Moving things around for clarity.

This commit is contained in:
Tadas Baltrusaitis 2016-05-19 11:51:32 -04:00
parent 668588500c
commit fc27b5bbb6

View file

@ -155,228 +155,11 @@ void create_directory(string output_path)
void get_output_feature_params(vector<string> &output_similarity_aligned, vector<string> &output_hog_aligned_files, double &similarity_scale, void get_output_feature_params(vector<string> &output_similarity_aligned, vector<string> &output_hog_aligned_files, double &similarity_scale,
int &similarity_size, bool &grayscale, bool &rigid, bool& verbose, int &similarity_size, bool &grayscale, bool &rigid, bool& verbose,
bool &output_2D_landmarks, bool &output_3D_landmarks, bool &output_model_params, bool &output_pose, bool &output_AUs, bool &output_gaze, bool &output_2D_landmarks, bool &output_3D_landmarks, bool &output_model_params, bool &output_pose, bool &output_AUs, bool &output_gaze,
vector<string> &arguments) vector<string> &arguments);
{
output_similarity_aligned.clear();
output_hog_aligned_files.clear();
bool* valid = new bool[arguments.size()]; void get_image_input_output_params_feats(vector<vector<string> > &input_image_files, bool& as_video, vector<string> &arguments);
for (size_t i = 0; i < arguments.size(); ++i) void output_HOG_frame(std::ofstream* hog_file, bool good_frame, const cv::Mat_<double>& hog_descriptor, int num_rows, int num_cols);
{
valid[i] = true;
}
string input_root = "";
string output_root = "";
// First check if there is a root argument (so that videos and outputs could be defined more easilly)
for (size_t i = 0; i < arguments.size(); ++i)
{
if (arguments[i].compare("-root") == 0)
{
input_root = arguments[i + 1];
output_root = arguments[i + 1];
i++;
}
if (arguments[i].compare("-inroot") == 0)
{
input_root = arguments[i + 1];
i++;
}
if (arguments[i].compare("-outroot") == 0)
{
output_root = arguments[i + 1];
i++;
}
}
for (size_t i = 0; i < arguments.size(); ++i)
{
if (arguments[i].compare("-simalign") == 0)
{
output_similarity_aligned.push_back(output_root + arguments[i + 1]);
create_directory(output_root + arguments[i + 1]);
valid[i] = false;
valid[i + 1] = false;
i++;
}
else if (arguments[i].compare("-hogalign") == 0)
{
output_hog_aligned_files.push_back(output_root + arguments[i + 1]);
create_directory_from_file(output_root + arguments[i + 1]);
valid[i] = false;
valid[i + 1] = false;
i++;
}
else if (arguments[i].compare("-verbose") == 0)
{
verbose = true;
}
else if (arguments[i].compare("-rigid") == 0)
{
rigid = true;
}
else if (arguments[i].compare("-g") == 0)
{
grayscale = true;
valid[i] = false;
}
else if (arguments[i].compare("-simscale") == 0)
{
similarity_scale = stod(arguments[i + 1]);
valid[i] = false;
valid[i + 1] = false;
i++;
}
else if (arguments[i].compare("-simsize") == 0)
{
similarity_size = stoi(arguments[i + 1]);
valid[i] = false;
valid[i + 1] = false;
i++;
}
else if (arguments[i].compare("-no2Dfp") == 0)
{
output_2D_landmarks = false;
valid[i] = false;
}
else if (arguments[i].compare("-no3Dfp") == 0)
{
output_3D_landmarks = false;
valid[i] = false;
}
else if (arguments[i].compare("-noMparams") == 0)
{
output_model_params = false;
valid[i] = false;
}
else if (arguments[i].compare("-noPose") == 0)
{
output_pose = false;
valid[i] = false;
}
else if (arguments[i].compare("-noAUs") == 0)
{
output_AUs = false;
valid[i] = false;
}
else if (arguments[i].compare("-noGaze") == 0)
{
output_gaze = false;
valid[i] = false;
}
}
for (int i = arguments.size() - 1; i >= 0; --i)
{
if (!valid[i])
{
arguments.erase(arguments.begin() + i);
}
}
}
// Can process images via directories creating a separate output file per directory
