() << "\""<< endl;
if(!fs::exists(config_path)){
cout << "Config file does not exist" << endl;
exit(EXIT_FAILURE);
}
ifstream settings_file(config_path.string());
po::variables_map vm_config;
po::store(po::parse_config_file(settings_file , config_file), vm_config);
po::notify(vm_config);
if(vm_command.count("gpu_id")) gpu_id = vm_command["gpu_id"].as<string>();
else if (vm_config.count("gpu_id")) gpu_id = vm_config["gpu_id"].as<string>();
else gpu_id = "0";
// CNN paramters
if(vm_command.count("cnn_param_path")) cnn_param_path = vm_command["cnn_param_path"].as<string>();
else if (vm_config.count("cnn_param_path")) cnn_param_path = vm_config["cnn_param_path"].as<string>();
else cnn_param_path = root_dir / "content/caffeModel/alexnet_face.prototxt";
if(vm_command.count("cnn_model_path")) cnn_model_path = vm_command["cnn_model_path"].as<string>();
else if (vm_config.count("cnn_model_path")) cnn_model_path = vm_config["cnn_model_path"].as<string>();
else cnn_model_path = root_dir / "content/caffeModel/alexnet_face.caffemodel";
// check input requirements
if(vm_command.count("gaze_method")) gaze_method = vm_command["gaze_method"].as<string>();
else if (vm_config.count("gaze_method")) gaze_method = vm_config["gaze_method"].as<string>();
else gaze_method = "MPIIGaze";
if(vm_command.count("calib_screen")) calib_screen = vm_command["calib_screen"].as<string>();
else if (vm_config.count("calib_screen")) calib_screen = vm_config["calib_screen"].as<string>();
else calib_screen = root_dir / "content/calib/monitor_laptop.yml";
if(vm_command.count("calib_camera")) calib_camera = vm_command["calib_camera"].as<string>();
else if (vm_config.count("calib_camera")) calib_camera = vm_config["calib_camera"].as<string>();
else calib_camera = root_dir / "content/calib/calibration.yml";
// read calibration file
if(!fs::exists(calib_camera)){
cout << "Camera calibration file does not exist: " << calib_camera <<endl;
exit(EXIT_FAILURE);
}
else input_handler_.readCameraConfiguration(calib_camera.string());
if(!fs::exists(calib_screen)){
cout << "Camera-screen calibration file does not exist: " << calib_screen << endl;
exit(EXIT_FAILURE);
}
else input_handler_.readScreenConfiguration(calib_screen.string());
if(vm_command.count("input_type")) temp = vm_command["input_type"].as<string>();
else if (vm_config.count("input_type")) temp = vm_config["input_type"].as<string>();
else temp = "";
if (temp == "camera") {input_type_ = InputHandler::InputType::Camera;}
else if (temp == "video") {input_type_ = InputHandler::InputType::Video;}
else if (temp == "directory") {input_type_ = InputHandler::InputType::Directory;}
else cout<<"No input type specified, default value (camera) will be use" << endl;
if (vm_command.count("input")) temp = vm_command["input"].as<string>();
else if (vm_config.count("input")) temp = vm_config["input"].as<string>();
else temp = "0";
if (input_type_ == InputHandler::InputType::Camera) camera_id_ = stoi(temp);
else if (input_type_ == InputHandler::InputType::Video || input_type_ == InputHandler::InputType::Directory) input_dir_ = temp;
else cout<<"No input parameter specified, default value will be use" << endl;
if(vm_command.count("face_model")) is_face_model_ = true;
else if(vm_config.count("face_model")) is_face_model_ = vm_config["face_model"].as<bool>();
else is_face_model_ = true;
if(vm_command.count("save_video")) is_save_video_ = true;
