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// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html.
#include "test_precomp.hpp"
namespace opencv_test { namespace {
using namespace cv::face;
static bool myDetector( InputArray image, OutputArray ROIs, CascadeClassifier* face_cascade)
{
Mat gray;
std::vector<Rect> faces;
if(image.channels()>1){
cvtColor(image.getMat(),gray,COLOR_BGR2GRAY);
}
else{
gray = image.getMat().clone();
}
equalizeHist( gray, gray );
face_cascade->detectMultiScale( gray, faces, 1.1, 3, 0, Size(30, 30) );
Mat(faces).copyTo(ROIs);
return true;
}
TEST(CV_Face_FacemarkKazemi, can_create_default) {
string cascade_name = cvtest::findDataFile("face/lbpcascade_frontalface_improved.xml", true);
string configfile_name = cvtest::findDataFile("face/config.xml", true);
CascadeClassifier face_cascade;
EXPECT_TRUE(face_cascade.load(cascade_name));
FacemarkKazemi::Params params;
params.configfile = configfile_name;
Ptr<FacemarkKazemi> facemark;
EXPECT_NO_THROW(facemark = FacemarkKazemi::create(params));
EXPECT_TRUE(facemark->setFaceDetector((cv::face::FN_FaceDetector)myDetector, &face_cascade));
EXPECT_FALSE(facemark.empty());
}
TEST(CV_Face_FacemarkKazemi, can_loadTrainingData) {
string filename = cvtest::findDataFile("face/lbpcascade_frontalface_improved.xml", true);
string configfile_name = cvtest::findDataFile("face/config.xml", true);
CascadeClassifier face_cascade;
EXPECT_TRUE(face_cascade.load(filename));
FacemarkKazemi::Params params;
params.configfile = configfile_name;
Ptr<FacemarkKazemi> facemark;
EXPECT_NO_THROW(facemark = FacemarkKazemi::create(params));
EXPECT_TRUE(facemark->setFaceDetector((cv::face::FN_FaceDetector)myDetector, &face_cascade));
vector<String> filenames;
filename = cvtest::findDataFile("face/1.txt", true);
filenames.push_back(filename);
filename = cvtest::findDataFile("face/2.txt", true);
filenames.push_back(filename);
vector<String> imagenames;
vector< vector<Point2f> > trainlandmarks,Trainlandmarks;
vector<Rect> rectangles;
//Test getData function
EXPECT_NO_THROW(loadTrainingData(filenames,trainlandmarks,imagenames));
vector<Mat> trainimages;
for(unsigned long i=0;i<imagenames.size();i++){
string img = cvtest::findDataFile(imagenames[i], true);
Mat src = imread(img);
EXPECT_TRUE(!src.empty());
trainimages.push_back(src);
Trainlandmarks.push_back(trainlandmarks[i]);
}
string modelfilename = "face_landmark_model.dat";
Size scale = Size(460,460);
EXPECT_TRUE(facemark->training(trainimages,Trainlandmarks,configfile_name,scale,modelfilename));
}
TEST(CV_Face_FacemarkKazemi, can_detect_landmarks) {
string cascade_name = cvtest::findDataFile("face/lbpcascade_frontalface_improved.xml", true);
CascadeClassifier face_cascade;
face_cascade.load(cascade_name);
FacemarkKazemi::Params params;
Ptr<FacemarkKazemi> facemark;
EXPECT_NO_THROW(facemark = FacemarkKazemi::create(params));
EXPECT_TRUE(facemark->setFaceDetector((cv::face::FN_FaceDetector)myDetector, &face_cascade));
string imgname = cvtest::findDataFile("face/detect.jpg");
string modelfilename = cvtest::findDataFile("face/face_landmark_model.dat",true);
Mat img = imread(imgname);
EXPECT_TRUE(!img.empty());
EXPECT_FALSE(facemark.empty());
EXPECT_NO_THROW(facemark->loadModel(modelfilename));
vector<Rect> faces;
//Detect faces in the current image
EXPECT_TRUE(facemark->getFaces(img,faces));
//vector to store the landmarks of all the faces in the image
vector< vector<Point2f> > shapes;
EXPECT_NO_THROW(facemark->fit(img,faces,shapes));
shapes.clear();
}
}} // namespace
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