void get_image_input_output_params_feats(vector<vector<string> > &input_image_files, bool& as_video, vector<string> &arguments)
{
bool* valid = new bool[arguments.size()];
for(size_t i = 0; i < arguments.size(); ++i)
{
valid[i] = true;
if (arguments[i].compare("-fdir") == 0)
{
// parse the -fdir directory by reading in all of the .png and .jpg files in it
path image_directory (arguments[i+1]);
try
{
// does the file exist and is it a directory
if (exists(image_directory) && is_directory(image_directory))
{
vector<path> file_in_directory;
copy(directory_iterator(image_directory), directory_iterator(), back_inserter(file_in_directory));
// Sort the images in the directory first
sort(file_in_directory.begin(), file_in_directory.end());
vector<string> curr_dir_files;
for (vector<path>::const_iterator file_iterator (file_in_directory.begin()); file_iterator != file_in_directory.end(); ++file_iterator)
{
// Possible image extension .jpg and .png
if(file_iterator->extension().string().compare(".jpg") == 0 || file_iterator->extension().string().compare(".png") == 0)
{
curr_dir_files.push_back(file_iterator->string());
}
}
input_image_files.push_back(curr_dir_files);
}
}
catch (const filesystem_error& ex)
{
cout << ex.what() << '\n';
}
valid[i] = false;
valid[i+1] = false;
i++;
}
else if (arguments[i].compare("-asvid") == 0)
{
as_video = true;
}
}
// Clear up the argument list
for(int i=arguments.size()-1; i >= 0; --i)
{
if(!valid[i])
{
arguments.erase(arguments.begin()+i);
}
}
}
void output_HOG_frame(std::ofstream* hog_file, bool good_frame, const cv::Mat_<double>& hog_descriptor, int num_rows, int num_cols)
{
// Using FHOGs, hence 31 channels
int num_channels = 31;
hog_file->write((char*)(&num_cols), 4);
hog_file->write((char*)(&num_rows), 4);
hog_file->write((char*)(&num_channels), 4);
// Not the best way to store a bool, but will be much easier to read it
float good_frame_float;
if(good_frame)
good_frame_float = 1;
else
good_frame_float = -1;
hog_file->write((char*)(&good_frame_float), 4);
cv::MatConstIterator_<double> descriptor_it = hog_descriptor.begin();
for(int y = 0; y < num_cols; ++y)
{
for(int x = 0; x < num_rows; ++x)
{
for(unsigned int o = 0; o < 31; ++o)
{
float hog_data = (float)(*descriptor_it++);
hog_file->write ((char*)&hog_data, 4);
}
}
}
}
// Some globals for tracking timing information for visualisation // Some globals for tracking timing information for visualisation
double fps_tracker = -1.0; double fps_tracker = -1.0;
@ -443,193 +226,14 @@ void visualise_tracking(cv::Mat& captured_image, const LandmarkDetector::CLNF& f
void prepareOutputFile(std::ofstream* output_file, bool output_2D_landmarks, bool output_3D_landmarks, void prepareOutputFile(std::ofstream* output_file, bool output_2D_landmarks, bool output_3D_landmarks,
bool output_model_params, bool output_pose, bool output_AUs, bool output_gaze, bool output_model_params, bool output_pose, bool output_AUs, bool output_gaze,
int num_landmarks, int num_model_modes, vector<string> au_names_class, vector<string> au_names_reg) int num_landmarks, int num_model_modes, vector<string> au_names_class, vector<string> au_names_reg);
{
*output_file << "frame, timestamp, confidence, success";
if (output_gaze)
{
*output_file << ", gaze_0_x, gaze_0_y, gaze_0_z, gaze_1_x, gaze_1_y, gaze_2_z";
}
if (output_pose)
{
*output_file << ", pose_Tx, pose_Ty, pose_Tz, pose_Rx, pose_Ry, pose_Rz";
}
if (output_2D_landmarks)
{
for (int i = 0; i < num_landmarks; ++i)
{
*output_file << ", x_" << i;
}
for (int i = 0; i < num_landmarks; ++i)
{