else if(vm_config.count("save_video")) is_save_video_ = vm_config["save_video"].as<bool>();
else is_save_video_ = false;
if(vm_command.count("debug")) show_debug_ = true;
else if(vm_config.count("debug")) show_debug_ = vm_config["debug"].as<bool>();
else show_debug_ = false;
if(vm_command.count("output")) output_dir_ = vm_command["output"].as<string>();
else if(vm_config.count("output")) output_dir_ = vm_config["output"].as<string>();
else {
if (input_type_ == InputHandler::InputType::Video) output_dir_ = input_dir_.parent_path();
else if (input_type_ == InputHandler::InputType::Directory) output_dir_ = input_dir_.parent_path();
else if (input_type_ == InputHandler::InputType::Camera)
output_dir_ = root_dir;
}
string face_detector_root_path;
if(vm_command.count("openface_path")) face_detector_root_path = vm_command["openface_path"].as<string>();
else if(vm_config.count("openface_path")) face_detector_root_path = vm_config["openface_path"].as<string>();
else cout<< "No face detector root specified, default detector will be use" << endl;
if(vm_command.count("per_model_save_path")) per_model_save_path_ = vm_command["per_model_save_path"].as<string>();
else if (vm_config.count("per_model_save_path")) per_model_save_path_ = vm_config["per_model_save_path"].as<string>();
else per_model_save_path_ = root_dir.string() + "/content/calib/user0.txt";
if(vm_command.count("number_user")) temp = vm_command["number_user"].as<string>();
else if (vm_config.count("number_user")) temp = vm_config["number_user"].as<string>();
else temp = "5";
number_user = stoi(temp);
// initial class instance
if (input_type_ == InputHandler::InputType::Camera){ // Camera as input
input_handler_.setInputType(InputHandler::InputType::Camera);// set input type
input_handler_.setInput(camera_id_); // set Camera id
}
else if (input_type_ == InputHandler::InputType::Video) {
input_handler_.setInputType(InputHandler::InputType::Video);// set input type
input_handler_.setInput(input_dir_.string()); // set camera file
}
else if (input_type_ == InputHandler::InputType::Directory){
input_handler_.setInputType(InputHandler::InputType::Directory);
}
// initialize other classes
gaze_estimator_.setCameraParameters(input_handler_.camera_matrix_, input_handler_.camera_distortion_);
gaze_estimator_.setRootPath(root_dir.string());
gaze_estimator_.initialFaceDetector(number_user);
vector<std::string> arguments;
if (gaze_method == "MPIIGaze") {
arguments.push_back(cnn_param_path.string());
arguments.push_back(cnn_model_path.string());
if (is_face_model_)
arguments.emplace_back("face");
else
arguments.emplace_back("eye");
arguments.push_back(gpu_id);
gaze_estimator_.setMethod(GazeEstimator::Method::MPIIGaze, arguments);
}
else if (gaze_method == "OpenFace"){
//gaze_estimator_.setMethod(GazeEstimator::Method::OpenFace, arguments);
cout << "OpenFace gaze estimation is current not support" << endl;
exit(EXIT_FAILURE);
}
else {
cout << "The method setting is not right! Options are MPIIGaze or OpenFace!" << endl;
exit(EXIT_FAILURE);
}
}
OpenGaze::~OpenGaze() {
input_handler_.closeInput();
}
// do gaze estimation with camera as input
void OpenGaze::runGazeVisualization() {
input_handler_.initialize();
namedWindow("Gaze");
int key;
Mat input_image;
vector<Sample> output;
cv::VideoWriter m_writer;
if (is_save_video_){
boost::filesystem::path save_video_file;
save_video_file = output_dir_ / (input_dir_.stem().string() + "_gaze_video.avi");
