void WAY_cv()
{
String path, img_path;
CascadeClassifier faceCascade = new CascadeClassifier();
faceCascade.Load("haar_face.xml");
Mat img_array, gray, face_roi, pred_gray, pred_face_roi;
int[] labels = new int[20];
Mat[] features = new Mat[20];
for (int i = 0; i < people.Length; i++)
{
path = @"img\" + people[i];
for (int j = 0; j < 5; j++)
{
img_path = path + @"\" + i.ToString() + ".jpg";
img_array = Cv2.ImRead(img_path);
gray = new Mat();
Cv2.CvtColor(img_array, gray, ColorConversionCodes.BGR2GRAY);
Rect[] ret = faceCascade.DetectMultiScale(img_array, 1.1, 4);
face_roi = gray.AdjustROI(ret[0].Top, ret[0].Bottom, ret[0].Left, ret[0].Right);
labels[i * 5 + j] = i;
features[i * 5 + j] = face_roi;
}
}
OpenCvSharp.Face.LBPHFaceRecognizer recognizer;
recognizer = OpenCvSharp.Face.LBPHFaceRecognizer.Create();
recognizer.Train(features, labels);
pred_gray = new Mat();
Cv2.CvtColor(inCvImage, pred_gray, ColorConversionCodes.BGR2GRAY);
Rect[] ret2 = faceCascade.DetectMultiScale(pred_gray, 1.1, 4);
pred_face_roi = pred_gray.AdjustROI(ret2[0].Top, ret2[0].Bottom, ret2[0].Left, ret2[0].Right);
int ans = recognizer.Predict(pred_face_roi);
MessageBox.Show(people[ans] + " 입니다!, 아님 말고...");
}