*output_file << ", y_" << i;
}
}
if (output_3D_landmarks)
{
for (int i = 0; i < num_landmarks; ++i)
{
*output_file << ", X_" << i;
}
for (int i = 0; i < num_landmarks; ++i)
{
*output_file << ", Y_" << i;
}
for (int i = 0; i < num_landmarks; ++i)
{
*output_file << ", Z_" << i;
}
}
// Outputting model parameters (rigid and non-rigid), the first parameters are the 6 rigid shape parameters, they are followed by the non rigid shape parameters
if (output_model_params)
{
*output_file << ", p_scale, p_rx, p_ry, p_rz, p_tx, p_ty";
for (int i = 0; i < num_model_modes; ++i)
{
*output_file << ", p_" << i;
}
}
if (output_AUs)
{
std::sort(au_names_reg.begin(), au_names_reg.end());
for (string reg_name : au_names_reg)
{
*output_file << ", " << reg_name << "_r";
}
std::sort(au_names_class.begin(), au_names_class.end());
for (string class_name : au_names_class)
{
*output_file << ", " << class_name << "_c";
}
}
*output_file << endl;
}
// Output all of the information into one file in one go (quite a few parameters, but simplifies the flow) // Output all of the information into one file in one go (quite a few parameters, but simplifies the flow)
void outputAllFeatures(std::ofstream* output_file, bool output_2D_landmarks, bool output_3D_landmarks, void outputAllFeatures(std::ofstream* output_file, bool output_2D_landmarks, bool output_3D_landmarks,
bool output_model_params, bool output_pose, bool output_AUs, bool output_gaze, bool output_model_params, bool output_pose, bool output_AUs, bool output_gaze,
const LandmarkDetector::CLNF& face_model, int frame_count, double time_stamp, bool detection_success, const LandmarkDetector::CLNF& face_model, int frame_count, double time_stamp, bool detection_success,
cv::Point3f gazeDirection0, cv::Point3f gazeDirection1, const cv::Vec6d& pose_estimate, double fx, double fy, double cx, double cy, cv::Point3f gazeDirection0, cv::Point3f gazeDirection1, const cv::Vec6d& pose_estimate, double fx, double fy, double cx, double cy,
const FaceAnalysis::FaceAnalyser& face_analyser) const FaceAnalysis::FaceAnalyser& face_analyser);
{
double confidence = 0.5 * (1 - face_model.detection_certainty);
*output_file << frame_count + 1 << ", " << time_stamp << ", " << confidence << ", " << detection_success;
// Output the estimated gaze
if (output_gaze)
{
*output_file << ", " << gazeDirection0.x << ", " << gazeDirection0.y << ", " << gazeDirection0.z
<< ", " << gazeDirection1.x << ", " << gazeDirection1.y << ", " << gazeDirection1.z;
}
// Output the estimated head pose
if (output_pose)
{
*output_file << ", " << pose_estimate[0] << ", " << pose_estimate[1] << ", " << pose_estimate[2]
<< ", " << pose_estimate[3] << ", " << pose_estimate[4] << ", " << pose_estimate[5];
}
// Output the detected 2D facial landmarks
if (output_2D_landmarks)
{
for (int i = 0; i < face_model.pdm.NumberOfPoints() * 2; ++i)
{
*output_file << ", " << face_model.detected_landmarks.at<double>(i);
}
}
// Output the detected 3D facial landmarks
if (output_3D_landmarks)
{
cv::Mat_<double> shape_3D = face_model.GetShape(fx, fy, cx, cy);
for (int i = 0; i < face_model.pdm.NumberOfPoints() * 3; ++i)
{
*output_file << ", " << shape_3D.at<double>(i);
}
}
if (output_model_params)
{
for (int i = 0; i < 6; ++i)
{
*output_file << ", " << face_model.params_global[i];
}
for (int i = 0; i < face_model.pdm.NumberOfModes(); ++i)
{
*output_file << ", " << face_model.params_local.at<double>(i, 0);
}
}
if (output_AUs)
{
auto aus_reg = face_analyser.GetCurrentAUsReg();
vector<string> au_reg_names = face_analyser.GetAURegNames();
std::sort(au_reg_names.begin(), au_reg_names.end());