m_writer.open(save_video_file.string(), CV_FOURCC('M','J','P','G'), 25,
Size(input_handler_.getFrameWidth(),input_handler_.getFrameHeight()), true);
cout << "Saving video to " << save_video_file << endl;
}
// construct saving file
ofstream output_stream;
boost::filesystem::path output_file_name = output_dir_ / (input_dir_.stem().string() + "_gaze_output.txt");
output_stream.open(output_file_name.string());
cout << "Created output file: " << output_file_name.string() << endl;
// for fps calculation
double fps_tracker = -1.0;
double t_start = 0;
double t_end = 0;
unsigned int frame_count = 0;
while(true){// loop all the sample or read frame from Video
frame_count++;
t_start = t_end;
output.clear();
input_image = input_handler_.getNextSample();// get input image
if(input_handler_.isReachEnd()){ // check if all sample are processed
cout<<"Processed all the samples."<<endl;
break;
}
Mat undist_img;
undistort(input_image, undist_img, input_handler_.camera_matrix_, input_handler_.camera_distortion_);
gaze_estimator_.estimateGaze(undist_img, output); // do gaze estimation
input_handler_.projectToDisplay(output, gaze_estimator_.input_type_==GazeEstimator::InputType::face);
// get the fps values
t_end = cv::getTickCount();
fps_tracker = 1.0 / (double(t_end - t_start) / cv::getTickFrequency());
// save output
for(auto & sample : output) {
output_stream << frame_count << ",";
output_stream << sample.face_data.face_id << ",";
output_stream << sample.face_data.certainty << ",";
output_stream << sample.face_patch_data.face_center.at<float>(0) << ",";
output_stream << sample.face_patch_data.face_center.at<float>(1) << ",";
output_stream << sample.face_patch_data.face_center.at<float>(2) << ",";
output_stream << sample.gaze_data.gaze2d.x << ",";
output_stream << sample.gaze_data.gaze2d.y << ",";
output_stream << sample.eye_data.leye_pos.at<float>(0) << ",";
output_stream << sample.eye_data.leye_pos.at<float>(1) << ",";
output_stream << sample.eye_data.leye_pos.at<float>(2) << ",";
output_stream << sample.eye_data.reye_pos.at<float>(0) << ",";
output_stream << sample.eye_data.reye_pos.at<float>(1) << ",";
output_stream << sample.eye_data.reye_pos.at<float>(2) << endl;
}
if (is_save_video_ || show_debug_) {
//////// visualization //////////////////////////////////////////////////
// draw results
for(const auto & sample : output){
//drawLandmarks(sample, undist_img); // draw face landmarks
drawGazeOnFace(sample, undist_img); // draw gaze ray on face image
//drawGazeOnSimScreen(sample, undist_img); // draw screen target
}
if (show_debug_) {
// show fps
char fpsC[255];
std::sprintf(fpsC, "%02f", fps_tracker);
string fpsSt("FPS: ");
fpsSt += fpsC;
cv::putText(undist_img, fpsSt, cv::Point(100, 100), CV_FONT_HERSHEY_SIMPLEX, 1, CV_RGB(255, 0, 0), 2);
// show the image
imshow("Gaze", undist_img);
key = cv::waitKey(1);
if (key==27) exit(EXIT_SUCCESS); // press ESC to exit
}
if (is_save_video_) {
if (is_save_video_)
m_writer << undist_img;
}
}
}
if (is_save_video_)
m_writer.release();
}
void OpenGaze::runDataExtraction() {
assert(input_handler_.getInputType() == InputHandler::InputType::Directory);// Here we just accept the directory folder
input_handler_.initialize();
vector<Sample> output;
Mat input_image;
while(true){// loop all the sample or read frame from Video
output.clear();
input_image = input_handler_.getNextSample();// get input image
if(input_handler_.isReachEnd()){ // check if all sample are processed
