add new tutorial

dnn_tutorial/face_alignment.cpp

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+#include <opencv2/opencv.hpp>
+#include <opencv2/face.hpp>
+#include <math.h>
+#include <iostream>
+
+using namespace cv;
+using namespace cv::face;
+using namespace std;
+
+const String  lbpfilePath = "D:/opencv-3.4/opencv/build/etc/lbpcascades/lbpcascade_frontalface.xml";
+bool myDetector(InputArray image, OutputArray faces, CascadeClassifier *face_cascade);
+void face_alignment(Mat &face, Point left, Point right, Rect roi);
+
+int main(int argc, char** argv) {
+	Mat img = imread("D:/vcprojects/images/gaoyy.png");
+	namedWindow("input", CV_WINDOW_AUTOSIZE);
+	imshow("input", img);
+
+	CascadeClassifier face_cascade;
+	face_cascade.load(lbpfilePath);
+
+	FacemarkLBF::Params params;
+	params.n_landmarks = 68; // 68个标注点
+	params.initShape_n = 10;
+	params.stages_n = 5; // 算法的5个强化步骤
+	params.tree_n = 6; // 模型中每个标注点结构树 数目
+	params.tree_depth = 5; // 决策树深度
+
+	// 创建LBF landmark 检测器
+	Ptr<FacemarkLBF> facemark = FacemarkLBF::create(params);
+	facemark->setFaceDetector((FN_FaceDetector)myDetector, &face_cascade);
+
+	// 加载模型数据
+	facemark->loadModel("D:/vcprojects/images/lbfmodel.yaml");
+	cout << "Loaded model" << endl;
+
+	// 开始检测
+	printf("start to detect landmarks...\n");
+	vector<Rect> faces;
+	facemark->getFaces(img, faces);
+	vector< vector<Point2f> > shapes;
+	if (facemark->fit(img, faces, shapes))
+	{
+		Point eye_left; // 36th
+		Point eye_right; // 45th
+		for (unsigned long i = 0; i<faces.size(); i++) {
+			eye_left = shapes[i][36];
+			eye_right = shapes[i][45];
+			line(img, eye_left, eye_right, Scalar(255, 0, 0), 2, 8, 0);
+			face_alignment(img(faces[i]), eye_left, eye_right, faces[i]);
+
+			// 绘制人脸矩形区域
+			rectangle(img, faces[i], Scalar(255, 0, 0));
+			// 绘制人脸68个 landmark点位
+			for (unsigned long k = 0; k<shapes[i].size(); k++)
+				cv::circle(img, shapes[i][k], 2, cv::Scalar(0, 0, 255), FILLED);
+		}
+		namedWindow("Detected_shape");
+		imshow("Detected_shape", img);
+		waitKey(0);
+	}
+	return 0;
+}
+
+bool myDetector(InputArray image, OutputArray faces, CascadeClassifier *face_cascade)
+{
+	Mat gray;
+
+	if (image.channels() > 1)
+		cvtColor(image, gray, COLOR_BGR2GRAY);
+	else
+		gray = image.getMat().clone();
+
+	equalizeHist(gray, gray);
+
+	std::vector<Rect> faces_;
+	face_cascade->detectMultiScale(gray, faces_, 1.1, 1, CASCADE_SCALE_IMAGE, Size(50, 50));
+	Mat(faces_).copyTo(faces);
+	return true;
+}
+
+void face_alignment(Mat &face, Point left, Point right, Rect roi) {
+	int offsetx = roi.x;
+	int offsety = roi.y;
+
+	// 计算中心位置
+	int cx = roi.width / 2;
+	int cy = roi.height / 2;
+
+	// 计算角度
+	int dx = right.x - left.x;
+	int dy = right.y - left.y;
+	double degree = 180 * ((atan2(dy, dx)) / CV_PI);
+
+	// 旋转矩阵计算
+	Mat M = getRotationMatrix2D(Point2f(cx, cy), degree, 1.0);
+	Point2f center(cx, cy);
+	Rect bbox = RotatedRect(center, face.size(), degree).boundingRect();
+	M.at<double>(0, 2) += (bbox.width / 2.0 - center.x);
+	M.at<double>(1, 2) += (bbox.height / 2.0 - center.y);
+
+	// 对齐
+	Mat result;
+	warpAffine(face, result, M, bbox.size());
+	imshow("face-alignment", result);
+}