// write out ar the correct index
for (string au_name : au_reg_names)
{
for (auto au_reg : aus_reg)
{
if (au_name.compare(au_reg.first) == 0)
{
*output_file << ", " << au_reg.second;
break;
}
}
}
if (aus_reg.size() == 0)
{
for (size_t p = 0; p < face_analyser.GetAURegNames().size(); ++p)
{
*output_file << ", 0";
}
}
auto aus_class = face_analyser.GetCurrentAUsClass();
vector<string> au_class_names = face_analyser.GetAUClassNames();
std::sort(au_class_names.begin(), au_class_names.end());
// write out ar the correct index
for (string au_name : au_class_names)
{
for (auto au_class: aus_class)
{
if (au_name.compare(au_class.first) == 0)
{
*output_file << ", " << au_class.second;
break;
}
}
}
if (aus_class.size() == 0)
{
for (size_t p = 0; p < face_analyser.GetAUClassNames().size(); ++p)
{
*output_file << ", 0";
}
}
}
*output_file << endl;
}
void post_process_output_file(FaceAnalysis::FaceAnalyser& face_analyser, string output_file); void post_process_output_file(FaceAnalysis::FaceAnalyser& face_analyser, string output_file);
@ -1225,3 +829,421 @@ void post_process_output_file(FaceAnalysis::FaceAnalyser& face_analyser, string
} }
void prepareOutputFile(std::ofstream* output_file, bool output_2D_landmarks, bool output_3D_landmarks,
bool output_model_params, bool output_pose, bool output_AUs, bool output_gaze,
int num_landmarks, int num_model_modes, vector<string> au_names_class, vector<string> au_names_reg)
{
*output_file << "frame, timestamp, confidence, success";
if (output_gaze)
{
*output_file << ", gaze_0_x, gaze_0_y, gaze_0_z, gaze_1_x, gaze_1_y, gaze_2_z";
}
if (output_pose)
{
*output_file << ", pose_Tx, pose_Ty, pose_Tz, pose_Rx, pose_Ry, pose_Rz";
}
if (output_2D_landmarks)
{
for (int i = 0; i < num_landmarks; ++i)
{
*output_file << ", x_" << i;
}
for (int i = 0; i < num_landmarks; ++i)
{
*output_file << ", y_" << i;
}
}
if (output_3D_landmarks)
{
for (int i = 0; i < num_landmarks; ++i)
{
*output_file << ", X_" << i;
}
for (int i = 0; i < num_landmarks; ++i)
{
*output_file << ", Y_" << i;
}
for (int i = 0; i < num_landmarks; ++i)
{
*output_file << ", Z_" << i;
}
}
// Outputting model parameters (rigid and non-rigid), the first parameters are the 6 rigid shape parameters, they are followed by the non rigid shape parameters
if (output_model_params)
{
*output_file << ", p_scale, p_rx, p_ry, p_rz, p_tx, p_ty";
for (int i = 0; i < num_model_modes; ++i)
{
*output_file << ", p_" << i;
}
}
if (output_AUs)
{
std::sort(au_names_reg.begin(), au_names_reg.end());
for (string reg_name : au_names_reg)
{
*output_file << ", " << reg_name << "_r";
}
std::sort(au_names_class.begin(), au_names_class.end());
for (string class_name : au_names_class)
{
*output_file << ", " << class_name << "_c";
}
}
*output_file << endl;
}
// Output all of the information into one file in one go (quite a few parameters, but simplifies the flow)
void outputAllFeatures(std::ofstream* output_file, bool output_2D_landmarks, bool output_3D_landmarks,
bool output_model_params, bool output_pose, bool output_AUs, bool output_gaze,
const LandmarkDetector::CLNF& face_model, int frame_count, double time_stamp, bool detection_success,
cv::Point3f gazeDirection0, cv::Point3f gazeDirection1, const cv::Vec6d& pose_estimate, double fx, double fy, double cx, double cy,
const FaceAnalysis::FaceAnalyser& face_analyser)
{
double confidence = 0.5 * (1 - face_model.detection_certainty);
*output_file << frame_count + 1 << ", " << time_stamp << ", " << confidence << ", " << detection_success;
// Output the estimated gaze
if (output_gaze)
{
*output_file << ", " << gazeDirection0.x << ", " << gazeDirection0.y << ", " << gazeDirection0.z