cout << "Processed all the samples." << endl;
break;
}
Mat undist_img;
undistort(input_image, undist_img, input_handler_.camera_matrix_, input_handler_.camera_distortion_);
gaze_estimator_.getImagePatch(undist_img, output); // extract the face image
// save the output
for (int i=0; i<output.size(); ++i) {
string save_file_name = output_dir_.stem().string() + "/img_" + input_handler_.getFileName() + "_" +to_string(i)+".jpg";
cv::imwrite(save_file_name, output[i].face_patch_data.face_patch);
}
}
}
void OpenGaze::runGazeOnScreen() {
input_handler_.initialize();
int key;
Mat input_image, undist_img, show_img;
vector<Sample> output;
cv::namedWindow("screen", CV_WINDOW_NORMAL);
cv::setWindowProperty("screen", CV_WND_PROP_FULLSCREEN, CV_WINDOW_FULLSCREEN);
show_img = cv::Mat::zeros(input_handler_.getScreenHeight(), input_handler_.getScreenWidth(), CV_8UC3);
while(true){// loop all the sample or read frame from Video
output.clear();
if(input_handler_.isReachEnd()){ // check if all sample are processed
cout<<"Processed all the samples."<<endl;
break;
}
input_image = input_handler_.getNextSample();// get input image
undistort(input_image, undist_img, input_handler_.camera_matrix_, input_handler_.camera_distortion_);
gaze_estimator_.estimateGaze(undist_img, output); // do gaze estimation
input_handler_.projectToDisplay(output, gaze_estimator_.input_type_==GazeEstimator::InputType::face);
// save output
for(auto & sample : output) {
int loc_x = (int)(sample.gaze_data.gaze2d.x * input_handler_.getScreenWidth());
int loc_y = (int)(sample.gaze_data.gaze2d.y * input_handler_.getScreenHeight());
circle(show_img, cv::Point(loc_x, loc_y), 10, CV_RGB(255,255,255), -1);
}
imshow("screen", show_img);
cv::Mat save_img;
cv::resize(show_img, save_img, cv::Size(1280, 720));
key = cv::waitKey(1);
show_img = cv::Mat::zeros(input_handler_.getScreenHeight(), input_handler_.getScreenWidth(), CV_8UC3);
if (key==27) break; // press ESC to exit
}
cv::setWindowProperty("screen", CV_WND_PROP_FULLSCREEN, CV_WINDOW_NORMAL);
cv::destroyWindow("screen");
}
void OpenGaze::runPersonalCalibration(int num_calibration_point) {
if (input_handler_.getInputType() != InputHandler::InputType::Camera){ // personal calibration has to be done with camera
cout << "Error: the input type must be camera for personal calibration!" << endl;
exit(EXIT_FAILURE);
}
Mat input_image, undist_img;
input_handler_.initialize();
PersonalCalibrator m_calibrator(input_handler_.getScreenWidth(), input_handler_.getScreenHeight());
m_calibrator.generatePoints(num_calibration_point);
m_calibrator.initialWindow(); // show start windows
vector<cv::Point2f> pred, gt; // prediction and ground-truth
for (int i=0; i<num_calibration_point; ++i){
if (m_calibrator.showNextPoint()) {// wait for clicking
vector<Sample> output;
input_image = input_handler_.getNextSample(); // get the sample when user clicking
undistort(input_image, undist_img, input_handler_.camera_matrix_, input_handler_.camera_distortion_);
gaze_estimator_.estimateGaze(undist_img, output); // do gaze estimation
input_handler_.projectToDisplay(output, gaze_estimator_.input_type_==GazeEstimator::InputType::face);// convert to 2D projection
m_calibrator.confirmClicking(); // give feedback to user that they successfully did calibration
pred.emplace_back(output[0].gaze_data.gaze2d);
gt.emplace_back(cv::Point2f((m_calibrator.getCurrentPoint().x/(float)input_handler_.getScreenWidth()),
