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AAM scales
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@kurnianggoro
kurnianggoro committed Sep 6, 2017
1 parent 491f554 commit 28f7894
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Showing 6 changed files with 226 additions and 89 deletions.
8 changes: 4 additions & 4 deletions modules/face/include/opencv2/face/facemark.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -355,7 +355,7 @@ namespace face {
@param faces Output of the function which represent region of interest of the detected faces.
Each face is stored in cv::Rect container.
@param landmarks The detected landmark points for each faces.
@param config Algorithm specific on the fly parameters.
@param config Algorithm specific for running time parameters.
<B>Example of usage</B>
@code
Expand All @@ -365,9 +365,9 @@ namespace face {
facemark->fit(image, faces, landmarks);
@endcode
*/
virtual bool fit( InputArray image,
InputArray faces,
InputOutputArray landmarks,
virtual bool fit( InputArray image,\
InputArray faces,\
InputOutputArray landmarks,\
void * config = 0)=0;

/** @brief Set a user defined face detector for the Facemark algorithm.
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30 changes: 6 additions & 24 deletions modules/face/include/opencv2/face/facemarkAAM.hpp
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Expand Up @@ -69,6 +69,8 @@ namespace face {
int n;
int n_iter;
bool verbose;
int max_m, max_n, texture_max_m;
std::vector<float>scales;
};

/**
Expand All @@ -78,12 +80,14 @@ namespace face {
{
Config( Mat rot = Mat::eye(2,2,CV_32F),
Point2f trans = Point2f(0.0,0.0),
float scaling = 1.0
float scaling = 1.0,
int scale_id=0
);

Mat R;
Point2f t;
float scale;
int model_scale_idx;

};

Expand All @@ -102,7 +106,7 @@ namespace face {
{
int npts; //!< unused delete
int max_n; //!< unused delete
std::vector<int>scales;
std::vector<float>scales;
//!< defines the scales considered to build the model

/*warping*/
Expand Down Expand Up @@ -142,28 +146,6 @@ namespace face {

};

/** @brief A custom fitting function designed for AAM algorithm.
AAM fitting relies on basic shape as initializer. Therefore,
transformation paramters are needed to adjust the initial points in the fitting.
@param image Input image.
@param landmarks The fitted facial landmarks.
@param R Rotation matrix.
@param T Translation vector.
@param scale scaling factor.
<B>Example of usage</B>
@code
Mat R = Mat::eye(2, 2, CV_32F);
Point2f t = Point2f(0,0);
float scale = 1.0;
std::vector<Point2f> landmarks;
facemark->fitSingle(image, landmarks, R,T, scale);
@endcode
*/
virtual bool fitSingle( InputArray image, OutputArray landmarks, Mat R, Point2f T, float scale )=0;
virtual void getParams(Model & params) = 0;
//!< initializer
static Ptr<FacemarkAAM> create(const FacemarkAAM::Params &parameters = FacemarkAAM::Params() );
virtual ~FacemarkAAM() {}
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57 changes: 44 additions & 13 deletions modules/face/samples/facemark_demo_aam.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -60,7 +60,7 @@ Mentor: Delia Passalacqua
* 120.208690 270.389841
* ...
* }
* example of the dataset is available at http://www.ifp.illinois.edu/~vuongle2/helen/
* example of the dataset is available at https://ibug.doc.ic.ac.uk/download/annotations/lfpw.zip
*--------------------------------------------------*/

#include <stdio.h>
Expand All @@ -72,8 +72,8 @@ Mentor: Delia Passalacqua
#include "opencv2/face.hpp"

#include <iostream>
#include <fstream>
#include <string>
#include <ctime>

using namespace std;
using namespace cv;
Expand All @@ -93,25 +93,37 @@ Mentor: Delia Passalacqua
if(!parseArguments(argc, argv, parser,cascade_path,eyes_cascade_path,images_path, annotations_path, test_images_path))
return -1;

//! [instance_creation]
/*create the facemark instance*/
Ptr<FacemarkAAM> facemark = FacemarkAAM::create();
FacemarkAAM::Params params;
params.scales.push_back(2.0);
params.scales.push_back(4.0);
Ptr<FacemarkAAM> facemark = FacemarkAAM::create(params);
//! [instance_creation]

//! [load_dataset]
/*Loads the dataset*/
std::vector<String> images_train;
std::vector<String> landmarks_train;
loadDatasetList(images_path,annotations_path,images_train,landmarks_train);
//! [load_dataset]