<< ", " << gazeDirection1.x << ", " << gazeDirection1.y << ", " << gazeDirection1.z;
}
// Output the estimated head pose
if (output_pose)
{
*output_file << ", " << pose_estimate[0] << ", " << pose_estimate[1] << ", " << pose_estimate[2]
<< ", " << pose_estimate[3] << ", " << pose_estimate[4] << ", " << pose_estimate[5];
}
// Output the detected 2D facial landmarks
if (output_2D_landmarks)
{
for (int i = 0; i < face_model.pdm.NumberOfPoints() * 2; ++i)
{
*output_file << ", " << face_model.detected_landmarks.at<double>(i);
}
}
// Output the detected 3D facial landmarks
if (output_3D_landmarks)
{
cv::Mat_<double> shape_3D = face_model.GetShape(fx, fy, cx, cy);
for (int i = 0; i < face_model.pdm.NumberOfPoints() * 3; ++i)
{
*output_file << ", " << shape_3D.at<double>(i);
}
}
if (output_model_params)
{
for (int i = 0; i < 6; ++i)
{
*output_file << ", " << face_model.params_global[i];
}
for (int i = 0; i < face_model.pdm.NumberOfModes(); ++i)
{
*output_file << ", " << face_model.params_local.at<double>(i, 0);
}
}
if (output_AUs)
{
auto aus_reg = face_analyser.GetCurrentAUsReg();
vector<string> au_reg_names = face_analyser.GetAURegNames();
std::sort(au_reg_names.begin(), au_reg_names.end());
// write out ar the correct index
for (string au_name : au_reg_names)
{
for (auto au_reg : aus_reg)
{
if (au_name.compare(au_reg.first) == 0)
{
*output_file << ", " << au_reg.second;
break;
}
}
}
if (aus_reg.size() == 0)
{
for (size_t p = 0; p < face_analyser.GetAURegNames().size(); ++p)
{
*output_file << ", 0";
}
}
auto aus_class = face_analyser.GetCurrentAUsClass();
vector<string> au_class_names = face_analyser.GetAUClassNames();
std::sort(au_class_names.begin(), au_class_names.end());
// write out ar the correct index
for (string au_name : au_class_names)
{
for (auto au_class : aus_class)
{
if (au_name.compare(au_class.first) == 0)
{
*output_file << ", " << au_class.second;
break;
}
}
}
if (aus_class.size() == 0)
{
for (size_t p = 0; p < face_analyser.GetAUClassNames().size(); ++p)
{
*output_file << ", 0";
}
}
}
*output_file << endl;
}
void get_output_feature_params(vector<string> &output_similarity_aligned, vector<string> &output_hog_aligned_files, double &similarity_scale,
int &similarity_size, bool &grayscale, bool &rigid, bool& verbose,
bool &output_2D_landmarks, bool &output_3D_landmarks, bool &output_model_params, bool &output_pose, bool &output_AUs, bool &output_gaze,
vector<string> &arguments)
{
output_similarity_aligned.clear();
output_hog_aligned_files.clear();
bool* valid = new bool[arguments.size()];
for (size_t i = 0; i < arguments.size(); ++i)
{
valid[i] = true;
}
string input_root = "";
string output_root = "";
// First check if there is a root argument (so that videos and outputs could be defined more easilly)
for (size_t i = 0; i < arguments.size(); ++i)
{
if (arguments[i].compare("-root") == 0)
{
input_root = arguments[i + 1];
output_root = arguments[i + 1];
i++;
}
if (arguments[i].compare("-inroot") == 0)
{
input_root = arguments[i + 1];
i++;
}
if (arguments[i].compare("-outroot") == 0)
{
output_root = arguments[i + 1];
i++;
}
}
for (size_t i = 0; i < arguments.size(); ++i)
{
if (arguments[i].compare("-simalign") == 0)
{
output_similarity_aligned.push_back(output_root + arguments[i + 1]);
create_directory(output_root + arguments[i + 1]);
valid[i] = false;
valid[i + 1] = false;
i++;
}
else if (arguments[i].compare("-hogalign") == 0)
{
output_hog_aligned_files.push_back(output_root + arguments[i + 1]);
create_directory_from_file(output_root + arguments[i + 1]);
valid[i] = false;