(m_calibrator.getCurrentPoint().y/(float)input_handler_.getScreenHeight())));
}
else
break; // if user press ESC button, we break
}
if (pred.size() > 0){
m_calibrator.generateModel(pred, gt, 1); // get the mapping model
string per_model_save_path_ = output_dir_.stem().string() + "/personal_gaze_model.yml";
m_calibrator.saveModel(per_model_save_path_);
}
}
void OpenGaze::drawGazeOnSimScreen(opengaze::Sample sample, cv::Mat &image) {
static const int dW = 640;
static const int dH = 360;
Mat debug_disp = Mat::zeros(Size(dW, dH), CV_8UC3);
Point2f g_s;
g_s.x = dW*sample.gaze_data.gaze2d.x;
g_s.y = dH*sample.gaze_data.gaze2d.y;
circle(debug_disp, g_s, 10, CV_RGB(255,0,0), -1);
debug_disp.copyTo(image(Rect(0, 0, dW, dH)));
}
void OpenGaze::drawGazeOnFace(opengaze::Sample sample, cv::Mat &image) {
// draw gaze on the face
if (gaze_estimator_.method_type_ == GazeEstimator::Method::MPIIGaze
&& gaze_estimator_.input_type_ == GazeEstimator::InputType::face) {
static const float gaze_length = 300.0;
Mat zero = Mat::zeros(1, 3, CV_32F);
Mat rvec, tvec;
sample.face_patch_data.head_r.convertTo(rvec, CV_32F);
sample.face_patch_data.head_t.convertTo(tvec, CV_32F);
vector<Point3f> cam_points;
Vec3f face_center(sample.face_patch_data.face_center.at<float>(0), sample.face_patch_data.face_center.at<float>(1), sample.face_patch_data.face_center.at<float>(2));
cam_points.emplace_back(face_center);
cam_points.emplace_back(face_center + gaze_length * sample.gaze_data.gaze3d);
vector<Point2f> img_points;
projectPoints(cam_points, zero, zero, input_handler_.camera_matrix_, input_handler_.camera_distortion_, img_points);
line(image, img_points[0], img_points[1], CV_RGB(255,0,0), 5); // gaze ray
circle(image, img_points[0], 5, CV_RGB(255,0,0), -1); // staring point
circle(image, img_points[1], 5, CV_RGB(255,0,0), -1); // end point
}
else if ((gaze_estimator_.method_type_ == GazeEstimator::Method::MPIIGaze
&& gaze_estimator_.input_type_ == GazeEstimator::InputType::eye)
|| gaze_estimator_.method_type_ == GazeEstimator::Method::OpenFace) {
int gaze_length = 300;
Mat zero = Mat::zeros(1, 3, CV_32F);
vector<Point3f> cam_points;
sample.eye_data.leye_pos.convertTo(sample.eye_data.leye_pos, CV_32F);
Vec3f leye_pose(sample.eye_data.leye_pos.at<float>(0),sample.eye_data.leye_pos.at<float>(1),sample.eye_data.leye_pos.at<float>(2));
cam_points.emplace_back(leye_pose);
cam_points.emplace_back(leye_pose + gaze_length*sample.gaze_data.lgaze3d);
Vec3f reye_pose(sample.eye_data.reye_pos.at<float>(0),sample.eye_data.reye_pos.at<float>(1),sample.eye_data.reye_pos.at<float>(2));
cam_points.emplace_back(reye_pose);
cam_points.emplace_back(reye_pose + gaze_length*sample.gaze_data.rgaze3d);
vector<Point2f> img_points;
projectPoints(cam_points, zero, zero, input_handler_.camera_matrix_, input_handler_.camera_distortion_, img_points);
line(image, img_points[0], img_points[1], CV_RGB(255,0,0), 5);
line(image, img_points[2], img_points[3], CV_RGB(255,0,0), 5);
circle(image, img_points[1], 3, CV_RGB(255,0,0), -1);
circle(image, img_points[3], 3, CV_RGB(255,0,0), -1);
}
}
void OpenGaze::drawLandmarks(opengaze::Sample sample, cv::Mat &image) {
cv::Rect_<int> face_bb = sample.face_data.face_bb;
rectangle(image, cv::Point(face_bb.x, face_bb.y),
cv::Point(face_bb.x+face_bb.width,face_bb.y+face_bb.height), CV_RGB(0,255,0), 5);
for(int p=0; p<6; ++p)
circle(image, sample.face_data.landmarks[p], 5, CV_RGB(0,255,0), -1);
}
}