//! [add_samples]
Mat image;
std::vector<Point2f> facial_points;
for(size_t i=0;i<images_train.size();i++){
image = imread(images_train[i].c_str());
loadFacePoints(landmarks_train[i],facial_points);
facemark->addTrainingSample(image, facial_points);
}
//! [add_samples]

//! [training]
/* trained model will be saved to AAM.yml */
facemark->training();
//! [training]

//! [load_test_images]
/*test using some images*/
String testFiles(images_path), testPts(annotations_path);
if(!test_images_path.empty()){
Expand All @@ -121,47 +133,66 @@ Mentor: Delia Passalacqua
std::vector<String> images;
std::vector<String> facePoints;
loadDatasetList(testFiles, testPts, images, facePoints);
//! [load_test_images]

//! [trainsformation_variables]
float scale ;
Point2f T;
Mat R;
//! [trainsformation_variables]

//! [base_shape]
FacemarkAAM::Data data;
facemark->getData(&data);
std::vector<Point2f> s0 = data.s0;
//! [base_shape]

//! [fitting]
/*fitting process*/
std::vector<Rect> faces;
//! [load_cascade_models]
CascadeClassifier face_cascade(cascade_path);
CascadeClassifier eyes_cascade(eyes_cascade_path);
//! [load_cascade_models]
for(int i=0;i<(int)images.size();i++){
printf("image #%i ", i);
//! [detect_face]
image = imread(images[i]);
myDetector(image, faces, face_cascade);
//! [detect_face]
if(faces.size()>0){
//! [get_initialization]
std::vector<FacemarkAAM::Config> conf;
std::vector<Rect> faces_eyes;
for(unsigned j=0;j<faces.size();j++){
if(getInitialFitting(image,faces[j],s0,eyes_cascade, R,T,scale)){
conf.push_back(FacemarkAAM::Config(R,T,scale));
conf.push_back(FacemarkAAM::Config(R,T,scale,(int)params.scales.size()-1));
faces_eyes.push_back(faces[j]);
}
}
if(conf.size()>0){
//! [get_initialization]

printf(" - face with eyes found %i", (int)conf.size());
//! [fitting_process]
if(conf.size()>0){
printf(" - face with eyes found %i ", (int)conf.size());
std::vector<std::vector<Point2f> > landmarks;

double newtime = (double)getTickCount();
facemark->fit(image, faces_eyes, landmarks, (void*)&conf);
double fittime = ((getTickCount() - newtime)/getTickFrequency());
for(unsigned j=0;j<landmarks.size();j++){
drawFacemarks(image, landmarks[j]);
drawFacemarks(image, landmarks[j],Scalar(0,255,0));
}
printf("%f ms\n",fittime*1000);
imshow("fitting", image);
waitKey(0);
}else{
printf("initialization cannot be computed - skipping\n");
}
//! [fitting_process]
}
printf("\n");
imshow("fitting", image);
waitKey(0);

} //for
//! [fitting]
}

bool myDetector( InputArray image, OutputArray ROIs, CascadeClassifier face_cascade){
Expand Down Expand Up @@ -255,7 +286,7 @@ Mentor: Delia Passalacqua
"{ @e eyes-cascade | | (required) path to the cascade model file for the eyes detector }"
"{ @i images | | (required) path of a text file contains the list of paths to all training images}"
"{ @a annotations | | (required) Path of a text file contains the list of paths to all annotations files}"
"{ t test-images | | Path of a text file contains the list of paths to the test images}"
"{ @t test-images | | Path of a text file contains the list of paths to the test images}"
"{ help h usage ? | | facemark_demo_aam -face-cascade -eyes-cascade -images -annotations [-t]\n"
" example: facemark_demo_aam ../face_cascade.xml ../eyes_cascade.xml ../images_train.txt ../points_train.txt ../test.txt}"
;
Expand All @@ -271,7 +302,7 @@ Mentor: Delia Passalacqua
model = String(parser.get<string>("eyes-cascade"));
images = String(parser.get<string>("images"));
annotations = String(parser.get<string>("annotations"));
test_images = String(parser.get<string>("t"));
test_images = String(parser.get<string>("test-images"));

if(cascade.empty() || model.empty() || images.empty() || annotations.empty()){
std::cerr << "one or more required arguments are not found" << '\n';
Expand Down
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