valid[i + 1] = false;
i++;
}
else if (arguments[i].compare("-verbose") == 0)
{
verbose = true;
}
else if (arguments[i].compare("-rigid") == 0)
{
rigid = true;
}
else if (arguments[i].compare("-g") == 0)
{
grayscale = true;
valid[i] = false;
}
else if (arguments[i].compare("-simscale") == 0)
{
similarity_scale = stod(arguments[i + 1]);
valid[i] = false;
valid[i + 1] = false;
i++;
}
else if (arguments[i].compare("-simsize") == 0)
{
similarity_size = stoi(arguments[i + 1]);
valid[i] = false;
valid[i + 1] = false;
i++;
}
else if (arguments[i].compare("-no2Dfp") == 0)
{
output_2D_landmarks = false;
valid[i] = false;
}
else if (arguments[i].compare("-no3Dfp") == 0)
{
output_3D_landmarks = false;
valid[i] = false;
}
else if (arguments[i].compare("-noMparams") == 0)
{
output_model_params = false;
valid[i] = false;
}
else if (arguments[i].compare("-noPose") == 0)
{
output_pose = false;
valid[i] = false;
}
else if (arguments[i].compare("-noAUs") == 0)
{
output_AUs = false;
valid[i] = false;
}
else if (arguments[i].compare("-noGaze") == 0)
{
output_gaze = false;
valid[i] = false;
}
}
for (int i = arguments.size() - 1; i >= 0; --i)
{
if (!valid[i])
{
arguments.erase(arguments.begin() + i);
}
}
}
// Can process images via directories creating a separate output file per directory
void get_image_input_output_params_feats(vector<vector<string> > &input_image_files, bool& as_video, vector<string> &arguments)
{
bool* valid = new bool[arguments.size()];
for (size_t i = 0; i < arguments.size(); ++i)
{
valid[i] = true;
if (arguments[i].compare("-fdir") == 0)
{
// parse the -fdir directory by reading in all of the .png and .jpg files in it
path image_directory(arguments[i + 1]);
try
{
// does the file exist and is it a directory
if (exists(image_directory) && is_directory(image_directory))
{
vector<path> file_in_directory;
copy(directory_iterator(image_directory), directory_iterator(), back_inserter(file_in_directory));
// Sort the images in the directory first
sort(file_in_directory.begin(), file_in_directory.end());
vector<string> curr_dir_files;
for (vector<path>::const_iterator file_iterator(file_in_directory.begin()); file_iterator != file_in_directory.end(); ++file_iterator)
{
// Possible image extension .jpg and .png
if (file_iterator->extension().string().compare(".jpg") == 0 || file_iterator->extension().string().compare(".png") == 0)
{
curr_dir_files.push_back(file_iterator->string());
}
}
input_image_files.push_back(curr_dir_files);
}
}
catch (const filesystem_error& ex)
{
cout << ex.what() << '\n';
}
valid[i] = false;
valid[i + 1] = false;
i++;
}
else if (arguments[i].compare("-asvid") == 0)
{
as_video = true;
}
}
// Clear up the argument list
for (int i = arguments.size() - 1; i >= 0; --i)
{
if (!valid[i])
{
arguments.erase(arguments.begin() + i);
}
}
}
void output_HOG_frame(std::ofstream* hog_file, bool good_frame, const cv::Mat_<double>& hog_descriptor, int num_rows, int num_cols)
{
// Using FHOGs, hence 31 channels
int num_channels = 31;
hog_file->write((char*)(&num_cols), 4);
hog_file->write((char*)(&num_rows), 4);
hog_file->write((char*)(&num_channels), 4);
// Not the best way to store a bool, but will be much easier to read it
float good_frame_float;
if (good_frame)
good_frame_float = 1;
else
good_frame_float = -1;
hog_file->write((char*)(&good_frame_float), 4);
cv::MatConstIterator_<double> descriptor_it = hog_descriptor.begin();
for (int y = 0; y < num_cols; ++y)
{
for (int x = 0; x < num_rows; ++x)
{
for (unsigned int o = 0; o < 31; ++o)
{
float hog_data = (float)(*descriptor_it++);
hog_file->write((char*)&hog_data, 4);
}
}
}
}